{"title":"Multi-hop energy-efficient routing protocol based on Minimum Spanning Tree for anisotropic Wireless Sensor Networks","authors":"Messous Sana, Liouane Noureddine","doi":"10.1109/ASET.2019.8871032","DOIUrl":null,"url":null,"abstract":"Wireless sensor network (WSN) is composed of many tiny sensor nodes deployed in isolated areas and planned to work for WSN research interest. These sensor nodes have several resource constraints such as limited battery power. Besides, sensing and communications tasks consume energy, so a power management using optimized routing methods may effectively extend node's operational time. Routing in Wireless Sensor Networks have received an increased interest by researchers and have been developed with different characteristics according to the exigence of application, the architecture of network, and specially the metric used to route packets (distance of path or number of hops, etc). The selection of an appropriate routing protocol is important since a well-designed routing protocol will increase transmission efficiency and maximize the overall network lifetime. A critical aspect of applications based on wireless sensor networks is their lifetime. In this paper, a new routing protocol strategy for wireless sensor nodes communications suitable for both isotropic and anisotropic networks distributions is proposed. This approach focuses on the minimum number of hops of each node to discover the optimal paths inserting them in its routing table. The main idea of this algorithm comes from the Minimum Spanning Tree (MST) graph theory with a modification of Prim's algorithm. Further, the simulation results show that our proposed approach significantly performs in terms of minimization of the number of individual transmissions in a random sensor network for both isotropic and anisotropic sensing area.","PeriodicalId":216138,"journal":{"name":"2019 International Conference on Advanced Systems and Emergent Technologies (IC_ASET)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 International Conference on Advanced Systems and Emergent Technologies (IC_ASET)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ASET.2019.8871032","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
Wireless sensor network (WSN) is composed of many tiny sensor nodes deployed in isolated areas and planned to work for WSN research interest. These sensor nodes have several resource constraints such as limited battery power. Besides, sensing and communications tasks consume energy, so a power management using optimized routing methods may effectively extend node's operational time. Routing in Wireless Sensor Networks have received an increased interest by researchers and have been developed with different characteristics according to the exigence of application, the architecture of network, and specially the metric used to route packets (distance of path or number of hops, etc). The selection of an appropriate routing protocol is important since a well-designed routing protocol will increase transmission efficiency and maximize the overall network lifetime. A critical aspect of applications based on wireless sensor networks is their lifetime. In this paper, a new routing protocol strategy for wireless sensor nodes communications suitable for both isotropic and anisotropic networks distributions is proposed. This approach focuses on the minimum number of hops of each node to discover the optimal paths inserting them in its routing table. The main idea of this algorithm comes from the Minimum Spanning Tree (MST) graph theory with a modification of Prim's algorithm. Further, the simulation results show that our proposed approach significantly performs in terms of minimization of the number of individual transmissions in a random sensor network for both isotropic and anisotropic sensing area.