Wireless Sensor Networks are generally characterized by a large number of small sensing devices (sensors), often randomly disposed all over the region of interest in order to perform a monitoring activity on a set of target points. One of the key issues in this scenario involves the maximization of the amount of time in which this activity can be carried on and is usually known as Maximum Network Lifetime Problem (MNLP), under the constraint given by the limited power of the batteries contained in the sensors. In most of the works on the subject available in the literature, MNLP is faced by scheduling the sensors in subsets (covers) that are individually able to cover the whole set of targets. A drawback of such approaches is that the amount of energy that is needed to deliver the sensed data is not modeled; individual sensors inside a cover might be very far from each other and from wherever the information needs to be sent. To overcome this drawback and take into account communication costs, we look for a solution composed by connected covers. n this work we present an exact approach for the problem and for some variants of it, as well as some preliminary results.

Scheduling Sensors in Wireless Networks to Extend Lifetime and Maintain Connectivity

GENTILI, Monica;RAICONI, ANDREA
2010-01-01

Abstract

Wireless Sensor Networks are generally characterized by a large number of small sensing devices (sensors), often randomly disposed all over the region of interest in order to perform a monitoring activity on a set of target points. One of the key issues in this scenario involves the maximization of the amount of time in which this activity can be carried on and is usually known as Maximum Network Lifetime Problem (MNLP), under the constraint given by the limited power of the batteries contained in the sensors. In most of the works on the subject available in the literature, MNLP is faced by scheduling the sensors in subsets (covers) that are individually able to cover the whole set of targets. A drawback of such approaches is that the amount of energy that is needed to deliver the sensed data is not modeled; individual sensors inside a cover might be very far from each other and from wherever the information needs to be sent. To overcome this drawback and take into account communication costs, we look for a solution composed by connected covers. n this work we present an exact approach for the problem and for some variants of it, as well as some preliminary results.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11386/4168253
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