Download Algorithms for Sensor Systems: 7th International Symposium by Shlomi Dolev (auth.), Thomas Erlebach, Sotiris Nikoletseas, PDF

By Shlomi Dolev (auth.), Thomas Erlebach, Sotiris Nikoletseas, Pekka Orponen (eds.)

This booklet constitutes the completely refereed post-conference complaints of the seventh foreign Workshop on Algorithms for Sensor platforms, instant advert Hoc Networks, and self reliant cellular Entities, ALGOSENSORS 2011, held in Saarbrücken, Germany, in September 2011. The sixteen revised complete papers awarded including invited keynote talks have been rigorously reviewed and chosen from 31 submissions. The papers are prepared in tracks: sensor networks, masking issues corresponding to localization, lifetime maximization, interference keep an eye on, neighbor discovery, self-organization, detection, and aggregation; and advert hoc instant and cellular platforms together with the subjects: routing, scheduling and skill optimization within the SINR version, non-stop tracking, and broadcasting.

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Additional info for Algorithms for Sensor Systems: 7th International Symposium on Algorithms for Sensor Systems, Wireless Ad Hoc Networks and Autonomous Mobile Entities, ALGOSENSORS 2011, Saarbrücken, Germany, September 8-9, 2011, Revised Selected Papers

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With b − a = 1/k, the expected lifetime of each sensor in k-RoundRobin is E[T ] = kμT , with a maximum lifetime of 2k. However, in order to cover the whole line, we have to run k parallel queues, so that the expected normalized lifetime of each sensor is E[Tˆ] = μT . For a set of n sensors, the total expected lifetime is nμT , so the expected average network lifetime E[T¯] is μT . Similar calculations show that the variance of each sensor’s lifetime is (kσT )2 , while the normalized variance is σT2 and the variance of the mean is V ar(T¯) = σT2 /n.

Mitra, U. ) DCOSS 2009. LNCS, vol. 5516, pp. 245–258. Springer, Heidelberg (2009) 3. : Efficient Energy Management in Sensor Networks. Ad Hoc and Sensor Networks 2, 71–90 (2005) 4. : Restricted Strip Covering and the Sensor Cover Problem. In: Proceedings of the 18th Annual ACM-SIAM Symposium on Discrete Algorithms, pp. 1056–1065 (2007) 5. : Improving Network Lifetime Using Sensors with Adjustable Sensing Ranges. Int. J. Sensor Networks 1(1), 41–49 (2006) 40 A. Bar-Noy and B. Baumer 6. : Maximum Lifetime of Sensor Networks with Adjustable Sensing Range.

We show one such example in Figure 1. Buchsbaum et al. [4] proved the NP-hardness of RSC and gave an O(log log log n)-approximation algorithm. Recently, a constant factor approximation algorithm for RSC was discovered by Gibson and Varadarajan [7]. Much of the related work on network lifetime has focused on duty cycling, wherein the goal is to maximize the number of covers k, rather than explicitly maximizing the network lifetime T . The notion of decomposability of multiple coverings can be found in Pach [10].

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