The rationale for this project stems from the widespread diffusion of smartphones, tablets, and other mobile devices with diverse networking and multimedia capabilities, and the associated blossoming of all kinds of data-hungry multimedia services. According to Cisco, global mobile data will experience a growth of more than 26 times in only five years for the period 2010-2015.

This poses dramatic challenges to mobile telecom operators all over the world. Major operators in the US and Europe are experiencing severe problems in coping with the mobile data traffic generated by their users. Considerable progress is constantly made at the physical layer to increase raw bitrates, and clearly LTE and LTE advanced will help in this direction, but this is neither sufficient nor cost-efficient to accommodate all the increase in data service demand. This is because the trend of the traffic demand is exponentially increasing, while the improvements at the physical layer are bounded by the famous Shannon theorem and by the fact that the licensed spectrum is a limited and scarce resource [IW10]. Moreover, provisioning “additional” 4G infrastructure (even in the “lightweight version” of LTE relays) bears significant costs both at the deployment and the management phases.

As a result, it is expected that the amount of traffic generated by 4G users will be about one order of magnitude larger than the bandwidth operators will be able to deliver [INT09]. The operator will need to decide to either drastically reduce the quality of service (QoS) for all the users, or block a significant fraction of the users to provide acceptable QoS to a few. Both alternatives are largely sub-optimal and generate user dissatisfaction.

The MOTO project proposes a traffic offloading architecture that exploits in a synergic way a diverse set of offloading schemes, including offloading from cellular to other wireless infrastructures (such as Wi-Fi), and also offloading to multi-hop ad hoc communications between users devices.

In practice, this architecture is promised to offer many other advantages in addition to reducing load on operators’ infrastructures:

  • Reduce communication delays by pushing the information closer to users. Indeed, downloading data from geographically close neighbours can considerably reduce delays.
  • Exploit “social” information to build, maintain, and adapt the constructed ad hoc networks. It is clear that users present at the same event in the same time-share at least one common interest.
  • Reduce energy consumption by limiting redundant traffic on the infrastructure and by allowing communication among nearby peers (reduced transmission powers).