多媒體高速網路之服務品質保證式智慧型訊務控制機制

Abstract

為了支援多媒體服務之叢集性傳輸(bursty-transmission) 和異質性服務品質(quality of services, QoS) 之要求，我們需要一套精確設計的訊務控制(traffic control)機制，藉以在滿足連線頻寬與服務品質要求的狀況下，進一步有效地提升系統資源的使用效率。現有文獻已指出，多媒體服務其多樣化且多變的訊務特性、以及各式各樣的傳輸與服務品質上的需求，已經使得整體網路的行為更加複雜，因此有必要應用智慧型技術(intelligent techniques) 來解決多媒體高速網路環境中的訊務控制課題。在本論文中，我們探討在ATM和IP這兩種多媒體高速網路環境下，應用類神經/乏晰智慧型技術之訊務控制機制，並著重在「連線允諾控制 (connection admission control, CAC)」與「訊務監控調節(traffic policing)」這兩個主要的訊務控制功能。

我們首先探討在ATM網路中，採用「時域(time-domain)」訊務參數與類神經乏晰技術來進行連線允諾控制決策的「類神經乏晰連線允諾控制(neural fuzzy connection admission control, NFCAC)」方法。該允諾控制方法由於採用了類神經乏晰控制器做為控制決策的核心，因此也可以視為是一種整合性的技術：結合了乏晰邏輯系統的高階語意控制功能，以及類神經網路的自我學習能力。透過挑選適當的輸入信號（包含時域訊務參數與部分系統性能量測統計值）和設計較佳的控制法則，該允諾控制方法的類神經乏晰控制器即可以從中習得既有的連線允諾控制的專家知識，並提供一套快速、精確而有效的計算程序來實現足夠強健(robust) 的連線允諾控制功能。模擬結果顯示，與傳統的幾種（同樣採用時域訊務參數的）連線允諾控制機制相較起來，我們在此所提出的類神經乏晰連線允諾控制方法可以在滿足服務品質保證的基本條件下，達到最好的系統資源使用率；同時，若再與傳統方法中具有類神經網路學習功能的方法比較起來，此類神經乏晰連線允諾控制方法也有較快的學習收斂速度。

接著，在前述採用時域訊務參數的連線允諾控制方法之外，我們還另外探討採用「頻域 (frequency-domain)」訊務參數與類神經網路技術來進行連線允諾控制決策的「功率頻譜基礎之類神經網路連線允諾控制(power-spectrum-based neural-net connection admission control, PNCAC)」方法。該允諾控制方法採用類神經網路控制器作為控制決策的核心，並以呼叫連線訊務源和既有連線訊務源的「功率頻譜密度(power spectral density, PSD) 參數」作為該控制器的（部分）輸入信號來進行連線允諾的決策控制。其理論基礎主要源自於，已知一個訊務源的功率頻譜密度函數(PSD function) 包含該訊務源的（時域）自我相關與叢集特性，並且已經有研究文獻證實，功率頻譜密度函數的確可以完全掌握並描述一個訊務源在一個佇列系統(queueing system) 的行為表現特性，因此其特徵參數（也就是前述簡稱的「功率頻譜密度參數」）自然也就可以視為是該訊務源的一種訊務參數，並且可以對應到其一定的佇列行為特性。此研究發現，開啟了我們以訊務源的頻域訊務參數，亦即「功率頻譜密度參數」，來進行連線允諾控制的初始構想和概念。隨後，透過我們所提出的一套功率頻譜密度函數合成演算法，可以很快速地由兩個訊務源各自的功率頻譜密度參數，求得其合成訊務源的功率頻譜密度參數（的合理近似值），如此也使得採用「功率頻譜密度參數」來進行連線允諾控制成為實際可行且適合的方案。模擬結果顯示，我們所設計並提出採用「功率頻譜密度參數」的類神經網路連線允諾控制方法，可以在變動的網路訊務特性的環境下，達到相當穩定而強健的控制效能。

