Main Conference
Track 3 – Wireless Networks
Session T3-S20
UAV (Unmanned Aerial Vehicle) 1
Conference
10:40 AM
—
12:10 PM KST
Local
May 27 Wed, 6:40 PM
—
8:10 PM PDT
UAV Trajectory and Sub-channel Assignment for UAV Based Wireless Networks
Nguyen Minh Dat (INRS-EMT & University of Quebec, Canada); Tai Manh Ho (École de Technologie Supérieure ÉTS, Canada); Long Bao Le (INRS, University of Quebec, Canada); Andre Girard (INRS-EMT and GERAD, Canada)
1
In this paper, we study the trajectory control and sub-channel assignment for unmanned aerial vehicles (UAVs) based wireless networks with wireless backhaul links. This design aims to optimize the max-min rate subject to data transmission demands of ground users (GUs). The underlying problem is a mixed integer nonlinear optimization problem because of the complicated relationship between the UAV-GU channel gains and the UAV's location in each time slot of the flight period. To tackle this problem, we employ the alternating optimization approach where we iteratively optimize the sub-channel assignment and UAV trajectory control until convergence. Moreover, the difference of convex functions (DC) optimization method and the arithmetic and geometric means (AM-GM) inequality are employed to convexify and solve the non-convex UAV trajectory sub-problem. Via extensive numerical studies, we illustrate the effective UAV's trajectory considering capacity-limited access and backhaul links and the non-negligible rate gain of the proposed design compared to a baseline employing the circular UAV trajectory around the center of service area and a heuristic algorithm for sub-channel assignment.
Flight Scheduling and Trajectory Control in UAV-Based Wireless Networks
Minh Tri Nguyen (EMT-INRS, University of Quebec, Canada); Long Bao Le (INRS, University of Quebec, Canada)
0
In this paper, we study the flight scheduling and trajectory control for UAV-based wireless networks. Particularly, we are interested in optimizing the flight time, trajectory, and power allocation for the UAVs serving the set of ground users. Our design allows UAVs to be dispatched at different time with different flight durations and trajectories to balance between communication and flying energy consumption considering UAVs' limited energy. To gain insights into the problem, we first study the single-UAV setting where we show mathematically that there exists a unique optimal flying duration to maximize the system throughput. Then, we investigate the double-UAV network scenario and we present an algorithm to optimize the trajectories, power allocation, user association for the UAVs. Via numerical studies, we show that the network throughput is maximized when the flying duration for each UAV is equal to its corresponding optimal flying duration in case of the single-UAV network.
Distributed Topology Control based on Swarm Intelligence In Unmanned Aerial Vehicles Networks
Qianyi Zhang, Gang Feng, Shuang Qin and Yao Sun (University of Electronic Science and Technology of China, China)
1
Unmanned aerial vehicles (UAVs) have shown enormous potential in both public and civil domains. Although multi-UAV systems can collaboratively accomplish missions efficiently, UAV network(UAVNET) design faces many challenging issues, such as high mobility, dynamic topology, power constraints, and varying quality of communication links. Topology control plays a key role for providing high network connectivity while conserving power in UAVNETs. In this paper, we propose a distributed topology control algorithm based on discrete particle swarm optimization with articulation points(AP-DPSO). To reduce signaling overhead and facilitate distributed control, we first identify a set of articulation points (APs) to partition the network into multiple segments. The local topology control problem for individual segments is formulated as a degree-constrained minimum spanning tree problem. Each node collects local topology information and adjusts its transmit power to minimize power consumption. We conduct simulation experiments to evaluate the performance of the proposed AP-DPSO algorithm. Numerical results show that AP-DPSO outperforms some known algorithms including LMST and LSP, in terms of network connectivity, average link length and network robustness for a dynamic UAVNET.
Trajectory Design and Generalization for UAV Enabled Networks:A Deep Reinforcement Learning Approach
Xuan Li (Beijing University Of Posts And Telecommunications, China); Qiang Wang (Beijing University of Posts and Telecommunications, China); Jie Liu (Beijing University of Post and Telecommunications, China); Wenqi Zhang (Beijing University of Posts and Telecommunications, China)
0
In this paper, an unmanned aerial vehicle (UAV) flies as a base station (BS) to provide wireless communication service. We propose two algorithms for designing the trajectory of the UAV and analyze the impact of different training approaches on transferring to new environments. When the UAV is used to track users that move along some specific paths, we propose a proximal policy optimization (PPO) -based algorithm to maximize the instantaneous sum rate (MSR-PPO). The UAV is modeled as a deep reinforcement learning (DRL) agent to learn how to move by interacting with the environment. When the UAV serves users along unknown paths for emergencies, we propose a random training proximal policy optimization (RT-PPO) algorithm which can transfer the pre-trained model to new tasks to achieve quick deployment. Unlike classical DRL algorithms that the agent is trained on the same task to learn its actions, RT-PPO randomizes the features of tasks to get the ability to transfer to new tasks. Numerical results reveal that MSR-PPO achieves a remarkable improvement and RT-PPO shows an effective generalization performance.
Performance Analysis of Temporal Correlation in Finite-Area UAV Networks with LoS/NLoS
Ruixin Jin (Beijing University of Post and Telecommunications, China); Liyun Yang (Beijing University of Posts and Telecommunications, China); Hongtao Zhang (Beijing University of Posts and Telecommunications & Key Lab of Universal Wireless Communications, Ministry of Education, China)
0
In the existing works, the finite-area distribution of Unmanned Aerial Vehicle (UAV) and the effects of LoS and NLoS in air-to-ground channels have not been modeled when analyzing the temporal correlation in UAV networks, which makes the current analyses unsuitable for the practical deployment in hotspots. This paper analyzes the temporal correlation by deriving the expression of the interference correlation and joint coverage probability in mobile UAV networks, where all UAVs move independently in a finite area and the channel fading is calculated based on air-to-ground channel model with LoS and NLoS. Specifically, the temporal correlation is measured by incorporating the fluctuations caused by probability variation of LoS and the reliable network topology caused by finite mobility into the wireless channels. Furthermore, the non-uniform distribution caused by random mobility of UAVs is considered over different time slots. The results show that the interference correlation decreases as the moving distance of UAVs increases, and the decreasing interference correlation offsets part of the decrease in joint coverage probability caused by increasing moving distance of UAVs.
Session Chair
Yao Sun (University of Electronic Science and Technology of China, China)
Session T3-S21
Security and Privacy 1
Conference
10:40 AM
—
12:10 PM KST
Local
May 27 Wed, 6:40 PM
—
8:10 PM PDT
Bloom Filter Based Low-Latency Provenance Embedding Schemes in Wireless Networks
J Harshan, Amogh Vithalkar, Naman Jhunjhunwala, Manthan Kabra and Prafull Manav (Indian Institute of Technology Delhi, India); Yih-Chun Hu (University of Illinois at Urbana-Champaign, USA)
1
A number of applications in next-generation multi- hop networks impose low-latency requirements on data transmission thereby necessitating the underlying relays to introduce negligible delay when forwarding the packets. While traditional relaying techniques such as amplify-and-forward may help the packets to satisfy latency-constraints, such strategies do not facilitate the destination in determining security threats, if any, during the packet's journey. Inspired by the problem of relaying packets that have low-latency constraints, we revisit the design of provenance embedding algorithms to reduce delays on the packets and yet assist the destination in determining the provenance with no knowledge on the network topology. We propose a new class of provenance embedding techniques, referred to as double- edge (DE) embedding techniques, wherein a subset of the relay nodes in the path strategically skip the provenance embedding process to reduce the delays on the packets. Under the framework of DE embedding techniques, we propose a deterministic skipping strategy among the nodes such that the destination can recover the provenance of every packet. Using fixed-size bloom filters as tools to implement the double-edge embedding ideas, we propose upper bounds on the error-rates of the DE embedding technique as a function of the number of nodes in the network, number of hops, bloom filter size, and the number of hash functions used by each node. Subsequently, we demonstrate the efficacy of the DE embedding technique on a testbed of Digi XBee devices, and show that it outperforms competitive baselines both in terms of latency as well as error-rates.
