P. Endo, M. S. Batista, G. Gonçalves, Moisés Rodrigues, D. Sadok, J. Kelner, A. Sefidcon, F. Wuhib
{"title":"Self-organizing strategies for resource management in Cloud Computing: State-of-the-art and challenges","authors":"P. Endo, M. S. Batista, G. Gonçalves, Moisés Rodrigues, D. Sadok, J. Kelner, A. Sefidcon, F. Wuhib","doi":"10.1109/LatinCloud.2013.6842215","DOIUrl":null,"url":null,"abstract":"Due to the growth of Cloud Computing, the supporting infrastructure has become more complex, and the centralized solutions suffer resource management difficulties due to the large scale and the dynamicity of the scenario. Consequently, distributed solutions have been proposed in the literature and the self-organizing ones have attracted particular interest due to their robustness and adaptability characteristics. Techniques, such as bio-inspired computing, multi-agent systems, and evolutionary techniques are used to manage resources. The main goal of this paper is to present a start study about how self-organizing solutions are applied in resource management of Cloud providers, as well as to highlight the main research challenges in this area.","PeriodicalId":344490,"journal":{"name":"2nd IEEE Latin American Conference on Cloud Computing and Communications","volume":"123 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2nd IEEE Latin American Conference on Cloud Computing and Communications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/LatinCloud.2013.6842215","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7
Abstract
Due to the growth of Cloud Computing, the supporting infrastructure has become more complex, and the centralized solutions suffer resource management difficulties due to the large scale and the dynamicity of the scenario. Consequently, distributed solutions have been proposed in the literature and the self-organizing ones have attracted particular interest due to their robustness and adaptability characteristics. Techniques, such as bio-inspired computing, multi-agent systems, and evolutionary techniques are used to manage resources. The main goal of this paper is to present a start study about how self-organizing solutions are applied in resource management of Cloud providers, as well as to highlight the main research challenges in this area.