Algorithms for generalized round robin routing

Arian, Yair; Levy, Yonatan

doi:10.1016/0167-6377(92)90091-g

Cited by 31 publications

(16 citation statements)

References 5 publications

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“…An exhaustive numerical analysis reveals that a broker deterministically forwarding jobs to queues according to a proposed billiard scheme [5,21], a generalization of round-robin, yields a response time remarkably close to our lower bound. In other words, we empirically claim the proposed billiard scheme achieves the minimum response time that, in turn, is very-well captured by our bound and approximations.…”

Section: Our Contributionmentioning

confidence: 99%

“…We consider the case where the broker forwards jobs to queues according to billiard sequences, see [5,21], that are constructed through the SG algorithm introduced in [21] (easily implementable in network brokers with a very limited cost). The SG algorithm takes as input the fraction of jobs to send to the queues (given by the solution of (21)) and an initial-position vector x ∈ R N which we assume such that x i = 1 if µ i = max j µ j and 0 otherwise (we point the reader to [21] for further details on the SG algorithm and billiard sequences).…”

Section: Quasi-optimality Of Billiard Sequencesmentioning

confidence: 99%

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The price of forgetting in parallel and non-observable queues

Anselmi¹,

Gaujal²

2011

Performance Evaluation

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We consider a broker-based network of non-observable parallel queues and analyze the minimum expected response time and the optimal routing policy when the broker has the memory of its previous routing decisions. We provide lower bounds on the minimum response time by means of convex programming that are tight, as follows by a numerical comparison with a proposed routing scheme. The Price of Forgetting (PoF), the ratio between the minimum response times achieved by a probabilistic broker and a broker with memory, is shown to be unbounded or arbitrarily close to one depending on the coe cient of variation of the service time distributions. In the case of exponential service times, the PoF is bounded from above by two, which is tight in heavy-tra c, and independent of the network size and heterogeneity. These properties yield a simple engineering product-form approximating tightly the minimum response time. Finally, we put our results in the context of game theory revisiting the Price of Anarchy (PoA) of parallel queues: It can be decomposed into the product of the PoA achieved by a probabilistic broker (already well understood) and the PoF. IntroductionIn the context of *-computing and manufacturing systems, users submit jobs without knowing which machine will handle their execution. A central broker is usually in charge of distributing incoming jobs to a set of resources to optimize some utility or cost function. The mean response time (simply response time in the following), the expected time it takes for a job to join the system and return to its issuer, is an important metric that is usually taken into account to achieve a better exploitation of resources and improve the average quality of service.The problem of nding the routing strategy (or policy) that minimizes response time and the resulting response time itself are well-known problem in queueing theory and the literature is overwhelming. There are two main classes of routing strategies: Closed-loop policies, where the broker knows the state of each resource (number of jobs), and open-loop policies, where the broker does not know their state. Computing the best closed-loop policy is known to be a hard problem and a lot of work has been devoted to the computation of good approximations; see, e.g., [9,27, 33] and the references therein.The focus of this paper is on the open-loop case, and more precisely on o -line policies. Indeed, the state of the queues may not to be known on-line to the broker because of a number of reasons whose e ects become worse and worse as the network size increases: i) Communicating the system state to the broker increases the network load, ii) the information received by the broker can be out of date, and iii) the synchronization that results from knowing the system state can degrade the performance [26]. A celebrated case is when the broker only knows the service time distributions of the network resources (or queues in the following) and dispatches jobs to queues according to an i.i.d. probabilistic law. The probabili...

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Section: Our Contributionmentioning

confidence: 99%

Section: Quasi-optimality Of Billiard Sequencesmentioning

confidence: 99%

The price of forgetting in parallel and non-observable queues

Anselmi¹,

Gaujal²

2011

Performance Evaluation

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“…FCFS [6], an algorithm in which task that arrives first will be scheduled first of all and resources are allocated to that task as it needs. Once the task is executed, the next task in queue is scheduled next.…”

Section: Comparison Of Various Task Scheduling Algorithms a Firstmentioning

confidence: 99%

A Review Paper on Various Task Scheduling Algorithms in Cloud Computing

Kaur

2017

IJARCSSE

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Abstract-Cloud Computing is a computing environment where different services are provided to users over the Web. Task Scheduling is one of the important aspects of Cloud Computing, improving the performance of the cloud system. Task Scheduling involves assignment of resources to a particular task for the task to be completed within possible minimum time. Task Scheduling helps in achieving efficient utilization of resources. This paper presents a review of various task scheduling algorithms in Cloud Computing.

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“…With future research in mind, we note that these studies suggest other approaches worth investigating, e.g., extensions of the mathematical programming techniques in and the algorithms (Arian and Levy, 1992) derived from Hajek's results on regular binary sequences (Hajek, 1985). Although the latter lack the established performance bounds of the golden-ratio policy, simulations in the earlier queueing models show they are superior algorithms.…”

Section: Is Large Ifmentioning

confidence: 99%

“…We remark that this problem is closely related to the design and analysis of polling/ splitting sequences in the context of queueing (and in particular, communication) systems (Andrews et al, 1997;Arian and Levy, 1992;1993), where algorithms are described as template driven or generalized round robin. With future research in mind, we note that these studies suggest other approaches worth investigating, e.g., extensions of the mathematical programming techniques in and the algorithms (Arian and Levy, 1992) derived from Hajek's results on regular binary sequences (Hajek, 1985).…”

Section: Is Large Ifmentioning

confidence: 99%

Optimization Issues in Web Search Engines

Liu

Nain²

Handbook of Optimization in Telecommunications

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Crawlers are deployed by a Web search engine for collecting information from different Web servers in order to maintain the currency of its data base of Web pages. We present studies on the optimization of Web search engines from different perspectives. We first investigate the number of crawlers to be used by a search engine so as to maximize the currency of the data base without putting an unnecessary load on the network. Both the static setting, where crawlers are always active, and the dynamic setting where, crawlers may be activated/deactivated as a function of the state of the system, are addressed. We then consider the optimal scheduling of the visits of these crawlers to the Web pages assuming these pages are modified at different rates. Finally, we briefly discuss some other optimization issues of Web search engines, including page ranking and system optimization.

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Algorithms for generalized round robin routing

Cited by 31 publications

References 5 publications

The price of forgetting in parallel and non-observable queues

The price of forgetting in parallel and non-observable queues

A Review Paper on Various Task Scheduling Algorithms in Cloud Computing

Optimization Issues in Web Search Engines

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