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Multi-Agent Technology to Improve the Internet of Things Routing Algorithm using Ant Colony Optimization
Objective: To improve the Internet of Things routing algorithm using ant colony optimization based on multi agent technology. Methods: The IOT environment contains various types of networks and every network could use a special sort of ACO algorithmic program. This vogue depends on network’s specs, status, and needs. This IOT environment had several intersections between completely different networks that result from various coverage areas, this intersections are known as overlapped areas. A Dual agent is used to generate an optimized routing algorithm in overlapped areas. The effectiveness of the proposed routing algorithmic program is measured in various terms and they are delay time, packet loss ratio, throughput, overhead of management bits, and energy consumption ratio. Findings: Network Simulator NS-2 is employed to evaluate the proposed algorithmic program performance. We have planned our routing algorithm to enhance our packet delivery rate and avoid the overlapped intersections victimization the multi-agent technology. With efficiency it will scale back delay and improves the packet delivery ratio with minimum route price. Applications: The proposed routing algorithm uses an ACO algorithm to obtain the best routing path and it will maximize the network lifetime with minimizing data gathering delay in WSN. The performance of routing protocols will increase with increasing the packet delivery ratio.
ACO Ant Colony Optimization, IOT-Internet of Things, Multi-Agent Technology, NS-2 - Network Simulator 2
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