Ergodic Secrecy Rate of K-user MISO Broadcast Channel with Improved Random Beamforming
Ye Fan, Xuewen Liao and Zhenzhen Gao (Xi'an Jiaotong University, China)
1
In this paper, we study the secrecy performance of multiple-input single-output (MISO) wiretap channel with random beamforming (RB), where the eavesdropper is equipped with multiple antennas. In traditional RB schemes, the transmitter utilizes only one antenna to emit information signal and adopts the rest antennas to produce a random beamforming vector for security. To make full use of the power resource and improve the secrecy performance, we propose a power-minimizing and signal-splitting random beamforming (PM-SSRB) scheme, where the random beamforming vector is generalized with arbitrary number of transmit antennas based on power-minimizing. To evaluate the secrecy performance of the proposed scheme, we analyze the ergodic secrecy rate and derive the closed-form expression of the ergodic rate of the MISO wiretap channel. Simulation results show that, compared with the traditional hybrid artificial fast-fading scheme (AFF) and artificial noise (AN) scheme, the proposed SSRB scheme and PM-SSRB scheme perform much better in terms of the ergodic secrecy rate in all power regimes. More importantly, when the eavesdropper has more antennas than the transmitter, our schemes always outperform the AFF and AN schemes. The PM-SSRB scheme is also shown to be superior to the secret-key AFF scheme.
A Secure Authentication Scheme for Remote Diagnosis and Maintenance in Internet of Vehicles
Ruhui Ma and Jin Cao (Xidian University, China); Dengguo Feng (State Key Laboratory of Cryptology, Beijing, China); Hui Li (Xidian University, China); Ben Niu (Institute of Information Engineering, Chinese Academy of Sciences, China); Fenghua Li (State Key Laboratory of Information Security, Institute of Information Engineering, CAS, China); Lihua Yin (Guangzhou University, China)
0
Due to the low latency and high speed of 5G networks, the Internet of Vehicles (IoV) under the 5G network has been rapidly developed and has broad application prospects. The Third Generation Partnership Project (3GPP) committee has taken remote diagnosis as one of the development cores of IoV. However, how to ensure the security of remote diagnosis and maintenance services is also a key point to ensure vehicle safety, which is directly related to the safety of vehicle passengers. In this paper, we propose a secure and efficient authentication scheme based on extended chebyshev chaotic maps for remote diagnosis and maintenance in IoVs. In the proposed scheme, to provide strong security, anyone, such as the vehicle owner or the employee of the Vehicle Service Centre (VSC), must enter the valid biometrics and password in order to enjoy or provide remote diagnosis and maintenance services, and the vehicle and the VSC should authenticate each other to ensure that they are legitimate. The security analysis and performance evaluation results show that the proposed scheme can provide robust security with ideal efficiency.
WiRE: Security Bootstrapping for Wireless Device-to-Device Communication
Yinrong Tao, Sheng Xiao and Bin Hao (Hunan University, China); Qingquan Zhang (University of Illinois, Urbana Champaign, USA); Ting Zhu (University of Maryland, Baltimore County, USA); Zhuo Chen (Office of Ecology Protection, Management and Construction Hunan Province, China)
0
Rapidly evolving wireless technologies enable devices to directly exchange information without infrastructural support. In these device-to-device (D2D) communication scenarios, it is often difficult to setup cryptographic keys to initialize the secure communication, especially when the D2D connections are mobile and dynamic. This paper proposes an application layer solution scheme to bootstrap secure communications using the inherent randomness in the wireless transmissions. The proposed scheme is lightweight, easy to deploy and compatible with many physical layer wireless technologies. This paper contains security analysis to the scheme and conducts experiments to demonstrate its practicality.
Utility-aware Exponential Mechanism for Personalized Differential Privacy
Ben Niu (Institute of Information Engineering, Chinese Academy of Sciences, China); Yahong Chen (Institute of Information Engineering, CAS & School of Cyber Security, UCAS, China); Boyang Wang (University of Cincinnati, USA); Jin Cao (Xidian University, China); Fenghua Li (Institute of Information Engineering, CAS & School of Cyber Security, UCAS, P.R. China)
0
Personalized Differential Privacy (PDP) was proposed to satisfy users' different privacy requirements. However, most of the existing PDP mechanisms may significantly destroy the utility of released statistical results. Differentially private statistical results with poor utility may mislead the data analysts, thus it may even decrease the acceptability of the technique used to protect data privacy. Therefore, in this paper, our goal is to pursue higher data utility while satisfying personalized differential privacy. To achieve this goal, we propose the Utility- aware Personalized Exponential Mechanism (UPEM) to effectively achieve PDP while pursuing better utility. UPEM distinguishes the different possible results with the same personalized score, which is used in Personalized Exponential Mechanism (PEM) [1]. PEM considers the personalized privacy budgets of changing elements to achieve PDP. Based on PEM, our UPEM further considers the quantitative changes of these changing tuples to enhance the utility. We confirm the effectiveness and efficiency of UPEM through extensive experiments.
Session Chair
J Harshan (Indian Institute of Technology Delhi, India)
Session T3-S22
Resource Management and Optimization 1
Conference
10:40 AM
—
12:10 PM KST
Local
May 27 Wed, 6:40 PM
—
8:10 PM PDT
QoS-Driven Stochastic Analysis for Heterogeneous Cognitive Radio Networks
Muyu Mei, Qinghai Yang and Meng Qin (Xidian University, China); Kyung Sup Kwak (Inha University, Korea (South)); Ramesh R. Rao (UCSD, USA)
1
The future 5G wireless network is largely driven by the increasing heavy traffic and spectrum scarcity. Cognitive Radio (CR) techniques provide a potential solution for improving the spectrum efficiency. In this paper, we study the stochastic framework for the CR networks, considering different quality of service (QoS) requirements. To analyze the performance of the CR network, we adopt a poisson point process (PPP) to capture the mobility and randomness of user location. A stochastic- network-calculus (SNC) based approach is proposed to model the wireless transmission and evaluate the network performance. In order to achieve the performance metrics of end-to-end (E2E) delay and backlog in the entire network, we propose a new conception named as effective service process (ESP) which is able to capture the QoS requirements of users. Furthermore, we evaluate the performance in the exponential domain, which can present the E2E analysis more directly. The simulation results verify the theoretical analysis and show that the performance in the CR networks can be derived perfectly with the proposed approach, considering the stochastic traffic arrival and designed service model in our schedule.
Joint User-Centric Clustering and Frequency Allocation in Ultra-Dense C-RAN
Qiang Liu, Sun Songlin and Hui Gao (Beijing University of Posts and Telecommunications, China)
3
This paper considers the downlink ultra-dense cloud radio access network (C-RAN), which employs multiple radio remote head (RRH) cooperation to guarantee the minimum achievable transmission rate for each user equipment (UE). However, due to the limited orthogonal frequency resources, it is difficult to achieve this goal. To maximize the coverage probability of the system, we focus on the joint user-centric clustering and frequency allocation problem. To reduce the computational complexity, this problem is split into two sub-problems: user- centric clustering and frequency allocation. Firstly, we propose a novel binary user-centric clustering strategy, which includes serving clusters and silent clusters. This strategy determines the acceptable combination of serving clusters and silent clusters to guarantee the minimum transmission rate for each UE and simplify the complexity of the subsequent frequency allocation. Then based on the generated clusters, a new graph generation method is proposed. The advantage of this graph is that we can allocate frequency resources by simply judging the relationship between the serving clusters in the graph without complicated calculations. Numerical simulation results show that the joint binary user-centric clustering and location-based frequency allocation scheme is superior to the benchmark solutions in terms of the coverage probability.
