Designing cost-effective content distribution networks

Bektaş, Tolga; Oğuz, Osman; Ouveysi, Iradj

doi:10.1016/j.cor.2005.09.013

Cited by 48 publications

(32 citation statements)

References 32 publications

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“…Bektas, Oguz, and Ouveysi [4] present a model for a fully meshed network that determines optimal storage locations of each program and routing of programs to demand nodes, and Bektas, Oguz, and Ouveysi [5] present a content distribution model with multiple programs for a logical network, where servers are directly connected to the central server and each of the demand nodes is directly connected to one of the servers. Ogryczak [35] extends the well-known network center problem and presents an algorithm for equitable location of facilities in a general network using a lexicographic minimax objective.…”

Section: Other Referencesmentioning

confidence: 99%

Equitable bandwidth allocation in content distribution networks

Luss¹

2010

Naval Research Logistics

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Applications for content distribution over networks, such as Video-on-Demand (VOD), are expected to grow significantly over time. Effective bandwidth allocation schemes that can be repeatedly executed must be deployed since new programs are often installed at various servers while other are deleted. We present a model for bandwidth allocation in a content distribution network that consists of multiple trees, where the root of each tree has a server that broadcasts multiple programs throughout the tree. Each network link has limited capacity and may be used by one or more of these trees. The model is formulated as an equitable resource allocation problem with a lexicographic maximin objective function that attempts to provide equitable service performance for all requested programs at the various nodes. The constraints include link capacity constraints and tree-like ordering constraints imposed on each of the programs. We present an algorithm that provides an equitable solution in polynomial time for certain performance functions. At each iteration, the algorithm solves single-link maximin optimization problems while relaxing the ordering constraints. The algorithm selects a bottleneck link, fixes various variables at their lexicographic optimal solution while enforcing the ordering constraints, and proceeds with the next iteration.

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Section: Other Referencesmentioning

confidence: 99%

Equitable bandwidth allocation in content distribution networks

Luss¹

2010

Naval Research Logistics

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“…In fact, the CDN-related design problems to which it can be applicable are numerous. Examples are web object replication [15,18], request routing [18], cache location [16] and topological design for service overlay networks [17]. A common characteristic of these CDN design problems is that their optimization objectives are influenced by the accuracy of estimated traffic demands.…”

Section: Discussionmentioning

confidence: 99%

“…This criterion is chosen based on a general observation that the decision makers are (in many cases) risk-averse, meaning that the RSP solution CDN providers want is neither the "optimal" for a particular traffic demand scenario nor the "worst" for any scenario but one that performs reasonably well across all the scenarios. Such risk-averse behavior may also be observed from capacity overprovisioning employed by top-tier Internet service providers as a means to provide good service to all IP traffic in their backbone networks [18]. Hence, CDN providers may want to optimize the worst-case network performance in order to prevent severe unpredicted performance degradation and the need for future expensive network capacity upgrading.…”

Section: B Choice Of Robustness Criteriamentioning

confidence: 99%

Managing Traffic Demand Uncertainty in Replica Server Placement with Robust Optimization

Georgoulas

Amin

et al. 2006

NETWORKING 2006. Networking Technologies, Services, and Protocols; Performance of Computer and Communication Networks; Mobile A

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Abstract. The replica server placement problem determines the optimal location where replicated servers should be placed in content distribution networks, in order to optimize network performance. The estimated traffic demand is fundamental input to this problem and its accuracy is essential for the target performance to be achieved. However, deriving accurate traffic demands is far from trivial and uncertainty makes the target performance hard to predict. We argue that it is often inappropriate to optimize the performance for only a particular set of traffic demands that is assumed accurate. In this paper, we propose a scenario-based robust optimization approach to address the replica server placement problem under traffic demand uncertainty. The objective is to minimize the total distribution cost across a variety of traffic demand scenarios while minimizing the performance deviation from the optimal solution. Empirical results demonstrate that robust optimization for replica server placement can achieve good performance under all the traffic demand scenarios while nonrobust approaches perform significantly worse. This approach allows content distribution providers to provision better and predictable quality of service for their customers by reducing the impact of inaccuracy in traffic demand estimation on the replica server placement optimization.

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“…Data placement problems have been studied extensively in the context of database management (Gavish and Suh 1992;Liu Sheng and Lee 1992;Pirkul 1986;Wolfson et al 1997), organization of distributed file systems (Bokhari 1987;Laning and Leonard 1983), cooperative caching in networks (Korupolu et al 1999), and more recently, content delivery networks and Web traffic (Bektas et al 2007(Bektas et al , 2008; Rodolakis et al 2006;Sivasubramanian et al 2004). Related problems of on-line data management were considered in the competitive analysis framework, e.g.…”

Section: Related Workmentioning

confidence: 99%

Decomposition algorithms for data placement problem based on Lagrangian relaxation and randomized rounding

Drwal

Józefczyk

2013

Ann Oper Res

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The data placement problem arises in the design and operation of Content Delivery Networks-computer systems used to efficiently distribute Internet traffic to the users by replicating data objects (media files, applications, database queries, etc.) and caching them at multiple locations in the network. This allows not only to reduce the processing load on the server hardware, but also helps eliminating transmission network congestion. Currently all major Internet content providers entrust their offered services to such systems. In this paper we formulate the data placement problem as quadratic binary programming problem, taking into account server processing time, storage capacity and communication bandwidth. Two decomposition-based solution approaches are proposed: the Lagrangian relaxation and randomized rounding. Computational experiments are conducted in order to evaluate and compare the performance of presented algorithms.

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Designing cost-effective content distribution networks

Cited by 48 publications

References 32 publications

Equitable bandwidth allocation in content distribution networks

Equitable bandwidth allocation in content distribution networks

Managing Traffic Demand Uncertainty in Replica Server Placement with Robust Optimization

Decomposition algorithms for data placement problem based on Lagrangian relaxation and randomized rounding

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