The DISCO network calculator: a toolbox for worst case analysis
valuetools '06 Proceedings of the 1st international conference on Performance evaluation methodolgies and tools
Validating the sensor network calculus by simulations
WICON '07 Proceedings of the 3rd international conference on Wireless internet
Energy conservation in wireless sensor networks: A survey
Ad Hoc Networks
Energy-Efficent TDMA Design Under Real-Time Constraints in Wireless Sensor Networks
MASCOTS '07 Proceedings of the 2007 15th International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems
A load balancing energy efficient clustering algorithm for MANETs
International Journal of Communication Systems
Network calculus: a theory of deterministic queuing systems for the internet
Network calculus: a theory of deterministic queuing systems for the internet
Energy efficient and QoS based routing protocol for wireless sensor networks
Journal of Parallel and Distributed Computing
Sensor network calculus – a framework for worst case analysis
DCOSS'05 Proceedings of the First IEEE international conference on Distributed Computing in Sensor Systems
Optimal multi-sink positioning and energy-efficient routing in wireless sensor networks
ICOIN'05 Proceedings of the 2005 international conference on Information Networking: convergence in broadband and mobile networking
VIBE: An energy efficient routing protocol for dense and mobile sensor networks
Journal of Network and Computer Applications
Journal of Network and Computer Applications
Journal of Network and Computer Applications
| Hi-index | 0.00 |
Placing a certain number of sinks at appropriate locations in WSNs reduces the number of hops between a sensor and its sink resulting in less exchanged messages between nodes and consequently less energy consumption. Since finding the optimal number of the sinks to be added and their locations is an NP Hard problem, we propose in this paper, a topological level solution that uses a meta-heuristic based on Particle Swarm Optimization (PSO) to decide on the number of sinks and their locations; more specifically we use Discrete PSO (DPSO) with local search. Traffic Flow Analysis (TFA) is used to calculate the fitness function of the network defined as the maximum worst case delay. Since TFA is usually used to analyze networks with one sink, we present the extension that allows it to be used with multiple sinks. Furthermore, we formulated the problem, discretized it, and applied PSO while introducing local search to the inner workings of the algorithm. Extensive experiments were conducted to evaluate the efficiency of DPSO. DPSO was compared with Genetic Algorithm-based Sink Placement (GASP), which is considered the state-of-the-art in solving the multiple sink placement problem. In all scenarios, DPSO was 2 to 3 times faster than GASP. When compared with respect to delay, DPSO achieved less delay in most scenarios, except for few scenarios where it performed similar to GASP or a bit worst. Topologies with random as well as heavy tailed distribution were used in the experiments. Moreover, we present via simulation the substantial benefit of adding more sinks to a wireless network.