Trading Based Service-Oriented Spectrum-Aware RAN-Slicing Under Spectrum Sharing
Kajia Jiao and Xuanheng Li (Dalian University of Technology, China); Miao Pan (University of Houston, USA); Fan Jiang (Xian University of Posts and Telecommunications, China); Ming Li (Dalian University of Technology, China)
1
The fast development on emerging services makes our telecommunications networks witness two key problems. One is the flexibility to fulfill the diverse service requests and the other is the shortage on spectrum. Network slicing and spectrum sharing have been regarded as two prominent solutions, which, however, are barely jointly studied. When taking the shared spectrum into account, its unique feature of heterogeneity and uncertainty will bring new challenges for the slicing. In this paper, we propose a service-oriented spectrum-aware RAN-slicing trading (SSRT) scheme with a comprehensive consideration on both aspects. For the SSRT scheme, we jointly slice three kinds of resources, namely, time, spectrum (including both licensed one and shared one), and network facilities, according to the diverse traffic requests, which are classified into delay-tolerant (DT) ones and delay-sensitive (DS) ones, as well as the willing payments from different service providers (SPs). To achieve both inter-slice and intra-slice isolation, we construct a three-dimensional (3D) conflict graph and formulate the SSRT scheme into a mixed-integer nonlinear programming (MINLP) problem with a cross-layer spectrum-aware resource allocation and a hybrid transmission mode (including both single-hop and multi-hop). Since finding all the maximum independent sets (MIS) for the 3D conflict graph is an NP-hard problem, we further develop an iterative heuristic algorithm for the MIS determination.
Throughput Analysis in Cache-enabled Millimeter Wave HetNets with Access and Backhaul Integration
Chenwu Zhang, Hao Wu, Hancheng Lu and Jinxue Liu (University of Science and Technology of China, China)
3
Recently, a mmWave-based access and backhaul integration heterogeneous networks (HetNets) architecture (mAB- HetNets) has been envisioned to provide high wireless capacity. Since the access link and the backhaul link share the same mm- wave spectral resource, a large spectrum bandwidth is occupied by the backhaul link, which hinders the wireless access capacity improvement. To overcome the backhaul spectrum occupation problem and improve the network throughput in the existing mABHetNets, we introduce the cache at base stations (BSs). In detail, by caching popular files at small base stations (SBSs), mABHetNets can offload the backhaul link traffic and transfer the redundant backhaul spectrum to the access link to increase the network throughput. However, introducing cache in SBSs will also incur additional power consumption and reduce the transmission power, which can lower the network throughput. In this paper, we investigate spectrum partition between the access link and the backhaul link as well as cache allocation to improve the network throughput in mABHetNets. With the stochastic geometry tool, we develop an analytical framework to characterize cache-enabled mABHetNets and obtain the signal- to-interference-plus-noise ratio (SINR) distributions in line-of- sight (LoS) and non-line-of-sight (NLoS) paths. Then we utilize the SINR distribution to derive the average potential throughput (APT). Extensive numerical results show that introducing cache can bring up to 80% APT gain to the existing mABHetNets.
Jointly Optimizing Helpers Selection and Resource Allocation in D2D Mobile Edge Computing
Yang Li, Gaochao Xu and Jiaqi Ge (Jilin University, China); Peng Liu (Northeast Forestry University, China); Xiaodong Fu (Jilin University, China); Zhenjun Jin (Changchun University of Technology, China)
3
Device-to-Device (D2D) communication has attracted extensive researches because of its ability to reduce latency and improve the spectrum resource utilization. This paper studies a D2D Mobile Edge Computing (MEC) system which contains multiple busy smart devices (SDs) and multiple idle smart devices. To minimize the total energy consumption of the MEC system and satisfy the latency constraints of SDs, the computation intensive task of each busy SD can be partially offloaded to one or more idle SDs as helpers. Therefore, a joint optimization problem of helpers selection and communication and computation resources allocation is proposed. The problem is formulated as an integer- mixed non-convex optimization problem which is a NP-hard problem. We thus propose a two-phase iterative approach by jointly optimizing helpers selection and communication and computation resources allocation. In the first phase, we obtain the suboptimal helpers selection policy with convex optimization techniques and block coordinate descent method. In the second phase, the resource allocation strategy is achieved by applying block coordinate descent after obtaining the suboptimal helpers selection policy. The simulation results demonstrate that not only the proposed algorithm achieves fast convergence in both phases, but also the overall energy consumption is less than other benchmarks.
CIRNO: Leveraging Capacity Interference Relationship for Dense Networks Optimization
Srikant Manas Kala (IIT HYDERABAD, India); Vanlin Sathya (University of Chicago, USA); Winston K.G. Seah (Victoria University of Wellington, New Zealand); Bheemarjuna Reddy Tamma (IIT Hyderabad, India)
3
To meet the rising data-offloading demands, IEEE 802.11-based WiFi networks have undergone consistent den- sification. The unlicensed spectrum has also been harnessed through LTE-WiFi coexistence. However, in dense and ultra-dense networks (DNs/UDNs), the network capacity is even more adversely impacted by the endemic interference. Yet, the precise nature of Capacity Interference Relationship (CIR) in DNs/UDNs and LTE-WiFi coexistence remains to be studied. Densification also exacerbates the challenges to network optimization. The conventional approaches to simplify the complex SINR-Capacity constraints lead to high convergence times in DN/UDN optimization. We investigate the CIR in dense and ultra-dense WiFi (IEEE 802.11a) and LTE-WiFi (LTU/LAA) networks through real-time experiments. We then subject the empirical data to linear and polynomial regression to determine the nature of CIR and demonstrate that strong linear correlations may exist. We also study the impact of predictor variables, topology, and radio access technology on CIR. Most importantly, we propose CIRNO, a CIR-inspired network optimization approach, wherein the empirically determined CIR equation replaces the theoretically assumed SINR-Capacity constraints in optimization formulations. We evaluate CIRNO by implementing three recent works on optimization. We demonstrate the relevance of CIR and CIRNO in DNs/UDNs through a significant reduction in convergence times (by over 50%) while maintaining high accuracy (over 95%). To the best of our knowledge, this is the first work to statistically analyze CIR in DNs/UDNs and LTE-WiFi heterogeneous networks (HetNets) and to use CIR regression equations in network optimization.
Session Chair
Bheemarjuna Reddy Tamma (IIT Hyderabad, India)
Session T3-S23
Mobility and Handoff Management
Conference
2:00 PM
—
3:30 PM KST
Local
May 27 Wed, 10:00 PM
—
11:30 PM PDT
Efficient Drone Mobility Support Using Reinforcement Learning
Yun Chen (The University of Texas at Austin, USA); Xingqin Lin (Ericsson Research, USA); Talha Ahmed Khan (Ericsson Research); Mohammad Mozaffari (Ericsson Research, Santa Clara, CA, USA., USA)
0
Flying drones can be used in a wide range of applications and services from surveillance to package delivery. To ensure robust control and safety of drone operations, cellular networks need to provide reliable wireless connectivity to drone user equipments (UEs). To date, existing mobile networks have been primarily designed and optimized for serving ground UEs, thus making the mobility support in the sky challenging. In this paper, a novel handover (HO) mechanism is developed for a cellular-connected drone system to ensure robust wireless connectivity and mobility support for drone-UEs. By leveraging tools from reinforcement learning, HO decisions are dynamically optimized using a Q-learning algorithm to provide an efficient mobility support in the sky. The results show that the proposed approach can significantly reduce (e.g., by 80%) the number of HOs, while maintaining connectivity, compared to the baseline HO scheme in which the drone always connects to the strongest cell.
ProSCH: Proxy aided Secondary Cell Handover in Ultra-Dense mmWave Network
Goodsol Lee, Siyoung Choi, Junseok Kim, Kim Youngseok and Saewoong Bahk (Seoul National University, Korea (South))
1
The ultra-dense network (UDN) is a promising technology that overcomes the instability of high-frequency millimeter wave (mmWave) communication in a cellular network. With a short distance between cells and variability of mmWave, a handover occurs frequently in UDN with mmWave. Hence fast handover is essential to provide reliable service. One of the important things for fast handover is prompt signaling between base stations (BSs) through backhaul. However, conventional handovers assumed backhaul has very short latency with ideal deployment. In practice, with non-ideal latency and deployment of backhaul, handover is delayed for backhaul. We find that this delayed handover led to the performance reduction of TCP, the dominant traffic of nowadays. So we propose a ProSCH, the novel handover scheme that operates on a practical backhaul network while guaranteeing TCP performance. ProSCH reduces a handover interruption time by considering the backhaul latency in the handover signaling process, and uses a TCP proxy on BS to forward data without loss after handover. Through extensive ns-3 simulation, we show that ProSCH outperforms conventional schemes in terms of handover interruption time, backhaul load, throughput, and delay.
