Abstract
We propose a mobility-assisted on-demand routing algorithm for mobile ad hoc networks in the presence of location errors. Location awareness enables mobile nodes to predict their mobility and enhances routing performance by estimating link duration and selecting reliable routes. However, measured locations intrinsically include errors in measurement. Such errors degrade mobility prediction and have been ignored in previous work. To mitigate the impact of location errors on routing, we propose an on-demand routing algorithm taking into account location errors. To that end, we adopt the Kalman filter to estimate accurate locations and consider route confidence in discovering routes. Via simulations, we compare our algorithm and previous algorithms in various environments. Our proposed mobility prediction is robust to the location errors.
Highlights
A mobile ad hoc network (MANET) [1] consists of a set of wireless mobile nodes that dynamically exchange data among themselves without relying on any fixed infrastructure
The ad hoc on-demand distance vector routing algorithm (AODV) was proposed as a reactive routing algorithm to allow mobile nodes to quickly adapt to topology changes and link breaks in mobile ad hoc networks [5]
This paper proposed an on-demand routing algorithm with enhanced mobility prediction that takes into account the location errors
Summary
A mobile ad hoc network (MANET) [1] consists of a set of wireless mobile nodes that dynamically exchange data among themselves without relying on any fixed infrastructure. In [9, 10], the authors modeled the distribution of path duration and analyzed the relation between path duration and other factors such as relative speed, transmission range, and number of hops Their analysis shows that routing protocol with higher path duration can improve the network performance. In [11], the authors investigate the distribution of path duration and design a scheme to select a route with the largest expected duration and provide reliable network services in MANETs. Location information enables nodes to predict mobility and estimate path durations more accurately. The proposed algorithms in [12, 13] anticipate the link expiration time (LET) based on measured locations and velocities and were applied to routing protocols to reduce overheads in [12] or to select the most reliable route that has the longest path duration [13].
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