TWI536774B - Network Management Method Based on Predicting Circuit Carrying Capacity and Computer Program Product - Google Patents

Description

基於預測電路承載容量之網路管理方法及其電腦程式產品 Network management method based on prediction circuit carrying capacity and computer program product thereof

本發明係一種網路管理方法，尤指一種基於預測電路承載容量之網路管理方法。 The invention relates to a network management method, in particular to a network management method based on a prediction circuit carrying capacity.

電信商為讓設置之電信路徑可滿足用戶申租時之服務，在現行之電信路徑網路管理上，常需定期監控各個電路之訊務負荷程度，並適時的調度訊務量至適切之電路上，以讓各個不同服務速率(20M、100M等)之電路可發揮最佳之效能。 In order to ensure that the set telecommunications path can satisfy the user's service when renting, the telecommunications provider often needs to regularly monitor the traffic load of each circuit in the current telecommunication path network management, and timely dispatch the traffic volume to the appropriate circuit. In order to achieve the best performance of the circuit of different service rates (20M, 100M, etc.).

惟現行之管理系統僅能依據各個電路之訊務負荷程序進行監控，並無法針對電路內之訊務分佈進行更為準確之模型來進行評估分析。因此目前網管人員多憑藉過往經驗進行調度，而此種人工作業方式使得網管人員在調度訊務至新的電路之前，並無法確切的得知此次調度是否會對收納移撥訊務之電路其服務狀態有所影響。 However, the current management system can only monitor according to the traffic load procedures of each circuit, and cannot perform a more accurate model for the traffic distribution in the circuit for evaluation and analysis. Therefore, at present, network administrators rely on their past experience for scheduling. This kind of manual operation method makes it impossible for network administrators to know whether the dispatch will be used for the circuit that accommodates the transfer of traffic before dispatching the traffic to the new circuit. Service status has an impact.

綜上所述，如何提供一種可科學化評估電路上之訊務模型以進行後續監控以及訊務調度之技術內容乃本領域亟需解決之技術問題。 In summary, how to provide a technical model for scientifically evaluating the signal model on the circuit for subsequent monitoring and traffic scheduling is a technical problem that needs to be solved in the field.

為解決前揭之技術問題，本發明之目的係藉由預測電路負載容量以進行電信路徑之監控以及調度。 In order to solve the above-mentioned technical problems, the object of the present invention is to perform monitoring and scheduling of telecommunication paths by predicting circuit load capacity.

為達上述目的，本發明提出一種基於預測電路承載容量之網 路管理方法，應用於一電腦裝置，該方法包含下列步驟：首先，提取至少一速率類別電路，以對各速率類別電路建構一電路樣本。接著，依據各電路樣本之訊務指標，以提供各電路樣本之訊務特徵值。又依據各訊務特徵值以提供一電路壅塞機率模型。最後，依據各速率類別電路之上網路由以及各電路壅塞機率模型以提供符合一電信服務門檻之至少一速率類別電路。 In order to achieve the above object, the present invention proposes a network based on prediction circuit carrying capacity The road management method is applied to a computer device, and the method comprises the following steps: First, at least one rate class circuit is extracted to construct a circuit sample for each rate class circuit. Then, according to the traffic indicators of each circuit sample, the traffic characteristic values of each circuit sample are provided. Further, according to each traffic characteristic value, a circuit congestion probability model is provided. Finally, the network routing of each rate category circuit and the circuit congestion probability model are provided to provide at least one rate class circuit that meets a telecommunications service threshold.

為達上述目的，本發明提出一種基於預測電路承載容量之網路管理電腦程式產品，當電腦裝置載入並執行時，可完成前述網路管理方法所述之步驟。 To achieve the above object, the present invention provides a network management computer program product based on a predicted circuit carrying capacity, which can complete the steps described in the foregoing network management method when the computer device is loaded and executed.

綜上所述，本發明之基於預測電路承載容量之網路管理方法及其電腦程式產品透過機率模型分析各個電路之承載容量，並據此挑選出適切之電路來重配置訊務作業。 In summary, the network management method based on the predicted circuit carrying capacity and the computer program product of the present invention analyze the carrying capacity of each circuit through a probability model, and accordingly select a suitable circuit to reconfigure the traffic operation.

