NDLI: Robot routing in sparse wireless sensor networks with continuous ant colony optimization

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Robot routing in sparse wireless sensor networks with continuous ant colony optimization

Content Provider	ACM Digital Library
Author	Comarela, Giovanni Pappa, Gisele Lobo Almeida, Jussara Almeida, Virgílio Gonçalves, Kênia
Abstract	Sparse wireless sensor networks are characterized by the distances the sensors are from each other. In this type of network, gathering data from all sensors in a point of interest might be a difficult task, and in many cases a mobile robot is used to travel along the sensors and collect data from them. In this case, we need to provide the robot with a route that minimizes the traveled distance and allows data collection from all sensors. This problem can be modeled as the classic Traveling Salesman Problem (TSP). However, when the sensors have an influence area bounded by a circle, for example, it is not necessary that the robot touches each sensor, but only a point inside the covered area. In this case, the problem can be modeled as a special case TSP with Neighborhoods (TSPN). This work presents a new approach based on continuous Ant Colony Optimization (ACO) and simple combinatorial technique for TSP in 0order to solve that special case of TSPN. The experiments performed indicate that significant improvements are obtained with the proposed heuristic when compared with other methods found in literature.
Starting Page	599
Ending Page	606
Page Count	8
File Format	PDF
ISBN	9781450306904
DOI	10.1145/2001858.2002055
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2011-07-12
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Ant colony optimization Wireless sensor networks Global optimization
Content Type	Text
Resource Type	Article

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