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2.
云数据中心包含大量计算机,运作成本很高。有效整合资源、提高资源利用率、节约能源、降低运行成本是云数据中心关注的热点。云数据中心通过虚拟化技术将计算资源、存储资源和网络资源构建成动态的虚拟资源池;使用虚拟资源管理技术实现云计算资源自动部署、动态扩展、按需分配;用户采用按需和即付即用的方式获取资源。因此,数据中心对提高资源利用率的迫切需求,促使人们寻求新的方式以建设下一代数据中心。 相似文献
3.
We investigate that resource provisioning and scheduling is a prominent problem due to heterogeneity as well as dispersion of cloud resources. Cloud service providers are building more and more datacenters due to demand of high computational power which is a serious threat to environment in terms of energy requirement. To overcome these issues, we need an efficient meta-heuristic technique that allocates applications among the virtual machines fairly and optimizes the quality of services (QoS) parameters to meet the end user objectives. Binary particle swarm optimization (BPSO) is used to solve real-world discrete optimization problems but simple BPSO does not provide optimal solution due to improper behavior of transfer function. To overcome this problem, we have modified transfer function of binary PSO that provides exploration and exploitation capability in better way and optimize various QoS parameters such as makespan time, energy consumption, and execution cost. The computational results demonstrate that modified transfer function-based BPSO algorithm is more efficient and outperform in comparison with other baseline algorithm over various synthetic datasets. 相似文献
4.
现有云资源管理平台存在着瞬时资源利用率峰值易引发迁移、动态负载效果不佳等问题。依据云资源动态调度模型,提出了有效的基于迁移技术的虚拟机动态调度算法。算法将物理节点负载与虚拟机迁移损耗评估、多次触发控制、目标节点定位三者有机结合,实现云计算数据中心高效的动态负载均衡。实验结果表明,该算法优于CloudSim的DVFS调度策略,在保证应用服务水平的同时能减少虚拟机迁移次数和物理机启用数量。 相似文献
5.
云计算中的服务调度与资源调度对云计算的性能有重要影响,在分析现有云计算调度模式的基础上,针对云计算数据密集与计算密集的特点,提出分层调度策略以实现云计算中的服务与资源调度。分层调度策略对任务进行划分确定作业优先级,并通过数据局部性和总任务完成率对资源进行分配。数值评价部分应用分层调度与已有调度进行比较。实验结果表明,所采用的调度有效提高了资源利用率,为云服务的进一步研究提供了思路。 相似文献
7.
Peer-to-peer (P2P) overlay networks such as BitTorrent and Avalanche are increasingly used for disseminating potentially large
files from a server to many end users via the Internet. The key idea is to divide the file into many equally-sized parts and
then let users download each part (or, for network coding based systems such as Avalanche, linear combinations of the parts)
either from the server or from another user who has already downloaded it. However, their performance evaluation has typically
been limited to comparing one system relative to another and has typically been realized by means of simulation and measurements.
By contrast, we provide an analytic performance analysis that is based on a new uplink-sharing version of the well-known broadcasting
problem. Assuming equal upload capacities, we show that the minimal time to disseminate the file is the same as for the simultaneous
send/receive version of the broadcasting problem. For general upload capacities, we provide a mixed integer linear program
(MILP) solution and a complementary fluid limit solution. We thus provide a lower bound which can be used as a performance
benchmark for any P2P file dissemination system. We also investigate the performance of a decentralized strategy, providing
evidence that the performance of necessarily decentralized P2P file dissemination systems should be close to this bound and,
therefore, that it is useful in practice.
Research of G. Weiss is supported in part by Israel Science Foundation Grants 249/02 and 454/05.
Collaboration of the authors was supported in part by European Network of Excellence Euro-NGI. 相似文献
8.
The Journal of Supercomputing - Cloud infrastructure provides resources needed for tasks for resource scheduling. This work uses a genetic algorithm based on encoded chromosome (GEC-DRP) to manage... 相似文献
9.
如何进一步实现云计算环境下的资源利用最大化是目前研究的热点.建立云计算环境下的资源分配模型,云计算资源调度使用蝙蝠算法,同时引入膜计算概念,提出一种基于膜计算的蝙蝠算法,将膜系统内部分解为主膜和辅助膜,在辅助膜内进行蝙蝠的个体局部寻优,将优化后的个体传送到主膜间进行全局优化,从而达到了云计算资源优化分配要求.通过CloudSim平台与其他算法进行仿真对比表明算法提高了云计算环境下的系统处理时间和效率,使得云计算环境下的资源分配更加合理. 相似文献
10.