S11~S14‧‧‧步驟 S11~S14‧‧‧Steps

S111~S113‧‧‧步驟 S111~S113‧‧‧Steps

S21~S26‧‧‧步驟 S21~S26‧‧‧Steps

第1圖係為本發明之電路壅塞機率模型建構流程圖。 The first figure is a flow chart for constructing the circuit congestion probability model of the present invention.

第2圖係為本發明之電路查測方法之流程圖。 Figure 2 is a flow chart of the circuit inspection method of the present invention.

第3A~4C圖係為本發明之一實施例示意圖。 3A-4C are schematic views of an embodiment of the present invention.

以下將描述具體之實施例以說明本發明之實施態樣，惟其並非用以限制本發明所欲保護之範疇。 The specific embodiments are described below to illustrate the embodiments of the invention, but are not intended to limit the scope of the invention.

請參閱第1圖，其為本發明之電路壅塞機率模型建構流程圖。其步驟說明如下： Please refer to FIG. 1 , which is a flowchart of constructing a circuit congestion probability model of the present invention. The steps are as follows:

S11：收集各個速率類別電路之訊務，各個速率類別電路代表可提供不同速率之電信路徑，例如100M電路、20M電路等。接著執行S12或定期執行S111。 S11: Collecting traffic of each rate category circuit, each rate category circuit represents a telecommunication path that can provide different rates, such as a 100M circuit, a 20M circuit, and the like. Then S12 is executed or S111 is periodically executed.

S111：追蹤訊務收集成功比率(連續日收集成功數/設定數)，接著執行S112。 S111: Tracking the traffic collection success rate (continuous day collection success number/set number), and then executing S112.

S112：比對訊務收集門檻值，接著執行S113。 S112: Compare the traffic collection threshold, and then execute S113.

S113：判斷是否符合信賴標準，若是則執行S13；若否則執行S111。 S113: Determine whether the trust criterion is met, if yes, execute S13; if otherwise, execute S111.

S12：取得母體樣本取樣數。前述母體樣本之抽樣設計係以每一母體區間(各個速率類別之電路)之信心水準95%，即訊務收集比率達95%，且在三個標準差內為依據。接著執行S13。 S12: Obtain the sample number of the parent sample. The sampling design of the aforementioned maternal sample is 95% confidence level for each maternal interval (circuit of each rate category), that is, the traffic collection ratio is 95%, and is based on three standard deviations. Then S13 is executed.

S13：對各個速率類別電路進行母體抽樣，以取得訊務樣本資料，接著執行S14。 S13: Perform parent sampling on each rate category circuit to obtain traffic sample data, and then perform S14.

S14：計算各個速率類別電路之申租速率忙時承載訊務之特徵值，接著執行S15。 S14: Calculate the feature value of the busy rate carrying service of the rate rate circuit of each rate category circuit, and then execute S15.

S15：建立電路壅塞機率模型，本案係以中央極限定理為基礎(亦即，各速率類別電路之用戶其使用行為各自獨立)，並分層抽樣分析各速率類別電路之訊務，計算個別訊務指標(如平均數、變異數)，利用每5分鐘訊務資料，綜合整理為日訊務、月訊務中長期訊務資料等，以產生各類速率電路的總指標值、總訊務量等各網路訊務指標(KPI)。 S15: Establishing a circuit congestion probability model, the case is based on the central limit theorem (that is, users of each rate class circuit are independent in their use behavior), and stratified sampling analysis of the traffic of each rate category circuit, calculating individual traffic Indicators (such as averages, variances), using 5 minutes of traffic information, comprehensively organized into daily traffic, monthly traffic medium and long-term traffic data, etc., to generate the total index value and total traffic volume of various rate circuits. And other network traffic indicators (KPIs).

請參閱第2圖，其為電路查測方法之流程圖。各步驟說明如下： Please refer to FIG. 2, which is a flow chart of the circuit detection method. The steps are explained as follows:

S21：取得電路之上網全路由資訊，接著執行S22。 S21: Obtain the full routing information of the circuit on the Internet, and then execute S22.

