Reference Architecture for Self-adaptive Management in Wireless Sensor Networks

Self-adaptive component-based architectures facilitate the building of systems able of dynamically adapting to varying execution contexts. Such a dynamic adaptation is particularly relevant in the domain of wireless sensor networks (WSNs), where numerous and unexpected changes of the execution context prevail. In this paper, we introduce a reference architecture for WSNs in order to contribute to middleware development for enabling self-adaptive behavior in service-oriented WSNs. This reference architecture follows the autonomic computing model MAPE-K, for making decisions aiming to attend self-adaptive WSN requirements. At the end of this paper, we present a case study to explain how instantiate our reference architecture in order to create a specific concrete middleware for WSN.