一种基于蚁群优化的云数据中心负载均衡技术

Ekta Gupta, Vidya Deshpande
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引用次数: 30

摘要

由于大量的请求被提交到数据中心,负载均衡是云数据中心面临的主要挑战之一。现有的负载均衡技术主要集中在提高服务质量、按时提供预期输出等方面。因此,有必要开发负载平衡技术,以提高云计算的性能,同时实现最佳的资源利用率。所提出的负载均衡技术基于蚁群优化算法,通过检测服务器的过载和负载不足,从而在识别出的数据中心服务器之间进行负载均衡操作。所建议的技术确保了可用性,实现了有效的资源利用,最大限度地增加了云处理的请求数量,并最大限度地减少了服务多个请求所需的时间。算法的复杂度取决于数据中心的网络结构。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Technique Based on Ant Colony Optimization for Load Balancing in Cloud Data Center
As a large number of requests are submitted to the data center, load balancing is one of the main challenges in Cloud Data Center. Existing load Balancing techniques mainly focus on improving the quality of services, providing the expected output on time etc. Therefore, there is a need to develop load balancing technique that can improve the performance of cloud computing along with optimal resource utilization. The proposed technique of load balancing is based on Ant Colony Optimization which detects overloaded and under loaded servers and thereby performs load balancing operations between identified servers of Data Center. The proposed technique ensures availability, achieves efficient resource utilization, maximizes number of requests handled by cloud and minimizes time required to serve multiple requests. The complexity of proposed algorithm depends on datacenter network architecture.
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