Traffic-Aware Efficient Mapping of Wireless Body Area Networks to Health Cloud Service Providers in Critical Emergency Situations

Abstract

In a post-disaster situation, increased concentration of patients in an area increases the traffic load of the network significantly, which degrades its performance with respect to mapping cost and network throughput. Therefore, to manage the increased traffic load and to provide ubiquitous medical services, we propose a disease-centric health-care management system using wireless body area networks (WBAN) in the presence of multiple health-cloud service providers (H-CSP). The theory of Social Network Analysis (SNA) is adopted to optimize the computational complexity and the traffic load of the network in an area, considering different disease types and the criticality indices of the WBANs. In such a scenario, Disease-centric Patient Group (DPG) formation among coexisting WBANs ensures optimized traffic load and reduced computational complexity. However, the formation of DPG alone is not sufficient to provide Quality-of-Service (QoS) to each WBAN. Therefore, to address these issues, we formulate a pricing model for the efficient mapping of critical WBANs from a DPG to a H-CSP to optimize the expected packet delivery delay and the network throughput. Consequently, to identify the critical WBANs from a DPG, we design a decision parameter based on an assortment of selection parameters. The performance of the Efficient Healthcare Management (HCM) scheme is analyzed based on distinct measures such as cost effectiveness, service delay, and throughput. Simulation results exhibit significant improvement in the network performance over the existing schemes.