R × W: a scheduling approach for large-scale on-demand data broadcast
IEEE/ACM Transactions on Networking (TON)
Speed is as powerful as clairvoyance
Journal of the ACM (JACM)
Non-clair voy ant multiprocessor scheduling of jobs with changing execution characteristics
Journal of Scheduling - Special issue: On-line scheduling
Approximating the average response time in broadcast scheduling
SODA '05 Proceedings of the sixteenth annual ACM-SIAM symposium on Discrete algorithms
Broadcast scheduling: algorithms and complexity
Proceedings of the nineteenth annual ACM-SIAM symposium on Discrete algorithms
Improved Approximation Algorithms for Broadcast Scheduling
SIAM Journal on Computing
Scalably scheduling processes with arbitrary speedup curves
SODA '09 Proceedings of the twentieth Annual ACM-SIAM Symposium on Discrete Algorithms
Throughput maximization of real-time scheduling with batching
ACM Transactions on Algorithms (TALG)
Speed scaling of processes with arbitrary speedup curves on a multiprocessor
Proceedings of the twenty-first annual symposium on Parallelism in algorithms and architectures
Design and Analysis of Online Batching Systems
Algorithmica
Better scalable algorithms for broadcast scheduling
ICALP'10 Proceedings of the 37th international colloquium conference on Automata, languages and programming
New models and algorithms for throughput maximization in broadcast scheduling
WAOA'10 Proceedings of the 8th international conference on Approximation and online algorithms
Minimizing maximum flowtime of jobs with arbitrary parallelizability
WAOA'10 Proceedings of the 8th international conference on Approximation and online algorithms
Server Scheduling to Balance Priorities, Fairness, and Average Quality of Service
SIAM Journal on Computing
Online scalable scheduling for the lk-norms of flow time without conservation of work
Proceedings of the twenty-second annual ACM-SIAM symposium on Discrete Algorithms
An online scalable algorithm for average flow time in broadcast scheduling
ACM Transactions on Algorithms (TALG)
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Batch scheduling gives a powerful way of increasing the throughput by aggregating multiple homogeneous jobs. It has applications in large scale manufacturing as well as in server scheduling. In batch scheduling, when explained in the setting of server scheduling, the server can process requests of the same type up to a certain number simultaneously. Batch scheduling can be seen as capacitated broadcast scheduling, a popular model considered in scheduling theory. In this paper, we consider an online batch scheduling model. For this model we address flow time objectives for the first time and give positive results for average flow time, the k-norms of flow time and maximum flow time. For average flow time and the k-norms of flow time we show algorithms that are O(1)-competitive with a small constant amount of resource augmentation. For maximum flow time we show a 2-competitive algorithm and this is the best possible competitive ratio for any online algorithm.