Robust TOA-Based Source Self-Positioning With Clock Imperfection
Pengcheng He, Xiaohu Jiang and Qingjiang Shi (Tongji University, China)
0
Source positioning is a key issue in a range of applications such as sensing, monitoring and tracking, etc. In this paper, we address the source localization problem with unknown clock skew and outliers in the TOA measurements. Considering the measurement outliers, we present a robust localization formulation by introducing Huber loss. Furthermore, we develop a lightweight iterative localization algorithm using majorization-minimization (MM) method with guaranteed convergence. In addition, we propose a novel semidefinite-relaxation- based algorithm for the proposed robust localization formulation. Simulations demonstrate that our proposed MM-based localization algorithms could achieve better performance than SDR-based localization algorithms in terms of both localization accuracy and computational time, for both cases with or without outliers.
On the Feasibility of Location-based Discovery and Vertical Handover in IEEE 802.11ah
Serena Santi (University of Antwerp - imec, Belgium); Filip Lemic (University of Antwerpen - imec, Belgium); Jeroen Famaey (University of Antwerp & Imec, Belgium)
1
Multi-Radio Access Technology (RAT) IoT devices are able to combine the high coverage of Low-Power Wide-Area (LPWA) technologies with the higher data-rates of shorter range technologies such as IEEE 802.11ah. In such scenarios, a discovery procedure has to be used for detecting the availability of a IEEE 802.11ah network. Currently, these procedures consume substantial energy, as the discovery has to be periodically performed, even if the IEEE 802.11ah technology is not available, which is undesirable for low-power Internet of Things (IoT) devices. We propose using the device's location information for making more optimized discovery and handover decisions. We demonstrate the feasibility of this approach in performing energy efficient handovers between various LPWA technologies and IEEE 802.11ah based on estimated location. We carry out our evaluation in terms of the energy consumption of the procedure and the duration of the device's association to IEEE 802.11ah. We show that the location-based procedure substantially reduces the energy consumption of the mobile device compared to the traditional discovery based on periodical listening for beacons.
Cellular Network Planning under Variable QoS Requirements Using Voronoi Algorithm
Mohsen Abedi (Aalto University, Finland); Risto Wichman (Aalto University School of Electrical Engineering, Finland)
1
We study the optimization of base station (BS) localization in cellular networks with non-uniform service demand distribution taking into account a variety of server-side and user-side requirements. To this end, we propose a power Voronoi algorithm (PVA) to obtain uniform traffic volume shares per cell while simultaneously meeting the user-side and server-side requirements of the heterogeneous devices. We describe a numerical method to solve the optimization problem by updating the weights associated to different cells in the PVA. Then, we take into account minimum signal to interference plus noise ratio at all devices as a user-side requirement. It is observed that BSs are concentrated in the areas with condensed demand and high SINR requirements. To show the advantages of the proposed method, the results are compared for different SINR requirement distributions giving insight on the performance of the algorithm.
Session Chair
Mohsen Abedi (Aalto University, Finland)
Session T3-S24
Rate Control and Transport Protocol
Conference
2:00 PM
—
3:30 PM KST
Local
May 27 Wed, 10:00 PM
—
11:30 PM PDT
Bandwidth profile for multi-timescale fairness
Szilveszter Nádas (Ericsson Research, Hungary); Balazs Varga (Ericsson, Hungary); Illes Horvath (MTA-BME Information Systems Research Group); Andras Meszaros (Technical University of Budapest (BME), Hungary); Miklos Telek (Technical University of Budapest, Hungary)
0
We propose a novel approach to provide fairness on multiple timescales in the framework of core-stateless resource sharing paradigm. We illustrate the unique advantages of multi- timescale fairness. We introduce a new marking scheme, called multi-timescale bandwidth profile. It assigns drop precedence to flows based on their traffic history on multiple timescales. Additionally, we provide dimensioning guidelines for the introduced profile in an access-aggregation network scenario and present its simulation-based performance analysis.
Source Rate Control for Opportunistic Routing
Che-Jung Hsu (Fu Jen Catholic University, Taiwan); Huey-Ing Liu (Fu-Jen Catholic University, Taiwan)
0
Due to the popularity of wireless networks, opportunistic routing emerges and improves performance by utilizing the broadcast nature of wireless communication. However, without controlling source rate, capacity of bottleneck could be consumed by its neighbors and that leads to lower throughput. This work showed how source rate impacts the performance of opportunistic routing and proposed a source rate-based congestion control at layer 2 for better throughput. Simulation results showed that throughput is improved by about 35% with source rate control and fewer resources consumed.
SMS: Smart Multipath Switch for improving the throughput of Multipath TCP for Smartphones
Madhan Raj Kanagarathinam (Samsung R&D Institute India Bangalore, India); Harikrishnan Natarajan (Reliance Jio Infocomm Pvt Ltd, India); Karthikeyan Arunachalam (Samsung R&D Institute India - Bangalore, India); Sandeep Irlanki (Samsung R&D Institute & Samsung, India); Venkata Sunil Kumar (Samsung R&D India - Bangalore, India)
2
Multipath TCP (MPTCP) is an enhancement of TCP, capable of using multiple network paths to enhance the throughput and reliability. The current implementation of MPTCP does not consider wireless network characteristics. Unlike the wired networks, the path characteristic and mode of operations may vary among various wireless network interfaces dynamically. Hence we propose Smart Multipath Switch (SMS), dynamic MPTCP subflow management for the wireless network. SMS uses a learning-based approach, adapts to ad-hoc wireless conditions, thereby dynamically controls and manages the subflow in MPTCP for better user experience and network utilization. To demonstrate the effectiveness of our proposal, we performed live air experiments with the help of Samsung Galaxy S8 in different locations (Korea, Thailand, and India) and also performed simulations in our lab at Samsung Electronics, Headquarters. Our experiments show that the proposed solution provides the aggregation ratio consistently above 80%. Furthermore, the SMS, using auto-tuning logic, improves the throughput by up to 51.5% compared with legacy.
CQUIC: Cross-Layer QUIC for Next Generation Mobile Networks
Gaurav Sinha and Madhan Raj Kanagarathinam (Samsung R&D Institute India Bangalore, India); Sujith Rengan Jayaseelan (Samsung R&D Institute India - Bangalore, India); Gunjan Kumar Choudhary (Samsung Research & Development India, Bangalore, India)
2
Requirements for Next Generation Mobile Networks (NGMN) include low latency, higher throughput, scalability, and energy efficiency. As 5G millimeter wave (mmWave) band is short-range, the handover is inevitable. Google proposed QUIC (Quick UDP Internet Connection), which aims to address these challenges. However, Google QUIC (GQUIC), follows "WiFi-First" policy causing frequent network switching, which can lead to a throughput reduction and fast battery degradation. In this paper, we propose Cross-layer QUIC (CQUIC) framework, that follows "WiFi-if-best" policy to enhance the throughput and resilience by using a Cross-Layer approach. CQUIC proposes a novel migration scheme in QUIC which adapts to the dynamic network characteristics. GQUIC protocol with low bandwidth and high round-trip-time fail to migrate for seamless User Experience. CQUIC algorithm predicts Cross- Layer Score (CLS) which incorporates predicted Signal-to- Interference Noise Ratio (SINR), QUIC Bandwidth, round-trip- time (RTT) stats from QUIC Session and models the handover decision pro-actively. Compared with state-of-the-art methods such as GQUIC and HTTP (using TCP) this paper reveals the significant benefits of the proposed method. A series of experimental results obtained in live air network over Samsung Galaxy S10 devices show CQUIC outperforms the GQUIC by 20%, TCP by 36% and MPTCP (Backup) by 17% in terms of throughput. Furthermore, CQUIC compared with MPTCP, reduces the data consumption over mobile network and operates green by reducing the power consumption by 25%.
