Abstract
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.
Highlights
Wireless Body Area Network (WBAN) is a kind of wireless communication networks centered on the human body, which can collect physiological, behavioral and other health-related data in real time through multiple medical sensor nodes arranged on the surface, inside or near the human body [1]
We propose a Two-Stage Potential Game based Computation Offloading Strategy (TPOS) for WBANs, which separates the strategy space in the game decision by stages
In this paper, we have proposed a Two-Stage Potential Game based Computation Offloading Strategy (TPOS) for WBANs with considering the task priorities and user priorities
Summary
Wireless Body Area Network (WBAN) is a kind of wireless communication networks centered on the human body, which can collect physiological, behavioral and other health-related data in real time through multiple medical sensor nodes arranged on the surface, inside or near the human body [1]. Stymied by the restriction of energy and different delays of various user priorities (UP) data in WBAN, the effective computation offloading strategies are transforming into the multi-objective collaborative optimization problems. We conduct the offloading and unloading decisions and allocate different local and server computing resources to tasks of certain WBANs with different UPs. The two-stage optimization improves the feasibility of the algorithm. We model the resource allocation problem of different tasks in different WBANs as multi-user game problem. They play games as game players to determine the amount of computing resources and communication resources acquired. We use a potential game to solve resource allocation and offload decision problems. The maximum computing resources of WBAN and MEC are represented by FnW and FM , and FM is much larger than FnW
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