Vehicle-to-Vehicle Forwarding in Green Vehicular Infrastructure

Abstract

<p>Smart scheduling can be used to reduce infrastructure-to-vehicle</p> <p>energy costs in delay tolerant vehicular</p> <p>networks (Hammad et al., 2010).. In this thesis we show that by combining</p> <p>this with vehicle-to-vehicle (V2V) forwarding, energy efficiency can</p> <p>be increased beyond that possible in the single hop case. This is</p> <p>accomplished by having the roadside infrastructure forward packets</p> <p>through vehicles which are in energy favourable locations. We first</p> <p>derive offline bounds on the downlink energy usage for a given input</p> <p>sample function when V2V forwarding is used. Separate bounds are given</p> <p>for the off-channel and in-channel forwarding cases. These bounds are</p> <p>used for comparisons with a variety of proposed online scheduling</p> <p>algorithms. The paper then introduces online algorithms for both</p> <p>fixed bit rate and variable bit rate air interface options. The first</p> <p>algorithm is based on a greedy local optimization (GLOA). A version of</p> <p>this algorithm which uses a minimum cost flow graph scheduler is also</p> <p>introduced. A more sophisticated algorithm is then proposed which is</p> <p>based on a finite window group optimization (FWGO). Versions of these</p> <p>algorithms are also proposed which use in-channel vehicle-to-vehicle</p> <p>scheduling. The proposed algorithms are also adapted to the variable</p> <p>bit rate air interface case. Results from a variety of experiments</p> <p>show that the proposed scheduling algorithms can significantly improve</p> <p>the downlink energy requirements of the roadside unit compared to the</p> <p>case where vehicle-to-vehicle packet forwarding is not used. The</p> <p>performance improvements are especially strong under heavy loading</p> <p>conditions and when the variation in vehicle communication</p> <p>requirements or vehicle speed is high.</p>