Novel MultiPipe QUIC Protocols to Enhance the Wireless Network Performance
Gunjan Kumar Choudhary (Samsung Research & Development India, Bangalore, India); Madhan Raj Kanagarathinam (Samsung R&D Institute India Bangalore, India); Karthikeyan Arunachalam and Sujith Rengan Jayaseelan (Samsung R&D Institute India - Bangalore, India); Harikrishnan Natarajan (Reliance Jio Infocomm Pvt Ltd, India); Debabrata Das (International Institute of Information Technology - Bangalore, India); Gaurav Sinha (Samsung R&D Institute India Bangalore, India)
3
To improve the performance of the Transmission Control Protocol (TCP), the Quick UDP Internet Connections (QUIC) was introduced. However, from the recent literature, in the wireless networks, QUIC does not fully utilize the link capacity, because of varying network wireless medium characteristics for an application. To the best of our knowledge, for the first time, this paper has proposed two novel protocols to overcome the wireless network's challenges, by MultiPipe (multi sessions) QUIC protocol (MP-QUIC). The two MP-QUIC's novel protocols are (i) Round Robin MP-QUIC (RR-MP-QUIC) and (ii) Cross-Layer Burst Aware MP-QUIC (CBA-MP-QUIC). In RR-MP-QUIC, multiple pipes are created between source as well as destination and assign a pipe to each object in a round-robin manner. We set up the testbed over live air commercial network. The experimental results reveal that the RR-MP-QUIC Page Load Time (PLT) of a web page decreases by 76% with respect to QUIC. Furthermore, to improve the performance of RR-MP- QUIC, we proposed CBA-MP-QUIC, which optimally creates pipes, efficiently schedules the objects and understands with respect to cross-layer (wireless channel characteristics and load in data link layer) parameters. Hence this adapts dynamically to the network conditions and maintains fairness between the applications in User Equipment (UE) and within the same application. Experimental result of CBA-MP-QUIC on live air improves the web page PLT by 143% with respect to QUIC.
Session Chair
Huey-Ing Liu (Fu Jen Catholic University, Taiwan)
Session T3-S25
Resource Management and Optimization 2
Conference
2:00 PM
—
3:30 PM KST
Local
May 27 Wed, 10:00 PM
—
11:30 PM PDT
Centralized Scheduling with Sum-Rate Optimization in Flexible Half-Duplex Networks
Shalanika Gangani Dayarathna (University of Melbourne, Australia); Mohsen Mohammadkhani Razlighi (Monash University, Australia); Rajitha Senanayake (University of Melbourne, Australia); Nikola Zlatanov (Monash University, Australia); Jamie S Evans (University of Melbourne, Australia)
0
In this paper, we focus on maximization of the instantaneous sum-rate in flexible half-duplex networks, where nodes have the flexibility to choose to either transmit, receive or be silent in a given time slot. Since the corresponding optimization problem is NP-hard, we design low-cost algorithms that give sub-optimal solutions with good performance. We first consider two existing approximation techniques to simplify the sum-rate optimization problem: arithmetic-geometric means inequality and another utilising the tight lower bound approximation. We then propose a novel pattern search algorithm that performs close to exhaustive search but with significantly lower complexity. Comparing the performance of the proposed algorithm with respect to existing resource allocation techniques, we observe that our proposed algorithm provides significant sum-rate gains.
Binary Power Optimality for Two Link Full-Duplex Network
Shalanika Gangani Dayarathna, Rajitha Senanayake and Jamie S Evans (University of Melbourne, Australia)
0
In this paper, we analyse the optimality of binary power allocation in a network that includes full-duplex communication links. Considering a network with four communicating nodes, two of them operating in half-duplex mode and the other two in full-duplex mode, we prove that binary power allocation is optimum for the full-duplex nodes when maximizing the sum rate. We also prove that, for half-duplex nodes binary power allocation is not optimum in general. However, for the two special cases, 1) the low signal-to-noise-plus-interference (SINR) regime and, 2) the approximation by the arithmetic mean-geometric mean inequality, binary power allocation is optimum for the approximated sum rate even for the half-duplex nodes. We further analyse a third special case using a symmetric network for which the optimum power allocation is binary, under a sufficient condition. Numerical examples are included to illustrate the accuracy of the results.
Resource Allocation for mMTC/H2H Coexistence with H2H's Success Probability of Data Transmission
Tao Wang, Yichen Wang and Dongyang Xu (Xi'an Jiaotong University, China); Zhangnan Wang (Xi`an Jiaotong University, China)
0
To accommodate massive machine-type communication (mMTC) in the networks originally designed for human- to-human (H2H) communication, we investigate the resource allocation for the mMTC/H2H coexisting network where the conventional random access (RA) and data transmission procedures are tailored for mMTC. The resource allocation strategy jointly consider the resource allocation of physical random access channel (PRACH) and physical uplink shared channel (PUSCH), aiming to support more MTC users while protecting the quality- of-service (QoS) of traditional H2H communication. A Markov chain is utilized to explicitly model the RA and data transmissions of H2H, and H2H's success probability of data transmission is derived under the analysis of stationary distribution. Then, we formulate a nonlinear integer programming (NLIP) problem which aims to maximize MTC throughput while guaranteeing H2H's success probability of data transmission. By solving the optimization problem with a modified particle swarm optimization method, we obtain the resource allocation strategy that achieves a balance between PRACH and PUSCH in terms of resource efficiency. Simulation results demonstrate the superiority of our proposed resource allocation strategy over traditional LTE strategy in the scenario of mMTC/H2H coexistence.
Towards Reconfigurable Intelligent Surfaces Powered Green Wireless Networks
Siyuan Sun (ShanghaiTech University, China); Min Fu (ShanghaiTech University & Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, China); Yuanming Shi and Yong Zhou (ShanghaiTech University, China)
1
The adoption of reconfigurable intelligent surface (RIS) in wireless networks can enhance the spectrum- and energy-efficiency by controlling the propagation environment. Although the RIS does not consume any transmit power, the circuit power of the RIS cannot be ignored, especially when the number of reflecting elements is large. In this paper, we propose the joint design of beamforming vectors at the base station, active RIS set, and phase-shift matrices at the active RISs to minimize the network power consumption, including the RIS circuit power consumption, while taking into account each user's target data rate requirement and each reflecting element's constant modulus constraint. However, the formulated problem is a mixed-integer quadratic programming (MIQP) problem, which is NP-hard. To this end, we present an alternating optimization method, which alternately solves second order cone programming (SOCP) and MIQP problems to update the optimization variables. Specifically, the MIQP problem is further transformed into a semidefinite programming problem by applying binary relaxation and semidefinite relaxation. Finally, an efficient algorithm is developed to solve the problem. Simulation results show that the proposed algorithm significantly reduces the network power consumption and reveal the importance of taking into account the RIS circuit power consumption.
Interference Detection and Resource Allocation in LTE Unlicensed Systems
Lifeng Lai and Daquan Feng (Shenzhen University, China); Fu-Chun Zheng (Harbin Institute of Technology, Shenzhen, China & University of York, United Kingdom (Great Britain))
0
In this paper, we consider the interference detection and resource allocation issue in Long-Term Evolution Unlicensed (LTE-U) system with carrier aggregation (CA). First, to avoid the co-channel interference between the WiFi and LTE-U users, we adopt the logistic regression method to train a classifier model for the base stations (BSs) to find the users that are susceptible to the interference from the WiFi. Then, we formulate the optimization problem with the goal to maximize the downlink (DL) throughput while guaranteeing the quality-of-service (QoS) for each user. To make the original problem more tractable, we first split it into two sequential subproblems and then propose a dual decomposition method to solve them efficiently. The numerical results show that the proposed schemes can significantly improve the overall throughput and outperform the existing schemes.
Session Chair
Rajitha Senanayake (University of Melbourne, Australia)
Session T3-S26
UAV (Unmanned Aerial Vehicle) 2
Conference
4:00 PM
—
5:30 PM KST
Local
May 28 Thu, 12:00 AM
—
1:30 AM PDT
Reducing Energy Consumed by Repositioning of Flying Base Stations Serving Mobile Users
Zdenek Becvar, Pavel Mach and Mohammadsaleh Nikooroo (Czech Technical University in Prague, Czech Republic)
1
Unmanned Aerial Vehicles (UAVs), acting as flying base stations (FlyBSs), are seen as a promising solution for future mobile networks, as the FlyBSs can serve space and time varying heterogeneous traffic in areas where deployment of conventional static base stations is uneconomical or infeasible. However, an energy consumption of the FlyBSs is a critical issue. In this paper, we target a scenario where the FlyBSs serve slowly moving users, e.g., visitors of an outdoor music festival or a performance. In such scenario, rotary-wing FlyBSs are not efficient due to a high energy consumption while not moving (given by an effect of a "helicopter" dynamics). Hence, we consider small airships or balloons. We develop a closed-form solution that determines new positions of the FlyBSs so that the energy consumption for a movement of the FlyBSs is reduced significantly (by 45-94% depending on the number of deployed FlyBSs) while sum capacity of the users is decreased only marginally (less than 1% for before-mentioned energy savings). Moreover, the proposed solution does not require any prediction of users' movement, thus, it is not affected by the prediction error or uncertainty of the users' behavior.
