LAUSR.org creates dashboard-style pages of related content for over 1.5 million academic articles. Sign Up to like articles & get recommendations!

Mobility-prediction and energy optimization for multi-channel multi-interface ad hoc networks in the presence of location errors

Photo by mbrunacr from unsplash

We present a mobility-prediction and energy optimization solution for multi-channel multi-interface (MCMI) ad hoc networks in the presence of location errors. This solution includes routing of the MCMI communication links… Click to show full abstract

We present a mobility-prediction and energy optimization solution for multi-channel multi-interface (MCMI) ad hoc networks in the presence of location errors. This solution includes routing of the MCMI communication links that adapt to dynamic channel, traffic conditions, interference and mobility of nodes. We start first with implementing a novel cross-layer routing solution in order to share information between network and MAC layer, the benefit of this technique is to collect information about the channel quality and residual energy of the nodes and send them directly to the network layer. Next, we present a mobility-prediction model using Kalman filter to predict accurate locations and enhance routing performance, through estimating link duration and selecting reliable routes. The performance of proposed mechanism is measured using NS2.35 simulations with different scenarios and varying load in a network. Comparative analysis of simulation results shows better performance of our protocol (ME-MCMI AODV) in terms of reducing end-to-end delay, total dropped packets and increasing network lifetime and packet delivery ratio (PDR).

Keywords: mobility; prediction energy; mobility prediction; channel

Journal Title: Indonesian Journal of Electrical Engineering and Computer Science
Year Published: 2021

Link to full text (if available)


Share on Social Media:                               Sign Up to like & get
recommendations!

Related content

More Information              News              Social Media              Video              Recommended



                Click one of the above tabs to view related content.