S22：依據電路壅塞機率模型來計算單一速率類別電路收容各類申租速率之總承載訊務之特徵值，例如訊務指標：各速率類別電路短中長期(日訊務、月訊務中長期)訊務量之平均值、變異數，接著執行S23。 S22: Calculate the characteristic value of the total bearer traffic of the single rate category circuit to accommodate various subscription rates according to the circuit congestion probability model, for example, the traffic indicator: each rate category circuit is short, medium and long term (day traffic, monthly traffic medium and long term) The average value of the traffic, the number of variations, and then S23.

S23：透過電路壅塞機率模型將此電路各特徵值導入機率密度函式以進行機率模型最佳配適以計算電路壅塞機率，並估算各類型電路之承載容量機率模型，選擇的執行S24或S25。前述之機率密度函式Φ(z)(常態分佈之機率密度函式)如下所示： S23: Introduce the characteristic values of the circuit into the probability density function through the circuit congestion probability model to optimize the probability model to calculate the circuit congestion probability, and estimate the bearing capacity probability model of each type of circuit, and select S24 or S25. The aforementioned probability density function Φ( z ) (the probability density function of the normal distribution) is as follows:

σ：標準差 σ: standard deviation

S24~26：網管人員可利用此承載容量機率模型在電路供裝時判斷用戶可由哪條電路進行供裝(為了不產生訊務壅塞，而選擇低承載容量機率的電路)。同時，網路人員也可藉由此承載容量機率模型，輸入欲進行供裝的用戶數，即時模擬試算此電路供裝後的壅塞機率，作為電路的頻寬適切性評估參考依據。 S24~26: The network management personnel can use this load capacity probability model to determine which circuit the user can supply when the circuit is installed (in order not to generate traffic congestion, the circuit with low load capacity probability is selected). At the same time, the network personnel can also input the capacity probability model, input the number of users to be installed, and simulate the probability of the plugging after the circuit is installed, as a reference for evaluating the bandwidth suitability of the circuit.

為因應瞬息萬變的網路趨勢變化，需建立確保此機率模型正確性之機制下則需透過定期確認訊務資料收集成效、追蹤訊務之收集成功比率(連續日收集成功數/設定數)、比對訊務收集門檻值，以確保母體樣本之有效性及獲得信賴標準之統計。而當有效取樣數不足時，即再加入新樣本或追蹤修正原有樣本不足問題，來提供有效之樣本比率，確保後續統計 檢定及分析母體之正確性。 In order to respond to the ever-changing trend of the network, it is necessary to establish a mechanism to ensure the correctness of the probability model. It is necessary to regularly confirm the effectiveness of the collection of traffic data, and to track the success rate of the collection of traffic (continuous daily collection success/set number), ratio Collect statistics on the threshold of the traffic to ensure the validity of the maternal sample and the statistics of the trust criteria. When the number of valid samples is insufficient, then add new samples or track the problem of correcting the original samples to provide an effective sample ratio to ensure follow-up statistics. Verify and analyze the correctness of the parent.

前述之承載容量機率模型配適可適用於各網路階層之各類電路，但運用在骨幹網路將可獲得最大成效，使得網管人員可透過管控骨幹網路之狀態，以限制每一條路由的用戶供裝數，而無須再多耗費一條電路之建置成本，據以提供穩健的網路環境。 The above-mentioned bearer capacity probability model can be applied to various types of circuits at various network levels, but the maximum efficiency can be obtained by using the backbone network, so that the network administrator can control the status of the backbone network to limit each route. Users can install a number without having to spend more than one circuit to build a stable network environment.

請共同參閱第1圖~第4圖，其為本發明之一實施例，第1圖以及第2圖所述之流程更可藉由電腦程式產品實現之。於該實施例中，當網路人員得知某電路發生壅塞告警(頻寬使用率>85%)而需進行網路資源的調配，在不考慮新建電路下，網管人員需將此電路之部分用戶移撥其他電路進行服務(如第3A~3C圖所示；*為訊務重負荷電路)。 Please refer to FIG. 1 to FIG. 4 together, which is an embodiment of the present invention, and the processes described in FIG. 1 and FIG. 2 can be realized by a computer program product. In this embodiment, when the network personnel knows that a circuit has a congestion alarm (bandwidth usage > 85%) and needs to allocate network resources, the network administrator needs to be part of the circuit without considering the new circuit. The user transfers other circuits for service (as shown in Figures 3A-3C; * is the traffic heavy-duty circuit).

