Computational Intelligence in Wireless Sensor and Ad Hoc Networks

Editorial Computational Intelligence in Wireless Sensor and Ad Hoc Networks Sergio Toral,1Ciprian Dobre,2Bernabé Dorronsoro,3Mesut Günes,4and Daniel G. Reina1 1Department of Electronic Engineering, University of Seville, 41092 Sevilla, Spain 2Computer Science Department, University Politehnica of Bucharest, 060042 Bucharest, Romania 3School of Engineering, University of Cadiz, 11519 Cadiz, Spain 4Communication and Networked Systems (ComSys), Institute of Computer Science, University of Munster, 48149 M¨ unster, Germany Correspondence should be addressed to Sergio Toral; sto[email protected] Received 25 February 2016; Accepted 25 February 2016 Copyright © 2016 Sergio Toral et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Multihop wireless sensor network is a mature research field that covers many topics and different classes of networks. Despite previous results and a vast literature on the topic, many problems related to modern network infrastructures such as coverage, deployment, routing, broadcasting, mobility, and energy consumption are still challenging, as solving them to optimality is certainly far from easy. Additionally, the desirable performance features are usually in conflict, meaning that tuning the network to improve one of them will negatively impact others. This difficulty, together with the high number of network parameters involved and their multiple dependencies, advises using computational intelligence optimization algorithms. These tools perform an efficient search on large spaces thanks to the good exploration and exploitation behaviors they provide. Therefore, they allow exploring accurate solutions beyond the knowledge of the network designer, learning the properties of the environment, and adapting their behavior to the changing conditions. The scope of our special issue is to encourage new research and developments in the field. We open the special issue with a survey that addresses the main aspects of the application of evolutionary algorithms in mobile multihop networks.First,anintroductiononmobilemultihopnetworks (MANETs, VANETs, and DTNs) is given, and after that the survey focuses on the application of evolutionary algorithms to multihop related problems. Relevant existing work for each type of mobile multihop network and some futureworkandopenchallengesarementionedattheend. We expect this survey will help new researchers to have an overviewofthefieldandrapidlycontributewithnewresearch and developments. The paper “An Intelligent Strategy for Tactical MovementsofUAVsinDisasterScenarios”proposesaninteresting approach for decision making of tactical movements of UAVs in disaster scenarios. Both simulated annealing algorithm and a dissimilarity metric like the Jaccard distance are used to decide the next movements of UAVs in order to maximize the number of covered victims in the disaster area. A new mobility model for disaster scenarios is employed for the evaluation of the proposed tactical movements. In “An Efficient Large-Scale Sensor Deployment Using a Parallel Genetic Algorithm Based on CUDA,” a genetic algorithm is used to solve a deployment problem of wireless sensor networks in battlefield environments. In order to importantly reduce the computing time to find a solution, the authors implemented a massively parallel genetic algorithm for CUDA (standing for Compute Unified Device Architecture). The obtained simulation results demonstrate that the computing time can be reduced to 55-56 times when applying the proposed CUDA. A Monte Carlo based tracking application for wireless sensor networks is proposed in “NMCT: A Novel Monte Carlo-Based Tracking Algorithm Using Potential Proximity Information.” The approach uses both area-based and neighbor-based filtering to solve the main problems of traditional methods like the requirement of a high number Hindawi Publishing Corporation International Journal of Distributed Sensor Networks Volume 2016, Article ID 7049593, 2 pages http://dx.doi.org/10.1155/2016/7049593 2 International Journal of Distributed Sensor Networks of anchors. This work also compares the proposed NMCT method versus other typical algorithms used in wireless sensor scenarios. The paper “Modeling of Multihop Wireless Sensor Networks with MAC, Queuing, and Cooperation” presents a Markoviandecisionprocess(MDP)frameworkformultihop wireless sensor networks (MHWSNs). The proposed framework is evaluated in two types of MHWSNs such as energy constrained (EC) networks and energy harvesting (EH) networks. From the presented analysis of both networks, it canbeobservedthatECandEHnetworksfallintotwo branches of MDP theory, which are finite-horizon process and infinite-horizon process, respectively. Finally, Multiattribute Routing Scheme (MARS) routing protocol for opportunistic networks is presented in “Resource Aware Routing in Heterogeneous Opportunistic Networks.” The protocol uses neural networks to learn rules. The main objective of MARS is to use Simple Multiattribute Rating Technique (SMART) in order to maximize node’s utility and to improve the delivery of packets in real and synthetic tracebased opportunistic scenarios. Theworkpresentedinthisspecialissueaimstocontribute and stimulate the research on the application of computational intelligence techniques to the multihop ad hoc networks field, where more work is needed to understand the dependencies of the network performance on the network parameters. Acknowledgments The editors would like to thank the authors and reviewers for all the hard work towards ensuring the high standards of the special issue. Sergio Toral Ciprian Dobre Bernab´ e Dorronsoro Mesut G¨ unes Daniel G. Reina