The resource discovery problem arises in the context of peer to peer (P2P) networks, where at any point of time a peer may be placed at or removed from any location over a general purpose network (e.g., an Internet site). A node (peer) can communicate with another node directly if and only if it knows a certain routing information to that other node. Hence, a critical task is for the peers to convey this routing information to each other.The problem was formalized by Harchol-Balter et al. and the specific P2P application they had in mind was the logical networks G0 of servers placed by Akamai at various Internet sites. The routing information needed for a node to reach another peer is that peer’s identifier (e.g., IP address). A logical directed edge represents the fact that the peer at the tail of the edge knows the IP address of the one at its head. The problem is to compute the connected components in the underlying graph of G0 (namely, the undirected graph obtained from G0 by removing edge directionality). A number of algorithms were developed in Harchol-Balter et al. for this problem in the model of a synchronous network over a weakly connected directed graph. That is, the assumption was that some clock delivers pulses to every node every time unit at the same time, and a message delivery takes one time unit. The best of these algorithms was randomized. Subsequently, a deterministic algorithm for the problem on synchronous networks with improved complexity was presented in a paper by Kutten et al.The current paper extends the deterministic algorithm of Kutten et al. to the environment of asynchronous networks, where no clock pulses are assumed, and the message delivery time may vary and is not known. We managed to maintain complexities similar to those of the synchronous algorithm of Kutten et al. (translated to the asynchronous model). These are lower than the complexities that would be needed to synchronize the system. The main technical difficulty in a directed, weakly connected system is to ensure that nodes take steps that are consistent with each other, even if their knowledge about each other is not symmetric. Here, this task is further complicated by the fact that there is no timeout mechanism (which does exist in synchronous systems) to assist in ensuring consistency. In particular, as opposed to the case in synchronous systems, an asynchronous algorithm cannot first transform every directed edge to be bidirectional and second, apply an algorithm for bidirectional graph. Thus, our result takes another step towards representing the actual setting in a realistic manner. 相似文献
11.
Resource allocation is a complicated task in cloud computing environment because there are many alternative computers with varying capacities. The goal of this paper is to propose a model for task-oriented resource allocation in a cloud computing environment. Resource allocation task is ranked by the pairwise comparison matrix technique and the Analytic Hierarchy Process giving the available resources and user preferences. The computing resources can be allocated according to the rank of tasks. Furthermore, an induced bias matrix is further used to identify the inconsistent elements and improve the consistency ratio when conflicting weights in various tasks are assigned. Two illustrative examples are introduced to validate the proposed method. 相似文献
12.
Over recent years, peer-to-peer (P2P) systems have become an important part of Internet. Millions of users have been attracted to their structures and services. P2P computing is a distributed computing paradigm that uses Internet to connect thousands, or even millions, of users into a single large virtual computer based on the sharing of computational resources. One of the most critical aspects to the design of P2P computing systems is the development of scheduling techniques to manage the computational resources efficiently and in a scalable way. This paper proposes a cooperative scheduling mechanism with a two-level topology designed to work on large-scale distributed computing P2P systems. Our main contribution is proposing three criteria that only use local information to schedule tasks thus providing scalability to the overall scheduling system. By setting up these three criteria, the system can be easily adapted to work efficiently with very different kinds of distributed applications. The extensive experimentation carried out justifies the importance of good scheduling in such heterogeneous systems, but also emphasizes the importance of having a scheduling algorithm capable of being adapted to the requirements of different kinds of application. 相似文献
13.
P2P video streaming networks are found as a scalable solution and an alternative for traditional client–server based video
streaming over the Internet. One of the significant issues affecting the success of any P2P streaming network is cooperation
between peers. Practical observations have proved the prevalence of free riders in P2P networks that degrade their performance.
To solve this problem, using incentive mechanisms, which encourage peers to contribute more in the network, is necessary.
In this paper, we designed and proposed a distributed and scalable incentive mechanism for mesh based P2P video streaming
networks. In the proposed approach the contribution of the peers is measured and maintained in a distributed fashion. Furthermore,
we proposed an incentive sending side scheduler in which peers are served based on their contribution in the network. Our
simulation evaluations show the efficiency of the proposed approach in improving the overall perceived video quality by the
non-free rider nodes and consequently in the whole network. 相似文献
14.
