一种运用模糊综合评判的实时服务器负载均衡算法
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摘要
针对大数据时代,实时服务器集群负载平衡问题,本文提出了基于模糊综合评判的服务器负载均衡算法.依据模糊数学的理论,将影响服务器性能的因素作为多参量进行总体评价,即对集群中各服务器先建立因素集和评判集,通过实验评议的方法计算资源权重向量,根据模糊综合评判的基本原理,求出资源权重向量到服务能力向量的映射矩阵,然后利用主因素型公式进行多参量综合评判,从网络集群中选取隶属度最大的服务器作为本次任务重定向的目标.实验结果表明,本算法对服务器的性能评判准确,实时性强,避免了基于单因素评判算法的不足,能够解决实时服务器集群的负载平衡问题.
To the load balancing problem of real-time server cluster in the era of big data,the algorithm of load balancing based on fuzzy comprehensive evaluation was put forward. The algorithm is inspired by fuzzy comprehensive evaluation applied in agricultural seed selection and planting geographical climate of choice. Inspired by which is good for multi-factor processing,a newmethod is proposed: According to the theory of fuzzy math,weight vector was computed by experiment evaluation method,the factors which influenced the performance of servers were taken as parameters,and were carried on the comprehensive judgement. That is the factor set and judgement set were built at first,the resource weight vector were taken in,then the mapping matrix from the resource weight to the service ability was computed,and the comprehensive judgement of parameters was carried on according to the formula,the server which has the maximal fuzzy membership was taken as the objective one at last. The experiments' results show: the capacity of server can be evaluated correctly,the object server had strong real time performance in this algorithm,and the shortcomings of method based on single factor were avoided,the load balancing problem of real time server can be solved.
To the load balancing problem of real-time server cluster in the era of big data,the algorithm of load balancing based on fuzzy comprehensive evaluation was put forward. The algorithm is inspired by fuzzy comprehensive evaluation applied in agricultural seed selection and planting geographical climate of choice. Inspired by which is good for multi-factor processing,a newmethod is proposed: According to the theory of fuzzy math,weight vector was computed by experiment evaluation method,the factors which influenced the performance of servers were taken as parameters,and were carried on the comprehensive judgement. That is the factor set and judgement set were built at first,the resource weight vector were taken in,then the mapping matrix from the resource weight to the service ability was computed,and the comprehensive judgement of parameters was carried on according to the formula,the server which has the maximal fuzzy membership was taken as the objective one at last. The experiments' results show: the capacity of server can be evaluated correctly,the object server had strong real time performance in this algorithm,and the shortcomings of method based on single factor were avoided,the load balancing problem of real time server can be solved.
引文
[1] Su Yue-ming,Li Chen,Tian Li-hua. A consistent hashing load balancing strategy based on fragmentation and it's application[J].Computer Technology and Development,2017,27(11):62-65.
[2] Luo Wei,Jiang Yuan-jian,Li Yang,et al. Optimization of distributed IMS architecture based on load balancing[J]. Computer Technology and Development,2017,27(10):187-191.
[3] Nie Shi-qing,Zhong Yong,Cui Meng-tian. Hierarchical load balancing algorithm based on load entropy[J]. Journal of Computer Applications,2016,36(S2):33-36,48.
[4] Li Wen-zhong,Guo Sheng,Xu Ping,et al. An adaptive load balancing algorithm for service composition[J]. Journal of Software,2006,17(5):1068-1077.
[5] Zhang yong,Zhang Jie-hui,Liu bin. Big Data dynamic migration method based on global load balancing in cloud environment[J].Computer Science,2018,45(1):196-199.
[6] Keqiang He,Eric Rozner,Kanak Agarwal. Presto:edge-based load balancing for fast datacenter networks[C]. Acm Conference on Special Interest Group on Data Communication,2015,45(4):465-478.
[7] Ming wang,Jianfeng Guan. An adaptive dynamic feedback load balancing algorithm based on Qos in distributed file system[J].Journal of Communications and Information Networks,2017,2(3):30-40.
[8] Suthan V,Kavitha K V. Dynamic load balancing in cloud based multimedia system with genetic algorithm[C]. International Conference on Inventive Computation Technologies(ICICT),2017:1-4.
[9] Liang Bao-song,Cao Dian-li. Fuzzy mathematics and it's applications[M]. Beijing:Science Press,2007:40-41.
[10]Baidu Encyclopedia,Fuzzy comprehensive evaluation method[EB/OL]. https://baike. baidu. com/item/模糊综合评价法/2162444?fr=aladdin,2013-06-05/2013-06-10.
