行動資訊服務環境的理想，是要提供一個無所不在的資訊環境，讓使用者可以在任何地方、任何時間，利用各種有線或無線的傳輸網路去存取可用資源。行動通訊與行動計算的飛越發展使得行動資訊服務的理想指日可待。而無線網路要支援一些即時多媒體通訊傳輸，服務品質便成為很重要的課題，頻寬計算更是其中最關鍵的議題。除了現有IEEE 802.11無法有效支援多跳接網路使之達到服務品質的保證外，也由於Ad Hoc網路移動性及流量多變性的特性，要在這樣的無線環境下支援服務品質便成為一個困難的挑戰。由於我們參考的論文皆在TDMA的環境下探討頻寬保證的問題，但是這在無線多跳接網路下十分複雜且受限制。因此我們針對此問題提出一個簡單的頻寬計算方法來估算網路現有頻寬，用於頻寬繞徑演算法上以支援無線網路服務品質。實驗結果顯示我們的方法比過去的頻寬計算方法更簡單、誤差少、適用於各種MAC層的通訊協定，也容易與現有頻寬繞徑演算法結合以執行允入控制機制。透過我們的方法，可以有效地支援無線多跳接網路服務品質。 / The idea of mobile computing service is to provide a ubiquitous information environment. However, the present mobile ad hoc networks still can’t support real-time transmission very effectively. In other words, the capability of supporting QoS guarantee has become a very important issue. IEEE 802.11 PCF adopts the polling scheme to provide time-bounded traffic services, which is not suitable in multi-hop networks. Moreover, due to mobility and traffic dynamics, the network resource management is more difficult. Thus, QoS support in such an environment is a challenge. Specifically, path bandwidth calculation is the first key element. All the bandwidth routing papers we referenced were using TDMA. However, they are restricted in TDMA systems and somehow complicated in path bandwidth calculation. We propose a simple path bandwidth calculation solution that can be used whatever MAC protocol is. It is also easy to implement call admission control and to combine with bandwidth routing algorithms. The simulation results illustrate that the statistical error rates of our path bandwidth calculation are within an acceptable range. By path bandwidth calculation, bandwidth routing algorithm is also developed to achieve the objective of supporting QoS in wireless multihop networks effectively.

光纖通訊產業將有望成為本世紀新興的高科技產業。其原因在於後PC數位資訊時代下，透過網際網路進行商務活動的數量激增，其頻寬之需求驟增以提供及時語音/數據及影像之服務;再者幾乎所有已開發及開發中的國家都積極投入新的網路建設中，以厚植其資訊國力。這種積極性又在各國開放電信市場一致行動下，令光通訊產業的未來發展倍受矚目，甚至已有人直呼為「光革命」。為了滿足整個新市場、新環境的需求，光通訊材料/原件與設備產品正在全球各國產/學/研通力合作下，被投入大量的研發經費，積極地發展中。另一方面，因網路產業泡沫化與世界經濟景氣衰退的影響，各國財政支出緊縮與投資市場對新科技產業投資的質疑與延滯，對新興科技產業影響甚鉅。進而影響到許多潛力無窮的新興企業資金需求計畫與投資業界對此類產業合理評價便相當重要，尤其值得財務及投資業界財務及投資業界深入探究，亦是本研究主要研究目的。 本研究依Aaker的分析架構，針對此一產業進行外在與內在分析，其外在分析為整個產業的環境分析、產業分析、競爭對手分析與顧客分析。由於光通訊產業涉及光通訊上下游廠商的價值活動，如上游骨幹業者光纖通訊設備商，與中游的光主動元件、光被動元件，及生產相關的光半導體業者，及接近下游用戶端的光服務業，故在這一部分，我們會採用策略矩陣觀點，進行產業的討論。經過本研究分析後發現資源整合策略與即時回應市場的核心技術與核心能力之關鍵性-以垂直分工模式，取代傳統式的垂直整合式水平分工。以網絡關係整合市場、研發、生產資源。 新興科技產業的評價本來就有其困難。因此對新興高科技產業投資前的評價與投資後管理決策，乃吸引了許多財務分析師紛紛尋找合宜的方法進行評價。於此，依本研究對投資人的建議是從現金流量的角度來評斷獲利能力，並考量資金的機會成本。對光通訊產業的建議是投資人的信心與青睞是需長期經營與信任，除公開而透明的財務資訊外，其經營管理與洞悉產業環境之發展趨勢及應變之能力，亦是關鍵之鑰。健全的財務後盾，以財務指標為管理依據。