Efficient Deployment of UAV-powered Sensors for Optimal Coverage and Connectivity
Oktay Cetinkaya and Geoff V Merrett (University of Southampton, United Kingdom (Great Britain))
4
The Internet of Things (IoT) digitizes the physical world with wireless devices sensing their surroundings and delivering periodic notifications of parameters they are monitoring. However, this operation is bound by finite-capacity batteries, in which replenishment is practically infeasible due to the envisioned size of the IoT networks. By also considering the autonomous and self-sufficient service vision of the IoT paradigm, the need for novel approaches overcoming the energy constraints is evident. Here, unmanned aerial vehicles (UAVs) come into prominence. The UAVs can remotely energize wireless devices, via wireless power transfer (WPT), and thus guarantee reliable sensing coverage as well as longevity in the IoT domain. However, this can be only achieved by the precise alignment of both UAVs and wireless devices. Thus, this paper presents an efficient deployment strategy based on the circle packing problem, in which a lower- bound for the required number of wireless devices achieving optimal coverage is derived. The analysis, based on empirical measurements, reveals the design considerations for an energy harvesting (EH)-aided UAV scenario with regard to Federal Communications Commission (FCC) regulations, power consumption of wireless devices, and reporting frequency requirements of the IoT applications. Our results elaborate on a number of trade-offs, based on UAV, device, and medium characteristics, and provide realistic guidelines, achieving optimal coverage while meeting application requirements.
Multi-UAV Collaborative Data Collection for IoT Devices Powered by Battery
Yue Wang (Beijing University of Posts and Telecommunication, China); Xiang Ming Wen (Beijing University of posts and telecommunications, China); Zhiqun Hu (Hubei University, China); Zhaoming Lu (BUPT, China); Jiansong Miao and Chuanzhi Sun (Beijing University of Posts and Telecommunications, China); Hang Qi (Beijing University of Posts and Telecommunications & BUPT, China)
1
Due to the limited energy of the Internet of Things (IoT) device, unmanned aerial vehicle (UAV) as a mobile fusion center can effectively prolong the lifetime of IoT device via supporting communication with the device directly. Moreover, since UAV's energy constrained, it will be a good measure to take multiple UAVs to collect data from devices in large areas. In this paper, we investigate multi-UAV collaborative data collection system, where multiple UAVs collect data from two- dimensional distributed devices on flying mode or hovering mode. The objective is to minimize UAVs' total flight time while allowing each device to complete data upload successfully with limited energy. To this end, firstly, a cell partition based on Voronoi diagram is used to allocate the collection areas of each UAV. Then, in each associated area, UAV determines the whole trajectory to serve devices. Lastly, given load requirement of ground devices and energy limitation, the optimal data collection mode of each device is decided to minimize flight time of each UAV. Simulation results show that the proposed multi-UAV data collection scheme can shorten collection task completion time significantly.
Resource Allocation for UAV Assisted Wireless Networks with QoS Constraints
Weihang Ding (Kings College London, China); Zhaohui Yang (King's College London, United Kingdom (Great Britain)); Mingzhe Chen (Princeton University, USA); Jiancao Hou and Mohammad Shikh-Bahaei (King's College London, United Kingdom (Great Britain))
1
For crowded and hotspot area, unmanned aerial vehicles (UAVs) are usually deployed to increase the coverage rate. In the considered model, there are three types of services for UAV assisted communication: control message, non-realtime communication, and real-time communication, which can cover most of the actual demands of users in a UAV assisted communication system. A bandwidth allocation problem is considered to minimize the total energy consumption of this system while satisfying the requirements. Two techniques are introduced to enhance the performance of the system. The first method is to categorize the ground users into multiple user groups and offer each group a unique RF channel with different bandwidth. The second method is to deploy more than one UAVs in the system. Bandwidth optimization in each scheme is proved to be a convex problem. Simulation results show the superiority of the proposed schemes in terms of energy consumption.
Trajectory Design for Energy Harvesting UAV Networks: A Foraging Approach
Xuanlin Liu (Beijing University of Posts and Telecommunications, China); Mingzhe Chen (Princeton University, USA); Sihua Wang (Beijing University of Posts and Telecommunications, China); Walid Saad (Virginia Tech, USA); Changchuan Yin (Beijing University of Posts and Telecommunications, China)
1
In this paper, the problem of trajectory design for energy harvesting unmanned aerial vehicles (UAVs) is studied. In the considered model, the UAV acts as a moving base station to serve the ground users, while collecting energy from the charging stations located at the center of a user group. Meanwhile, to serve ground users and harvest energy, the UAV must be examined and repaired regularly. In consequence, it is necessary to optimize the trajectory design of the UAV while jointly considering the maintenance costs, the number of users that are served by the UAV, and the energy consumption and harvesting. To capture the relationship among these factors, we first model the completion of service and the harvested energy as reward, and the energy consumption during the deployment as cost. Then, the deployment profitability is defined as the reward to the cost of the UAV trajectory. Based on this definition, the trajectory design problem is formulated as an optimization problem whose goal is to maximize the deployment profitability of the UAV. To solve this problem, a foraging algorithm is proposed to find the optimal trajectory so as to maximize the deployment profitability. The proposed algorithm can find the optimal trajectory for the UAV with a polynomial time complexity. Fundamental analysis shows that the proposed algorithm can achieve the maximal deployment profitability. Simulation results show that the proposed algorithm can effectively reduce the operation time and achieve up to 25.6% gain in terms of the deployment profitability compared to Q-learning algorithm.
Session Chair
Oktay Cetinkaya (University of Southampton, United Kingdom)
Session T3-S27
Security and Privacy 2
Conference
4:00 PM
—
5:30 PM KST
Local
May 28 Thu, 12:00 AM
—
1:30 AM PDT
Post Quantum Security Solution for Data Aggregation in Wireless Sensor Networks
Aarti Agarkar (Sinhgad College of Engineering, Pune); Mandar Karyakarte (Vishwakarma Institute of Information Technology, India); Himanshu Agrawal (Swinburne University of Technology, Australia & Australia, unknown)
0
Data aggregation has been one of the most widely researched topics for Wireless Sensor Network (WSN) as it helps in increasing the effective life time of the network and reduces the packet transmission overhead. Besides other challenges, security is one of the serious challenges during data aggregation. Numerous solutions on security for data aggregation for WSN are based on homomorphic encryption technique or Elliptic Curve Cryptography (ECC) based solutions and thus are vulnerable to attacks by quantum machines. This paper presents a post-quantum security solution using lattice cryptography. The proposed solution is applying Learning with Errors over Rings (R-LWE) for encryption of data in the data aggregation process at the gateway module of WSN. Security analysis shows that the proposed scheme provides confidentiality, integrity and authenticity during communication. Performance analysis shows that the proposed scheme is lightweight and shows better performance compared to Elliptic Curve Elgamal (ECEG) cryptography based scheme and symmetric homomorphic based scheme.
Rogue Access Point Localization Leveraging Compressive Sensing via Kernel Optimization
Qiaolin Pu and Joseph Kee-Yin Ng (Hong Kong Baptist University, Hong Kong); Shijie Deng and Fawen Zhang (Chongqing University of Posts and Telecommunications, China)
1
With the pervasive infrastructures of WLAN, user's privacy has emerged as an important security and privacy problem. Rogue Access Points (AP), as one of the threat, is expected to be detected and located accurately. Therefore, in this paper, we propose a novel rogue AP localization method leveraging compressive sensing (CS) via kernel optimization. Although the CS based technique has been widely used in mobile user localization system, this is the first time to apply it to reversely localize AP. In addition, designing an appropriate kernel is the key to successful application of CS technique, however, traditional Gaussian or Bernoulli random kernels could not be utilized in rogue AP localization system, due that the kernel is related to the number and distribution of monitors, which could not randomly change every time. Hence, for CS kernel optimization, we firstly deduce the minimum number of monitors required in this system through a theoretical analysis which aims at justifying the validity of problem formulation. Then an Equiangular Tight Frame (ETF) based monitors distribution scheme is presented to achieve higher location accuracy. Finally, we perform both simulations and experiments to demonstrate the superiority of our approach as compare to other methods theoretically and practically.
