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Veeravalli, Bharadwaj; Barlas, Gerassimos

doi:10.1023/a:1009623825393

Cited by 29 publications

(3 citation statements)

References 16 publications

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“…The idea of combining multiple geographically distributed servers for video data delivery was originally introduced in [20]. The idea of using multiple connections to geographically distributed mirror sites has been also suggested by Rodriguez et.al.…”

Section: Related Workmentioning

confidence: 99%

“…The problem of a single client with multiple servers has been examined before in the literature [20], where a thorough comparison of single and multiinstallment strategies is available. The derivations presented in subsections 4.1 and 4.2 are simplifications of work presented in [3].…”

Section: Problem Descriptionmentioning

confidence: 99%

“…The framework needed for scheduling such a delivery has been originally presented in [20] and further expanded and refined in subsequent publications [3] for the case of a single client. In this paper we address the problem of how a system with multiple clients and servers behaves and what are the characteristics of the services offered.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Optimizing Continuous Media Delivery by Multiple Distributed Servers to Multiple Clients Using a Genetic Algorithm

Barlas

El-Fakih

2004

Management of Multimedia Networks and Services

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Abstract. In this paper we explore the potential of a VoD system that is based on a paradigm that has been recently proposed: that of combining many distributed servers to handle the delivery of each requested media. When faced with a system comprised of N servers and M clients, the problems to be addressed are: (i) how to split the delivery task among different servers and (ii) how to pair clients and servers, the objective being to minimize the access time of the clients. To this end, we present an analytical framework that enables the division of the delivery process for each client in a distributed manner. This framework is coupled with a genetic algorithm that enables an optimal or near-optimal solution to the problem of pairing clients and servers, in a small number of generations. The paper is concluded by a rigorous study of a N -servers, M -clients system that answers a number of important questions like, what is the quality of service achieved and how our proposed system behaves under increased load.

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Section: Related Workmentioning

confidence: 99%

Section: Problem Descriptionmentioning

confidence: 99%

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Optimizing Continuous Media Delivery by Multiple Distributed Servers to Multiple Clients Using a Genetic Algorithm

Barlas

El-Fakih

2004

Management of Multimedia Networks and Services

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Multi‐installment divisible load processing in heterogeneous distributed systems

Drozdowski

Lawenda

2007

Concurrency and Computation

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SUMMARYDivisible loads are parallel applications with fine granularity and negligible data dependencies. Such computations can be divided into parts of arbitrary sizes and processed independently in parallel. The load distribution process incurs considerable communication delays. To reduce processor waiting time during the computation initialization phase, the load is distributed in multiple small installments rather than in one big chunk. In this paper we analyze multi-installment divisible load processing in heterogeneous distributed systems. Scheduling divisible loads in heterogeneous systems is hard because the sizes of the installments should be adjusted to the communication and computation capabilities of the system. We show that ignoring heterogeneity of the distributed system may result in arbitrarily bad solutions. Two algorithms are proposed to gear the load chunk sizes to different communication and computation speeds: an optimization branch-and-bound algorithm and a heuristic based on a genetic search method. The running times of both methods and the quality of the solutions are compared. Then, we use these algorithms to study the features of the multi-installment divisible load scheduling problem. We demonstrate that it has both combinatorial and algebraic nature, and that optimum solutions are harder to find with the growing heterogeneity of the system.

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An energy‐aware scheduling algorithm for divisible loads in a bus network

Duan-yang

Yang

Cheng

2015

Concurrency and Computation

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SUMMARYThe schedule of divisible loads is one of the most typical problems in the research and application of parallel and distributed systems. For these large-scale systems, the energy consumption problem has drawn great attention in recent years because of falling hardware costs and the growing concern of energy costs. In computing-intensive systems, energy is primarily consumed by CPUs, and dynamic voltage-frequency scaling technology is capable of adjusting CPUs' speed as well as saving energy. In this paper, we focus on computing-intensive applications and study the energy-aware scheduling problem for divisible loads in a bus network. The energy-speed model is introduced to characterize the problem based on dynamic voltage scaling, and the energy-aware scheduling problem is analyzed in the application layer above the operating system. The problem can be formulated mathematically as a nonlinear programming problem, and the solution is achieved using the Lagrange multiplier method under Kuhn-Tucker conditions. Based on the analytical results, an energy-aware scheduling scheme called ENERG for divisible loads is presented. Finally, the energy-aware scheme is compared with two other schemes to show the effectiveness and efficiency of the energy savings of our algorithm. Additionally, the experimental results illustrate the influence of network transmission delay on energy consumption.

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Untitled

Cited by 29 publications

References 16 publications

Optimizing Continuous Media Delivery by Multiple Distributed Servers to Multiple Clients Using a Genetic Algorithm

Optimizing Continuous Media Delivery by Multiple Distributed Servers to Multiple Clients Using a Genetic Algorithm

Multi‐installment divisible load processing in heterogeneous distributed systems

An energy‐aware scheduling algorithm for divisible loads in a bus network

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