Multi-Task Mapping and Resource Allocation Mechanism in Software Defined Sensor Networks
Lishui Chen, Dapeng Wu, Zhidu Li · 2020
Traditional wireless sensor network (WSN) is deployed based on specific task lacking of flexibility and ability to process and compute multi-task in parallel, which usually leads to deploy redundant WSNs for diversified Internet of things (IoT) requirements. In order to solve the problem, a software defined wireless sensor network (SDWSN) resource scheduling and mapping mechanism is proposed for multi-task scenarios in WSNs. In particular, SDWSN is introduced to support diversified IoT applications on a same WSN by abstracting the physical resources into logical ones. In order to fully explore the resources of WSN, a network virtual layer is set between data layer and control layer of the SDWSN through FlowVisor, which can enable a sensor node in SDWSN to process and compute multi-task in parallel. In addition, a dynamic alliance is establish for each task through the non-linear weight discrete particle swarm (NWDPSO) algorithm to complete resource mapping from logical network to physical network. The results show that the proposed multi-task resource scheduling and mapping mechanism can not only improve resource utilization and load balancing, but also reduces network energy consumption and task completion time.