TY  - JOUR
T1  - A Novel Enhanced Coverage Optimization Algorithm for
Effectively Solving Energy Optimization Problem for WSN
AU - Kumar, M. Senthil AU - Chaturvedi, Ashish 
JO  - Research Journal of Applied Sciences
VL  - 8
IS  - 6
SP  - 340
EP  - 345
PY  - 2013
DA  - 2001/08/19
SN  - 1815-932x
DO  - rjasci.2013.340.345
UR  - https://makhillpublications.co/view-article.php?doi=rjasci.2013.340.345
KW  - Ant Colony Optimization (ACO)
KW  -three types of pheromones
KW  -energy efficient coverage
KW  -probabilistic sensor detection
KW  -Point of Interest (PoI)
AB  - In Wireless Sensor Network (WSN), Efficient-Energy Coverage 
  (EEC) is one of the important issues for considering the (WSNs) implementation. 
  In this study, researchers have developed the new algorithm ECO (Enhanced Coverage 
  Optimization) for solving the EEC problem effectively. The proposed algorithm 
  uses three types of significant work for effectively solving the problem. One 
  of the three pheromones is the local pheromone which helps an ant organize its 
  coverage set with fewer sensors. The other two pheromones are global pheromones, 
  one of which is used to optimize the number of required active sensors per Point 
  of Interest (PoI) and the other is used to form a sensor set that has as many 
  sensors as an ant has selected the number of active sensors by using the former 
  pheromone. This study also introduces one technique that leads to a more realistic 
  approach to solving the EEC problem that is to utilize the probabilistic sensor 
  detection model. The main goal of ECO is efficient coverage on target area with 
  minimum energy consumption and increased network’s 
  lifetime.
ER  -