請參閱第3A~3C圖，透過操作介面得知共有23路電路可承接欲改接/移撥之用戶訊務。為避免移撥用戶之訊務造成新承接電路之訊務壅塞，接著透過篩選去除其電路頻寬使用率大於特定門檻值(例如，頻寬使用率大於70%)之電路(虛線方框部分所示之電路)：TPE4-KLAL-GE-125(頻寬使用率：70.2%)、TPE4-KLAL-GE-89(頻寬使用率：72.5%)、TPE4-KLAL-GE-121(頻寬使用率：78.7%)，而選出20條頻寬使用率小於70%之電路，網管人員可自20路電路中進行改接。接著，再利用承載容量機率模型推估，自23路電路中先行自動過濾掉9條訊務收集比率未達信賴係數(例如訊務收集比率達95%，且在三個標準差內為依據)的電路，而挑選出8條壅塞機率小於0.5之電路可進行改接(如第4A~4C圖所示)。 Please refer to the figure 3A~3C. Through the operation interface, it is known that a total of 23 circuits can take over the user traffic to be changed/transferred. In order to avoid the traffic jam of the new receiving circuit caused by the transfer of the user's traffic, the circuit whose bandwidth usage is greater than a specific threshold (for example, the bandwidth usage is greater than 70%) is removed by screening (the dotted square box portion) Circuit shown: TPE4-KLAL-GE-125 (bandwidth usage: 70.2%), TPE4-KLAL-GE-89 (bandwidth usage: 72.5%), TPE4-KLAL-GE-121 (bandwidth use) Rate: 78.7%), and select 20 circuits with bandwidth usage less than 70%, network administrators can change from 20 circuits. Then, using the load capacity probability model to estimate, the 9 traffic collection ratios are automatically filtered out of the 23-way circuit, and the trust factor is not reached (for example, the traffic collection ratio is 95%, and is based on three standard deviations). The circuit is selected, and 8 circuits with a probability of less than 0.5 are selected for reconnection (as shown in Figures 4A-4C).

進一步說明之，前述之承載容量機率模型先行過濾出的9路不適宜電路中，其中有3路電路係為近日內其訊務狀態不穩定之電路，此3 條電路雖未達到電路重荷門檻，但因傳輸品質不穩則判定為不適合改接電路對象。並又在壅塞機率高於0.5的名單中濾除出5條不適宜電路。雖在第3圖中，此8路電路皆在備選名單中，其中6條電路頻寬使用率更在60%以下，尤其，第3圖之備選電路TPE4-KLAL-GE-116頻寬使用率數值僅48.8%為最適宜改接之電路，但此電路卻是近日訊務較不穩定之電路，因此在承載容量機率模型的推估下，此電路判斷為不適宜改接。較為適宜改接的電路為TPE4-KLAL-GE-84，此電路未在重荷預警名單。 Further, among the nine unsuitable circuits that are first filtered out by the above-mentioned bearer capacity probability model, three of the circuits are circuits whose signal state is unstable in the past day. Although the circuit does not reach the threshold of the circuit, it is determined that it is not suitable for the circuit object because the transmission quality is unstable. And 5 unsuitable circuits are filtered out in the list of clogging probability higher than 0.5. Although in Figure 3, the eight circuits are in the alternate list, and the six circuit bandwidth usage is more than 60%. In particular, the alternative circuit TPE4-KLAL-GE-116 bandwidth in Figure 3 The usage rate is only 48.8%, which is the most suitable circuit for reconnection. However, this circuit is a circuit with relatively unstable traffic in recent days. Therefore, under the estimation of the probability model of the carrying capacity, this circuit judges that it is not suitable for reconnection. The circuit that is more suitable for reconnection is TPE4-KLAL-GE-84. This circuit is not in the heavy load warning list.

