{"title":"An Energy-Efficient Allocation Technique for Distributing Resources in a Heterogeneous Data Center","authors":"Mohd Mursleen, Yogesh Kothyari","doi":"10.1109/ICACCE46606.2019.9079973","DOIUrl":null,"url":null,"abstract":"Now a days currently there is a lot of power consumption in data centers due to high demand in cloud services like online data storage services, software services on cloud like Google Apps, Sales force and platform as a service on cloud. Due to heavy usage of all these services over the Cloud, now a day's Data Centers are consuming a heavy amount of Energy. This heavy Energy Consumption by data centers is not only including the higher running cost of data centers but it is also effecting the environment inversely. There are basically two ways in which we can reduce energy consumption in Data Centers, first way is by minimising the parameter of data centers while the second method is by exercising an efficiently constructed asset allocation technique to get the optimal balance between energy consumption and performance of the data centers. In this paper, we are dealing with the second approach which is a software based approach i.e. designing an efficient resource allocation technique while the first approach is a hardware based approach. Furthermore, here we will not only deal with homogeneous data centers but we are also considering the heterogeneous data centers. So, our prime focus of this research work is to allocate the resources in homogeneous and heterogeneous data centers in such a manner that energy consumed by data centers usage becomes optimal and energy consumption is reduced without effecting in the performance of data centers. Therefore, for the above we have come up with a novel algorithm toward energy efficiency in such a way that it takes care of scheduling the algorithm fairly while allocating the resources of data centers.","PeriodicalId":317123,"journal":{"name":"2019 International Conference on Advances in Computing and Communication Engineering (ICACCE)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 International Conference on Advances in Computing and Communication Engineering (ICACCE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICACCE46606.2019.9079973","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
Now a days currently there is a lot of power consumption in data centers due to high demand in cloud services like online data storage services, software services on cloud like Google Apps, Sales force and platform as a service on cloud. Due to heavy usage of all these services over the Cloud, now a day's Data Centers are consuming a heavy amount of Energy. This heavy Energy Consumption by data centers is not only including the higher running cost of data centers but it is also effecting the environment inversely. There are basically two ways in which we can reduce energy consumption in Data Centers, first way is by minimising the parameter of data centers while the second method is by exercising an efficiently constructed asset allocation technique to get the optimal balance between energy consumption and performance of the data centers. In this paper, we are dealing with the second approach which is a software based approach i.e. designing an efficient resource allocation technique while the first approach is a hardware based approach. Furthermore, here we will not only deal with homogeneous data centers but we are also considering the heterogeneous data centers. So, our prime focus of this research work is to allocate the resources in homogeneous and heterogeneous data centers in such a manner that energy consumed by data centers usage becomes optimal and energy consumption is reduced without effecting in the performance of data centers. Therefore, for the above we have come up with a novel algorithm toward energy efficiency in such a way that it takes care of scheduling the algorithm fairly while allocating the resources of data centers.