Workload Allocation Scheme for Mobile Social Network

There exists many idle resources in the network which can be used to accomplish huge tasks. In this paper, we focus on those idle computational resources especially in mobile social networks (MSNs). Based on the unique features of MSN, open-crowdsourcing is introduced. In the proposed system, a large work is divided into smaller modules, and is distributed among the nodes. Still the partition of work segment is a critical problem. The lack of global information, leads to unbalanced workload distribution on participating nodes. In this paper, we find that, for a work at different processing stages, one should adopt distinct workload exchanging schemes. Based on this observation, we propose an adaptive workload allocation scheme. This approach improves the system throughput and reduces the completion time of the task. In addition to traditional scheduling parameters, we consider a human’s rejection, contact delay, and social similarity.