The Experts below are selected from a list of 4131 Experts worldwide ranked by ideXlab platform
Kun Yang - One of the best experts on this subject based on the ideXlab platform.
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toward cloud based vehicular networks with efficient resource management
arXiv: Distributed Parallel and Cluster Computing, 2013Co-Authors: Yan Zhang, Wenlong Xia, Stein Gjessing, Kun YangAbstract:In the era of Internet of Things, all components in intelligent transportation systems will be connected to improve transport safety, relieve traffic congestion, reduce air pollution and enhance the comfort of driving. The vision of all vehicles connected poses a significant challenge to the collection and storage of large amounts of traffic-related data. In this article, we propose to integrate cloud computing into vehicular networks such that the vehicles can share computation resources, storage resources and bandwidth resources. The proposed architecture includes a vehicular cloud, a roadside cloud, and a central cloud. Then, we study cloud resource allocation and Virtual Machine Migration for effective resource management in this cloud-based vehicular network. A game-theoretical approach is presented to optimally allocate cloud resources. Virtual Machine Migration due to vehicle mobility is solved based on a resource reservation scheme.
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Toward cloud-based vehicular networks with efficient resource management
IEEE Network, 2013Co-Authors: Rong Yu, Wenlong Xia, Stein Gjessing, Yan Zhang, Kun YangAbstract:In the era of the Internet of Things, all components in intelligent transportation systems will be connected to improve transport safety, relieve traffic congestion, reduce air pollution, and enhance the comfort of driving. The vision of all vehicles connected poses a significant challenge to the collection and storage of large amounts of traffic-related data. In this article, we propose to integrate cloud computing into vehicular networks such that the vehicles can share computation resources, storage resources, and bandwidth resources. The proposed architecture includes a vehicular cloud, a roadside cloud, and a central cloud. Then we study cloud resource allocation and Virtual Machine Migration for effective resource management in this cloud-based vehicular network. A game-theoretical approach is presented to optimally allocate cloud resources. Virtual Machine Migration due to vehicle mobility is solved based on a resource reservation scheme.
Chen Xiaowei - One of the best experts on this subject based on the ideXlab platform.
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Virtual Machine Migration system design based on mobile ipv4 ipv6
Microelectronics & Computer, 2011Co-Authors: Chen XiaoweiAbstract:It can fully use heterogeneous network resources,provide resource requirement for cloud computing platform,this paper designed an IPv4/IPv6 Virtual Machine Migration transition framework based on tunnel technology,prefix management,address pool management and mobile IP.The framework application tradition IPv4/IPv6 transition technology and mobile IP technology for Virtual Machine Migration in cloud computing.It uses the paper designed cloud computing control engine as a core and IPv4/IPv6 plug-in collaboration completion Virtual Machine Migration.Experiment shows the framework can provides IPv4/IPv6 cloud computing service for client and support IPv4/IPv6 Virtual Machine seamless Migration.The framework can be applied to construction cloud computing platform in the IPv4/IPv6 transition period.
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live Migration transition framework of mobile ipv4 ipv6 Virtual Machine
Journal of Computer Applications, 2011Co-Authors: Chen XiaoweiAbstract:In order to fully use IPv4/IPv6 heterogeneous network resources and provide resource requirement for cloud computation platform,the authors designed an IPv4/IPv6 Virtual Machine Migration transition framework for cloud computation based on tunnel technology,prefix management,address pool management and mobile IP.The framework used the designed cloud computation control engine as a core to translate and link heterogeneous network,and needed Network Address Translation-Protocol Translation(NAT-PT) and tunnel technology collaboration.The framework was established for IPv4/IPv6 Virtual Machine seamless live Migration in the early,middle,late period of IPv4 to IPv6 transition,and IPv4/IPv6 cloud computation service was provided for client.The framework could be applied to construct cloud computation platform in the IPv4/IPv6 transition period.
Dongcheng Zhao - One of the best experts on this subject based on the ideXlab platform.
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live Migration for multiple correlated Virtual Machines in cloud based data centers
IEEE Transactions on Services Computing, 2018Co-Authors: Gang Sun, Dan Liao, Dongcheng ZhaoAbstract:With the development of cloud computing, Virtual Machine Migration is emerging as a promising technique to save energy, enhance resource utilizations, and guarantee Quality of Service (QoS) in cloud datacenters. Most of existing studies on the Virtual Machine Migration, however are based on a single Virtual Machine Migration. Although there are some researches on multiple Virtual Machines Migration, the author usually does not consider the correlation among these Virtual Machines. In practice, in order to save energy and maintain system performance, cloud providers usually need to migrate multiple correlated Virtual Machines or migrate the entire Virtual datacenter (VDC) request. In this paper, we focus on the efficient online live Migration of multiple correlated VMs in VDC requests, for optimizing the Migration performance. To solve this problem, we propose an efficient VDC Migration algorithm (VDC-M). We use the US-wide US National Science Foundation (NSF) network as substrate network to conduct extensive simulation experiments. Simulation results show that the performance of the proposed algorithm is promising in terms of the total VDC remapping cost, the blocking ratio, the average Migration time and the average downtime.
Depeng Jin - One of the best experts on this subject based on the ideXlab platform.
