An efficient resource utilization and power management techniques for cloud computing environment

Abstract

With the increase in demand for centralized and outsourcing for newlineprovision of needs to the clients on a demand basis, almost all of the newlineinformation handling and processing concerns, financial concerns and utility newlineservice providers have begun a migration towards cloud computing. newlineThe efficiency and effectiveness of any cloud implementation network lies in optimization of certain critical parameters like scheduling,resource allocation, Virtual Machine migration and mapping of tasks, cost newlineeffective scheduling approach, pricing of services offered, energy savings newlinetowards green computing, cost reduction, computation complexity and time. newlineAmong these several attributes, this thesis has taken and investigated the newlineproblem of resource utilization and power management techniques for cloud newlinecomputing environment. Altogether all the proposed techniques are different newlinefrom each other. These techniques provide better results than existing newlinemethods.The issue of resource allocation has been taken as the first newlineobjective of the thesis with a number of attributes that needs optimization newlinerelated to task scheduling. The primary objective of the task scheduler is to newlineeffectively allocate the available number of resources for completion of the newlinejob within the stipulated time. When the completion of the task exceeds the newlinestipulated time period, there is a reduction in the value of QoS. Based on the newlinefindings of the literature survey regarding various parameters and issues newlinesurrounding the problem of efficient resource allocation, a statistical value newlinedistribution algorithm has been proposed in this thesis for efficient newlinescheduling of available resources to execution of a given task based on a hot newlinespot/cold spot concept. The proposed algorithm has been implemented for a newline newline