Load Adaptive Caching Points for a Content Distribution Network

Abstract

-The unprecedented growth in content demand on smartphones has significantly increased the energy consumption of current cellular and backbone networks. Apart from achieving stringent carbon footprint targets, provisioning high data rates to city vehicular users while maintaining quality of service (QoS) remains a serious challenge. In previous work, to support content delivery at high data rates, the number and locations of caching points (CPs) within a content distribution network (CDN) were optimized while reducing the operational energy consumption compared to typical cellular networks. Further reduction in energy consumption may be possible through sleep cycles, which reduces transmission energy consumption. However, sleep cycles degrade the quality of service. Therefore, in this paper, we propose a novel load adaptation technique for a CP which not only enhances content download rate but also reduces transmission energy consumption through random sleep cycles. Unlike a non-load adaptive (deterministic) CP, the performance results reveal that the load adaptive CP achieves considerably lower average piece delay (approximately 60% on average during the day), leveraging the introduction of random sleep cycles to save transmission energy. The proposed CP saves up to 84% transmission energy during off-peak hours and 33% during the whole day while fulfilling content demand in a city vehicular environment.

Optimized Processing Placement Over a Vehicular Cloud

“…In [44], the authors improved the energy efficiency of content distribution to city vehicular users by using renewable energy and adaptive caching points. They also studied the impact of load adaptive caching points on the energy efficiency in [45], and several vehicular network scenarios with energy efficient adaptive/non-adaptive fog servers with renewable/ non-renewable energy in [46]. A multi objective resource allocation model in vehicular clouds was proposed in [48].…”

Energy efficient Nano Servers provisioning for Information Piece Delivery in a vehicular environment

“…However, to the best of our knowledge, rate adaptation has never been used in the context of saving non-renewable energy, or improving QoS, if renewable energy is available. In [11], traffic sensing based data load adaptation was proposed in a city vehicular scenario, which inspired us to formulate the concept of energy aware rate adaptation, proposed in this paper. The load adaptation is based on traffic sensing in real time, which guides us to vary the data rate of a device.…”