Bargaining Solution-Based Resource Allocation Scheme for Cloud-Assisted Wireless Body Area Networks

Abstract

Wireless body area network (WBAN) is an emerging technology that has enormous potentials for continuous health monitoring of various diseases. For different medical and healthcare applications, the collected physiological data from multiple WBANs are further transmitted to the remote medical cloud servers. However, several technical issues and challenges are associated with the integration of WBANs and cloud computing services. In this study, we develop a new cloud-assisted WBAN control scheme to effectively use the limited system resource. By employing the main ideas of Generalized Gini and Choquet bargaining solutions, our approach unfolds into dual stages of bargaining processes while increasing the flexibility and adaptability. In particular, we consider the unique features of cloud-assisted WBAN applications and provide a generalized fair-efficient solution for the resource allocation problem. Numerical simulation results demonstrate that we can verify the superiority of our proposed scheme over the existing protocols. Lastly, major further challenges and future research directions about the cloud-assisted WBAN paradigm are summarized and discussed.