Genetic algorithms + data structures = evolution programs (2nd, extended ed.)
Genetic algorithms + data structures = evolution programs (2nd, extended ed.)
Dynamic fine-grained localization in Ad-Hoc networks of sensors
Proceedings of the 7th annual international conference on Mobile computing and networking
Wireless sensor networks: a survey
Computer Networks: The International Journal of Computer and Telecommunications Networking
Localization for mobile sensor networks
Proceedings of the 10th annual international conference on Mobile computing and networking
Discrete & Computational Geometry
Approximating the Nondominated Front Using the Pareto Archived Evolution Strategy
Evolutionary Computation
Comparison of Multiobjective Evolutionary Algorithms: Empirical Results
Evolutionary Computation
Distributed weighted-multidimensional scaling for node localization in sensor networks
ACM Transactions on Sensor Networks (TOSN)
Evolutionary Algorithms for Solving Multi-Objective Problems (Genetic and Evolutionary Computation)
Evolutionary Algorithms for Solving Multi-Objective Problems (Genetic and Evolutionary Computation)
Wireless sensor network localization techniques
Computer Networks: The International Journal of Computer and Telecommunications Networking
Second-Order Cone Programming Relaxation of Sensor Network Localization
SIAM Journal on Optimization
Muiltiobjective optimization using nondominated sorting in genetic algorithms
Evolutionary Computation
Collaborative Localization in Wireless Sensor Networks
SENSORCOMM '07 Proceedings of the 2007 International Conference on Sensor Technologies and Applications
Further Relaxations of the Semidefinite Programming Approach to Sensor Network Localization
SIAM Journal on Optimization
Optimization Schemes For Wireless Sensor Network Localization
International Journal of Applied Mathematics and Computer Science
Information Sciences: an International Journal
Understanding and solving flip-ambiguity in network localization via semidefinite programming
GLOBECOM'09 Proceedings of the 28th IEEE conference on Global telecommunications
Multiobjective evolutionary algorithms: a comparative case studyand the strength Pareto approach
IEEE Transactions on Evolutionary Computation
A fast and elitist multiobjective genetic algorithm: NSGA-II
IEEE Transactions on Evolutionary Computation
Engineering Applications of Artificial Intelligence
Wireless sensor network positioning based on the unilateral side of two reference nodes
Computers and Electrical Engineering
Hi-index | 0.00 |
Abstract: To know the location of nodes plays an important role in many current and envisioned wireless sensor network applications. In this framework, we consider the problem of estimating the locations of all the nodes of a network, based on noisy distance measurements for those pairs of nodes in range of each other, and on a small fraction of anchor nodes whose actual positions are known a priori. The methods proposed so far in the literature for tackling this non-convex problem do not generally provide accurate estimates. The difficulty of the localization task is exacerbated by the fact that the network is not generally uniquely localizable when its connectivity is not sufficiently high. In order to alleviate this drawback, we propose a two-objective evolutionary algorithm which takes concurrently into account during the evolutionary process both the localization accuracy and certain topological constraints induced by connectivity considerations. The proposed method is tested with different network configurations and sensor setups, and compared in terms of normalized localization error with another metaheuristic approach, namely SAL, based on simulated annealing. The results show that, in all the experiments, our approach achieves considerable accuracies and significantly outperforms SAL, thus manifesting its effectiveness and stability.