Resource Allocation in Quantum-Key-Distribution- Secured Datacenter Networks With Cloud–Edge Collaboration

Abstract

Datacenter networks (DCNs) with cloud-edge collaboration are emerging to satisfy the communication, computation, and caching (3C) requirements of future services such as cloud-based IoT services. However, the enroute data over DCNs with cloud-edge collaboration is likely to suffer from cyberattacks such as eavesdropping. A large number of services require not only 3C resources, but also cryptographic resources for encryption to ensure high security. Quantum key distribution (QKD) is a practical approach to provide secret keys for remote users with information-theoretic security against eavesdropping attacks from quantum computing. A QKD-secured DCN (QKD-DCN) with cloud-edge collaboration can be deployed to satisfy the communication, computation, caching, and cryptographic (4C) requirements of services. This paper innovatively solves the new 4C resource-allocation (4CRA) problem in the network to minimize the cryptographic resource consumption. It formulates an integer linear programming (ILP) model and proposes a heuristic cryptographic-dependent 4C resource-allocation algorithm to find optimal solutions. The proposed algorithm is compared with two baseline 4CRA algorithms which respectively consider the minimized service delivery latency and the first-fit resource availability. Analytical simulations show that the proposed algorithm minimizes the key-resource-consumption ratio and the average key-resource consumption under static and dynamic traffic scenarios in different network topologies.