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Virtual Machine Migration planning in software defined networks
IEEE Transactions on Cloud Computing, 2019Co-Authors: Huandong Wang, Ying Zhang, Depeng JinAbstract:Live Migration is a key technique for Virtual Machine (VM) management in data center networks, which enables flexibility in resource optimization, fault tolerance, and load balancing. Despite its usefulness, the live Migration still introduces performance degradations during the Migration process. Thus, there has been continuous efforts in reducing the Migration time in order to minimize the impact. From the network's perspective, the Migration time is determined by the amount of data to be migrated and the available bandwidth used for such transfer. In this paper, we examine the problem of how to schedule the Migrations and how to allocate network resources for Migration when multiple VMs need to be migrated at the same time. We consider the problem in the Software-defined Network (SDN) context since it provides flexible control on routing. More specifically, we propose a method that computes the optimal Migration sequence and network bandwidth used for each Migration. We formulate this problem as a mixed integer programming, which is NP-hard. To make it computationally feasible for large scale data centers, we propose an approximation scheme via linear approximation plus fully polynomial time approximation, and obtain its theoretical performance bound and computational complexity. Through extensive simulations, we demonstrate that our fully polynomial time approximation (FPTA) algorithm has a good performance compared with the optimal solution of the primary programming problem and two state-of-the-art algorithms. That is, our proposed FPTA algorithm approaches to the optimal solution of the primary programming problem with less than 10 percent variation and much less computation time. Meanwhile, it reduces the total Migration time and service downtime by up to 40 and 20 percent compared with the state-of-the-art algorithms, respectively.
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Virtual Machine Migration planning in software defined networks
International Conference on Computer Communications, 2015Co-Authors: Huandong Wang, Ying Zhang, Depeng JinAbstract:Live Migration is a key technique for Virtual Machine (VM) management in data center networks, which enables flexibility in resource optimization, fault tolerance, and load balancing. Despite its usefulness, the live Migration still introduces performance degradations during the Migration process. Thus, there has been continuous efforts in reducing the Migration time in order to minimize the impact. From the network's perspective, the Migration time is determined by the amount of data to be migrated and the available bandwidth used for such transfer. In this paper, we examine the problem of how to schedule the Migrations and how to allocate network resources for Migration when multiple VMs need to be migrated at the same time. We consider the problem in the Software-defined Network (SDN) context since it provides flexible control on routing. More specifically, we propose a method that computes the optimal Migration sequence and network bandwidth used for each Migration. We formulate this problem as a mixed integer programming, which is NP-hard. To make it computationally feasible for large scale data centers, we propose an approximation scheme via linear approximation plus fully polynomial time approximation, and obtain its theoretical performance bound. Through extensive simulations, we demonstrate that our fully polynomial time approximation (FPTA) algorithm has a good performance compared with the optimal solution and two state-of-the-art algorithms. That is, our proposed FPTA algorithm approaches to the optimal solution with less than 10% variation and much less computation time. Meanwhile, it reduces the total Migration time and the service downtime by up to 40% and 20% compared with the state-of-the-art algorithms, respectively.
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Virtual Machine Migration planning in software defined networks
arXiv: Networking and Internet Architecture, 2014Co-Authors: Huandong Wang, Ying Zhang, Depeng JinAbstract:In this paper, we examine the problem of how to schedule the Migrations and how to allocate network resources for Migration when multiple VMs need to be migrated at the same time. We consider the problem in the Software-defined Network (SDN) context since it provides flexible control on routing. More specifically, we propose a method that computes the optimal Migration sequence and network bandwidth used for each Migration. We formulate this problem as a mixed integer programming, which is NP-hard. To make it computationally feasible for large scale data centers, we propose an approximation scheme via linear approximation plus fully polynomial time approximation, and obtain its theoretical performance bound. Through extensive simulations, we demonstrate that our fully polynomial time approximation (FPTA) algorithm has a good performance compared with the optimal solution and two state of-the-art algorithms. That is, our proposed FPTA algorithm approaches to the optimal solution with less than 10% variation and much less computation time. Meanwhile, it reduces the total Migration time and the service downtime by up to 40% and 20% compared with the state-of-the-art algorithms, respectively.
Rong Yu - One of the best experts on this subject based on the ideXlab platform.
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Toward cloud-based vehicular networks with efficient resource management
IEEE Network, 2013Co-Authors: Rong Yu, Wenlong Xia, Stein Gjessing, Yan Zhang, Kun YangAbstract:In the era of the Internet of Things, all components in intelligent transportation systems will be connected to improve transport safety, relieve traffic congestion, reduce air pollution, and enhance the comfort of driving. The vision of all vehicles connected poses a significant challenge to the collection and storage of large amounts of traffic-related data. In this article, we propose to integrate cloud computing into vehicular networks such that the vehicles can share computation resources, storage resources, and bandwidth resources. The proposed architecture includes a vehicular cloud, a roadside cloud, and a central cloud. Then we study cloud resource allocation and Virtual Machine Migration for effective resource management in this cloud-based vehicular network. A game-theoretical approach is presented to optimally allocate cloud resources. Virtual Machine Migration due to vehicle mobility is solved based on a resource reservation scheme.
