Algorithmic Aspects of Wireless Sensor Networks: Fourth by Roger Wattenhofer (auth.), Sándor P. Fekete (eds.)

By Roger Wattenhofer (auth.), Sándor P. Fekete (eds.)

This booklet constitutes the reviewed court cases of the Fourth overseas Workshop on Algorithmic features of instant Sensor Networks, ALGOSENSORS 2008, held in Reykjavik, Iceland, Wroclaw, Poland, July 12, 2008.

The workshops geared toward bringing jointly examine contributions regarding varied algorithmic and complexity-theoretic facets of instant sensor networks. the subjects contain yet will not be constrained to optimization difficulties, noise and likelihood, robots and excursions.

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Extra resources for Algorithmic Aspects of Wireless Sensor Networks: Fourth International Workshop, ALGOSENSORS 2008, Reykjavik, Iceland, July 2008. Revised Selected Papers

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This minimalistic model serves to explore the fundamental performance limits of low-cost sensors for such surveillance tasks as estimating the number of people, vehicles or ships in a field of interest to first degree of approximation, to be followed by more expensive sensing and localization if needed. This simple abstract setting allows us to explore the intrinsic complexity of a fundamental problem, and derive rigorous worst-case performance bounds. We show that even in the 1-dimensional setting (for instance, sensors counting vehicles on a road), the problem is non-trivial: target count can be estimated within relative accuracy of √ factor 2 and this is the best possible in the worst-case.

We now show that a feasible target placement can be obtained even for non-ideal sensors, Theorem 5. Given a set of n non-ideal sensors and their readings, we can find a placement for targets in the network which satisfies all sensor readings. Of course, both the target placement as well as the number of targets estimated may be different from the ones found using non-noisy counts, but the approximations are guaranteed to be within the range of accuracy given by our theorems. In the next section, we consider the target counting problem when the sensors and the targets are scattered in a two-dimensional plane.

We have t +/σ Cq ≤ (t + 1/σ) + d(vj , vkt ) + d(vkt , s) /σ ≤ Ck + (dI + 2)/σ = Ck + γ/σ. That is, packet q ∈ S(i) arrives at most γ/σ time units after packet k ∈ J \ S(i), which contradicts the fact that q and k are in different components. Thus this case never occurs and the claim holds. We now describe Interleaved SRPT. The algorithm partitions the set of packets J in two subsets, J in := {j ∈ J : δj < γ ∗ } and J out := {j ∈ J : δj ≥ γ ∗ }. The two subsets are scheduled in an interleaved fashion using SRPT.

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