Posts Tagged ‘Wireless sensor network’

Development of a New Routing Protocol by using Multi-objective and Swarm Intelligent Approaches for Wireless Sensor Network on Maritime Environment Monitoring

December 1, 2017

This is the abstract for my International Research Collaboration and Scientific Publication with two French Institutions as international collaborators.

As the largest archipelago country in the world, Indonesia has great potential to be the world’s maritime axis. The maritime axis is a strategic idea which embodied to ensure inter-island connectivity, shipping and fishery industries development, marine transportation improvement and focus on maritime security. So maritime monitoring is crucial in order to prevent sea pollution, fish theft, sovereignty offenses, territorial disputes, and piracy. Nowadays, maritime monitoring has been a very interesting issue over the last decade. With the rapid advancement of technology and the Internet, sensor network technology has become very important in monitoring the aquatic environment. Maritime responsibilities, such as vigilance and patrolling, wildlife  monitoring, and aqua-culture inspection, mostly require large operational teams and expensive equipment. In this research proposal, we will study a scalable robotics system based on swarm intelligence. We take advantage of bio-inspired artificial evolution approaches in order to synthesize scalable and robust collective behaviors for the nodes or the drones. In this research proposal, we will study and propose a system which composed of potentially hundreds sensor nodes or thousands of autonomous drones. Each drone could equipped with a number of different sensors. The use of numerous nodes or drones introduces redundancy in the system, which  decreases the impact of hardware declines and has the potential to improve operational efficiency by admitting a wider area to be covered simultaneously. On the other hand, automating such missions greatly minimizes the maintenance cost while increasing scalability and availability. The behaviors of nodes or drones are then combined hierarchically, allowing the overall behavior for a particular mission to be quickly configured and tested in simulation. The goals of this research is to developing a new mechanism which enable swarm intelligence of nodes or drones to operate as a robust wireless sensor network (WSN) for maritime environment monitoring.
Keywords: Maritime, Swarm Intelligence, Sensor, WSN



November 13, 2017

The instruction is valid for Matlab version R2007b.

First dowload and save grTheory toolobox (save it in Tools): Open the Matlab and go to the File/Set Path and click on the Add Folder. Insert the path to your grTheory toolbox.  (more…)

Operator calculus approach for route optimizing and enhancing wireless sensor network

October 1, 2017

This is the abstract of my paper which accepted and published at Journal of Network and Computer Applications,Vol 97, pp. 1-10. 2017. DOI: 10.1016/j.jnca.2017.08.007.

Route optimization is one of important feature in wireless sensor networks in order to enhancing the life time of WSNs. Since Centrality is one of the greatest challenges in computing and estimating the important node metrics of a structural graph, it is necessary to calculate and determine the importance of a node in a network. This paper proposes an alternative way to optimizing the route problems which is based on multi-constrained optimal path (MCOP) and operator calculus approach. A novel routing protocol called Path Operator Calculus Centrality (POCC) is proposed as a new method to determine the main path which contains high centrality nodes in a wireless sensor network deployment. The estimation of centrality is using the operator calculus approach based on network topology which provides optimal paths for each source node to base station. Some constraints such as energy level and bit error rate (BER) of node are considered to define the path centrality in this approach. The simulation evaluation shows improved performance in terms of energy consumption and network lifetime.

Wireless Sensor Network, Multi-constrained Optimal Path Centrality, Path Centrality, Operator Calculus

Performance Analysis of Evolutionary Multi-Objective Based Approach for Deployment of Wireless Sensor Network with The Presence of Fixed Obstacles

November 11, 2014

Here is the abstract from our paper that already accepted and will be presented on Globecom 2014 that will be held in Austin, Texas, USA from 8 – 12 December 2014.

AbstractIn this paper, a study about wireless sensor network (WSN) deployment strategy is demonstrated and made workable for the use of multi-objective approach. The development of sensor nodes by considering multiple objectives and existence of fixed obstacles is an important optimization problem. There are two objectives in this study, connectivity and coverage as two fundamental issues in wireless sensor networks deployment. In this work a multi-objective evolutionary algorithms based on elitist non-dominated sorting genetic algorithm (NSGA-II) is proposed to address this problem. Two proposed functions, ranking function and fitness function, are used to determine the best optimal solution from Pareto optimal fronts. Further we presented simulation and analysis to verify and validate the deployment of wireless sensor network in area with the presence of permanent obstacles.

KeywordsMulti-objective optimization, Wireless Sensor Network, Deployment, Genetic Algorithm, Obstacle.

Evolutionary Multi-Objective Based Approach for Wireless Sensor Network Deployment

January 14, 2014


Here is the abstract from our paper that already accepted and will be presented on ICC 2014 (International Conference on Communication) that will be held in the beautiful city of Sydney, Australia from 10-14 June 2014.

Abstract: A multi-objective evolutionary algorithm is designed to address some problems in many fields. This paper is a study about deployment strategy for achieving coverage and connectivity as two fundamental issues in wireless sensor networks. To achieve the best deployment, our approach is based on elitist non-dominated sorting genetic algorithm (NSGA-II). There are two objectives in this study, connectivity and coverage. We defined a fitness function to achieved the best deployment of nodes. Further we performed simulation to verify and validate the deployment of wireless sensor network as an output from our proposed mechanism. We measured some performance parameters to investigate and analyze our proposed sensor-deployment. Our simulation results show that our proposed algorithm can maintain coverage and connectivity in given sensing area with a relatively small number of sensor nodes in a given area.