The Power of Migration for Online Slack Scheduling

We investigate the power of migration in online scheduling for parallel identical machines. Our objective is to maximize the total processing time of accepted jobs. Once we decide to accept a job, we have to complete it before its deadline d that satisfies d >= (1+epsilon)p + r, where p is the processing time, r the submission time and the slack epsilon > 0 a system parameter. Typically, the hard case arises for small slack epsilon << 1, i.e. for near-tight deadlines. Without migration, a greedy acceptance policy is known to be an optimal deterministic online algorithm with a competitive factor of (1+epsilon)/epsilon (DasGupta and Palis, APPROX 2000). Our first contribution is to show that migrations do not improve the competitive ratio of the greedy acceptance policy, i.e. the competitive ratio remains (1+epsilon)/epsilon for any number of machines. Our main contribution is a deterministic online algorithm with almost tight competitive ratio on any number of machines. For a single machine, the competitive factor matches the optimal bound of (1+epsilon)/epsilon of the greedy acceptance policy. The competitive ratio improves with an increasing number of machines. It approaches (1+epsilon) ln((1+epsilon)/epsilon) as the number of machines converges to infinity. This is an exponential improvement over the greedy acceptance policy for small epsilon. Moreover, we show a matching lower bound on the competitive ratio for deterministic algorithms on any number of machines

Lower bounds for Smith's rule in stochastic machine scheduling

We consider the problem to minimize the weighted sum of completion times in nonpreemptive parallel machine scheduling. In a landmark paper from 1986, Kawaguchi and Kyan [5] showed that scheduling the jobs according to the WSPT rule -also known as Smith's rule- has a performance guarantee of ${1\over 2}(1+\sqrt{2}) \approx 1.207$. They also gave an instance to show that this bound is tight. We consider the stochastic variant of this problem in which the processing times are exponentially distributed random variables. We show,somehow counterintuitively, that the performance guarantee of the WSEPT rule, the stochastic analogue of WSPT, is not better than 1.229. This constitutes the first lower bound for WSEPT in this setting, and in particular, it shows that even with exponentially distributed processing times, stochastic scheduling has somewhat nastier worst-case examples than deterministic scheduling. In that respect, our analysis sheds new light on the fundamental differences between deterministic and stochastic scheduling

06251 Abstracts Collection -- Multi-Robot Systems: Perception, Behaviors, Learning, and Action

From 19.06.06 to 23.06.06, the Dagstuhl Seminar 06251 ``Multi-Robot Systems: Perception, Behaviors, Learning, and Action\u27\u27 was held in the International Conference and Research Center (IBFI), Schloss Dagstuhl. During the seminar, several participants presented their current research, and ongoing work and open problems were discussed. Abstracts of the presentations given during the seminar as well as abstracts of seminar results and ideas are put together in this paper. The first section describes the seminar topics and goals in general. Links to extended abstracts or full papers are provided, if available

Understanding User Behavior: From HPC to HTC

AbstractIn this paper, we investigate the differences and similarities in user job submission behavior in High Performance Computing (HPC) and High Throughput Computing (HTC). We consider job submission behavior in terms of parallel batch-wise submissions, as well as delays and pauses in job submission. Our findings show that modeling user-based HTC job submission behavior requires knowledge of the underlying bags of tasks, which is often unavailable. Furthermore, we find evidence that subsequent job submission behavior is not influenced by the different complexities and requirements of HPC and HTC jobs

Preemptive Weighted Completion Time Scheduling of Parallel Jobs

In this paper we present a new algorithm for the off-line scheduling of parallel and independent jobs on a parallel processor system. To this end we introduce a machine model which is based on existing multiprocessors and accounts for the penalty of preemption. After examining the relation between the makespan and the total weighted completion time costs for the scheduling of parallel jobs it is shown that the new algorithm achieves a small approximation factor for both total weighted completion time and makespan scheduling. To fine tune the algorithm a fairly simple numerical optimization problem is derived. This way different preemption penalties can be considered when determining the approximation factor. Finally, we compare the costs of the generated preemptive schedules with those of non-preemptive schedules for the same problem

How to Design a Job Scheduling Algorithm

Abstract. We discuss the components of a general approach to design algorithms for resource management in parallel processing systems. Starting from the observation that in this area the average influence of research publications on practical implementations is negligible, we address the three main categories constraints, objectives, and evaluation. For each category, we describe common approaches and restrictions and give some general rules that should be followed when presenting a new algorithm for resource management. As an example we present a resource management method for the IaaS model of Cloud Computing that extends the spot instance approach of Amazon. For this example, we first discuss technical, organizational, and usage constraints based on existing concepts and research results. Then we briefly describe resource management objectives from the viewpoint of a provider. After presenting our algorithmic concept, we show that an evaluation with theoretical means can also yield meaningful results in practice

Erkenntnisse und Thesen zur Langzeitarchivierung von Forschungsdaten.

Findings of the study published in the book are summarised and suggestions are given for further action on a professional and political level

Implications and Recommendations on Research Data Curation

This chapter of the book summarizes findings of the baseline study and draws recommendations regarding political and other issues of the topic