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Study of load balancing algorithms for Cloud Computing

机译:云计算的负载均衡算法研究

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The significance of distributed applications is constantly rising due to technological advancements such as increasing internetworking of various computing devices and widespread usage of smart phones. Cloud computing is an information technology paradigm that enables ubiquitous access to shared pools of configurable system resources. Load balancing is one among various challenging issues in cloud computing. It is a mechanism to distribute the user requests among the virtual machines so that the requests are assigned proportional to the capacity of each virtual machine. Balancing of requests prevents the virtual machines from being either overloaded or under loaded. This paper presents a comparison of performance of load balancing algorithms in cloud computing. The algorithms considered for study are Throttled and Equally Spread Current Execution. Particle swarm optimization is also simulated to solve load balancing dynamically. The proposed work compares response time of all the three techniques. The simulation results show that particle swarm optimization performs better for dynamic changes in the system.
机译:由于技术进步,例如各种计算设备的互联网络增加以及智能电话的广泛使用,分布式应用程序的重要性正在不断提高。云计算是一种信息技术范例,可以无所不在地访问可配置系统资源的共享池。负载平衡是云计算中各种具有挑战性的问题之一。它是一种在虚拟机之间分配用户请求的机制,以使请求的分配与每个虚拟机的容量成比例。请求平衡可防止虚拟机过载或负载不足。本文提出了云计算中负载均衡算法性能的比较。研究中考虑使用的算法为节流和均分电流执行。还模拟了粒子群优化以动态解决负载平衡。拟议的工作比较了所有三种技术的响应时间。仿真结果表明,粒子群算法在系统动态变化方面表现更好。

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