Improved Clustering with Optimization and Intelligent Path Selection
J. Deepika

J. Deepika, Department of Information Technology, Sona College of Technology, Salem, Tamil Nadu, India.

Manuscript received on January 13, 2020. | Revised Manuscript received on January 21, 2020. | Manuscript published on February 10, 2020. | PP: 2310-2313 | Volume-9 Issue-4, February 2020. | Retrieval Number: D1828029420/2020©BEIESP | DOI: 10.35940/ijitee.D1828.029420
Open Access | Ethics and Policies | Cite | Mendeley
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (

Abstract: Wireless sensor networks (WSN) are widely used networking paradigm in research areas and clustering is one of the trusted mechanism for storing and processing data among the nodes in the network. The clustering makes use of a single node for transferring data to the sink node with sustaining the energy of all other nodes in the network and does the procedure of storing and processing of data using an optimization technique called as Ant Colony Optimization (ACO). The ACO is proposed in accordance along clustering which is the optimization technique used for robust communication between source node and destination node. The clustering mechanism used for sending data along the best path among the source and destination in the network so that the data can reach the destination rapidly and that helps in availing the faster response between source node and destination node. The ACO will greatly influence the dropped packets and that the delay occurring in the network based on the traffic available among the nodes in the network. 
Keywords: Ant Colony Optimization (ACO) Clustering, Optimization, Wireless Sensor Networks (WSN).
Scope of the Article:  Clustering