預算法全IP核心網路品質管理中可彌補預測誤差的資源配置方法


Forecasting Error Tolerable Resource Allocation in Budget-Based QoS Management for All-IP Core Networks


陳逸民

通訊與資訊科技的大幅進步,電信自由化帶來的激烈競爭,以及網際網路的蓬勃發展,刺激大量多媒體網路資訊的流通,為了因應此種趨勢,網路提供者已趨向合併數據及電信網路朝單一的All-IP網路方向發展。為了保證時效性服務在All-IP網路上的品質,網路服務品質(QoS)已成為All-IP網路的主要研究議題。不同的網路應用各有不同的特性與需求;對於那些比較不注重傳輸延遲時間的應用,增加網路頻寬或許就已足夠應付需求,但是對於那些具有互動特性(interactive)、重視傳輸延遲時間的應用,像VoIP,除了增加網路頻寬外,All-IP網路必須提供服務品質保證才能獲得網路營運者的支持。本研究團隊設計一個管理架構,在此架構上提供完整的End-to-End QoS保證,以符合All-IP網路上各種不同服務需求。此架構下,核心網路的資源配置是由Bandwidth Broker (BB)統籌分配整個網域的資源,資源配置採以批發零售的方式,每個Ingress Router根據需求預測向BB預先批購資源,BB再依此配置資源給各個Ingress Router。為了彌補預測誤差所造成的資源浪費,本研究提出了數種資源配置的方式試圖提升網路資源的使用率,其中中央保留資源法以中央統籌的方式,即時的配置事先保留的資源給有需要的Ingress Router;超額分配法則以類似航空公司訂位的方式,大膽地超額配置資源給各個Ingress Router試圖增加資源使用率。本論文利用簡單的模擬比較兩種資源配置法於彌補預測誤差上的效能,實驗結果顯示當預測誤差小時,使用中央保留資源法保留小比例資源統籌較為適合,預測誤差大時,使用超額分配法超額配置大比例資源則較恰當。

In response to the great progress of communications and computer technologies, aggressive deployment of broadband fiber optical network, advance of Internet technology, and the global standardization of IP technology, the telecommunication industry is moving toward a converged network, which uses a single global IP based packet-switching network to carry all types of network services. Diverse types of services demand diverse QoS requirements making it a great challenge to support potential services with guaranteed QoS on All-IP networks. Our research group proposes a Budget-Based QoS (BBQ) management architecture to facilitate network operators of diversified networks. With BBQ management architecture, network operators can adjust their network architectures and management polities to support as many services as possible with end-to-end QoS guarantee. In this thesis, basing on BBQ QoS system, we propose resource pre-planning mechanism to management core network. According to demand forecast from historical data and considering pre-planning cost, pre-planning mechanism will find optimal policy to reduce management cost. In order to compensate the potential resource waste due to forecasting error, several resource allocation approach are proposed. Central Pool approach reserves resource in central pool and allocates it to those Ingress Routers who need. Overbook approach is similar to overbooking in airline booking system. It over-commits resource to Ingress Routers to improve resource utilization. In this thesis, we simulate the two resource allocation approaches and evaluate the forecasting error tolerating performance through experiments under different circumstances. We suggest operators choose Central Pool approach with less reservation when forecast error is low and choose Overbook approach with more overbook when forecast error is high.