A Time-constraint Satisfying and Cost-reducing node evaluation metric for Message Routing in Mobile Crowd Sensing Networks
Qian Wang, Zhipeng Gao, Kun Niu, Yang Yang, Xuesong Qiu

TL;DR
This paper introduces a novel node evaluation metric for message routing in mobile crowd sensing networks that reduces redundant data and improves delivery efficiency by considering time constraints and contact probabilities.
Contribution
The paper proposes a new method for evaluating nodes based on transient cluster detection and contact probability, effectively reducing computational complexity and redundant data in message routing.
Findings
Outperforms existing data forwarding approaches in delivery ratio.
Reduces network overhead significantly.
Simplifies transient cluster detection process.
Abstract
In mobile crowd sensing networks data forwarding through opportunistic contacts between 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. However most of them neglect a kind of redundant data whose Time-To-Live is expired. For reducing this kind of redundant data we 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. We propose a method to detect node's transient cluster, which is…
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Taxonomy
TopicsOpportunistic and Delay-Tolerant Networks · Human Mobility and Location-Based Analysis · Mobile Crowdsensing and Crowdsourcing
