Complex wireless sensor network applications as those in Internet of Things or in-network processing are pushing the requirements for energy efficiency and data processing drastically. Executing the tasks of such complex applications in a single node may lead it to die soon, since the nodes in WSNs are usually with limited and generally irreplaceable power sources. How to distribute the tasks across the network and simultaneously balance the energy consumption of each node to achieve energy efficiency and to extend the network lifetime are crucial and urgent requirements in WSNs. Energy-aware task allocation (sometimes also called workload distribution) technologies, which have been deeply studied in multiprocessor systems, grid computing, and system on chip (SoC), are attracting the attention of the research community in WSNs. Due to the limited energy source and computing capability as well as the wireless communication, the task allocation problem in WSNs is different from traditional wired systems. This chapter provides an application-level taxonomy and an in-depth review of task allocation approaches in WSNs. It enables the readers to gain a clear view of current task allocation approaches, by taking the evaluation metrics and the modeling methods of the problem into account.
|Title of host publication||Mission-Oriented Sensor Networks and Systems: Art and Science. Volume 1: Foundations|
|Editors||Habib M. Ammari|
|Publication status||Published - 2019|
|Name||Studies in Systems, Decision and Control|