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111.
Geographically distributed cloud platforms enable an attractive approach to large-scale content delivery. Storage at various sites can be dynamically acquired from (and released back to) the cloud provider so as to support content caching, according to the current demands for the content from the different geographic regions. When storage is sufficiently expensive that not all content should be cached at all sites, two issues must be addressed: how should requests for content be routed to the cloud provider sites, and what policy should be used for caching content using the elastic storage resources obtained from the cloud provider. Existing approaches are typically designed for non-elastic storage and little is known about the optimal policies when minimizing the delivery costs for distributed elastic storage.In this paper, we propose an approach in which elastic storage resources are exploited using a simple dynamic caching policy, while request routing is updated periodically according to the solution of an optimization model. Use of pull-based dynamic caching, rather than push-based placement, provides robustness to unpredicted changes in request rates. We show that this robustness is provided at low cost. Even with fixed request rates, use of the dynamic caching policy typically yields content delivery cost within 10% of that with the optimal static placement. We compare request routing according to our optimization model to simpler baseline routing policies, and find that the baseline policies can yield greatly increased delivery cost relative to optimized routing. Finally, we present a lower-cost approximate solution algorithm for our routing optimization problem that yields content delivery cost within 2.5% of the optimal solution. 相似文献
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113.
The presented work is part of a larger research program dealing with developing tools for coupling biogeochemical models in contaminated landscapes. The specific objective of this article is to provide researchers with a data porting tool to build hexagonal raster using information from a rectangular raster data (e.g. GIS format). This tool involves a computational algorithm and an open source software (written in C). The method of extending the reticulated functions defined on 2D networks is an essential key of this algorithm and can also be used for other purposes than data porting. The algorithm allows one to build the hexagonal raster with a cell size independent from the geometry of the rectangular raster. The extended function is a bi-cubic spline which can exactly reconstruct polynomials up to degree three in each variable. We validate the method by analyzing errors in some theoretical case studies followed by other studies with real terrain elevation data. We also introduce and briefly present an iterative water routing method and use it for validation on a case with concrete terrain data. 相似文献
114.
Miada A. Murad Mariya M. Kaleemullah Soha S. Zaghloul 《通讯和计算机》2014,(3):278-283
Moveable bubble flow control is an efficient technique to avoid deadlock for torus networks. However, it does not take into consideration the load balance feature. Therefore, this leads to inefficient resources utilization. Moreover, packets may be discarded due to the congestion of a network area. On the other hand, there are other algorithms that consider load balancing such as rHALB (r hop adaptive load-balanced)routing technique. Nonetheless, rHALB detects deadlock using the timeout threshold. This concept of deadlock detection may give incorrect responses in case the traffic is high. Therefore, packets are dropped although there is no deadlock. At the end, this affects the whole performance of the network. This paper proposes a new routing algorithm for tori interconnection networks, namely, the LBMBS (load-balanced moveable bubble scheme). LBMBS integrates both concepts of moveable bubble and rHALB in order to provide at the end a load-balanced efficient deadlock-free algorithm. The protocol details are given and compared against other routing algorithms in the literature. 相似文献
115.
研究在不使用局部搜索情况下参数组合对改进型蚁群算法的影响。以带时间窗的车辆路径问题为例,针对基于最大最小蚁群算法的改进蚁群算法中的五个参数,运用均匀设计法对最优参数配置问题进行了研究。仿真实验表明改进的蚁群算法效果明显,能有效解决Solomon数据集中的R类和RC类问题,且具有较强的鲁棒性。对最优参数的局部调整没有明显提高算法获取最优解能力的问题,分析了其可能的原因。 相似文献
116.
针对现有的贪婪方法不能有效处理拓扑结构中链路故障的问题,提出单链路故障和多链路故障本地化恢复策略。首先,通过利用克莱因伯格的贪婪嵌入给出单链路故障恢复策略;然后,将其扩展到多链路故障的情况;最后,在基于Python/C++的仿真环境下对提出的技术进行评估。实验结果表明,该技术仅需要非常有限的资源,且造成的路由质量损耗也有限,可以实现快速切换,可依网络生成树中链路数目扩展。该技术的可扩展性、简单性和低开销使其适合于大型网络。 相似文献
117.
在非结构化P2P搜索中,由于缺少全局性的管理机制,网络节点无法获得整个网络的拓扑结构及目标数据的定位信息,因此查询消息的路由过程具有较高的随机性,不仅查询性能低,而且宽带消耗大。为在有效控制网络冗余消息规模的同时提高数据的搜索范围,在分析现有2类典型非结构化P2P路由算法的基础上,提出一种基于节点的MQR算法。利用网络节点的状态信息及搜索过程中查询消息的TTL值状态信息,从数据的搜索范围与网络使用情况2个方面来提高非结构化P2P网络搜索性能。仿真实验结果表明,与传统的P2P路由算法APS和Random Walk相比,该算法在搜索准确率、网络利用率及召回率方面有更好的表现。 相似文献
118.
119.
针对传统的物流运输调度问题(Vehicle Routing Problem,VRP)中车辆之间不协作会造成资源浪费的情况,提出整合资源条件下的运输调度问题(Vehicle Routing Problem with Integration of resources,VRPIR),建立了相应的数学模型。由于混沌具有良好的遍历性,而粒子群优化算法(Particle Swarm Optimization,PSO)具有概念简单,参数少,容易实现等优点,将混沌优化方法引入到粒子群优化算法中,应用混沌粒子群优化算法(Chaos Particle Swarm Algorithm,CPSO)求解VRPIR和VRP,并用CPSO和PSO分别求解VRPIR,实验结果证明该算法优于粒子群优化算法,也证明了提出的VRPIR模型优于VRP,能节省资源,且最小化成本。 相似文献
120.
Claudia Archetti Nicola Bianchessi Stefan Irnich M. Grazia Speranza 《International Transactions in Operational Research》2014,21(3):353-374
In this paper, we present and compare formulations for the inventory routing problem (IRP) where the demand of customers has to be served, over a discrete time horizon, by capacitated vehicles starting and ending their routes at a depot. The objective of the IRP is the minimization of the sum of inventory and transportation costs. The formulations include known and new mathematical programming formulations. Valid inequalities are also presented. The formulations are tested on a large set of benchmark instances. One of the most significant conclusions is that the formulations that use vehicle‐indexed variables are superior to the more compact, aggregate formulations. 相似文献