本案不僅透過電路壅塞機率模型先行過濾品質不穩的電路，並依據各電路之所註記之訊務狀態來濾除傳輸品質不穩定電路，除此之外，網管人員為求審慎下還可再從8條建議電路名單中模擬估算，推估各速率用戶改接後，對各電路所造成的可負荷程度，從中挑選最適宜之電路，作為電路的頻寬適切性評估參考依據。據此，本發明之方法及其電腦程式產品得以提高電路頻寬使用成效，強化網路服務品質，以及提供更強健之網路服務環境。 This case not only filters the unstable quality circuit through the circuit congestion probability model, but also filters out the transmission quality unstable circuit according to the signal state of each circuit's annotation. In addition, the network management personnel can also carefully In the eight recommended circuit lists, the simulation estimation is carried out to estimate the loadability of each circuit after the user is changed. The most suitable circuit is selected as the reference for the bandwidth suitability evaluation of the circuit. Accordingly, the method of the present invention and its computer program product can improve the use of circuit bandwidth, enhance the quality of network services, and provide a more robust network service environment.

上列詳細說明係針對本發明之一可行實施例之具體說明，惟該實施例並非用以限制本發明之專利範圍，凡未脫離本發明技藝精神所為之等效實施或變更，均應包含於本案之專利範圍中。 The detailed description of the preferred embodiments of the present invention is intended to be limited to the scope of the invention, and is not intended to limit the scope of the invention. The patent scope of this case.

S11~S14‧‧‧步驟 S11~S14‧‧‧Steps

S111~S113‧‧‧步驟 S111~S113‧‧‧Steps

Claims (10)

一種基於預測電路承載容量之網路管理方法，應用於一電腦裝置，包含下列步驟：提取至少一速率類別電路，以對各該速率類別電路建構一電路樣本；依據各該電路樣本之訊務指標，以提供各該電路樣本之訊務特徵值；依據各該訊務特徵值以提供一電路壅塞機率模型；以及依據各該速率類別電路之上網路由以及各該電路壅塞機率模型以提供符合一電信服務門檻之該至少一速率類別電路，其中該電信服務門檻係電路頻寬使用率或壅塞機率。 A network management method based on predicting circuit bearer capacity is applied to a computer device, comprising the steps of: extracting at least one rate class circuit to construct a circuit sample for each of the rate class circuits; and according to each of the circuit sample signal indicators Providing a traffic characteristic value of each of the circuit samples; providing a circuit congestion probability model according to each of the traffic characteristic values; and providing an online communication route according to each of the rate category circuits and each of the circuit congestion probability models to provide a conforming to a telecommunications The at least one rate class circuit of the service threshold, wherein the telecommunication service threshold is a circuit bandwidth usage rate or a congestion probability. 如請求項1所述之方法，其中各該電路樣本之信心水準係達95%以上。 The method of claim 1, wherein the confidence level of each of the circuit samples is greater than 95%. 如請求項1所述之方法，更依據各該速率類別電路之申租速率忙時承載訊務之該訊務特徵值以提供該電路壅塞機率模型。 The method of claim 1, further, according to the rate of interest of each rate category circuit, carrying the traffic characteristic value of the traffic to provide the circuit congestion probability model. 如請求項1所述之方法，其中更依據一訊務收集門檻值提取該至少一速率類別電路。 The method of claim 1, wherein the at least one rate class circuit is further extracted according to a traffic collection threshold. 如請求項4所述之方法，其中該訊務收集門檻值係一頻寬使用率。 The method of claim 4, wherein the traffic collection threshold is a bandwidth usage rate. 如請求項1所述之方法，其中該訊務指標係包含訊務平均數或訊務變異數。 The method of claim 1, wherein the traffic indicator comprises a traffic average or a traffic variation. 如請求項1所述之方法，更依據各該速率類別電路之訊務狀態以提供符合該電信服務門檻之該至少一速率類別電路。 The method of claim 1 further relies on the traffic status of each of the rate class circuits to provide the at least one rate class circuit that meets the telecommunication service threshold. 如請求項7所述之方法，其中該訊務狀態更包含該速率類別電路之訊務負荷程度。 The method of claim 7, wherein the traffic state further comprises a traffic load level of the rate class circuit. 如請求項7所述之方法，其中該訊務狀態更包含該速率類別電路之預警訊 息。 The method of claim 7, wherein the traffic status further includes an early warning message of the rate class circuit. interest. 一種基於預測電路承載容量之網路管理電腦程式產品，當電腦裝置載入並執行時，可完成如請求項1至9任一項所述之方法。 A network management computer program product based on a predicted circuit carrying capacity, which can be completed as described in any one of claims 1 to 9 when the computer device is loaded and executed.