Efficient and Secure Traffic Scheduling Based on Private Sketch

Yang Chen, Huishu Wu and Xuhao Ren ()
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Yang Chen: Beijing Institute of Tracking and Telecommunication Technology, Beijing 100094, China
Huishu Wu: Faculty of Law, University of Montreal, 2900 Edouard Montpetit Blvd, Montreal, QC H3T 1J4, Canada
Xuhao Ren: School of Cyberspace Science and Technology, Beijing Institute of Technology, Beijing 100081, China

Mathematics, 2025, vol. 13, issue 2, 1-21

Abstract: In today’s data–driven world, the explosive growth of network traffic often leads to network congestion, which seriously affects service performance and user experience. Network traffic scheduling is one of the key technologies to deal with congestion problems. Traditional traffic scheduling methods often rely on static rules or pre–defined policies, which make it difficult to cope with dynamically changing network traffic patterns. Additionally, the inability to efficiently manage tail contributors that disproportionately contribute to traffic can further exacerbate congestion issues. In this paper, we propose ESTS, an efficient and secure traffic scheduling based on private sketch, capable of identifying tail contributors to adjust routing and prevent congestion. The key idea is to develop a randomized admission ( R A ) structure, linking two count–mean–min (CMM) sketches. The first CMM sketch records cold items, while the second, following the R A structure, stores hot items with high frequency. Moreover, considering that tail contributors may leak private information, we incorporate Gaussian noise uniformly into the CMM sketch and R A structure. Experimental evaluations on real and synthetic datasets demonstrate that ESTS significantly improves the accuracy of feature distribution estimation and privacy preservation. Compared to baseline methods, the ESTS framework achieves a 25% reduction in average relative error and a 30% improvement in tail contributor identification accuracy. These results underline the framework’s efficiency and reliability.

Keywords: private sketch; traffic scheduling; tail contributors (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2025
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