Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: In mobile crowd sensing networks data forwarding through opportunistic contacts beten participants. Data is replicated to encountered participants. For optimizing data delivery ratio and reducing redundant data a lot of data forwarding schemes, which selectively replicate data to encountered participants through node's data forwarding metric are proposed. Hover most of them neglect a kind of redundant data whose Time-To-Live is expired. For reducing this kind of redundant data  proposed a new method to evaluate node's data forwarding metric, which is used to measure the node's probability of forwarding data to destination within data's constraint time. The method is divided into two parts. The first is evaluating nodes whether have possibility to contact destination within time constraint based on transient cluster.  propose a method to detect node's transient cluster, which is based on node's contact rate. Only node, which has possibility to contact destination, has chances to the second step. It effectively reduces the computational complexity. The second is calculating data forwarding probability of node to destination according to individual ICT (inter contact time) distribution. Evaluation results show that our proposed transient cluster detection method is more simple and quick. And from two aspects of data delivery ratio and network overhead our approach outperforms other existing data forwarding approach.
['Qian Wang', 'Zhipeng Gao', 'Kun Niu', 'Yang Yang', 'Xuesong Qiu']
I am writing a research paper on a idea A Time-constraint Satisfying and Cost-reducing node evaluation metric for Message Routing in Mobile Crowd Sensing Networks
[{"from": "human", "value": "I am writing a research paper on a idea A Time-constraint Satisfying and Cost-reducing node evaluation metric for Message Routing in Mobile Crowd Sensing Networks"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: In mobile crowd sensing networks data forwarding through opportunistic contacts beten participants. Data is replicated to encountered participants. For optimizing data delivery ratio and reducing redundant data a lot of data forwarding schemes, which selectively replicate data to encountered participants through node's data forwarding metric are proposed. Hover most of them neglect a kind of redundant data whose Time-To-Live is expired. For reducing this kind of redundant data  proposed a new method to evaluate node's data forwarding metric, which is used to measure the node's probability of forwarding data to destination within data's constraint time. The method is divided into two parts. The first is evaluating nodes whether have possibility to contact destination within time constraint based on transient cluster.  propose a method to detect node's transient cluster, which is based on node's contact rate. Only node, which has possibility to contact destination, has chances to the second step. It effectively reduces the computational complexity. The second is calculating data forwarding probability of node to destination according to individual ICT (inter contact time) distribution. Evaluation results show that our proposed transient cluster detection method is more simple and quick. And from two aspects of data delivery ratio and network overhead our approach outperforms other existing data forwarding approach."}]