Energy Efficient Ant Colony Algorithms for Data Aggregation in Wireless Sensor Networks

Computer Science – Networking and Internet Architecture

Scientific paper

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

To appear in Journal of Computer and System Sciences

Scientific paper

In this paper, a family of ant colony algorithms called DAACA for data aggregation has been presented which contains three phases: the initialization, packet transmission and operations on pheromones. After initialization, each node estimates the remaining energy and the amount of pheromones to compute the probabilities used for dynamically selecting the next hop. After certain rounds of transmissions, the pheromones adjustment is performed periodically, which combines the advantages of both global and local pheromones adjustment for evaporating or depositing pheromones. Four different pheromones adjustment strategies are designed to achieve the global optimal network lifetime, namely Basic-DAACA, ES-DAACA, MM-DAACA and ACS-DAACA. Compared with some other data aggregation algorithms, DAACA shows higher superiority on average degree of nodes, energy efficiency, prolonging the network lifetime, computation complexity and success ratio of one hop transmission. At last we analyze the characteristic of DAACA in the aspects of robustness, fault tolerance and scalability.

No associations

LandOfFree

Say what you really think

Search LandOfFree.com for scientists and scientific papers. Rate them and share your experience with other people.

Rating

Energy Efficient Ant Colony Algorithms for Data Aggregation in Wireless Sensor Networks does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Energy Efficient Ant Colony Algorithms for Data Aggregation in Wireless Sensor Networks, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Energy Efficient Ant Colony Algorithms for Data Aggregation in Wireless Sensor Networks will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFWR-SCP-O-335301

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.