Andrea Seraghiti, S. Delpriori, E. Lattanzi, A. Bogliolo
{"title":"Self-adapting maxflow routing algorithm for WSNs: practical issues and simulation-based assessment","authors":"Andrea Seraghiti, S. Delpriori, E. Lattanzi, A. Bogliolo","doi":"10.1145/1456223.1456361","DOIUrl":null,"url":null,"abstract":"Autonomous wireless sensor networks are subject to power, bandwidth, and resource limitations that can be represented as capacity constraints imposed to their equivalent flow networks. The maximum sustainable workload of a sensor net work (i.e., the maximum data flow from the sensor nodes to the collection point which is compatible with the capacity constraints) is the maxflow of the flow network.\n This paper presents a self-adapting maxflow routing algorithm which is able to route any sustainable workload while automatically adapting to time-varying operating conditions. The algorithm has been implemented on top of OMNeT++ [1] in order to address practical issues and to enable simulation-based assessment and design exploration Simulation results demonstrate the effectiveness and the applicability of the proposed approach","PeriodicalId":309453,"journal":{"name":"International Conference on Soft Computing as Transdisciplinary Science and Technology","volume":"46 3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Soft Computing as Transdisciplinary Science and Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/1456223.1456361","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
Autonomous wireless sensor networks are subject to power, bandwidth, and resource limitations that can be represented as capacity constraints imposed to their equivalent flow networks. The maximum sustainable workload of a sensor net work (i.e., the maximum data flow from the sensor nodes to the collection point which is compatible with the capacity constraints) is the maxflow of the flow network.
This paper presents a self-adapting maxflow routing algorithm which is able to route any sustainable workload while automatically adapting to time-varying operating conditions. The algorithm has been implemented on top of OMNeT++ [1] in order to address practical issues and to enable simulation-based assessment and design exploration Simulation results demonstrate the effectiveness and the applicability of the proposed approach