An adaptive dynamic load balancing algorithm based on QoS is proposed to improve the performance of load balancing in distributed file system,combining the advantages of a variety of load balancing algorithms.The new ...An adaptive dynamic load balancing algorithm based on QoS is proposed to improve the performance of load balancing in distributed file system,combining the advantages of a variety of load balancing algorithms.The new algorithm uses a tuple containing the number of files and the total file size as the QoS measure for the requested task.The master node sets a threshold for the requested task based on the QoS to filter storage nodes that meet the requirements of the task.In order to guarantee the reliability of the new algorithm,we consider the impact of CPU utilization,memory usage,disk IO occupancy rate,network bandwidth usage and hard disk usage on load balancing performance when calculating the real-time load balancing of storage nodes.The heterogeneity of the network is considered when the master node schedule task assignments to ensure the fairness of the algorithm.The comprehensive evaluation value is determined based the performance load ratio,which is calculated from the real-time load value of the storage node and a performance value after normalization.The master node assigns tasks to the storage node with the highest comprehensive evaluation value.The storage nodes provide adaptive feedback based on changes in the degree of connectivity,rather than periodic update of the load information.The actual distributed file system environment is set up on the server cluster,the performance of the new algorithm is tested through a contrast experiment.The experimental results show that the new algorithm can effectively reduce the average response time of the system,improve throughput,and enable the system load to reach a good balance.展开更多
物联网作为国内外新兴的热门技术,正在深刻地影响着人们的生产生活,它在带来诸多好处的同时也给信息存储领域带来挑战.物联网信息存储中心需要根据其数据特性结合分布式实时数据库信息存储管理的优点,设计与之相适应的数据存储方案,而...物联网作为国内外新兴的热门技术,正在深刻地影响着人们的生产生活,它在带来诸多好处的同时也给信息存储领域带来挑战.物联网信息存储中心需要根据其数据特性结合分布式实时数据库信息存储管理的优点,设计与之相适应的数据存储方案,而数据分配策略作为数据存储方案的关键技术是研究的重点.根据物联网传感器信息的海量性、时空相关性、访问失衡性和连续变化性,需要一种基于时域的数据分配模型与之相适应,以此设计出基于自适应时域负载反馈的动态数据分配策略(adaptive time domain data allocation,ATDA).策略根据数据特征,将静态数据分配问题归约成简单线性规划问题,同时采用自适应时域对负载信息进行反馈,最后设置动态负载门限函数实现数据的动态分配.实验表明,该策略与同类Random、Bubba算法相比,在系统短时域负载均衡(LBST)、系统数据迁移量(DM)方面具有更好的性能.展开更多
在移动应用层组播通信中,热点地区可能会因用户过多而导致用户流服务满意度降低,非热点地区却可能会出现资源浪费现象,引起整个系统性能下降。提出了一种基于移动终端主动反馈的自适应负载均衡机制(Adaptive Load Balancing Mechanism b...在移动应用层组播通信中,热点地区可能会因用户过多而导致用户流服务满意度降低,非热点地区却可能会出现资源浪费现象,引起整个系统性能下降。提出了一种基于移动终端主动反馈的自适应负载均衡机制(Adaptive Load Balancing Mechanism based Mobile Terminal Active Feedback,ALBM-MTAF)。ALBM-MTAF利用网络相关性能指标模拟移动终端(用户)所获得的流媒体服务满意度(Streaming Media Service Satisfaction,SMSS),通过终端用户主动反馈SMSS不断进行自适应的调整,将SMSS较差地域的子节点切换到SMSS较好的父节点上,从而实现整个系统的负载均衡。模拟实验表明,该机制具有良好的负载均衡效果,并能保证通信的质量。展开更多
基金supported in part by the National Basic Research Program of China("973"Program)(No.2013CB329102).
文摘An adaptive dynamic load balancing algorithm based on QoS is proposed to improve the performance of load balancing in distributed file system,combining the advantages of a variety of load balancing algorithms.The new algorithm uses a tuple containing the number of files and the total file size as the QoS measure for the requested task.The master node sets a threshold for the requested task based on the QoS to filter storage nodes that meet the requirements of the task.In order to guarantee the reliability of the new algorithm,we consider the impact of CPU utilization,memory usage,disk IO occupancy rate,network bandwidth usage and hard disk usage on load balancing performance when calculating the real-time load balancing of storage nodes.The heterogeneity of the network is considered when the master node schedule task assignments to ensure the fairness of the algorithm.The comprehensive evaluation value is determined based the performance load ratio,which is calculated from the real-time load value of the storage node and a performance value after normalization.The master node assigns tasks to the storage node with the highest comprehensive evaluation value.The storage nodes provide adaptive feedback based on changes in the degree of connectivity,rather than periodic update of the load information.The actual distributed file system environment is set up on the server cluster,the performance of the new algorithm is tested through a contrast experiment.The experimental results show that the new algorithm can effectively reduce the average response time of the system,improve throughput,and enable the system load to reach a good balance.
文摘物联网作为国内外新兴的热门技术,正在深刻地影响着人们的生产生活,它在带来诸多好处的同时也给信息存储领域带来挑战.物联网信息存储中心需要根据其数据特性结合分布式实时数据库信息存储管理的优点,设计与之相适应的数据存储方案,而数据分配策略作为数据存储方案的关键技术是研究的重点.根据物联网传感器信息的海量性、时空相关性、访问失衡性和连续变化性,需要一种基于时域的数据分配模型与之相适应,以此设计出基于自适应时域负载反馈的动态数据分配策略(adaptive time domain data allocation,ATDA).策略根据数据特征,将静态数据分配问题归约成简单线性规划问题,同时采用自适应时域对负载信息进行反馈,最后设置动态负载门限函数实现数据的动态分配.实验表明,该策略与同类Random、Bubba算法相比,在系统短时域负载均衡(LBST)、系统数据迁移量(DM)方面具有更好的性能.
文摘在移动应用层组播通信中,热点地区可能会因用户过多而导致用户流服务满意度降低,非热点地区却可能会出现资源浪费现象,引起整个系统性能下降。提出了一种基于移动终端主动反馈的自适应负载均衡机制(Adaptive Load Balancing Mechanism based Mobile Terminal Active Feedback,ALBM-MTAF)。ALBM-MTAF利用网络相关性能指标模拟移动终端(用户)所获得的流媒体服务满意度(Streaming Media Service Satisfaction,SMSS),通过终端用户主动反馈SMSS不断进行自适应的调整,将SMSS较差地域的子节点切换到SMSS较好的父节点上,从而实现整个系统的负载均衡。模拟实验表明,该机制具有良好的负载均衡效果,并能保证通信的质量。
