Abstract
We study the competitiveness of online deadline scheduling problems. It is assumed that jobs are non-preemptive and we want to maximize, in an online manner, the sum of the length of jobs completed before their deadlines. When there is a single machine, Goldwasser [4] showed that the optimal deterministic competitiveness of this problem is \(2+ \frac{1} k\), where each job of length L can be delayed for at least k · L before it is started, while still meeting its deadline.
In this paper we generalize the framework of the above problem in two ways: First we replace the adversary by a set of mweak adversaries, each of which can generate arbitrary jobs that never overlap each other. Assuming that job sequence is generated by the team of m weak adversaries for some fixed m, we present a tight analysis of an optimal online algorithm by extending the previous analysis by Goldwasser. Next we allow online algorithms to abort the currently running job and to restart it from the scratch, if it can meet the deadline. This capability of abort and restart is different from preemptiveness because only jobs that are scheduled without interrupt are regarded to be successfully scheduled. We present a constant competitive algorithm for this model.
This research was supported by grant No. R08-2003-000-10569-0(2003) from the Basic Research Program of the Korea Science and Engineering Foundation.
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References
Baruah, S., Harita, J., Sharma, X.: Online scheduling to maximize task completions. In: Proc. of IEEE Real-Time Systems Symposium, pp. 228–237 (1994)
Borodin, A., El-Yaniv, R.: Online computation and competitive analysis. Cambridge University Press, Cambridge (1998)
Goldman, S., Parwatikar, J., Suri, S.: On-line scheduling with hard deadlines. Journal of Algorith 34(2), 370–389 (2000)
Goldwasser, M.: Patience is a virtue: the effect of slack on competitiveness for admission control. In: Proc. of 10th ACM-SIAM SODA, pp. 396–405 (1999)
Kalyanasundaram, B., Pruhs, K.: Maximizing jon completion online. In: Bilardi, G., Pietracaprina, A., Italiano, G.F., Pucci, G. (eds.) ESA 1998. LNCS, vol. 1461, pp. 235–246. Springer, Heidelberg (1998)
Lee, J.-H.: Online deadline scheduling: multiple machines and randomization. In: Proc. of SPAA, pp. 21–25 (2003)
Lee, J.-H., Chwa, K.-Y.: Online scheduling of parallel communications with individual deadlines. In: Aggarwal, A.K., Pandu Rangan, C. (eds.) ISAAC 1999. LNCS, vol. 1741, pp. 383–392. Springer, Heidelberg (1999)
Lipton, R.J., Tomkins, A.: Online interval scheduling. In: Proc. of 5-th ACM SODA, pp. 302–305 (1994)
Sgall, J.: Online scheduling. In: Fiat, A., Woeginger, G.J. (eds.) Dagstuhl Seminar 1996. LNCS, vol. 1442, pp. 196–231. Springer, Heidelberg (1998)
Sleator, D., Tarjan, R.: Amortized efficiency of list update and paging rules. Communications of ACM 2(28), 202–208 (1985)
van den Akker, M., Hoogeven, H., Vakhania, N.: Restarts can help in the on-line minimization of the maximum delivery time on a single machine. In: Paterson, M. (ed.) ESA 2000. LNCS, vol. 1879, pp. 427–436. Springer, Heidelberg (2000)
Woeginger, G.J.: On-line scheduling of jobs with fixed start and end times. Theoretical Computer Science 130, 5–16 (1994)
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Lee, JH. (2004). Online Deadline Scheduling: Team Adversary and Restart. In: Solis-Oba, R., Jansen, K. (eds) Approximation and Online Algorithms. WAOA 2003. Lecture Notes in Computer Science, vol 2909. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24592-6_16
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DOI: https://doi.org/10.1007/978-3-540-24592-6_16
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