Green Vehicular Content Distribution Network

With environmental awareness becoming a global concern, content distribution has become popular in the context of modern city scenario with obvious concerns for ICT power consumption. The business world demands huge amounts of information exchange for advertisement and connectivity, which is an integral part of a smart city.

In this thesis, a number of energy saving and performance improvement techniques are proposed for the content delivery scenario. These are: content cache location optimisation techniques for energy saving and transceiver load adaptive techniques that save energy while maintaining acceptable piece delay. With the recent advancement in Fog computing, nano-servers are introduced in the later part of the thesis for content delivery and process of user demands. Two techniques random sleep cycles and rate adaptation are proposed to save transmission energy. The quality of service in terms of piece delay and dropping probability are optimised by deploying renewable and non-renewable energy powered nano-servers (NS). Finally, mixed integer linear programming models (MILP) were developed alongside other optimisations methods like bisection, greedy and genetic algorithms which judiciously distribute renewable energy to the fog servers in order to minimise the piece delay and dropping probability in heavily loaded regions of the city area.