Privacy-Preserving Resource Management for Distributed Collaborative Edge Caching Systems

Caching sheds a light on reducing long-distance data transmissions over networks, while raising significant privacy concerns. Moving one step ahead, collaborative edge caching is proposed to facilitate preserving user privacy via reducing the external data exposure. However, it still fails to avert the risk of privacy leakage from nearby edge devices. To tackle this issue, we develop an analytical framework for privacy preserving joint communication and content allocation algorithm for distributed collaborative edge caching systems, in which edge devices collaboratively cache and share the content items based on the dummy-based privacy preservation mechanism. Specifically, we define the system request uncertainty criterion from the perspective of information entropy to measure the privacy preservation performance. Consequently, the closed-form relationship between the system request uncertainty and the resource allocation decisions on both communication resources and content items can be derived. Then, we decompose the NP-hard resource management problem into two parts, and propose 1) An optimal dummy request allocation strategy through investigating special properties of the maximal allocation reward gain; 2) An asymptotically-optimal content item allocation strategy with low-complexity based on extract penalty method (EPM); which are iterated to obtain a viable solution, followed by the proof of convergence and asymptotic monotone property. Finally, the performance improvements are verified by simulations.