Decentralized optimal control in shared resource pools of video service nodes in network convergence

Abstract

Network convergence is the major strategic decision to realize the leaping development of information industry, modern service industry and traditional industries. Business needs of large-scale video concurrent access and user-oriented provision of high-quality services will be the new challenges of application access system in the future network convergence. In the domain of video service network in network convergence, we focus on the problem of optimal resource allocation of RSPE (Real-time Service Provide Equipment) nodes in shared resource pools. In this paper, we propose a fully distributed optimal control solution, named RSPE-DOCS. RSPE-DOCS treats underlying physical servers as a shared resource pool, and RSPE nodes as resource consumers. RSPE-DOCS implements the information exchanging strategy and distributed optimization method among RSPE nodes, leading to a distributed optimal control framework. Experimental results indicate that RSPE-DOCS is able to ensure the convergence of dissemination process and find the optimal resource allocation, if the RSPE nodes are not changed substantially in resource management process.

Patent-Based Analysis of China’s Emergency Logistics Industry Convergence

“…How to allocate multi-task and multibusiness resources has become a key issue that needs attention. Song C and others put forward a fully distributed optimal control solution, RSPE-DOCS, to solve the problem of real-time service in the shared resource pool to improve the optimal resource allocation of equipment nodes, which realized the information exchange strategy and distributed optimization method between nodes and ensured that the optimal resource allocation scheme was found in the convergence process [25]. The future of industrial convergence is to realize the convergence of everything.…”