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In mobile crowd sensing networks data forwarding through opportunisticcontacts between participants. Data is replicated to encountered participants.For optimizing data delivery ratio and reducing redundant data a lot of dataforwarding schemes, which selectively replicate data to encounteredparticipants through node's data forwarding metric are proposed. However mostof them neglect a kind of redundant data whose Time-To-Live is expired. Forreducing this kind of redundant data we proposed a new method to evaluatenode's data forwarding metric, which is used to measure the node's probabilityof forwarding data to destination within data's constraint time. The method isdivided into two parts. The first is evaluating nodes whether have possibilityto contact destination within time constraint based on transient cluster. Wepropose a method to detect node's transient cluster, which is based on node'scontact rate. Only node, which has possibility to contact destination, haschances to the second step. It effectively reduces the computationalcomplexity. The second is calculating data forwarding probability of node todestination according to individual ICT (inter contact time) distribution.Evaluation results show that our proposed transient cluster detection method ismore simple and quick. And from two aspects of data delivery ratio and networkoverhead our approach outperforms other existing data forwarding approach.

A Time-constraint Satisfying and Cost-reducing node evaluation metric for Message Routing in Mobile Crowd Sensing Networks