MalPortrait: Sketch Malicious Domain Portraits Based on Passive DNS Data
Zhizhou Liang and Zang Tianning (Institute of Information Engineering, Chinese Academy of Sciences, China); Yuwei Zeng (University of Chinese Academy of Sciences & Institute of Information Engineering, China)
0
Malicious domain detection is of great significance for cybersecurity. Most prior works detect malicious domains based on individual features, which are only related to the attributes of domains themselves and can be easily changed to avoid detection. To solve the problem, we propose a novel system called MalPortrait, which combines individual features and association information of domains to detect malicious domains. In MalPortrait, we show the association information among domains by a domain association graph where vertices represent domains and edges connect domains resolved to the same IP. Based on the graph, we combine individual features (e.g., string-based, network-based) of each domain and its association information to generate new features. Compared with individual features, the new features are harder to be tampered with and can help determine whether a domain is malicious from a more comprehensive perspective. We evaluate MalPortrait on the passive DNS traffic collected from real-world large ISP networks. Our experimental results show that MalPortrait can accurately identify malicious domain names with a precision of 96.8% and a recall of 95.5%. Compared with prior works, MalPortrait performs better and hardly relies on additional knowledge (e.g., IP reputation, Domain whois).
Revisiting Compressive Sensing based Encryption Schemes for IoT
Gajraj Kuldeep and Qi Zhang (Aarhus University, Denmark)
1
Compressive sensing (CS) is regarded as one of the promising solutions for IoT data encryption as it achieves simultaneous sampling, compression, and encryption. Theoretical work in the literature has proved that CS provides computational secrecy. It also provides asymptotic perfect secrecy for Gaussian sensing matrix with constraints on input signal. In this paper, we design an attack decoding algorithm based on block compressed sensing decoding algorithm to perform ciphertext- only attack on real-life time series IoT data. It shows that it is possible to retrieve vital information in the plaintext under some conditions. Furthermore, it is also applied to a State-of-the- Art CS-based encryption scheme for smart grid, and the power profile is reconstructed using ciphertext-only attack. Additionally, the statistical analysis of Gaussian and Binomial measurements is conducted to investigate the randomness provided by them.
Robust Self-Protection Against Application-Layer (D)DoS Attacks in SDN Environment
Chafika Benzaid, Mohammed Boukhalfa and Tarik Taleb (Aalto University, Finland)
1
The expected high bandwidth of 5G and the envisioned massive number of connected devices will open the door to increased and sophisticated attacks, such as application- layer DDoS attacks. Application-layer DDoS attacks are complex to detect and mitigate due to their stealthy nature and their ability to mimic genuine behavior. In this work, we propose a robust application-layer DDoS self-protection framework that empowers a fully autonomous detection and mitigation of the application-layer DDoS attacks leveraging on Deep Learning (DL) and SDN enablers. The DL models have been proven vulnerable to adversarial attacks, which aim to fool the DL model into taking wrong decisions. To overcome this issue, we build a DL-based application-layer DDoS detection model that is robust to adversarial examples. The performance results show the effectiveness of the proposed framework in protecting against application-layer DDoS attacks even in the presence of adversarial attacks.
Session Chair
Aarti Agarkar (Sinhgad College of Engineering, Pune, India)
Session T3-S28
Resource Management and Optimization 3
Conference
4:00 PM
—
5:30 PM KST
Local
May 28 Thu, 12:00 AM
—
1:30 AM PDT
An Efficient QoS-Aware Computational Resource Allocation Scheme in C-RAN
Mojgan Barahman (Instituto Superior Técnico/ University of Lisbon, Portugal); Luis M. Correia (IST/INESC-ID - University of Lisbon & INESC, Portugal); Lúcio Studer Ferreira (ISTEC / ULHT COPELABS / INESC-ID, Portugal)
0
In this paper, one proposes an approach to optimize the computational resource utilization of baseband unit pools in a Cloud Radio Access Network. The problem of resource allocation is formulated and solved as a constrained nonlinear optimization one, based on the concept of bargaining in cooperative game theory. The goal is to minimize resource usage by on-demand resource allocation, per instantaneous requirements of base stations, whilst taking Quality of Service into account. In the event of a shortage of resources, implying that not all demand can be served at the same time, baseband units are prioritized with a weighting policy. Real-time requirements and the priority of services being run on a baseband unit are the two contributors in calculating the weight in a timeslot. Lower prior baseband units, however, are always guaranteed to receive a minimum of resources to prevent them from crashes. Simulation results in a heterogeneous services environment show a minimum 83% improvement in allocation efficiency, compared to a fixed resource allocation scheme based on peak-hour traffic demands. Results also confirm that, in case of a resource shortage, 100% of the resources are fairly distributed among baseband units, fairness being governed by the weight of the baseband units in the pool.
Maximum Allowable Transfer Interval Aware Scheduling for Wireless Remote Monitoring
Mounssif Krouka and Anis Elgabli (University of Oulu, Finland); Mehdi Bennis (Centre of Wireless Communications, University of Oulu, Finland)
2
In this paper, we tackle the problem of remote monitoring (e.g., remote factory) in which a number of sensor nodes are transmitting time sensitive measurements to a remote monitoring site. We assume that packets generated by different sensors have different sizes. Moreover, different sensors have different Maximum Allowable Transfer Intervals (MATIs). We consider minimizing a metric that maintains a trade-off between minimizing the average MATI violation of all sensors, and minimizing the probability that the MATI violation of each sensor exceeds a predefined threshold. We formulate the problem as a stochastic optimization problem with integer constraints. In order to solve this problem, we first relax the original intractable formulation to a tractable problem. Then, we use the Lyapunov stochastic optimization framework to solve the relaxed problem. Simulation results show that the proposed algorithm outperforms the considered baselines in terms of minimizing the probability of the MATI violation for all sensors.
User Association in Software-Defined Wi-Fi Networks for Enhanced Resource Allocation
Blas Gómez (University of Castilla-La Mancha, Spain); Estefania Coronado (Fondazione Bruno Kessler, Italy); José Villalón (UCLM, Spain); Roberto Riggio (Fondazione Bruno Kessler, Italy); Antonio Garrido (University of Castilla-La Mancha, Spain)
1
Although 4G and 5G Radio Access Technologies (RATs) aim to usher in faster connectivity that is able to cope with mobile traffic demands, this capability is sometimes hindered by poor indoor signal quality caused by distance from base stations and the materials used in the construction of buildings. These factors have led to Wi-Fi being adopted as the technology of choice in indoor scenarios. Although the deployment of Wi-Fi Access Points (APs) can be planned, the user-AP association procedure is not defined by the standard but left to the vendor's choice, which for simplicity is usually driven by signal strength. This approach leads to uneven user distributions and poor resource utilization. To overcome this rigidity, in this paper, we leverage Software-Defined Networking (SDN) to propose a joint user association and channel assignment solution in Wi-Fi networks. Our approach considers average signal strength, channel occupancy, and AP load to make better user association decisions. Experimental results have demonstrated that the proposed solution improves the aggregated goodput by 22% with respect to approaches based on signal strength. Furthermore, user level fairness is also improved.
