To reduce fetching cost from a remote source,it is natural to cache information near the users who may access the information later.However,with development of 5 G ultra-dense cellular networks andmobile edge computin...To reduce fetching cost from a remote source,it is natural to cache information near the users who may access the information later.However,with development of 5 G ultra-dense cellular networks andmobile edge computing(MEC),a reasonable selection among edge servers for content delivery becomes a problem when the mobile edge obtaining sufficient replica servers.In order to minimize the total cost accounting for both caching and fetching process,we study the optimal resource allocation for the content replica servers’ deployment.We decompose the total cost as the superposition of cost in several coverages.Particularly,we consider the criterion for determining the coverage of a replica server and formulate the coverage as a tradeoff between caching cost and fetching cost.According to the criterion,a coverage isolation(CI) algorithm is proposed to solve the deployment problem.The numerical results show that the proposed CI algorithm can reduce the cost and obtain a higher tolerance for different centrality indices.展开更多
In distributed parallel server system, location and redundancy of repficas have great influence on availability and efficiency of the system. In order to improve availability and efficiency of the system, two phase de...In distributed parallel server system, location and redundancy of repficas have great influence on availability and efficiency of the system. In order to improve availability and efficiency of the system, two phase decision algorithm of replica allocation is proposed. The algorithm which makes use of auto-regression model dynamically predicts the future count of READ and WRITE operation, and then determines location and redundancy of replicas by considering availability, CPU and bands of the network. The algorithm can not only ensure the requirement of availability, but also reduce the system resources consumed by all the operations in a great scale. Analysis and test show that communication complexity and time complexity of the algorithm satisfy O（n）, resource optimizing scale increases with the increase of READ count.展开更多
基金supported by NSFC(61571055)fund of SKL of MMW(K201815)Important National Science and Technology Specific Projects(2017ZX03001028)
文摘To reduce fetching cost from a remote source,it is natural to cache information near the users who may access the information later.However,with development of 5 G ultra-dense cellular networks andmobile edge computing(MEC),a reasonable selection among edge servers for content delivery becomes a problem when the mobile edge obtaining sufficient replica servers.In order to minimize the total cost accounting for both caching and fetching process,we study the optimal resource allocation for the content replica servers’ deployment.We decompose the total cost as the superposition of cost in several coverages.Particularly,we consider the criterion for determining the coverage of a replica server and formulate the coverage as a tradeoff between caching cost and fetching cost.According to the criterion,a coverage isolation(CI) algorithm is proposed to solve the deployment problem.The numerical results show that the proposed CI algorithm can reduce the cost and obtain a higher tolerance for different centrality indices.
文摘In distributed parallel server system, location and redundancy of repficas have great influence on availability and efficiency of the system. In order to improve availability and efficiency of the system, two phase decision algorithm of replica allocation is proposed. The algorithm which makes use of auto-regression model dynamically predicts the future count of READ and WRITE operation, and then determines location and redundancy of replicas by considering availability, CPU and bands of the network. The algorithm can not only ensure the requirement of availability, but also reduce the system resources consumed by all the operations in a great scale. Analysis and test show that communication complexity and time complexity of the algorithm satisfy O（n）, resource optimizing scale increases with the increase of READ count.
