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Conference Paper: Minimum-latency aggregation scheduling in wireless sensor networks under physical interference model

TitleMinimum-latency aggregation scheduling in wireless sensor networks under physical interference model
Authors
Keywordsdata aggregation
minimum latency
physical interference model
wireless sensor networks
Issue Date2010
PublisherAssociation for Computing Machinery
Citation
The 13th ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems (MSWiM 2010), Bodrum, Turkey, 17-21 October 2010. In Proceedings of 13th MSWiM, 2010, p. 360-367 How to Cite?
AbstractMinimum-Latency Aggregation Scheduling (MLAS) is a problem of fundamental importance in wireless sensor networks. There however has been very little effort spent on designing algorithms to achieve sufficiently fast data aggregation under the physical interference model which is a more realistic model than traditional protocol interference model. In particular, a distributed solution to the problem under the physical interference model is challenging because of the need for global-scale information to compute the cumulative interference at any individual node. In this paper, we propose a distributed algorithm that solves the MLAS problem under the physical interference model in networks of arbitrary topology in O(K) time slots, where K is the logarithm of the ratio between the lengths of the longest and shortest links in the network. We also give a centralized algorithm to serve as a benchmark for comparison purposes, which aggregates data from all sources in O(log3n) time slots (where n is the total number of nodes). This is the current best algorithm for the problem in the literature. The distributed algorithm partitions the network into cells according to the value K, thus obviating the need for global information. The centralized algorithm strategically combines our aggregation tree construction algorithm with the non-linear power assignment strategy in [9]. We prove the correctness and efficiency of our algorithms, and conduct empirical studies under realistic settings to validate our analytical results. © 2010 ACM.
Persistent Identifierhttp://hdl.handle.net/10722/125682
ISBN
References

 

DC FieldValueLanguage
dc.contributor.authorLi, Hen_HK
dc.contributor.authorHua, QSen_HK
dc.contributor.authorWu, Cen_HK
dc.contributor.authorLau, FCMen_HK
dc.date.accessioned2010-10-31T11:45:48Z-
dc.date.available2010-10-31T11:45:48Z-
dc.date.issued2010en_HK
dc.identifier.citationThe 13th ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems (MSWiM 2010), Bodrum, Turkey, 17-21 October 2010. In Proceedings of 13th MSWiM, 2010, p. 360-367en_HK
dc.identifier.isbn978-1-4503-0274-6-
dc.identifier.urihttp://hdl.handle.net/10722/125682-
dc.description.abstractMinimum-Latency Aggregation Scheduling (MLAS) is a problem of fundamental importance in wireless sensor networks. There however has been very little effort spent on designing algorithms to achieve sufficiently fast data aggregation under the physical interference model which is a more realistic model than traditional protocol interference model. In particular, a distributed solution to the problem under the physical interference model is challenging because of the need for global-scale information to compute the cumulative interference at any individual node. In this paper, we propose a distributed algorithm that solves the MLAS problem under the physical interference model in networks of arbitrary topology in O(K) time slots, where K is the logarithm of the ratio between the lengths of the longest and shortest links in the network. We also give a centralized algorithm to serve as a benchmark for comparison purposes, which aggregates data from all sources in O(log3n) time slots (where n is the total number of nodes). This is the current best algorithm for the problem in the literature. The distributed algorithm partitions the network into cells according to the value K, thus obviating the need for global information. The centralized algorithm strategically combines our aggregation tree construction algorithm with the non-linear power assignment strategy in [9]. We prove the correctness and efficiency of our algorithms, and conduct empirical studies under realistic settings to validate our analytical results. © 2010 ACM.en_HK
dc.languageengen_HK
dc.publisherAssociation for Computing Machinery-
dc.relation.ispartofProceedings of the 13th ACM International Conference on Modeling, Analysis, and Simulation of Wireless and Mobile Systems, MSWiM 2010en_HK
dc.subjectdata aggregationen_HK
dc.subjectminimum latencyen_HK
dc.subjectphysical interference modelen_HK
dc.subjectwireless sensor networksen_HK
dc.titleMinimum-latency aggregation scheduling in wireless sensor networks under physical interference modelen_HK
dc.typeConference_Paperen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=9781450302746&volume=&spage=360&epage=367&date=2010&atitle=Minimum-latency+aggregation+scheduling+in+wireless+sensor+networks+under+physical+interference+model-
dc.identifier.emailWu, C:cwu@cs.hku.hken_HK
dc.identifier.emailLau, FCM:fcmlau@cs.hku.hken_HK
dc.identifier.authorityWu, C=rp01397en_HK
dc.identifier.authorityLau, FCM=rp00221en_HK
dc.description.naturelink_to_OA_fulltext-
dc.identifier.doi10.1145/1868521.1868581en_HK
dc.identifier.scopuseid_2-s2.0-78650222013en_HK
dc.identifier.hkuros175395en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-78650222013&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.spage360en_HK
dc.identifier.epage367en_HK
dc.publisher.placeUnited States-
dc.description.otherThe 13th ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems (MSWiM 2010), Bodrum, Turkey, 17-21 October 2010. In Proceedings of 13th MSWiM, 2010, p. 360-367-
dc.identifier.scopusauthoridLi, H=35292662600en_HK
dc.identifier.scopusauthoridHua, QS=15060090400en_HK
dc.identifier.scopusauthoridWu, C=15836048100en_HK
dc.identifier.scopusauthoridLau, FCM=7102749723en_HK

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