Traffic Aware Beamformer Design for Integrated Access and Backhaul with Flexible TDD
Laddu Praneeth Roshan Jayasinghe, Antti Tölli, Jarkko Kaleva and Matti Latva-aho (University of Oulu, Finland)
0
Integrated access and backhaul (IAB) networks consist of IAB-donor, IAB-nodes, and user-equipments (UEs). Both IAB-donor and IAB-node provide access to UEs while IAB-donor and IAB-nodes exchange UEs data via wireless in-band backhaul using the same frequency-time resources shared with access links. Multi-antenna beamformer techniques can be used to mitigate the complicated cross-link interference scenarios arising from IAB systems. In this paper, an iterative beamformer design with the weighted queue minimization (WQM) objective is proposed for the time-division-duplexed (TDD) based IAB system. In the considered TDD based IAB model, in a given timeslot, IAB-nodes and IAB-donor are assumed to be different uplink (UL)/downlink (DL) transmission modes to mitigate conventional half-duplex loss. Also, the beamformer design is carried out over two timeslots, considering both UL and DL transmission at each node. Specifically, user-specific UL/DL queues are introduced at the IAB-nodes to guarantee the BS to/from UE data delivery. The proposed beamformer solution is based on the iterative evaluation of Karush-Kuhn-Tucker (KKT) conditions of the optimization problem, which can practically be implemented in both centralized and decentralized manner. The numerical examples illustrate the superior system performance of the proposed method in comparison to the conventional half- duplex relaying system.
Online Optimal Resource Allocation for SWIPT-Based Mobile Edge Computing Systems
Hamed Mirghasemi (Université Catholique de Louvain-la-Neuve, Belgium); Luc Vandendorpe (Université catholique de Louvain, Belgium); Mateen Ashraf (University Catholique de Louvain, Louvain-la-Neuve, Belgium)
0
The integration of simultaneous wireless information and power transfer (SWIPT) and mobile-edge computing (MEC) technologies is emerging as a promising technique to overcome the performance limits of ultra-low power devices (ULPD) due to their low battery capacities and their limited computation capabilities in the Internet of Things (IoT) era. In this paper, we propose an online resource allocation algorithm for multi-user SWIPT-based MEC systems with the aim of maximizing the proportional fairness computational utility function subject to the stability of task and energy queues. Lyapunov optimization framework is used to jointly optimize the amounts of time allocated for energy harvesting, information decoding and offloading, the transmission power for offloading and CPU-cycles frequencies for local computing. Moreover, rigorous performance analysis has been done to prove the asymptotic optimality of our proposed algorithm. Simulation results are also presented to demonstrate the gains of our proposed algorithms over alternative online approaches and the impact of different network parameters on the performance of our algorithm.
Session Chair
Hamed Mirghasemi (Université Catholique de Louvain-la-Neuve, Belgium)
Session T3-S29
Multi-Connectivity
Conference
4:00 PM
—
5:30 PM KST
Local
May 28 Thu, 12:00 AM
—
1:30 AM PDT
Design and Analysis for Dual Connectivity and Raptor Codes Assisted Handover in Vehicular Networks
Mingcheng He, Cunqing Hua and Pengwenlong Gu (Shanghai Jiao Tong University, China)
0
A salient feature of the vehicular networks is the high mobility of the vehicles, which makes it a challenging issue to provide seamless handover using the conventional dedicated short range communication (DSRC) or cellular network technologies (e.g., 3G/4G). In this paper, we consider the adoption of the dual connectivity (DC) architecture in the vehicular network, which allows the user equipment (UE) to connect simultaneously to a master eNB (MeNB) and a secondary eNB (SeNB), and thus simplifies the signaling and provides enhanced mobility support. To further improve the performance, we propose a raptor codes based dual connectivity (RCDC) scheme, which can effectively address the out-of-order packet delivery problem in the DC scheme, and the coordination between the MeNB and SeNB is significantly reduced. We develop queueing models to characterize the delay performance of the DC and the RCDC schemes by taking into account the handover events in vehicular networks. Simulation results are provided to illustrate the performance of these two schemes under different vehicular network settings, which can prove that the RCDC scheme is more adaptable for the vehicle network with handover events.
Mesh Architecture for Efficient Integrated Access and Backhaul Networking
Bangzhao Zhai, Mengxin Yu, Aimin Tang and Xudong Wang (Shanghai Jiao Tong University, China)
1
Integrated access and backhaul (IAB) networking is envisioned as a key technology to support more flexible and dense deployment of base stations (BSs). However, existing directed acyclic graph (DAG) based IAB networking highly limits the flexibility and efficiency of link scheduling, due to the fixed parent-to-child relation between two adjacent IAB nodes. In this paper, a mesh-architecture based approach is developed to improve the efficiency of IAB networking. The key idea of the mesh architecture is to make the relationship between two adjacent IAB nodes configurable. Based on the mesh architecture, the two-stage scheduling scheme of IAB networks is revised. The typical scenarios where the mesh-architecture based IAB networking outperforms the DAG-based one are analyzed. Simulation results show that the mesh-architecture based IAB networking can effectively improve the throughput by 6.70%-40.56% and substantially reduce the delay under various traffic loads, as compared to the DAG-based IAB networking.
Evaluation of Multi-Connectivity Schemes for URLLC Traffic over WiFi and LTE
Marie-Theres Suer (TU Braunschweig & Robert Bosch GmbH, Germany); Christoph Thein and Hugues Tchouankem (Robert Bosch GmbH, Germany); Lars C Wolf (Technische Universität Braunschweig, Germany)
0
Emerging applications such as wireless industrial control or robotics raise strict requirements in terms of latency and reliability on wireless communication systems. It is still an open issue which wireless communication system can be used to enable industrial applications such as closed-loop control. A promising approach to improve latency and reliability of wireless communications is multi-connectivity (MC), i.e. using multiple communication paths simultaneously. Different scheduling schemes can be used to distribute the traffic over multiple links. The characteristics of these schemes and which one is best suited to enable reliable low-latency communications in different scenarios needs to be investigated. In this paper, we evaluate the latency and reliability performance of a local Wi-Fi and a private LTE network for traffic patterns as envisioned for industrial applications. Moreover, we assess the performance of different MC scheduling schemes operating on Application Layer over these two wireless links with focus on reliability and latency metrics. For the evaluated single-user scenario, WiFi provides a lower mean latency than LTE. The evaluation of MC scheduling schemes shows that packet duplication (PD) stabilizes the latency by mitigating outliers, while load balancing (LB) reduces the latency of nearly 50 percent of packets in a scenario with bad radio conditions. Our results suggest that using links with similar mean latency would be beneficial for all scheduling schemes.
Online Control of Traffic Split and Distributed Cell Group State Decisions for Multi-connectivity
Sunghoon Jung and Saewoong Bahk (Seoul National University, Korea (South))
1
This paper considers the problem of joint control of traffic split and cell group state decision for downlink communication via multi-connectivity in a cellular network. In this problem, a master node makes a decision on traffic split every T slots, and each secondary base station determines its cell group state between ‘activated’ and ‘deactivated’ to save UE power consumption. To ensure independent control of each cell group through its hosting base station, cell group state decision should be independent of each other, evolving asynchronously cell group state across cell groups. State decision for each cell group is performed dynamically according to changing environments. Such aperiodic state decision and asynchronous state evolution cause considerable difficulty in developing algorithms to solve the problem. To overcome the difficulties, we employ a frame- based Lyapunov optimization framework with variable frame sizes and develop online algorithms that are simple to implement but provably provide near optimal values. Simulation results are shown that our algorithm outperforms the other competitive schemes.
Multi-Connectivity for Reliable Wireless Industrial Communications: Gains and Limitations
Ali Haider Mahdi (Technische Universität Dresden, Germany); Tom Hößler (TU Dresden & Barkhausen Institut, Germany); Norman Franchi and Gerhard P. Fettweis (Technische Universität Dresden, Germany)
0
Realizing wireless mission-critical applications in industry, such as closed-loop control, necessitates ultra-reliable low-latency communications (URLLC) to achieve error-free message transmission with hard real-time requirements. Recently, multiconnectivity (MC) has been introduced as a promising scheme to ensure URLLC in Industry 4.0. However, implementing MC in mobile industrial communications rises multiple technical challenges, such as avoiding degradation in reliability due to fading and the shadowing effect, and managing multiple links in parallel which increases signaling overhead dramatically. To deal with these challenges, this paper investigates the gains and limitations of implementing MC in industrial wireless communications. It studies conflicting optimization problems using MC based on different radio parameters. Also, a link management scheme is introduced for MC to reduce the signaling overhead based on different radio parameters. The simulation results demonstrate gains and limitations of using MC and the selected parameters (frequency reuse factor, number of users, and frequency band) on the reliability and the signaling overhead in industrial communications.
Session Chair
Aimin Tang (Shanghai Jiao Tong University, China)