Critical hops calculation for energy conservation in a multi-hop Wireless Sensor Network

Lambor, Shilpa M.; Joshi, Siddharth

doi:10.1109/wcsn.2010.5712296

Cited by 3 publications

(3 citation statements)

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“…Here, f 0 (x) is the optimisation variable, f i (x) ≤ 0 depict the inequality constraints, and h j (x) = 0 depict the equality constraints. Then the optimal value p* of the optimisation problem is defined as (13) We now present the analysis of deducing the optimal hops in a multi-hop WSN ensuring power-efficient communication under SINR constraints.…”

Section: Problem Formulationmentioning

confidence: 99%

“…Since the subproblem has inequality constraints, we use Karush-Kuhn-Tucker (KKT) optimality conditions to derive analytical expression of globally optimal solution of the hop optimisation problem. The KKT conditions state that the necessary condition for p* [see (13)] to be an optimal solution is that there exists some (λ*, ν*) such that…”

Section: Feasibility Analysismentioning

confidence: 99%

“…However, minimising route length is not the best option [11, 12]. The research presented in this paper is an extension of our earlier research carried out in [13], wherein optimal hops were deduced analytically for the Friis free space propagation model given a fixed received power, under zero constraints. It is our observation that work carried out till date focuses on optimising either the transmit power or hop distance, maintaining the other constant [14].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Optimal hops for minimal route power under SINR constraints in wireless sensor networks

Lambor¹,

Joshi²

2018

IET wirel. sens. syst.

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This study attempts to deduce the optimal hops in a multi-hop wireless sensor network (WSN) ensuring powerefficient communication under signal-to-interference noise ratio (SINR) constraints. The authors model the total route power consumption under wireless channel quality constraints. WSNs usually employ a multiple-source, single-sink structure for information transfer, necessitating data aggregation. The authors calculate optimal hops for three different data aggregation schemes. They further propose a robust hybrid data aggregation strategy that demonstrates an improved performance with respect to minimal power consumption when compared with employing individual data aggregation schemes. The data aggregation scheme employing optimal hops has been implemented and results have been verified for an illustrative application in water supply and drainage monitoring system. The authors have formulated the problem as a standard convex optimisation problem. They employ Karush-Kuhn-Tucker optimality conditions to derive the analytical expressions of the globally optimal hops, which incorporate the influence of route power, receiver noise, and SINR thresholds. The transmit power and hop count are varied simultaneously until an optimised hop count is achieved. The relation between the node transmit power and the number of hops in the route is derived and the condition for feasible optimal hops is presented.

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Section: Problem Formulationmentioning

confidence: 99%

Section: Feasibility Analysismentioning

confidence: 99%