In the vast complex world the emergence of cloud computing and its applications and uses in load balancing has been raised up to the maximum level. The number of users accessing this service is increasing drastically day by day. As the cloud is made up of datacenters; which are very much powerful to handle large numbers of users still then the essentiality of load balancing is vital. However load balancing is a technique of distributing the loads among various nodes of a distributed system to minimize the response time, minimize the cost, minimize the resource utilization, and minimize the overhead. The aim of this paper is to briefly discuss about various efficient and enhanced load balancing algorithms and experimentally verify how to minimize the response time and processing time through the tool called cloud analyst.
“Cloud computing” is a term, which involves virtualization, distributed computing, networking, software and Web services. Our Objective is to develop an effective load balancing algorithm using Divisible Load Scheduling Theorem to maximize or minimize different performance parameters (throughput, latency for example) for the clouds of different sizes. Central to these issues lays the establishment of an efficient load balancing algorithm. The load can be CPU load, memory capacity, delay or network load. Load balancing is the process of distributing the load among various nodes of a distributed system to improve both resource utilization and job response time while also avoiding a situation where some of the nodes are heavily loaded while other nodes are idle or doing very little work. Load balancing ensures that all processor in the system or every node in the network does approximately the equal amount of work at any instant of time.
Scheduling a sequence of jobs released over time when the processing time of a job is only known at its completion is a classical problem in CPU scheduling in time-sharing and real time operating system. We discuss here different scheduling techniques used in Real-Time systems. Even if there are several scheduling policies, the preemptive scheduling policies hold promising results. In this paper we have done an extensive survey on various scheduling algorithms. We are extracting the positive characteristics of each scheduling and placed it on this paper.
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