Performance Analysis of IEEE 802.15.6-Based Coexisting Mobile WBANs With Prioritized Traffic and Dynamic Interference

Yuan, Xiaoming; Li, Changle; Ye, Qiang; Cheng, Nan; Zhang, Ning; Shen, Xuemin

doi:10.1109/twc.2018.2848223

Cited by 40 publications

(19 citation statements)

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“…With flexibility, scalability and low-cost characteristics, WBAN technology has been envisioned as one of the primary technologies for the e-Health Internet of Things (IoT) [9], [10]. WBAN has been widely deployed in densely populated scenarios, like wards and waiting rooms in hospitals [11].…”

Section: Preliminaries a Related Workmentioning

confidence: 99%

Edge-Enabled WBANs for Efficient QoS Provisioning Healthcare Monitoring: A Two-Stage Potential Game-Based Computation Offloading Strategy

et al. 2020

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Wireless Body Area Network (WBAN) as one of the primary Internet of Things (IoT) provides real time and continuous healthcare monitoring and has been widely deployed to improve the quality of peoples' life. In edge-enabled WBANs, intensive computing tasks could be offloaded to Mobile Edge Computing (MEC) servers, guaranteeing that the massive amount of health data with different user priorities could be processed in lower delay and energy consumption. Efficient computation offloading schemes are more critical to satisfy the massive data access and personalized service requirements for multiple Quality of Service (QoS) parameters constraint WBANs. In this paper, we propose a Two-Stage Potential Game based Computation Offloading Strategy (TPOS) to optimize resource allocation while taking into consideration the task priorities and user priorities of WBANs. Firstly, we construct a system utility maximization problem about the QoS of tasks. The reward, cost and penalty functions are given to model the computation offloading. Then, we propose a two-stage optimization method to solve the problem of mutual restriction strategies existing in the strategy space of the potential game model, reducing the computation complexity and improving the feasibility of the algorithm. Finally, performance evaluations on average processing delay, energy consumption and network utility are conducted to show the significance of the proposed TPOS algorithm. INDEX TERMS WBAN, edge computing, computation offloading, potential game, healthcare monitoring.

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Section: Preliminaries a Related Workmentioning

confidence: 99%

Edge-Enabled WBANs for Efficient QoS Provisioning Healthcare Monitoring: A Two-Stage Potential Game-Based Computation Offloading Strategy

et al. 2020

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“…After PTE, WSNC identifies the critical information controller to initiate the fast forwarding and process controller forwards the packets in the quickest and shortest route. To predict the fast packet transmission path, several researchers developed various routing algorithms [9][10][11].…”

Section: Literature Reviewmentioning

confidence: 99%

Optimal packet routing for wireless body area network using software defined network to handle medical emergency

Manickavasagam¹,

Amutha²,

Priyanka³

2020

IJECE

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<span lang="EN-US">The packet forwarding node selection is one of the main constraints in the Software Defined Network (SDN). To improve the network performance, the SDN controller has to choose the shortest and optimised path between source and destination in routine and emergency packet transmission. In e-health service, information of the emergency patient has to be transferred immediately to remote hospitals or doctors by using efficient packet routing approach in Wireless Body Area Network (WBAN). In WBAN, to improve the packet transmission, the optimal packet routing policy developed based on packets priority with the support of a greedy algorithm for SDN. The SDN Controller selects the forwarding node based on node propagation delay and available bandwidth between two forwarding nodes. The mesh network topology network created for implementation, implementation results are compared with existing research works. Finally, this algorithm implemented in our institution, Software defined communication testbed laboratory (SDCTestbed Lab) with the support of 13 Zodiac-Fx (Forwarding device), 2 Raspberry-Pi3 B+ Model (host) and Arduino kit (sensor node).</span>

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“…With the rapid development of social economy and the process of industrialization, the number of vehicles has been growing rapidly in cities [1]- [5]. However, owing to limited capacity, roads become crowded, which leads to a series of issues, e.g., traffic accident, environmental pollution.…”

Section: Introductionmentioning

confidence: 99%

Delay-Optimized V2V-Based Computation Offloading in Urban Vehicular Edge Computing and Networks

Chen

Liu

et al. 2020

IEEE Access

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The Internet of Vehicles (IoV) is an emerging paradigm, driven by recent advancements in vehicular communications and networking. Meanwhile, the capability and intelligence of vehicles are being rapidly enhanced, and this will have the potential of supporting a plethora of new exciting applications, which will integrate fully autonomous vehicles, the Internet of Things (IoT), and the environment. In view of the delay-sensitive property of these promising applications, as well as the high expense by using infrastructures and roadside units (RSU), the task offloading among vehicles has gained enormous popularity considering its free-of-charge and timely response. In this paper, by utilizing the gathering period of vehicles in urban environment due to stopped by traffic lights or Area of Interest (AOI), a task offloading scheme merely relying on vehicle-to-vehicle (V2V) communication is proposed by fully exploring the idle resources of gathered vehicles for task execution. Through formulating the task execution as a Min-Max problem among one task and several cooperative vehicles, the task executing time is optimized with the Max-Min Fairness scheme, which is further solved by the Particle Swarm Optimization (PSO) Algorithm. Extensive simulation demonstrate that our model could well meet the delay requirement of delay-sensitive application by cooperative computing among vehicles. INDEX TERMS Internet of vehicle, computing offloading, low latency, task allocation. LEI LIU (Student Member, IEEE) received the B.Eng. degree in communication engineering from Zhengzhou University, Zhengzhou, China, in 2010, and the M.Sc. degree in communication engineering from Xidian University, Xi'an, China, in 2013. He is currently pursuing the Ph.D. degree with Xidian University. He has published more than ten journals and conference publications. His research interests include vehicular ad hoc networks, intelligent transportation, mobile edge computing, and the Internet of Thing.

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Performance Analysis of IEEE 802.15.6-Based Coexisting Mobile WBANs With Prioritized Traffic and Dynamic Interference

Cited by 40 publications

References 42 publications

Edge-Enabled WBANs for Efficient QoS Provisioning Healthcare Monitoring: A Two-Stage Potential Game-Based Computation Offloading Strategy

Edge-Enabled WBANs for Efficient QoS Provisioning Healthcare Monitoring: A Two-Stage Potential Game-Based Computation Offloading Strategy

Optimal packet routing for wireless body area network using software defined network to handle medical emergency

Delay-Optimized V2V-Based Computation Offloading in Urban Vehicular Edge Computing and Networks

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