Leveraging evolutionary multiobjective games for configuring cloud-integrated body sensor networks

Body-in-the-Cloud (BitC) is a cloud-integrated architecture for body sensor networks (BSNs). This paper studies an evolutionary game theoretic algorithm to configure BSNs in an adaptive and stable manner. BitC allows BSNs to adapt their configurations (sensing intervals and sampling as well as data transmission intervals) to operational conditions (e.g., data request patterns) with respect to multiple performance objectives such as resource consumption and data yield. BitC theoretically guarantees that each BSN performs an evolutionarily stable configuration strategy, which is an equilibrium solution under given operational conditions. Simulation results verify this theoretical analysis; BSNs seek equilibria to perform adaptive and evolutionarily stable configuration strategies.