Mobile devices are often expected to perform computational tasks that may be beyond their processing or battery capability. Cloud computing techniques have been proposed as a means to offload a mobile device’s computation to more powerful resources. In this paper, we consider the case where powerful computing resources are employed on a vehicle, thus they can be re-positioned in real time. User-carried devices with no Internet connectivity wish to initiate computing tasks to be run on a remote computer. This scenario finds application in challenged environments and may be used in a military or disaster relief setting. It is further enabled by increasing feasibility of constructing a Mobile High Performance Computer (MHPC) using rugged computer hardware with form factors that can be deployed in vehicles. By analogy to prior work on message ferries and data mules, one can refer to the use of MHPCs as computational ferrying. After illustrating and motivating the computational ferrying concept, we turn our attention into the challenges facing
such a deployment. These include the well-known challenges of operating an opportunistic and intermittently connected network using message ferries – such as devising an efficient mobility plan for MHPCs and developing techniques for proximity awareness. In addition such a system must include computation offloading decision making mechanisms to be deployed by mobile users, techniques for scheduling computation on MHPCs, and for handling possible mobility of the users. In this paper, first we propose an architecture for the system components to be deployed on the mobile users and the MHPCs. We then provide solutions to the MHPC movement scheduling problem with sufficient generality to describe a number of plausible deployment scenarios. Finally, we report and discuss some preliminary results.

Monfared, A., Mostafa A., Zegura, E., Doria, D., Bruno, D., “Computational Ferrying: Challenges in Deploying a Mobile High Performance Computer”, IEEE Autonomic and Opportunistic Communications (AOC). Accepted for publication, 2015.