22 research outputs found
On the Definition of "On-Line" in Job Scheduling Problems
The conventional model of on-line scheduling postulates that jobs have non-trivial release dates, and are not known in advance. However, it fails to impose any stability constraints, leading to algorithms and analyses that must deal with unrealistic load conditions arising from trivial release dates as a special case. In an effort to make the model more realistic, we show how stability can be expressed as a simple constraint on release times and processing times. We then give empirical and theoretical justifications that such a constraint can close the gap between the theory and practice. As it turns out, this constraint seems to trivialize the scheduling problem
The Impact of More Accurate Requested Runtimes on Production Job Scheduling Performance
Abstract. The question of whether more accurate requested runtimes can significantly improve production parallel system performance has previously been studied for the FCFS-backfill scheduler, using a limited set of system performance measures. This paper examines the question for higher performance backfill policies, heavier system loads as are observed in current leading edge production systems such as the large Origin 2000 system at NCSA, and a broader range of system performance measures. The new results show that more accurate requested runtimes can improve system performance much more significantly than suggested in previous results. For example, average slowdown decreases by a factor of two to six, depending on system load and the fraction of jobs that have the more accurate requests. The new results also show that (a) nearly all of the performance improvement is realized even if the more accurate runtime requests are a factor of two higher than the actual runtimes, (b) most of the performance improvement is achieved when test runs are used to obtain more accurate runtime requests, and (c) in systems where only a fraction (e.g., 60%) of the jobs provide approximately accurate runtime requests, the users that provide the approximately accurate requests achieve even greater improvements in performance, such as an order of magnitude improvement in average slowdown for jobs that have runtime up to fifty hours.
Comparison of multi-criteria scheduling techniques
This paper proposes a novel schedule-based approach for scheduling a continuous stream of batch jobs on the machines of a computational Grid. Our new solutions represented by dispatching rule Earliest Gapâ Earliest Deadline First (EG-EDF) and Tabu search are based on the idea of filling gaps in the existing schedule. EG-EDF rule is able to build the schedule for all jobs incrementally by applying technique which fills earliest existing gaps in the schedule with newly arriving jobs. If no gap for a coming job is available EG-EDF rule uses Earliest Deadline First (EDF) strategy for including new job into the existing schedule. Such schedule is then optimized using the Tabu search algorithm moving jobs into earliest gaps again. Scheduling choices are taken to meet the Quality of Service (QoS) requested by the submitted jobs, and to optimize the usage of hardware resources. We compared the proposed solution with some of the most common queue-based scheduling algorithms like FCFS, EASY backfilling, and Flexible backfilling. Experiments shows that EG-EDF rule is able to compute good assignments, often with shorter algorithm runtime w.r.t. the other queue-based algorithms. Further Tabu search optimization results in higher QoS and machine usage while keeping the algorithm runtime reasonable
Truthful Mechanism Design for Multidimensional Covering Problems
We investigate multidimensional covering mechanism-design problems, wherein there are m items that need to be covered and n agents who provide covering objects, with each agent i having a private cost for the covering objects he provides. The goal is to select a set of covering objects of minimum total cost that together cover all the items. We focus on two representative covering problems: uncapacitated facility location (UFL) and vertex cover (VC). For multidimensional UFL, we give a black-box method to transform any Lagrangian-multiplier-preserving Ï-approximation algorithm for UFL to a truthful-in-expectation, Ï-approx. mechanism. This yields the first result for multidimensional UFL, namely a truthful-in-expectation 2-approximation mechanism. For multidimensional VC (Multi-VC), we develop a decomposition method that reduces the mechanism-design problem into the simpler task of constructing threshold mechanisms, which are a restricted class of truthful mechanisms, for simpler (in terms of graph structure or problem dimension) instances of Multi-VC. By suitably designing the decomposition and the threshold mechanisms it uses as building blocks, we obtain truthful mechanisms with approximation ratios (n is the number of nodes): (1) O(log n) for Multi-VC on any minor-closed family of graphs; and (2) O(r 2 log n) for r-dimensional VC on any graph. These are the first truthful mechanisms for Multi-VC with non-trivial approximation guarantees