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A Progressive Approach to Reducing Data Collection Latency in
Wireless Sensor Networks with Mobile Elements
Abstract
The introduction of mobile elements has created a new dimension to reduce and
balance the energy consumption in wireless sensor networks.
However, data collection latency may become higher due to the relatively slow travel speed
of mobile elements. Thus, the scheduling of mobile elements, i.e., how they traverse through the
sensing field and when they collect data from which sensor, is of ultimate importance and has
attracted increasing attention from the research community. Formulated as the traveling salesman
problem with neighborhoods (TSPN) and due to its NP-hardness, so far only approximation and
heuristic algorithms have appeared in the literature, but the former only have theoretical value
now due to their large approximation factors. In this paper, following a progressive
optimization approach, we first propose a combine-skip-substitute (CSS) scheme, which is
shown to be able to obtain solutions within a small range of the lower bound of the optimal
solution. We then take the realistic multirate features of wireless communications into account,
which have been ignored by most existing
work, to further reduce the data collection latency with the multirate CSS (MR-CSS) scheme.
Besides the correctness proof and performance analysis of the proposed schemes, we also show
their efficiency and potentials for further extensions through extensive simulation.

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A progressive approach to reducing data collection latency in wireless sensor networks with mobile elements

  • 1. A Progressive Approach to Reducing Data Collection Latency in Wireless Sensor Networks with Mobile Elements Abstract The introduction of mobile elements has created a new dimension to reduce and balance the energy consumption in wireless sensor networks. However, data collection latency may become higher due to the relatively slow travel speed of mobile elements. Thus, the scheduling of mobile elements, i.e., how they traverse through the sensing field and when they collect data from which sensor, is of ultimate importance and has attracted increasing attention from the research community. Formulated as the traveling salesman problem with neighborhoods (TSPN) and due to its NP-hardness, so far only approximation and heuristic algorithms have appeared in the literature, but the former only have theoretical value now due to their large approximation factors. In this paper, following a progressive optimization approach, we first propose a combine-skip-substitute (CSS) scheme, which is shown to be able to obtain solutions within a small range of the lower bound of the optimal solution. We then take the realistic multirate features of wireless communications into account, which have been ignored by most existing work, to further reduce the data collection latency with the multirate CSS (MR-CSS) scheme. Besides the correctness proof and performance analysis of the proposed schemes, we also show their efficiency and potentials for further extensions through extensive simulation.