A novel routing method for dynamic control in distributed computing power networks

Abstract

Driven by diverse intelligent applications, computing capability is moving from the central cloud to the edge of the network in the form of small cloud nodes, forming a distributed computing power network. Tasked with both packet transmission and data processing, it requires joint optimization of communications and computing. Considering the diverse requirements of applications, we develop a dynamic control policy of routing to determine both paths and computing nodes in a distributed computing power network. Different from traditional routing protocols, additional metrics related to computing are taken into consideration in the proposed policy. Based on the multi-attribute decision theory and the fuzzy logic theory, we propose two routing selection algorithms, the Fuzzy Logic-Based Routing (FLBR) algorithm and the low-complexity Pairwise Multi-Attribute Decision-Making (lPMADM) algorithm. Simulation results show that the proposed policy could achieve better performance in average processing delay, user satisfaction, and load balancing compared with existing works.