Amortized efficiency of list update and paging rules
Communications of the ACM
Minimizing mean flow time with release time constraint
Theoretical Computer Science
Approximability and nonapproximability results for minimizing total flow time on a single machine
STOC '96 Proceedings of the twenty-eighth annual ACM symposium on Theory of computing
Approximation algorithms for scheduling
Approximation algorithms for NP-hard problems
Approximating total flow time on parallel machines
STOC '97 Proceedings of the twenty-ninth annual ACM symposium on Theory of computing
Log-time algorithms for scheduling single and multiple channel data broadcast
MobiCom '97 Proceedings of the 3rd annual ACM/IEEE international conference on Mobile computing and networking
Online computation and competitive analysis
Online computation and competitive analysis
Minimizing the flow time without migration
STOC '99 Proceedings of the thirty-first annual ACM symposium on Theory of computing
Hierarchical resource management for Web server clusters with dynamic content
SIGMETRICS '99 Proceedings of the 1999 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
Scheduling to minimize average completion time: off-line and on-line algorithms
Proceedings of the seventh annual ACM-SIAM symposium on Discrete algorithms
The power of migration in multi-processor scheduling of real-time systems
Proceedings of the ninth annual ACM-SIAM symposium on Discrete algorithms
Flow and stretch metrics for scheduling continuous job streams
Proceedings of the ninth annual ACM-SIAM symposium on Discrete algorithms
Scheduling to minimize average stretch without migration
SODA '00 Proceedings of the eleventh annual ACM-SIAM symposium on Discrete algorithms
Eliminating migration in multi-processor scheduling
Journal of Algorithms
Dynamic Memory Allocation for Multiple-Query Workloads
VLDB '93 Proceedings of the 19th International Conference on Very Large Data Bases
Online Scheduling to Minimize Average Stretch
FOCS '99 Proceedings of the 40th Annual Symposium on Foundations of Computer Science
Task Assignment in a Distributed System: Improving Performance by Unbalancing Load
Task Assignment in a Distributed System: Improving Performance by Unbalancing Load
Connection scheduling in web servers
USITS'99 Proceedings of the 2nd conference on USENIX Symposium on Internet Technologies and Systems - Volume 2
Nonclairvoyant scheduling to minimize the total flow time on single and parallel machines
Journal of the ACM (JACM)
Approximating total flow time on parallel machines
Journal of Computer and System Sciences
Optimizing the stretch of independent tasks on a cluster: From sequential tasks to moldable tasks
Journal of Parallel and Distributed Computing
Reallocation problems in scheduling
Proceedings of the twenty-fifth annual ACM symposium on Parallelism in algorithms and architectures
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We study the problem of scheduling parallel machines online, allowing preemptions while disallowing migration of jobs that have been scheduled on one machine to another. For a given job, we measure the quality of service provided by an algorithm by the stretch of the job, defined as the ratio between the amount of time spent by the job in the system (the response time) and its processing time. For a sequence of jobs, we measure the performance of an algorithm by the average stretch achieved over all jobs. The scheduling goal is to minimize the average stretch. This problem is of relevance in many applications, e.g., wireless data servers and distributed server systems in wired networks. We prove an O(1) competitive ratio for this problem. The algorithm for which we prove this result is the one proposed in Awerbuch et al. (Proceedings of the ACM Symposium on the Theory of Computing (STOC '99), 1999, pp. 198-205) that has (tight) logarithmic competitive ratio for minimizing the average response time. Thus, the algorithm in Awerbuch et al. (Proceedings of the ACM Symposium on the Theory of Computing (STOC '99), 1999, pp. 198-205) simultaneously performs well for average response time as well as average stretch. We prove the O(1) competitive ratio against an adversary who not only knows the entire input ahead of time, but is also allowed to migrate jobs. Thus, our result shows that migration is not necessary to be competitive for minimizing average stretch; in contrast, we prove that preemption is essential, even if randomization is allowed.