New PDF release: Algorithms for Sensor Systems: 7th International Symposium

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

ISBN-10: 3642282091

ISBN-13: 9783642282096

This publication constitutes the completely refereed post-conference lawsuits 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 awarded including invited keynote talks have been rigorously reviewed and chosen from 31 submissions. The papers are equipped in tracks: sensor networks, masking themes corresponding to localization, lifetime maximization, interference keep watch over, neighbor discovery, self-organization, detection, and aggregation; and advert hoc instant and cellular structures together with the subjects: routing, scheduling and capability optimization within the SINR version, non-stop tracking, and broadcasting.

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Extra 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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In: Proceedings of the 2004 Intl. Conference on Parallel Processing Workshops, pp. 61–68 (2004) 13. html Appendix Pinned Disks. , xm } ⊆ X be the locations of active sensors, so that ri > 0 for all 1 ≤ i ≤ m. The unique radial assignment function R∗ (Y ) corresponding to pinned disks is then given recursively by (R∗ (Y ))i = ri = x1 if i = 1 . xi − (xi−1 + ri−1 ) if 2 ≤ i ≤ m Setting xm + rm = 1 to ensure a perfect fit yields m (−1)m−j xj . 1=2 j=1 We then define the polynomial f (Y ) = − 21 + proof of Lemma 2.

G. - perhaps they have been dropped from an airplane). , xn }. For any time t ≥ 0, we associate with each sensor i a sensing radius ri (t) ∈ [0, 1] and a corresponding coverage interval Ri (t) = [xi − ri (t), xi + ri (t)], and say that U is covered at time t if for every x ∈ U , there exists an 1 ≤ i ≤ n such that x ∈ Ri (t). We impose the constraint that each sensor has a unit battery charge that drains at the rate (ri (t))1/α for some fixed α > 0. Our goal is to construct a sensing schedule S = {ri (t)}ni=1 that covers U for as long as possible, and call this value the lifetime of the network.

Thus, our results are also valid for the special case in which pre-emptive scheduling is not allowed. A summary of our results is shown in Table 1. Table 1. Summary of lifetime results for RoundRobin algorithms. T is a random variable describing the per sensor lifetime under uniform random deployment. AC and W C show lower bounds for the average-case and upper bounds for the worst-case approximation ratios, respectively. 896 WC 2/3 2/3 2/3 2/3 Preliminaries For any set of sensor locations X, we assume that there exists some optimal schedule S = {ri (t)}ni=1 that will produce the longest possible lifetime TOP T .

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


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