另外，我們在連線允諾控制機制的研究外，也對於和連線允諾機制息息相關且為其必備輔助功能的訊務監控調節機制進行相關的研究。我們首先針對ATM網路定義的訊務監控調節機制，也就是所謂的使用參數控制(usage parameter control, UPC) 功能，提出兩種智慧型使用參數控制器，分別是「乏晰使用參數控制器」以及「類神經乏晰使用參數控制器」。「乏晰使用參數控制器」是在傳統ATM標準所建議並用來實現使用參數控制功能的「漏水桶方法(leaky bucket algorithm)」上，引進一個「乏晰水增量控制器(fuzzy increment controller, FIC)」；同理，「類神經乏晰使用參數控制器」即是在傳統漏水桶方法上增加了一個「類神經乏晰水增量控制器(neural fuzzy increment controller, NFIC)」。這兩個智慧型控制器皆是選用相同的兩個系統量測統計值，即受監控訊務源之長期平均封包速率和短期平均封包速率，來做為其輸入語意變數，並據此對受監控訊務源做出適應性的動態水增量調整決策。模擬結果顯示，我們所提出的兩種智慧型使用參數控制器，皆可比傳統的漏水桶方法具有較高的違法封包檢出正確率、較短的訊務違法反應時間以及較快的違法封包檢出速率；對於合法連線於用戶終端設備輸出處的訊務塑型器(traffic shaper, TS) 所造成的佇列延遲上，也有比較小的數值表現。而在兩智慧型使用參數控制器方法彼此的比較方面，類神經乏晰使用參數控制器也在上述幾個方面的表現上比乏晰的方法有稍佳的效能，特別是在訊務違法反應時間及違法封包檢出速率上有較明顯的差異。

最後，我們繼續針對IP網路環境上的訊務監控調節機制提出最佳化設計。而IP網路的訊務監控調節機制，主要是以定義在差異化服務(differentiated services, DiffServ) 模型中的「訊務調節器(traffic conditioner)」所執行的訊務調節功能為主，因此我們便針對訊務調節器中的核心關鍵性組件－訊務封包標記器(traffic maker)，以網際網路標準組織IETF所建議的「雙速率三顏色封包標記器(two-rate-three-color-marker, TRTCM)」方法為基礎，提出一「效能增強型訊務封包標記器(enhanced traffic marker)」方法，在既有（消極）的監控性管制調節功能之外，再增加公平標記與積極性封包合法位階促升(promotion) 功能。模擬結果顯示，我們所設計的「效能增強型訊務封包標記器」的確可以在一合成訊務流中，對其各組成分流的封包合法位階標記做到精確檢出及公平標記的目的。同時，其不僅可以在系統資源足夠的時候，把過去曾經因為「局部(local)」網路壅塞或較嚴格的訊務合約(traffic contract) 導致合法位階被調降的封包再度提升至其原有的合法位階標記，還能夠進一步積極地盡可能提升其他封包的合法位階以享有較佳品質的封包處理動作，如此可在不違反訊務合約的狀況下，達到充分利用系統資源並增進受監控訊務連線的上層應用程式服務品質的目的。因此模擬結果也顯示，我們所設計的「效能增強型訊務封包標記器」比起傳統單純的「雙速率三顏色封包標記器」方法，在各合法位階的訊務上皆有較高（但仍合於訊務合約）的封包輸出速率(throughput)。

To support bursty-transmission and heterogeneous quality of services (QoS) requirements for multimedia services, a suite of well-designed sophisticated traffic control scheme is required to effectively enhance the system utilization. The non-stationarity of work-loads, together with heterogeneous traffic characteristics and QoS constraints of multimedia services, indeed constitute the necessity for applying intelligent techniques in multimedia high-speed networks. In this dissertation, the traffic control functions involving the connection admission control (CAC) and the traffic policing for multimedia high-speed networks by neural/fuzzy intelligent techniques are studied. Both ATM and IP networks which can be utilized to construct the multimedia high-speed networks are considered in this dissertation.

