Bio-Inspired QOS Aware Resources Allocation and Management at the Cloud Data Center

Abstract

Cloud comprises of many hardware and software resources and managing these resources will play an important role in executing a clients request. Now-a-days clients from different parts of the world are demanding for various services at a rapid rate. In this present situation efficient load balancing algorithms will play an vital role in allocating the clients requests and also ensuring the usage of the resources in an intelligent way so that underutilization of the resources will not occur in the cloud environment. Clients demand for different cloud resources w.r.t Service Level Agreement (SLA) in a seamless manner, therefore resource allocation and management plays an important role in Infrastructure as a Service (IaaS) based cloud environment. Computing systems in the cloud environment heavily rely on virtualization technology and thus makes the servers feasible for independent applications. Further, virtualization process improves the power efficiency of the data centers (consolidation of physical machines (PMs)) and thereby enabling the assignment of multiple virtual machines (VMs) to a single physical PM. These VM instances can be procured in the form of On-Demand and Spot instances. Consequently, some of the PMs in the cloud data center can be turned off (sleep state) and resulting in low power consumption and thus making cloud data center more efficient. In this research work, the main focus is towards designing and development of efficient QoS aware load balancing and resources allocation/management algorithms using Bio-Inspired techniques which ensures fault tolerant task execution in heterogeneous cloud environment. Experimental results demonstrate that our proposed Bio-Inspired Load Balancing and QoS Aware Resources Allocation/Management algorithms outperforms peer research and benchmark algorithms in terms of efficient utilization of the cloud resources, improved reliability and reduced average response time.