{"title":"An Energy-Efficient Distributed Adaptive Cooperative Routing in Wireless Multimedia Sensor Networks","authors":"Jian Liu, Denghui Wang, Junhui Zhao","doi":"10.1109/ICCSN.2019.8905401","DOIUrl":null,"url":null,"abstract":"Since WMSN is rich in perceptual data, complex in processing tasks and powerful in network functions, it also puts forward higher requirements for QoS of WMSN. However, since WMSN is heterogeneous and the energy distribution is not uniform, many existing routing protocols do not take energy consumption into account while ensuring QoS. Therefore, how to make energy distributed more efficiently while ensuring QoS has become a challenge. This paper proposes an energy-efficient distributed adaptive cooperative routing to guarantee QoS and balance energy consumption in WMSN. By adaptively selecting some nodes for reinforcement learning to acquire their performance knowledge of reliability and delay, an optimal alternative path can be created to ensure both the QoS and balanced energy distribution. The simulation results show that the energy consumption is reduced by 20% while ensuring QoS compared with the traditional cooperative protocol and the distributed adaptive cooperative routing protocol.","PeriodicalId":330766,"journal":{"name":"2019 IEEE 11th International Conference on Communication Software and Networks (ICCSN)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE 11th International Conference on Communication Software and Networks (ICCSN)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCSN.2019.8905401","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
Since WMSN is rich in perceptual data, complex in processing tasks and powerful in network functions, it also puts forward higher requirements for QoS of WMSN. However, since WMSN is heterogeneous and the energy distribution is not uniform, many existing routing protocols do not take energy consumption into account while ensuring QoS. Therefore, how to make energy distributed more efficiently while ensuring QoS has become a challenge. This paper proposes an energy-efficient distributed adaptive cooperative routing to guarantee QoS and balance energy consumption in WMSN. By adaptively selecting some nodes for reinforcement learning to acquire their performance knowledge of reliability and delay, an optimal alternative path can be created to ensure both the QoS and balanced energy distribution. The simulation results show that the energy consumption is reduced by 20% while ensuring QoS compared with the traditional cooperative protocol and the distributed adaptive cooperative routing protocol.