Further connections between contract-scheduling and ray-searching problems

Angelopoulos, Spyros

doi:10.1007/s10951-021-00712-8

Cited by 9 publications

(14 citation statements)

References 29 publications

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“…A very recent work [2] studied this problem assuming that the hints are either adversarially generated, or trusted and thus guaranteed to be correct. The techniques we developed and the results we showed in this paper should be readily applicable in searching with noisy, erroneous hints, given the known connections between contract scheduling and searching under the competitive ratio [8,1].…”

Section: Discussionmentioning

confidence: 99%

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Contract Scheduling With Predictions

Angelopoulos,

Kamali

2020

Preprint

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Contract scheduling is a general technique that allows to design a system with interruptible capabilities, given an algorithm that is not necessarily interruptible. Previous work on this topic has largely assumed that the interruption is a worst-case deadline that is unknown to the scheduler. In this work, we study the setting in which there is a potentially erroneous prediction concerning the interruption. Specifically, we consider the setting in which the prediction describes the time that the interruption occurs, as well as the setting in which the prediction is obtained as a response to a single or multiple binary queries. For both settings, we investigate tradeoffs between the robustness (i.e., the worst-case performance assuming adversarial prediction) and the consistency (i.e, the performance assuming that the prediction is error-free), both from the side of positive and negative results.

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Section: Discussionmentioning

confidence: 99%

“…Contract scheduling is an abstraction of resource allocation under uncertainty, in a worst-case setting. As such it has connections to other problems of a similar nature, such as online searching under the competitive ratio [8,1,14].…”

Section: Introductionmentioning

confidence: 99%

Contract Scheduling With Predictions

Angelopoulos,

Kamali

2020

Preprint

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“…In addition, they conjectured that cyclic and monotone trajectories are in fact optimal. Along the same lines, [5] studied cyclic and monotone trajectories for searching m-rays. In a variation of the problem where the hidden item detections are not Bernoulli trials, [5] showed also that cyclic trajectories are in fact sub-optimal.…”

Section: Related Workmentioning

confidence: 99%

“…Along the same lines, [5] studied cyclic and monotone trajectories for searching m-rays. In a variation of the problem where the hidden item detections are not Bernoulli trials, [5] showed also that cyclic trajectories are in fact sub-optimal. For this and many other variations of probabilistically searching, where the probability of success is not known, optimal strategies remain open.…”

Section: Related Workmentioning

confidence: 99%

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Probabilistically Faulty Searching on a Half-Line

Bonato¹,

Georgiou²,

MacRury³

et al. 2020

Preprint

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We study p-Faulty Search, a variant of the classic cow-path optimization problem, where a unit speed robot searches the half-line (or 1-ray) for a hidden item. The searcher is probabilistically faulty, and detection of the item with each visitation is an independent Bernoulli trial whose probability of success p is known. The objective is to minimize the worst case expected detection time, relative to the distance of the hidden item to the origin. A variation of the same problem was first proposed by Gal [28] in 1980. Alpern and Gal [3] proposed a so-called monotone solution for searching the line (2-rays); that is, a trajectory in which the newly searched space increases monotonically in each ray and in each iteration. Moreover, they conjectured that an optimal trajectory for the 2-rays problem must be monotone. We disprove this conjecture when the search domain is the half-line (1-ray). We provide a lower bound for all monotone algorithms, which we also match with an upper bound. Our main contribution is the design and analysis of a sequence of refined search strategies, outside the family of monotone algorithms, which we call t-sub-monotone algorithms. Such algorithms induce performance that is strictly decreasing with t, and for all p ∈ (0, 1). The value of t quantifies, in a certain sense, how much our algorithms deviate from being monotone, demonstrating that monotone algorithms are sub-optimal when searching the half-line.

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Interruptible algorithms for multiproblem solving

Angelopoulos

López-Ortíz

2020

J Sched

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In this paper we address the problem of designing an interruptible system in a setting in which n problem instances, all equally important, must be solved concurrently. The system involves scheduling executions of contract algorithms (which offer a trade-off between allowable computation time and quality of the solution) in m identical parallel processors. When an interruption occurs, the system must report a solution to each of the n problem instances. The quality of this output is then compared to the best-possible algorithm that has foreknowledge of the interruption time and must, likewise, produce solutions to all n problem instances. This extends the well-studied setting in which only one problem instance is queried at interruption time.In this work we first introduce new measures for evaluating the performance of interruptible systems in this setting. In particular, we propose the deficiency of a schedule as a performance measure that meets the requirements of the problem at hand. We then present a schedule whose performance we prove that is within a small factor from optimal in the general, multiprocessor setting. We also show several lower bounds on the deficiency of schedules on a single processor. More precisely, we prove a general lower bound of (n + 1)/n, an improved lower bound for the two-problem setting (n = 2), and a tight lower bound for the class of round-robin schedules. Our techniques can also yield a simpler, alternative proof of the main result of Bernstein et al. [4] concerning the performance of cyclic schedules in multiprocessor environments.

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Further connections between contract-scheduling and ray-searching problems

Cited by 9 publications

References 29 publications

Contract Scheduling With Predictions

Contract Scheduling With Predictions

Probabilistically Faulty Searching on a Half-Line

Interruptible algorithms for multiproblem solving

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