Equipment allocation in video-on-demand network deployments

Thouin, Frederic; Coates, Mark

doi:10.1145/1404880.1404885

Cited by 11 publications

(7 citation statements)

References 14 publications

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“…In [83], a 2-step search heuristic is designed to find the near-optimal placement of VoD servers, a problem referred to as VoD Equipment Allocation problem (EAP). The network is represented as a logical star topology, where the nodes include end-users and the origin server, which is at the center of the topology.…”

Section: Othersmentioning

confidence: 99%

A Survey on Replica Server Placement Algorithms for Content Delivery Networks

Sahoo

Salahuddin

Glitho

et al. 2017

IEEE Commun. Surv. Tutorials

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This paper has been accepted for publication in IEEE Communications Surveys and Tutorials. The copyrights are with IEEE. Abstract: Content Delivery Networks (CDNs) have gained immense popularity over the years. Replica server placement is a key design issue in CDNs. It entails placing replica servers at meticulous locations, such that cost is minimized and Quality of Service (QoS) of end-users is satisfied. Many replica server placement models have been proposed in the literature of traditional CDN. As the CDN architecture is evolving through the adoption of emerging paradigms, such as, cloud computing and Network Functions Virtualization (NFV), new algorithms are being proposed. In this paper, we present a comprehensive survey of replica server placement algorithms in traditional and emerging paradigm based CDNs. We categorize the algorithms and provide a summary of their characteristics. Besides, we identify requirements for an efficient replica server placement algorithm and perform a comparison in the light of the requirements. Finally, we discuss potential avenues for further research in replica server placement in CDNs.

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Section: Othersmentioning

confidence: 99%

A Survey on Replica Server Placement Algorithms for Content Delivery Networks

Sahoo

Salahuddin

Glitho

et al. 2017

IEEE Commun. Surv. Tutorials

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“…Similarly, Kolesar and Walker (1974) considered the redeployment of fire companies in New York City while some of them are responding to a call. An example in digital network design problems is the equipment allocation for video on demand (VoD) network deployments (Thouin and Coates, 2008). VoD services are complex and resource demanding, so deployments involve careful design of many mechanisms where content attributes and usage should be taken into account.…”

Section: Literature Review On the Uflpmentioning

confidence: 99%

Solving the deterministic and stochastic uncapacitated facility location problem: from a heuristic to a simheuristic

Armas

Juan

Marquès

et al. 2017

Journal of the Operational Research Society

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The uncapacitated facility location problem (UFLP) is a popular combinatorial optimization problem with practical applications in different areas, from logistics to telecommunication networks. While most of the existing work in the literature focuses on minimizing total cost for the deterministic version of the problem, some degree of uncertainty (e.g., in the customers' demands or in the service costs) should be expected in real-life applications. Accordingly, this paper proposes a simheuristic algorithm for solving the stochastic UFLP (SUFLP), where optimization goals other than the minimum expected cost can be considered. The development of this simheuristic is structured in three stages: (i) first, an extremely fast savings-based heuristic is introduced; (ii) next, the heuristic is integrated into a metaheuristic framework, and the resulting algorithm is tested against the optimal values for the UFLP; and (iii) finally, the algorithm is extended by integrating it with simulation techniques, and the resulting simheuristic is employed to solve the SUFLP. Some numerical experiments contribute to illustrate the potential uses of each of these solving methods, depending on the version of the problem (deterministic or stochastic) as well as on whether or not a real-time solution is required.

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“…One example is the equipment allocation in Video on Demand (VoD) network deployments (Thouin and Coates 2008). VoD services are complex and resource demanding, so deployments involve careful design of many mechanisms where content attributes and usage should be taken into account.…”

Section: Flp Applications To Telecommunication Networkmentioning

confidence: 99%

Combining biased random sampling with metaheuristics for the facility location problem in distributed computer systems

Cabrera¹,

González-Martín²,

Juan³

et al. 2014

Proceedings of the Winter Simulation Conference 2014

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This paper introduces a probabilistic algorithm for solving the well-known Facility Location Problem (FLP), an optimization problem frequently encountered in practical applications in fields such as Logistics or Telecommunications. Our algorithm is based on the combination of biased random sampling -using a skewed probability distribution-with a metaheuristic framework. The use of random variates from a skewed distribution allows to guide the local search process inside the metaheuristic framework which, being a stochastic procedure, is likely to produce slightly different results each time it is run. Our approach is validated against some classical benchmarks from the FLP literature and it is also used to analyze the deployment of service replicas in a realistic Internet-distributed system.

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Equipment allocation in video-on-demand network deployments

Cited by 11 publications

References 14 publications

A Survey on Replica Server Placement Algorithms for Content Delivery Networks

A Survey on Replica Server Placement Algorithms for Content Delivery Networks

Solving the deterministic and stochastic uncapacitated facility location problem: from a heuristic to a simheuristic

Combining biased random sampling with metaheuristics for the facility location problem in distributed computer systems

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