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

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

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

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Extra resources 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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2. Lifetime on the Line with Adjustable Sensing Ranges 33 Proof. Consider X = { 41 , 34 }. The only two sensible assignments are shown in Figure 3. But while TOP T = 4, RoundRobin achieves a lifetime of only 2 32 . 4 4 3 3 2 2 1 1 0 0 s1 1 1 2 4 3 s2 4 0 1 0 s1 1 1 2 4 (b) TRR = (a) TOP T = 4 Fig. 3. 548-approximation of TOP T . Clearly, RoundRobin performs best when sensors are located close to 1/2, where the lifetime is close to 2, and poorly for sensors near 0 and 1, where the lifetime is 1.

Linear-work greedy parallel approximation algorithms for set covering and variants. In: Proceedings of the 23rd Annual ACM Symposium on Parallelism in Algorithms and Architectures, SPAA (2011) 5. : An Optimal Bifactor Approximation Algorithm for the Metric Uncapacitated Facility Location Problem. P. ) RANDOM 2007 and APPROX 2007. LNCS, vol. 4627, pp. 29–43. Springer, Heidelberg (2007) 6. : Improved approximation algorithms for a capacitated facility location problem. In: Proceedings of the 10th Annual ACM-SIAM Symposium on Discrete Algorithms (SODA), pp.

Hence, the algorithm results in online sensor fusion. We rigorously quantify the regret of the suggested algorithm compared to the best fused sensor. In this way, a designer of a sensor fusion algorithm has a wellquantified trade-off: choosing a large number of parameters, thus covering more families of fusion possibilities, at the price of higher regret. Due to space limitations, proofs are not included in this proceedings. 2 Preliminaries The basic setting we consider is the following. A set of sensors, S = {S1 , .

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