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Repeated game theory-based reducer selection strategy for energy management in SDWSN
Computer Networks ( IF 4.4 ) Pub Date : 2021-04-10 , DOI: 10.1016/j.comnet.2021.108094
S. Suja Golden Shiny , S. Sathya Priya , K. Murugan

The sensor-generated data by Internet of Things are considered to be the most common source of big data. A wide range of applications are relying on these data for analytics. While a considerable amount of data is sufficient for the application users to get valuable insights, sending vast amount of data to the cloud seems inappropriate and it only increases the communication cost in the network. It is well-known that an increase in communication cost increases energy depletion in the network. Since sensor nodes have a restricted power supply, it is necessary to harness the energy of nodes to prolong the network lifetime. In this paper, a solution for energy management of sensor nodes is proposed by integrating the software defined framework with the sensor network, software defined wireless sensor networks (SDWSN), that aids in processing the data inside the network before transferring it to the sink node. To this context, a game model has been formulated for selecting the appropriate nodes as reducers which will execute the reducer function. The software defined network (SDN) controller, geographically placed outside of the wireless sensor network, is responsible for selecting the reducers and dynamically load reducing function on them. Based on the selection, a routing protocol, routing via respective reducer (RVRR), that forwards data packets via in-network processing path and control packets via common path has been proposed. This remarkably reduces the communication cost, thereby prolonging the lifetime of the deployed network. The RVRR algorithm is implemented in NS-3 simulator to evaluate the performance of proposed work in SDWSN environment.



中文翻译:

基于重复博弈论的SDWSN能源管理减速器选择策略

物联网由传感器生成的数据被认为是大数据的最常见来源。大量的应用程序都依赖这些数据进行分析。尽管大量数据足以使应用程序用户获得有价值的见解,但将大量数据发送到云似乎并不适当,这只会增加网络中的通信成本。众所周知,通信成本的增加会增加网络中的能量消耗。由于传感器节点的电源受到限制,因此有必要利用节点的能量来延长网络寿命。本文通过将软件定义的框架与传感器网络,软件定义的无线传感器网络(SDWSN)集成在一起,提出了一种传感器节点能量管理的解决方案。有助于在将数据传输到接收器节点之前处理网络内部的数据。为此,已经制定了一种游戏模型,用于选择适当的节点作为减速器,以执行减速器功能。地理上位于无线传感器网络外部的软件定义网络(SDN)控制器负责选择减速器并在其上动态减少负载功能。基于该选择,已经提出了一种路由协议,该路由协议经由相应的reducer(RVRR)进行路由,该路由协议经由网络内处理路径转发数据分组并且经由公共路径转发控制分组。这显着降低了通信成本,从而延长了部署网络的寿命。RVRR算法在NS-3仿真器中实现,以评估SDWSN环境中拟议工作的性能。

更新日期:2021-04-14
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