[11] Chen Shui-li,Li Jing-gong,Wang Xiang-gong. Fuzzy set theory and its applications[M]. Beijing:Science Press,2005:207-222.
[1]苏跃明,李晨,田丽华.基于分片一致性哈希负载均衡策略与应用[J].计算机技术与发展,2017,27(11):62-65.
[2]罗威,姜元建,李洋,等.基于负载均衡的分布式IMS体系架构的优化[J].计算机技术与发展,2017,27(10):187-191.
[3]聂世青,钟勇,崔梦天.一种基于负载熵的层次负载均衡算法[J].计算机应用,2016,36(S2):33-36,48.
[4]李文中,郭胜,许平,等.服务组合中一种自适应的负载均衡算法[J].软件学报,2006,17(5):1068-1077.
[5]章勇,张洁卉,柳斌.全局负载均衡下云环境中的大数据动态迁移方法[J].计算机科学,2018,45(1):196-199.
[9]梁保松,曹殿立.模糊数学及其应用[M].北京:科学出版社,2007:40-41.
[10]百度百科,模糊综合评价法[EB/OL]. https://baike. baidu.com/item/模糊综合评价法/2162444? fr=aladdin,2013-06-05/2013-06-10.
[11]陈水利,李敬功,王向公.模糊集理论及其应用[M].北京:科学出版社,2005:207-222.
[2] Luo Wei,Jiang Yuan-jian,Li Yang,et al. Optimization of distributed IMS architecture based on load balancing[J]. Computer Technology and Development,2017,27(10):187-191.
[3] Nie Shi-qing,Zhong Yong,Cui Meng-tian. Hierarchical load balancing algorithm based on load entropy[J]. Journal of Computer Applications,2016,36(S2):33-36,48.
[4] Li Wen-zhong,Guo Sheng,Xu Ping,et al. An adaptive load balancing algorithm for service composition[J]. Journal of Software,2006,17(5):1068-1077.
[5] Zhang yong,Zhang Jie-hui,Liu bin. Big Data dynamic migration method based on global load balancing in cloud environment[J].Computer Science,2018,45(1):196-199.
[6] Keqiang He,Eric Rozner,Kanak Agarwal. Presto:edge-based load balancing for fast datacenter networks[C]. Acm Conference on Special Interest Group on Data Communication,2015,45(4):465-478.
[7] Ming wang,Jianfeng Guan. An adaptive dynamic feedback load balancing algorithm based on Qos in distributed file system[J].Journal of Communications and Information Networks,2017,2(3):30-40.
[8] Suthan V,Kavitha K V. Dynamic load balancing in cloud based multimedia system with genetic algorithm[C]. International Conference on Inventive Computation Technologies(ICICT),2017:1-4.
[9] Liang Bao-song,Cao Dian-li. Fuzzy mathematics and it's applications[M]. Beijing:Science Press,2007:40-41.
[10]Baidu Encyclopedia,Fuzzy comprehensive evaluation method[EB/OL]. https://baike. baidu. com/item/模糊综合评价法/2162444?fr=aladdin,2013-06-05/2013-06-10.
[11] Chen Shui-li,Li Jing-gong,Wang Xiang-gong. Fuzzy set theory and its applications[M]. Beijing:Science Press,2005:207-222.
[1]苏跃明,李晨,田丽华.基于分片一致性哈希负载均衡策略与应用[J].计算机技术与发展,2017,27(11):62-65.
[2]罗威,姜元建,李洋,等.基于负载均衡的分布式IMS体系架构的优化[J].计算机技术与发展,2017,27(10):187-191.
[3]聂世青,钟勇,崔梦天.一种基于负载熵的层次负载均衡算法[J].计算机应用,2016,36(S2):33-36,48.
[4]李文中,郭胜,许平,等.服务组合中一种自适应的负载均衡算法[J].软件学报,2006,17(5):1068-1077.
[5]章勇,张洁卉,柳斌.全局负载均衡下云环境中的大数据动态迁移方法[J].计算机科学,2018,45(1):196-199.
[9]梁保松,曹殿立.模糊数学及其应用[M].北京:科学出版社,2007:40-41.
[10]百度百科,模糊综合评价法[EB/OL]. https://baike. baidu.com/item/模糊综合评价法/2162444? fr=aladdin,2013-06-05/2013-06-10.
[11]陈水利,李敬功,王向公.模糊集理论及其应用[M].北京:科学出版社,2005:207-222.
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