{"title":"基于任务分配的异构分布式系统可靠性最大化改进细菌觅食算法","authors":"Farid Abbache, Hamoudi Kalla","doi":"10.1504/IJCNDS.2019.10013812","DOIUrl":null,"url":null,"abstract":"modified bacterial foraging algorithm for allocation and scheduling tasks on processors and links with high reliability is proposed (MBFA). MBFA ensure high reliability without redundancy of processors or links by using an efficient and simple structure. MBFA is improved by adding an efficient model to deal with the weak solution (i.e., allocation with low reliability). Also a simulated annealing technique is integrated into MBFA in order to strengthen the search of best solution. The efficiency and effectiveness of MBFA are tested using random generated problems. MBFA is tested over the published approaches HPSO and GAA using density parameter (DS), number of nodes (N) and the communication to computation ratio parameter (CCR). The results show the superiority of MBFA over the published approaches in all test cases.","PeriodicalId":209177,"journal":{"name":"Int. J. Commun. Networks Distributed Syst.","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Task allocation-based modified bacterial foraging algorithm for maximising reliability of a heterogeneous distributed system\",\"authors\":\"Farid Abbache, Hamoudi Kalla\",\"doi\":\"10.1504/IJCNDS.2019.10013812\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"modified bacterial foraging algorithm for allocation and scheduling tasks on processors and links with high reliability is proposed (MBFA). MBFA ensure high reliability without redundancy of processors or links by using an efficient and simple structure. MBFA is improved by adding an efficient model to deal with the weak solution (i.e., allocation with low reliability). Also a simulated annealing technique is integrated into MBFA in order to strengthen the search of best solution. The efficiency and effectiveness of MBFA are tested using random generated problems. MBFA is tested over the published approaches HPSO and GAA using density parameter (DS), number of nodes (N) and the communication to computation ratio parameter (CCR). The results show the superiority of MBFA over the published approaches in all test cases.\",\"PeriodicalId\":209177,\"journal\":{\"name\":\"Int. J. Commun. Networks Distributed Syst.\",\"volume\":\"13 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-05-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Int. J. Commun. Networks Distributed Syst.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1504/IJCNDS.2019.10013812\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Int. J. Commun. Networks Distributed Syst.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/IJCNDS.2019.10013812","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Task allocation-based modified bacterial foraging algorithm for maximising reliability of a heterogeneous distributed system
modified bacterial foraging algorithm for allocation and scheduling tasks on processors and links with high reliability is proposed (MBFA). MBFA ensure high reliability without redundancy of processors or links by using an efficient and simple structure. MBFA is improved by adding an efficient model to deal with the weak solution (i.e., allocation with low reliability). Also a simulated annealing technique is integrated into MBFA in order to strengthen the search of best solution. The efficiency and effectiveness of MBFA are tested using random generated problems. MBFA is tested over the published approaches HPSO and GAA using density parameter (DS), number of nodes (N) and the communication to computation ratio parameter (CCR). The results show the superiority of MBFA over the published approaches in all test cases.