  Opportunistic mobile networks consisting of intermittently connected mobile
devices have been exploited for various applications, such as computational
offloading and mitigating cellular traffic load. In contrast to existing work,
in this paper, we focus on cooperatively offloading data among mobile devices
to maximally improve the probability of data delivery from a mobile device to
intermittently connected infrastructure within a given time constraint, which
is referred to as the \textit{cooperative offloading} problem. Unfortunately,
the estimation of data delivery probability over an opportunistic path is
difficult and cooperative offloading is NP-hard. To this end, we first propose
a probabilistic framework that provides the estimation of such probability.
Based on the proposed probabilistic framework, we design a heuristic algorithm
to solve cooperative offloading at a low computation cost. Due to the lack of
global information, a distributed algorithm is further proposed. The
performance of the proposed approaches is evaluated based on both synthetic
networks and real traces. Experimental results show that the probabilistic
framework can accurately estimate the data delivery probability, cooperative
offloading greatly improves the delivery probability, the heuristic algorithm
approximates the optimum, and the performance of both the heuristic algorithm
and distributed algorithm outperforms other approaches.
