於5G雲端接取網路中以馬可夫決策過程達成最佳解之允入控制策略

A Markov Decision Process Based Approach to Achieving Optimal Admission Control for 5G Cloud Radio Networks

郭士庭(Shih-Ting Kuo)

指導教授 ： 林永松

國立臺灣大學/管理學院/資訊管理學研究所/碩士(2018年)

https://doi.org/10.6342/NTU201803101

摘要

在第五代行動通訊系統的環境下，即時的資源配置及管理方法對於網路運營商的重要性逐漸增加，5G系統架構將以雲端無線電接取網路為核心，其將基地台拆分為基頻單元及無線寬頻頭端，而其中負責基頻運算單元將以虛擬化技術將其集中至雲端無線電接取網路之伺服器群管理，本研究透過有效率的管理機制，包括基頻單元的移轉與伺服器開關機達成伺服器群利用率的提升及省電之功效，著重在於5G環境背景下各種類型任務的允入控制，可針對不同的任務類型及在不同的系統狀態下，同時考量系統的運算及操作成本及包含了伺服器電源能耗成本及基頻單元移轉成本，使用馬可夫決策過程尋求最佳的允入決策；綜合允入控制、內部資源配置及基頻單元操作移轉等成本因素，目標以找到長期時間下的系統淨獲利率最佳化。此研究模擬實驗了多個不同情境，包含不同的任務到達率及服務率、不同數量的伺服器及任務類型、不同的決策組合所能獲得的淨獲利和系統的作業成本相互影響決策的選擇至最後淨獲利的變化。

關鍵字

雲端無線電接取網路 (C-RAN) ； 允入控制 (Admission Control) ； 馬可夫決策過程 (Markov Decision Process) ； 第五代行動通訊 (5G) ； 淨獲利率 ； 最佳化

並列摘要

In fifth-generation (5G) radio access networks environment, resources allocation and management are more than more important for the network operator. The 5G system architecture have been proposed as a cloud architecture to provide a common connected resource pool for various applications and requirements. In this regard, that is a challenge to efficiently and effectively manage radio resources and allocate perspectives on the rapidly changing traffic load. Admission control mechanism is a key factor influencing the system performance with limited budget of the resource pool. Furthermore, the performance of system was also affected by several factors, such as rapidly increasing data traffic, power consumption of system, service reject penalty and operating cost of service. The problem is formulated as a mathematical programming problem, which was solved by the Markov decision process to determine a best strategy. The experimental results help operators to understand which type of tasks is to be admitted responding to the network state, to maximize net profit, and to achieve flexibility by leveraging cloud technology. In this research, we proposed several cases, including different situation, different cost of system operation, different number of types and number of servers, to experiment how the factors influence the net profit.

並列關鍵字

C-RAN ； Admission control ； Markov Decision Process ； 5G ； Net profit ； Optimization

參考文獻

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