{"title":"一种提高移动ADHOC网络能效和性能的最小-最大调度负载均衡方法","authors":"Venkatachalapathy K, Sundaranarayana D","doi":"10.2139/ssrn.3416460","DOIUrl":null,"url":null,"abstract":"Energy efficiency and traffic management in Mobile Ad hoc Networks (MANETs) is a complex process due to the self-organizing nature of the nodes. Quality of service (QoS) of the network is achieved by addressing the issues concerned with load handling and energy conservation. This manuscript proposes a min-max scheduling (M2S) algorithm for energy efficiency and load balancing (LB) in MANETs. The algorithm operates in two phases: neighbor selection and load balancing. In state selection, the transmission of the node is altered based on its energy and packet delivery factor. In the load balancing phase, the selected nodes are induced by queuing and scheduling the process to improve the rate of load dissemination. The different processes are intended to improve the packet delivery factor (PDF) by selecting appropriate node transmission states. The transmission states of the nodes are classified through periodic remaining energy update; the queuing and scheduling process is dynamically adjusted with energy consideration. A weight-based normalized function eases neighbor selection by determining the most precise neighbor that satisfies transmission and energy constraints. The results of the proposed M2SLB (Min-Max Scheduling Load Balancing) proves the consistency of the proposed algorithm by improving the network throughput, packet delivery ratio and minimizing delay and packet loss by retaining higher remaining energy.","PeriodicalId":100779,"journal":{"name":"Journal of Energy Finance & Development","volume":"58 6 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"A Min-Max Scheduling Load Balanced Approach to Enhance Energy Efficiency and Performance of Mobile ADHOC Networks\",\"authors\":\"Venkatachalapathy K, Sundaranarayana D\",\"doi\":\"10.2139/ssrn.3416460\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Energy efficiency and traffic management in Mobile Ad hoc Networks (MANETs) is a complex process due to the self-organizing nature of the nodes. Quality of service (QoS) of the network is achieved by addressing the issues concerned with load handling and energy conservation. This manuscript proposes a min-max scheduling (M2S) algorithm for energy efficiency and load balancing (LB) in MANETs. The algorithm operates in two phases: neighbor selection and load balancing. In state selection, the transmission of the node is altered based on its energy and packet delivery factor. In the load balancing phase, the selected nodes are induced by queuing and scheduling the process to improve the rate of load dissemination. The different processes are intended to improve the packet delivery factor (PDF) by selecting appropriate node transmission states. The transmission states of the nodes are classified through periodic remaining energy update; the queuing and scheduling process is dynamically adjusted with energy consideration. A weight-based normalized function eases neighbor selection by determining the most precise neighbor that satisfies transmission and energy constraints. The results of the proposed M2SLB (Min-Max Scheduling Load Balancing) proves the consistency of the proposed algorithm by improving the network throughput, packet delivery ratio and minimizing delay and packet loss by retaining higher remaining energy.\",\"PeriodicalId\":100779,\"journal\":{\"name\":\"Journal of Energy Finance & Development\",\"volume\":\"58 6 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Energy Finance & Development\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2139/ssrn.3416460\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Energy Finance & Development","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.3416460","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Min-Max Scheduling Load Balanced Approach to Enhance Energy Efficiency and Performance of Mobile ADHOC Networks
Energy efficiency and traffic management in Mobile Ad hoc Networks (MANETs) is a complex process due to the self-organizing nature of the nodes. Quality of service (QoS) of the network is achieved by addressing the issues concerned with load handling and energy conservation. This manuscript proposes a min-max scheduling (M2S) algorithm for energy efficiency and load balancing (LB) in MANETs. The algorithm operates in two phases: neighbor selection and load balancing. In state selection, the transmission of the node is altered based on its energy and packet delivery factor. In the load balancing phase, the selected nodes are induced by queuing and scheduling the process to improve the rate of load dissemination. The different processes are intended to improve the packet delivery factor (PDF) by selecting appropriate node transmission states. The transmission states of the nodes are classified through periodic remaining energy update; the queuing and scheduling process is dynamically adjusted with energy consideration. A weight-based normalized function eases neighbor selection by determining the most precise neighbor that satisfies transmission and energy constraints. The results of the proposed M2SLB (Min-Max Scheduling Load Balancing) proves the consistency of the proposed algorithm by improving the network throughput, packet delivery ratio and minimizing delay and packet loss by retaining higher remaining energy.