{"title":"Network Path Capability Identification and Performance analysis of Mobile Ad hoc Network","authors":"M. Patsariya, A. Rajavat","doi":"10.1109/CSNT48778.2020.9115772","DOIUrl":null,"url":null,"abstract":"In real time communication network capability measuring are crucial tasks because every resource of network is frequently change their state. In the mobile ad hoc network, link capacity utilization computation is very challenging task due to network topology frequently change, that totally depends on their network structure. So that in the ad hoc scenario all the network capacity utilization measure at end of simulation, where include the entire sub graph that will perform communication in any time. In the preceding some author calculates energy utilization, network congestion status and enhances the routing strategies. Through those work here we take every parameter that depends on the communication and find out the utilization, such parameters are network bandwidth, mobile node processing power, buffer, energy and signal strength utilization with respect to communication path between source to receiver. In this paper some of network parameter are initialize constant manner such as node initial energy, channel, buffer size, processing power that prefix and rest of parameter i.e. bandwidth, signal strength dynamically define at the time of communication. After that while communication start than all the parameter utilize that calculate with respect to complete path from source to destination. The utilize parameter apply into the fuzzy classification and calculate class level of particular complete path in ‘low’, ‘medium’, ‘high’ level that helps to identify the network capability utilization. The result section shows identification of network path resource utilization in terms of bandwidth, energy, signal strength, buffer and processing power and impacts of these parameter based on packet delivery fraction, routing load, throughput, no. of data sends, receives and energy consumption etc.","PeriodicalId":131745,"journal":{"name":"2020 IEEE 9th International Conference on Communication Systems and Network Technologies (CSNT)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE 9th International Conference on Communication Systems and Network Technologies (CSNT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CSNT48778.2020.9115772","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
In real time communication network capability measuring are crucial tasks because every resource of network is frequently change their state. In the mobile ad hoc network, link capacity utilization computation is very challenging task due to network topology frequently change, that totally depends on their network structure. So that in the ad hoc scenario all the network capacity utilization measure at end of simulation, where include the entire sub graph that will perform communication in any time. In the preceding some author calculates energy utilization, network congestion status and enhances the routing strategies. Through those work here we take every parameter that depends on the communication and find out the utilization, such parameters are network bandwidth, mobile node processing power, buffer, energy and signal strength utilization with respect to communication path between source to receiver. In this paper some of network parameter are initialize constant manner such as node initial energy, channel, buffer size, processing power that prefix and rest of parameter i.e. bandwidth, signal strength dynamically define at the time of communication. After that while communication start than all the parameter utilize that calculate with respect to complete path from source to destination. The utilize parameter apply into the fuzzy classification and calculate class level of particular complete path in ‘low’, ‘medium’, ‘high’ level that helps to identify the network capability utilization. The result section shows identification of network path resource utilization in terms of bandwidth, energy, signal strength, buffer and processing power and impacts of these parameter based on packet delivery fraction, routing load, throughput, no. of data sends, receives and energy consumption etc.