Firstly, a neural fuzzy connection admission control (NFCAC) scheme which based on the time-domain traffic parameters and provides QoS guarantees for ATM networks is proposed. The NFCAC scheme is an integrated method that combines the linguistic control capabilities of a fuzzy logic controller and the learning abilities of a neural network. With properly choosing input variables which involve the measured statistics of network performances, and well designing the rule structure for the NFCAC scheme, it can not only provide a robust framework to mimic experts’ knowledge embodied in existing connection admission control techniques but can also construct precise and efficient computational algorithms for connection admission control. Simulation results show that, compared with conventional CAC schemes, the proposed NFCAC can achieve superior system utilization, high learning speed, and simple design procedure, while keeping the QoS contract.

And then, as contrast to the CAC scheme based on the time-domain traffic parameters discussed above, a power-spectrum-based neural-net connection admission control (PNCAC) scheme is proposed for also the multimedia high-speed ATM networks. It employs a neural network controller to handle the CAC function according to the frequency-domain power spectral density (PSD) parameters of the traffic sources. Since the PSD function of an input traffic contains the correlation and burstiness properties of the traffic, and it has been proven capable to characterize the queueing performances of the input traffic, the PSD parameters describing the PSD function can well correspond to the queueing performances also. With a composition algorithm to easily obtain the three PSD parameters of an aggregate traffic, it is suitable to adopting PSD parameters for CAC accordingly. Simulation results show that, after well training the neural network, an optimal CAC decision hyperplane based on the input variables is constructed to provide an efficient and robust admission control under dynamic network environments, while the QoS requirements are strictly assured.

After that, in addition to the studies about CAC, a traffic policing mechanism is necessary to ensure that all established connections conform to their respective traffic contracts, so that the CAC can perform correctly. Therefore, two intelligent usage parameter controllers are first proposed to implement the traffic policing function, usage parameter control (UPC), for multimedia transmissions in ATM networks. One is the fuzzy usage parameter controller realized by the fuzzy leaky bucket algorithm, in which a fuzzy increment controller (FIC) is incorporated with the conventional leaky bucket algorithm; the other is the neural fuzzy usage parameter controller base on the neural fuzzy leaky bucket algorithm, where a neural fuzzy increment controller (NFIC) is added to the conventional leaky bucket algorithm. Both of FIC and NFIC properly choose the measured long-term and short-term mean cell rates, as input variables to adaptively determine the optimal increment value with respect to the traffic dynamics. Simulation results show that both intelligent leaky bucket algorithms have significantly outperformed the conventional leaky bucket algorithm, by higher selectivity and shorter responding time when taking control actions against a non-conforming connection, while reducing the queueing delay experienced by a conforming connection. Also, the neural fuzzy leaky bucket algorithm outperforms the fuzzy one in all aspects especially the responsiveness.

Finally, since the UPC is the traffic policing function defined in ATM networks, the traffic conditioner defined in the differentiated services (DiffServ) model is employed to handle the traffic policing function, namely the traffic conditioning, for the IP networks. An enhanced traffic marker (ETM) based on the Two-Rate-Three-Color-Marker (TRTCM) scheme is then proposed for the traffic conditioner to perform traffic policing by properly determining the conforming level of the incoming packet and making a corresponding color notation on the packet. The proposed ETM scheme introduces the features of aggressive promotion and fair share marking, and incorporates them into the existing traffic policing function. Simulation results show that the ETM scheme can fairly allocates the color notations among connections within an aggregate one. It also enhances the throughput of each conforming level for the aggregate connection to achieve as high rate as possible by not only restore the conforming levels of the previously demoted packets, but also aggressively promote the packets to higher conforming levels, so that the end-to-end QoS of the applications would be substantially improved while the traffic contract is still be respected. It can be concluded that the ETM scheme outperform the conventional TRTCM scheme in both aspects of marking fairness and traffic throughput of each conforming level under congested and under-loaded networks.