Comparison of load balancing algorithms in a Cloud

This paper presents an approach for scheduling algorithms that can maintain the load balancing and provides better improved strategies through efficient job scheduling and modified resource allocation techniques. 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 the processor in the system or every node in the network does approximately the equal amount of work at any instant of time. The simulated results provided in this paper based on scheduling algorithm ESCE (Equally Spread Current Execution) load .ESCE Scheduling algorithms handle the random selection based load distributed problem round robin , we have proposed ESCE scheduling algorithm and compared it with the round robin scheduling to estimate response time, processing time, which is having an impact on cost. Keywordscloud computing, virtual machine, round robin and ESCE algorithms, load balancing, simulation. INTRODUCTION Cloud computing provide infrastructure, platform, and software as services. These services are using pay-as-youuse model to customers, regardless of their location. Cloud computing is a cost effective model for provisioning services and it makes IT management easier and more responsive to the Changing needs of the business [1]. The access to the infrastructure incurs payments in real currency in cloud environment. Today network bandwidth, Less response time, minimum delay in data transfer and minimum data transfer cost are main challenging issues in cloud computing load balancing environment .In this study based on clouds scheduling algorithms round robin, ESCE (Equally Spread Current Execution) algorithms and compare them. Cloud sim is simulation based approach. The Simulation based approaches provide significant Benefits, as it allows researchers to test their proposed algorithms and protocols in a repeatable and controlled environment free of cost, and to find solution to the performance bottlenecks before deploying in the real cloud. The rest of this paper is organized as follows. The Literature review is discussed in section 2.Section 3 tells the problem definition or Section 4 present the design model of ESCE scheduling algorithm. Section 5 describes the simulation setup and performance analysis result. Finally, Section 6 concludes this paper. LITERATURE REVIEW Due to the recent emergence of cloud computing research in this area is in the preliminary stage. Jiyan et.al, (2010) have proposed a resource allocation mechanism with preemptable task execution which increases the utilization of clouds. They have proposed an adaptive resource allocation algorithm for cloud system with preemptable tasks but their approach does not pertain to cost optimization and time optimization [5]. Load balancing in cloud computing system[1] Ram Prasad Padhy, P Goutam Prasad Rao discussed on basic concepts of Cloud Computing and Load balancing and studied some existing load balancing algorithms, which can be applied to clouds. In addition to that, the closed-form solutions for minimum measurement and reporting time for single level tree networks with different load balancing strategies were also studied. The performance of these strategies with respect to the timing and the effect of link and measurement speed were studied. A comparison is also made between different strategies. Toufik Taibi1, Abdelouahab Abid and Engku Fariez Engku Azahan The paper described the features of a simulator to compare the performance of three dynamic load balancing algorithms. [3] Cloud Analyst: A Cloud Sim-based Visual Modeller for Analysing Cloud Computing Environments and Applications [2] Bhathiya Wickrema Singh all present how Cloud Analyst can be used to model and evaluate a real world problem through a case study of a social networking application deployed on the cloud. We have illustrated how the simulator can be used to effectively identify overall usage patterns and how such usage patterns affect data centres hosting the application. PROBLEM DEFINATION The random arrival of load in such an environment can cause some server to be heavily loaded while other server is idle or only lightly loaded. Equally load distributing improves performance by transferring load from heavily loaded server. Efficient scheduling and resource allocation is a critical characteristic of cloud computing based on which the performance of the system is estimated. The considered characteristics have an impact on cost optimization, which can be obtained by improved response time and processing time. DESIGN MODEL To handle the random selection based load distributed Jaspreet kaur/ International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 www.ijera.com Vol. 2, Issue 3, May-Jun 2012, pp.1169-1173 1670 | P a g e problem, we have proposed a scheduling algorithm and compared it with the existing round robin scheduling to estimate response time, processing time, which is having an impact on cost .A Comparison of Dynamic Load Balancing Algorithms.