Supporting High-Tech Crime Investigation through Dynamic Service Integration

Mazurek, Cezary; Stroiński, Maciej; Walczak, Dariusz; Wolski, Marcin

doi:10.1109/icns.2009.29

Cited by 5 publications

References 3 publications

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Scheduling CPU-Intensive Grid Applications Using Partial Information

Nóbrega

Assis

Brasileiro

2008

2008 37th International Conference on Parallel Processing

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Scheduling parallel applications on computational grids is a difficult task. In order to map the parallel application's tasks onto resources in a efficient way, grid schedulers apply scheduling heuristics. The existing scheduling heuristics can be broadly classified in two approaches: i) bin-packing schedulers, and ii) replication schedulers. The first approach requires complete and accurate information about the applications and the grid environment. The second approach does not use any information but, instead, applies the principle of task replication to achieve good performance. Each of these approaches have drawbacks; attaining accurate and complete information about resources and applications is not always possible in a grid environment, while the redundancy of replication schedulers yield an extra consumption of resources. In this work, we investigate the trade-off between these two approaches. We propose scheduling heuristics that use any available information to perform efficient scheduling of bag-of-tasks applications, a subclass of parallel applications. Our results show that judicious use of whatever information is available leads to a reduction on resource consumption, without compromising the application's performance.

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Scheduling CPU-Intensive Grid Applications Using Partial Information

Nóbrega

Assis

Brasileiro

2008

2008 37th International Conference on Parallel Processing

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Large-scale data collection: a coordinated approach

Cheng

Chou

Golubchik

et al.

IEEE INFOCOM 2003. Twenty-Second Annual Joint Conference of the IEEE Computer and Communications Societies (IEEE Cat. No.03CH37

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Abstract-In this paper we consider the problem of collecting a large amount of data from several different hosts to a single destination in a wide-area network. Often, due to congestion conditions, the paths chosen by the network may have poor throughput. By choosing an alternate route at the application level, we may be able to obtain substantially faster completion time. This data collection problem is a non-trivial one because the issue is not only to avoid congested link(s), but to devise a coordinated transfer schedule which would afford maximum possible utilization of available network resources. In this paper we present an approach for computing coordinated data collection schedules, which can result in significant performance improvements. We make no assumptions about knowledge of the topology of the network or the capacity available on individual links of the network, i.e., we only use end-to-end information. Finally, we also study the shortcomings of this approach in terms of the gap between the theoretical formulation and the resulting data transfers in wide-area networks. In general, our approach can be used for solving arbitrary data movement problems over the Internet. We use the Bistro platform to illustrate one application of our techniques.

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