PurposeThe objective of this study is to optimize task scheduling and resource allocation using an improved differential evolution algorithm (IDEA) based on the proposed cost and time models on cloud computing environment. MethodsThe proposed IDEA combines the Taguchi method and a differential evolution algorithm (DEA). The DEA has a powerful global exploration capability on macro-space and uses fewer control parameters. The systematic reasoning ability of the Taguchi method is used to exploit the better individuals on micro-space to be potential offspring. Therefore, the proposed IDEA is well enhanced and balanced on exploration and exploitation. The proposed cost model includes the processing and receiving cost. In addition, the time model incorporates receiving, processing, and waiting time. The multi-objective optimization approach, which is the non-dominated sorting technique, not with normalized single-objective method, is applied to find the Pareto front of total cost and makespan. ResultsIn the five-task five-resource problem, the mean coverage ratios C(IDEA, DEA) of 0.368 and C(IDEA, NSGA-II) of 0.3 are superior to the ratios C(DEA, IDEA) of 0.249 and C(NSGA-II, IDEA) of 0.288, respectively. In the ten-task ten-resource problem, the mean coverage ratios C(IDEA, DEA) of 0.506 and C(IDEA, NSGA-II) of 0.701 are superior to the ratios C(DEA, IDEA) of 0.286 and C(NSGA-II, IDEA) of 0.052, respectively. Wilcoxon matched-pairs signed-rank test confirms there is a significant difference between IDEA and the other methods. In summary, the above experimental results confirm that the IDEA outperforms both the DEA and NSGA-II in finding the better Pareto-optimal solutions. ConclusionsIn the study, the IDEA shows its effectiveness to optimize task scheduling and resource allocation compared with both the DEA and the NSGA-II. Moreover, for decision makers, the Gantt charts of task scheduling in terms of having smaller makespan, cost, and both can be selected to make their decision when conflicting objectives are present. 相似文献
15.
如何合理地分配云计算资源一直都是研究的热点.建立云计算环境下的资源调度模型,通过人工萤火虫算法个体最优与云计算节点资源分配对应起来,在算法中引入高斯变异算法,通过与经典函数比较,优化后的算法在搜索精度上以及收敛速度上有了很大的提高.通过在CloudSim平台上与经典智能算法的比较,该算法能够有效地提高云计算中的资源调度性能,缩短任务完成的时间,提高系统整体处理能力. 相似文献
16.
针对当前网格资源管理中任务与资源匹配的缺陷,基于信任效益函数和最小完成时间,提出了基于信任的Trust Mintime Min-Min算法.分析了传统的Min-Min算法,考虑Min-Min算法负载不平衡,对其在调度策略方面进行了改进.仿真实验表明,该算法不但可以有效地平衡负载,而且可以提高任务的完成率,兼顾计算的有效性和可靠性. 相似文献
17.
We examine the worst-case performance of a class of heuristic scheduling algorithms commonly referred to as priority-driven or list-scheduling algorithms. It is well known that these algorithms have anomalous, unpredictable performance when used to schedule nonpreemptive tasks with precedence constraints. We present a general method for deriving the worst-case performance of these algorithms. This method is easy to use, yet powerful enough to yield tight performance bounds for many classes of scheduling problems. We demonstrate the method for several problems to show it has wide applicability. We also present several task systems for which list-scheduling algorithms exhibit unavoidable worst-case performance and discuss the general characteristics of these task systems. These task systems are sometimes overlooked in simulation studies; consequently, the results of these studies may be overly optimistic.This work was partially supported by the US Navy. ONR Contract No. NVY N0001489 J1181 相似文献
18.
Resource scheduling problems are considered as multicriterial multi-index transport-type problems. Computational procedures for solving stated problems by using the direct search of an optimal node of a multidimensional multivalued cube are proposed. 相似文献
19.
A main challenge in project management is to provide methodologies that facilitate coordination among the projects in a portfolio or in a firm. Each incoming project in an existing portfolio affects its schedule, the resources availability and the planned performance. There are no analytical solutions for the problem of dynamic scheduling of resources for multiple projects in real time. Mathematical approaches, like integer programming or network based techniques, cannot describe the complexity of real problems (multi-projects environments have many interrelated elements), and have difficulties to adapt the analysis to dynamic changes.We propose a multi-agent system, where projects negotiate the procurement of resources through an auction mechanism all over the portfolio life. Both, projects and resources are modelled as agents. Projects demand resources for fulfilling their scheduled planned work, whereas resources offer their capabilities and workforce. This framework allows project portfolio management and the assessment in the decision of acceptance/rejection new projects. 相似文献
20.
如何对任务进行高效合理的调度是云计算需要解决的关键问题之一,针对云计算的编程模型框架,在传统粒子群优化算法(PSO)的基础上,提出了一种具有双适应度的粒子群算法(DFPSO)。通过该算法不但能找到任务总完成时间较短的调度结果,而且此调度结果的任务平均完成时间也较短。仿真分析结果表明,在相同的条件设置下,该算法优于传统的粒子群优化算法,当任务数量增多时,其综合调度性能优点明显。 相似文献
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