Abstract
Recently more number of routing protocols is discovered for better data routing in Wireless Sensor Network (WSN). However link failures exist in the network due to appearance of low energy nodes, low link gap connectivity while routing, etc. To compute low complexity routes and to minimize the energy consumption a nature bio inspired algorithm Ant Colony Optimization (ACO) mechanism is applied in the sensor networks. An Efficient and Optimal Routing using ACO is proposed. The premium route is determined with sub-premier nodes having high link-gap connectivity factor. The best premier nodes are selected from the sub-premier nodes on basis of bandwidth integrity and eternal energy factors for determining the premium route. The proposed work is validated by comparing the results of other existing techniques. The performance metrics proves that the proposed mechanism exhibits better throughput and delivery rate with low loss rate.
Highlights
Data Transmission from one end to the other end is generally carried out through the routing process
The performance of the existing system Three Pheromones ACO (TPACO) is compared with the proposed EOR-Ant Colony Optimization (ACO) system, which is analyzed in this work using simulation results
An Efficient and Optimal Routing using ACO scheme is implemented for improving the network characteristics and its functions
Summary
Data Transmission from one end to the other end is generally carried out through the routing process. Construction of reliable routes in wireless sensor networks is not so easy process since it includes good network properties like delay, energy efficiency, bandwidth, link-gap connectivity, etc., In networks every node is capable of sensing, processing the data, and transmitting to the other. Failures in reliability lead to network disaster and it leads to break in carrying out successful network operation results in intolerable serious effects [Koushanfar et al, 2005]. Reliable wireless sensor network can be defined as the network that functions adequately in terms of both connectivity between the sensor nodes and coverage of the targeted nodes i.e. Region of Interest (RoI).
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