• Journal of Information Processing Systems
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• v.5 no.4
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• pp.229-236
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• 2009

Sensors are deployed to gather physical, environmental data in sensor networks. Depending on scenarios, it is often assumed that it is difficult for batteries to be recharged or exchanged in sensors. Thus, sensors should be able to process users' queries in an energy-efficient manner. This paper proposes a spatial query processing scheme- Minimum Bounding Area Based Scheme. This scheme has a purpose to decrease the number of outgoing messages during query processing. To do that, each sensor has to maintain some partial information locally about the locations of descendent nodes. In the initial setup phase, the routing path is established. Each child node delivers to its parent node the location information including itself and all of its descendent nodes. A parent node has to maintain several minimum bounding boxes per child node. This scheme can reduce unnecessary message propagations for query processing. Finally, the experimental results show the effectiveness of the proposed scheme.

• Journal of KIISE:Computer Systems and Theory
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• v.31 no.5_6
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• pp.347-352
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• 2004

This thesis deals with a task scheduling on a message-passing system. Scheduling and allocation are very important issues since the inappropriate scheduling of tasks cannot exploit the true potential of the system and it can offset the grain from parallelization. It is difficult to apply previous schemes to message-passing system, because previous schemes assume the shared memory system. This thesis proposes an modified priority function and processor selection technique that consider the problems caused by the difference between previous models and message-passing environments. The priority function includes the cumulative communication cost which causes task execution to be delayed. The processor selection technique avoids the situation that a child task is assigned to the same Processor allocated to its parent task that has other unscheduled child tasks. We showed by some simulations that our modified features of task scheduling algorithm can make the better scheduling results than the previous algorithms.