The problem of joint radio and cloud resources allocation is studied for heterogeneous mobile cloud computing networks. The objective of the proposed joint resource allocation schemes is to maximize the total utility ...The problem of joint radio and cloud resources allocation is studied for heterogeneous mobile cloud computing networks. The objective of the proposed joint resource allocation schemes is to maximize the total utility of users as well as satisfy the required quality of service(QoS) such as the end-to-end response latency experienced by each user. We formulate the problem of joint resource allocation as a combinatorial optimization problem. Three evolutionary approaches are considered to solve the problem: genetic algorithm(GA), ant colony optimization with genetic algorithm(ACO-GA), and quantum genetic algorithm(QGA). To decrease the time complexity, we propose a mapping process between the resource allocation matrix and the chromosome of GA, ACO-GA, and QGA, search the available radio and cloud resource pairs based on the resource availability matrixes for ACOGA, and encode the difference value between the allocated resources and the minimum resource requirement for QGA. Extensive simulation results show that our proposed methods greatly outperform the existing algorithms in terms of running time, the accuracy of final results, the total utility, resource utilization and the end-to-end response latency guaranteeing.展开更多
Compression and encryption are widely used in network traffic in order to improve efficiency and security of some systems.We propose a scheme to concatenate both functions and run them in a paralle pipelined fashion,d...Compression and encryption are widely used in network traffic in order to improve efficiency and security of some systems.We propose a scheme to concatenate both functions and run them in a paralle pipelined fashion,demonstrating both a hardware and a software implementation.With minor modifications to the hardware accelerators,latency can be reduced to half.Furthermore,we also propose a seminal and more efficient scheme,where we integrate the technology of encryption into the compression algorithm.Our new integrated optimization scheme reaches an increase of 1.6X by using parallel software scheme However,the security level of our new scheme is not desirable compare with previous ones.Fortunately,we prove that this does not affect the application of our schemes.展开更多
基金supported by the National Natural Science Foundation of China (No. 61741102, No. 61471164)China Scholarship Council
文摘The problem of joint radio and cloud resources allocation is studied for heterogeneous mobile cloud computing networks. The objective of the proposed joint resource allocation schemes is to maximize the total utility of users as well as satisfy the required quality of service(QoS) such as the end-to-end response latency experienced by each user. We formulate the problem of joint resource allocation as a combinatorial optimization problem. Three evolutionary approaches are considered to solve the problem: genetic algorithm(GA), ant colony optimization with genetic algorithm(ACO-GA), and quantum genetic algorithm(QGA). To decrease the time complexity, we propose a mapping process between the resource allocation matrix and the chromosome of GA, ACO-GA, and QGA, search the available radio and cloud resource pairs based on the resource availability matrixes for ACOGA, and encode the difference value between the allocated resources and the minimum resource requirement for QGA. Extensive simulation results show that our proposed methods greatly outperform the existing algorithms in terms of running time, the accuracy of final results, the total utility, resource utilization and the end-to-end response latency guaranteeing.
基金partially supported by National Natural Science Foundation of China(No. 61202475,61572294,61502218)Outstanding Young Scientists Foundation Grant of Shandong Province(No.BS2014DX016)+3 种基金Nature Science Foundation of Shandong Province (No.ZR2012FQ029)Ph.D.Programs Foundation of Ludong University(No.LY2015033)Fujian Provincial Key Laboratory of Network Security and Cryptology Research Fund(Fujian Normal University)(No.15004)the Priority Academic Program Development of Jiangsu Higer Education Institutions,Jiangsu Collaborative Innovation Center on Atmospheric Environment and Equipment Technology
文摘Compression and encryption are widely used in network traffic in order to improve efficiency and security of some systems.We propose a scheme to concatenate both functions and run them in a paralle pipelined fashion,demonstrating both a hardware and a software implementation.With minor modifications to the hardware accelerators,latency can be reduced to half.Furthermore,we also propose a seminal and more efficient scheme,where we integrate the technology of encryption into the compression algorithm.Our new integrated optimization scheme reaches an increase of 1.6X by using parallel software scheme However,the security level of our new scheme is not desirable compare with previous ones.Fortunately,we prove that this does not affect the application of our schemes.
