General perfectly periodic scheduling

Brakerski, Zvika; Nisgav, Aviv; Patt-Shamir, Boaz

doi:10.1145/571825.571854

Cited by 15 publications

(24 citation statements)

References 14 publications

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“…Fast Distributed Resolution. To the best of our knowledge, the only previously known schedules with distributed resolutions of O(1) time per slot are the perfectly-periodic schedules introduced by Bar-Noy, Nisgav and Patt-Shamir [11] and further studied in [17,9]. Their approach takes to the extreme the concept of 'as evenly distributed as possible'; namely, the time-slots allocated to a client are required to constitute an arithmetic sequence.…”

Section: Related Workmentioning

confidence: 99%

On Centralized Smooth Scheduling

Litman

Moran-Schein

2009

Algorithmica

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This paper studies evenly distributed sets of natural numbers and their applications to scheduling in a distributed environment. Such sets, called smooth sets, have the property that their quantity within each interval is proportional to the size of the interval, up to a bounded additive deviation; namely, for ρ, ∆ ∈ R a set A of natural numbers is (ρ, ∆)-smooth if abs(|I| · ρ − |I ∩ A|) < ∆ for any interval I ⊂ N.The current paper studies scheduling persistent clients on a single slot-oriented resource in a flexible, predictable and distributed manner. Each client γ has a given rate ρ γ that defines the share of the resource he is entitled to receive and the goal is a smooth schedule in which, for some predefined ∆, each client γ is served in a (ρ γ , ∆)-smooth set of slots (natural numbers). The paper focuses on a distributed environment where each client by itself (without any inter-client communication) resolves (computes), slot after slot, whether or not it owns this slot. The paper presents extremely efficient schedules under which a client resolves each slot in a constant time.The paper considers two scheduling frameworks. The first one, the Flat Scheduling Framework, is the common problem where the rates of the clients are given a priori. In the second and novel framework, the Open-Market Scheduling Framework, fractions of the resource are bought and sold by dealers. Each dealer, upon receiving his fraction, may choose either to become a client and use his share, or to remain a dealer and sell fractions of his share to other dealers. In this framework, the allocation process is highly distributed; moreover, fractions of several resources can be combined into a single virtual resource of new capabilities.The paper presents two scheduling techniques. Both techniques, in both frameworks, produce smooth schedules with highly efficient distributed resolutions -a client resolves each slot in O(1) time on a RAM with a moderate number of memory words, all of a small size. Each technique has its pros and cons. For example, one technique utilizes 100% of the resource but its resolution algorithm requires a number of words which is linear in the number of clients; the other technique utilizes only 99% of the resource but its resolution algorithm requires just O(1) words.One of these techniques yields a solution to Tijdeman's Hierarchial Chairman Assignment Problem which outperforms prior solutions. The other technique naturally extends to the problem of scheduling multiple resources, under the restriction that a client may be served concurrently by at most one resource. The extension yields the first solution to this problem having efficient distributed resolution. Prior solutions produce a special type of smooth scheduling called P-fair scheduling, are centralized, and are less efficient than ours.

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Section: Related Workmentioning

confidence: 99%

On Centralized Smooth Scheduling

Litman

Moran-Schein

2009

Algorithmica

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“…Schedules that minimize response time for push-based broadcast have been extensively studied in the algorithmic community (e.g., [5] and [16]). These studies complement to our work in different aspects.…”

Section: Related Workmentioning

confidence: 99%

Time-critical on-demand data broadcast: algorithms, analysis, and performance evaluation

Tang

Lee

2006

IEEE Trans. Parallel Distrib. Syst.

148

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On-demand broadcast is an effective wireless data dissemination technique to enhance system scalability and deal with dynamic user access patterns. With the rapid growth of time-critical information services in emerging applications, there is an increasing need for the system to support timely data dissemination. This paper investigates online scheduling algorithms for time-critical on-demand data broadcast. We propose a novel scheduling algorithm called SIN-α that takes the urgency and number of outstanding requests into consideration. An efficient implementation of SIN-α is presented. We also analyze the theoretical bound of request drop rate when the request arrival rate rises towards infinity. Trace-driven experiments show that SIN-α significantly outperforms existing algorithms over a wide range of workloads and approaches the analytical bound at high request rates.

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“…The design of perfectly-smooth schedulers can be found in [7,8,9,10,11] and the design of an online perfectly-fair scheduler that maximizes the throughput is considered in [12,13,14]. Given that the packet arrival process to each user is independent and identically distributed (i.i.d),…”

Section: Data Forwarding In Wireless Sensor Networkmentioning

confidence: 99%

Design and analysis of a class-aware recursive loop scheduler for class-based scheduling

Rom

Sidi

Tan

2006

Performance Evaluation

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In this paper, we consider the problem of devising a loop scheduler that allocates slots to users according to their relative weights as smoothly as possible. Instead of the existing notion of smoothness based on balancedness, we propose a variance-based metric which is more intuitive and easier to compute.We propose a recursive loop scheduler for a class-based scheduling scenario based on an optimal Weighted Round Robin scheduler. We show that it achieves very good allocation smoothness with almost no degradation in intra-class fairness. In addition, we also demonstrate the equivalence between our proposed metric and the balancedness-based metric.

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General perfectly periodic scheduling

Cited by 15 publications

References 14 publications

On Centralized Smooth Scheduling

On Centralized Smooth Scheduling

Time-critical on-demand data broadcast: algorithms, analysis, and performance evaluation

Design and analysis of a class-aware recursive loop scheduler for class-based scheduling

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