Offloading cellular networks through ITS content download

Abstract

Content downloading by mobile users is expected to significantly increase the cellular network load. Vehicular users, in particular, are likely to engage in information retrieval on the move: in this context, Intelligent Transportation Systems (ITS) can play an important role in offloading the cellular infrastructure. We investigate the effectiveness of ITS in this task, considering that roadside units (RSUs) can exploit mobility prediction to decide which data they should fetch from the Internet and schedule transmissions to vehicles, either potential relays or downloaders. Rather than presenting a specific prediction scheme, we propose a model that allows us to express and account for any prediction technique in a simple, yet effective, manner. We then provide a probabilistic graph-based representation of the system that accounts for the prediction uncertainty. We use such a representation to study the network dynamics by efficiently solving a (non-integer) LP problem. Our results show that the above approach to content downloading through ITS can achieve an 80% offload of the cellular network. Also, we investigate the dependency of the system performance on the accuracy of the mobility prediction, and which prediction errors have the largest impact.

MMCD: Max-throughput and min-delay cooperative downloading for Drive-thru Internet systems

“…Upon receiving the beacon, a vehicle sends back a request when it has data to download from the RSU. Without loss of generality, we assume any contents requested by vehicular users are available at the RSU which obtains the contents in advance via the Internet by data prefetching methods [7]. The RSU can deal with the requests only one by one (i.e., unable to transfer data packets to multiple vehicles concurrently).…”

A traffic QoS aware approach for cellular infrastructure offloading using VANETs

“…An estimation of a suitable P A th will be handled in section V. The P A i between the vehicle i and the RSU is computed using (4). It evaluates the single-hop (LA I i ) or the multi-hop (LA V 2V i ) path that exists between the vehicle i and the RSU.…”

“…Numerous works have studied the system of offloading the cellular infrastructure while using the Wi-Fi hotspots and femtoCells. However, only very few works [4], [5] have considered using the intelligent transportation system (ITS) for the same purpose. In fact, vehicular ad hoc networks (VANET) are widespread and vehicles become intelligent and connected.…”

“…In reference [4], authors present an analytical study for content offloading through ITS. The problem formulation is based on maximizing a cost function.…”

“…The originality of this work is to include the traffic service class constraints in the offloading decision. Moreover, while comparing to [4], this work evaluates the impact of the load and the data volume variation on channel contention for the I2V link, and prioritizes the offload of flows with high I2V link connectivity duration.…”