Flow and stretch metrics for scheduling continuous job streams
Proceedings of the ninth annual ACM-SIAM symposium on Discrete algorithms
Speed is as powerful as clairvoyance
Journal of the ACM (JACM)
Theoretical Computer Science - Selected papers in honor of Manuel Blum
Improved algorithms for stretch scheduling
SODA '02 Proceedings of the thirteenth annual ACM-SIAM symposium on Discrete algorithms
Operating System Concepts, 4th Ed.
Operating System Concepts, 4th Ed.
Minimizing the Flow Time Without Migration
SIAM Journal on Computing
Server scheduling in the Lp norm: a rising tide lifts all boat
Proceedings of the thirty-fifth annual ACM symposium on Theory of computing
Multi-processor scheduling to minimize flow time with ε resource augmentation
STOC '04 Proceedings of the thirty-sixth annual ACM symposium on Theory of computing
Nonclairvoyant scheduling to minimize the total flow time on single and parallel machines
Journal of the ACM (JACM)
Minimizing average flow time on related machines
Proceedings of the thirty-eighth annual ACM symposium on Theory of computing
Competitive online scheduling for server systems
ACM SIGMETRICS Performance Evaluation Review
Approximating total flow time on parallel machines
Journal of Computer and System Sciences
Minimizing Average Flow-time: Upper and Lower Bounds
FOCS '07 Proceedings of the 48th Annual IEEE Symposium on Foundations of Computer Science
Modern Operating Systems
Scalably scheduling processes with arbitrary speedup curves
SODA '09 Proceedings of the twentieth Annual ACM-SIAM Symposium on Discrete Algorithms
Online scheduling to minimize the maximum delay factor
SODA '09 Proceedings of the twentieth Annual ACM-SIAM Symposium on Discrete Algorithms
Weighted flow time does not admit O(1)-competitive algorithms
SODA '09 Proceedings of the twentieth Annual ACM-SIAM Symposium on Discrete Algorithms
Proceedings of the forty-first annual ACM symposium on Theory of computing
Scheduling jobs with varying parallelizability to reduce variance
Proceedings of the twenty-second annual ACM symposium on Parallelism in algorithms and architectures
An online scalable algorithm for average flow time in broadcast scheduling
SODA '10 Proceedings of the twenty-first annual ACM-SIAM symposium on Discrete Algorithms
Better algorithms for minimizing average flow-time on related machines
ICALP'06 Proceedings of the 33rd international conference on Automata, Languages and Programming - Volume Part I
Longest wait first for broadcast scheduling [extended abstract]
WAOA'09 Proceedings of the 7th international conference on Approximation and Online Algorithms
On scheduling in map-reduce and flow-shops
Proceedings of the twenty-third annual ACM symposium on Parallelism in algorithms and architectures
The complexity of scheduling for p-norms of flow and stretch
IPCO'13 Proceedings of the 16th international conference on Integer Programming and Combinatorial Optimization
Minimizing maximum (weighted) flow-time on related and unrelated machines
ICALP'13 Proceedings of the 40th international conference on Automata, Languages, and Programming - Volume Part I
Coordination mechanisms from (almost) all scheduling policies
Proceedings of the 5th conference on Innovations in theoretical computer science
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We consider the problem of scheduling jobs that arrive online in the unrelated machine model to minimize lk norms of weighted flowtime. In the unrelated setting, the processing time and weight of a job depends on the machine it is assigned to, and it is perhaps the most general machine model considered in scheduling literature. Chadha et al. [10] obtained a recent breakthrough result in obtaining the first non-trivial algorithm for minimizing weighted flowtime (that is, the l1 norm) in this very general setting via a novel potential function based analysis. They described a simple algorithm and showed that for any ε 0 it is (1 + ε)-speed O(1/ε2)-competitive (a scalable algorithm). In this paper we give the first non-trivial and scalable algorithm for minimizing lk norms of weighted flowtime in the unrelated machine model; for any ε 0, the algorithm is O(k/ε2+2/k)-competitive. The algorithm is immediate-dispatch and non-migratory. Our result is of both practical and theoretical interest. Scheduling to minimize lk norms of flowtime for some small k 1 has been shown to balance total response time and fairness, which is desirable in practice. On the theoretical side, lk norms for k 1 pose substantial technical hurdles when compared to when k = 1 even for the single machine case. Our work develops a novel potential function as well as several tools that can be used to lower bound the optimal solution.