Resource Scheduling Strategy In Software-Defined Wireless Sensor Network

Wreless sensor network(WSN)consists of a series of miniature sensor nodes capable of monitoring physical and environmental factors,which is widely used in smart grid and environmental monitoring.However,traditional wireless sensor networks are deployed based on specific tasks,multiple networks of different vendors are deployed independently in the same monitoring area,so that resources cannot be shared with each other,and limited node resources cannot be effectively reused,resulting in low resource utilization.In addition,the sensor network,as the underlying access network of the Internet of Things,faces problems such as network heterogeneity,diversification of application scenarios,and dynamic changes in task requests.Therefore,how to meet different task requirements and improve resource utilization through flexible and scalable network architecture and reasonable resource scheduling strategy in the case of limited resources,heterogeneous networks and time-varying tasks is of great significance.Firstly,the inherent challenges and research significance of software-defined wireless sensor networks are introduced,current research hotspots are analyzed,and the typical architecture of software-defined wireless sensor networks is given;In addition,the resource scheduling mechanism in wireless sensor network and the resource scheduling strategy of software-defined wireless sensor network are described in detail.The characteristics of the existing scheduling mechanism are analyzed and summarized in depth.Secondly,in order to fully utilize the existing network resources and flexibly respond to the changes of network topology,software-defined networks(SDN)is introduced into WSN,and a resource scheduling strategy in hierarchical software defined wireless sensor networks(SDWSN)for multi-task concurrency scenarios is proposed.Decoupling control layer and data layer by SDN,WSN can flexibly schedule network resources and accomplish multiple tasks at the same time,and minimizing network total energy consumption under the premise of ensuring data quality;In addition,the software-defined master node can obtain the changes of network structure in time,and then implement intra-cluster resource scheduling strategy by cluster heads,which improves optimization efficiency and reduces energy consumption.The results show that the proposed global network resource scheduling strategy can improve energy efficiency and the utilization ofnetwork resources,intra-cluster resource scheduling reduces the control overhead of the master node while efficiently solving network dynamic events.Thirdly,in order to solve the problem of network heterogeneity,task time-varying and resource reuse,a virtualized software defined wireless sensor network resource scheduling and mapping mechanism is proposed for multi-task scenarios in the Internet of Things.A network virtual layer is created between data layer and control layer of the SDWSN through Flow Visor,and the logical network is divided into slices to share the underlying heterogeneous network resources for different tasks.In addition,a dynamic alliance is established for each task through the non-linear weight discrete particle swarm optimization(NWDPSO)algorithm to complete resource mapping from logical network to physical network.The results show that the resource scheduling mechanism improves resource utilization and load balancing,and reduces network energy consumption and task completion time.Finally,the research work of this paper is summarized,and the future research direction is prospected.