近幾年無線寬頻網路崛起，寄望WiMAX可以取代最後一哩，雖然WiMAX有QoS的設計，但是對於Call Admission Control、Bandwidth Allocation、Scheduler並沒有實際定義，給予廠商彈性設計。本篇論文提出以機器學習的方式依據網路狀態動態配置頻寬，以符合實際頻寬需求。 由於BS在配置頻寬的時候並沒有SS佇列的訊息，使得BS無法配置適合的頻寬，達到較好的效能，尤其是有期限的rtPS封包最為明顯。在系統負載較高的環境下，容易導致封包遺失提升，吞吐量降低的情形發生。因此本研究提出了支持向量機的方式，收集大量Training Data，訓練成動態頻寬配置模組；以動態配置適合的頻寬給rtPS，使rtPS在負載高的環境下的封包遺失率降低，且延遲能夠維持一定水準。搭配適應性頻寬配置策略，在低負載的環境下可以保留少許頻寬給Non Real Time Traffic，在高負載環境下，先滿足Real Time Traffic為原則。模擬工具採用NS 2-2.29、長庚大學-資策會的WiMAX模組，以及台大林智仁老師開發的支持向量機函式庫libSVM。 / In recent years, the rise of wireless broadband access networks. Hope that WiMAX can solve the last mile problem. Although WiMAX has QoS design, but for call admission control, bandwidth allocation, scheduler are not defined in standard. In this paper, we proposed a machine learning approach dynamic bandwidth allocation based on network state. BS because of the bandwidth allocation at a time when there is no message of SS’s queue. Enables BS can not configure a more suitable bandwidth to achieve better performance. In particular, there is the deadline of rtPS packets. At the higher loading on the system environment, easily lead to packet loss raise, lower throughput situations happen. In this study, a support vector machine approach to collect a large number of training data. Training modules into a dynamic bandwidth allocation. We can dynamically allocate bandwidth to fit rtPS. Adaptive bandwidth allocation strategy, at the low loading environment can keep some bandwidth for non real time traffic. At a high loading environment must first meet the real time traffic. We use Network Simulator 2-2.29, CGU-III WiMAX module, libSVM library.

大型天然災害會癱瘓通訊系統，嚴重影響到救災效率，本論文旨在快速進行可用的鄰台間無線電鏈結頻寬分配，供應急通訊系統使用。無線通訊技術的成熟，為使用者帶來極大的便利性，但當發生大規模的地震或強烈颱風等重大天然災害時，通訊系統卻常常因架構等因素，隨著電力與交通系統的損毀而癱瘓。由歷年大型災變中多數災區內之行動通訊系統全面中斷即可印證行動通訊系統其實是極為脆弱，而有效運作的通訊系統卻是災情傳遞、資源調度以及互助協調是否順利的關鍵因素。 本文所探討的應急通訊系統是利用倖存的連通基地台和斷訊卻沒有損毀的基地台，以無線電連接起來建構一個臨時性的通訊系統，稱為應急蜂巢式行動通訊網路(Contingency Cellular Network，CCN)。由於CCN鄰台間無線電鏈結的頻寬有限，大量話務將造成通訊系統壅塞，影響重要訊息傳遞，且災區各個地方需求與受災情況不盡相同，使得CCN頻寬資源需視各地需求與需求緊急程度進行規劃配置，以充分發揮頻寬效益傳遞重要資訊。本論文主要在探討如何在CCN網路拓樸、連外頻寬分配已決定的情況下，進行CCN跨基地台頻寬分配，以達到最大的救災效益。我們提出一適合CCN樹狀結構的頻寬分配優化模型，在兼顧涵蓋率的情況下追求救災效益的最大化，此模型可供使用者(救災指揮單位)系統化的解決CCN跨基地台頻寬分配問題。 本文所提出的頻寬分配模型包含CCN樹狀拓樸、鄰台間之無線電鏈結頻 寬資源限制、需求對(存在通訊需求之兩基地台)、差異化之通訊品質通道和頻寬效益遞減函數。我們證明此模型是NP-Hard問題，並提出一個考慮各需求對緊急程度以及通訊品質需求差異而進行快速頻寬分配的演算法，此演算法以貪婪法在各中間步驟挑選當下效益密度最高的選擇賦予頻寬，如此逐步計算得到最終解。 我們以電腦模擬的方式，評估CBBAG演算法搭配不同頻寬救災效益密度計算之效能。在我們的實驗中，CBBAG演算法搭配additive的頻寬救災效益密度計算方式所的效能最佳，在小規模模擬環境下，在所模擬的30個亂數產生的案例中，CBBAG演算法與最佳解相較，效能差距不超過9.4%。而在大規模環境下，在所模擬的10個亂數產生的案例中，CBBAG演算法與準最佳解相較，效能至少超過最少21.8%，最多43.26%。 最後我們以unit cost of coverage improvement比較兩種效益遞減函數在增加涵蓋率時所承擔的效益成本。由實驗結果可以發現，CBBAG演算法搭配1/sqrt(分配至某需求對的頻道數)效益遞減函數所付出的效益成本較小。

隨著智慧家庭概念與技術的興盛與成熟，未來ISP(Internet Service Provider)業者勢必面臨管理大量智慧家庭中各種不同應用競爭頻寬資源的情況。為因應大量且繁雜類型的應用服務彼此競爭智慧家庭端及ISP端的頻寬資源，考量並應用適當的頻寬分配法則以盡可能優化使用者體驗(QoE)是本研究的研究動機。相關文獻的排程演算法如TDPSS (Time Domain Priority Set Scheduler)、MSCDL (Mac Scheduler)、Proportional Fair (PF)及Adaptive Modified Largest Weighted Delay First (AMLWDF)等。若要用以管理大量智慧家庭的頻寬資源時，ISP業者須將家庭申辦頻寬方案以及ISP端的系統頻寬分開考量。ISP在整合(aggregate)多個家庭的頻寬資源請求時，會依服務類別分配頻寬，最後依據不同類別採取適當處理，進而提升不同應用的QoS品質。 本篇論文著重於延遲時間的考量，提出能分類來自各個智慧家庭中，屬於不同 QCI (QoS Class Identifier)級別的頻寬請求並以不同佇列存放，依DADS (Delay Aware Dynamical Scheduling)演算法計算優先權值。我們利用保障頻寬與動態配置頻寬給不同用戶服務佇列，並優先分配頻寬給較高優先權的用戶服務，以期在維持一定公平性的前提下，盡可能地降低延遲來提升QoS品質。 在我們的實驗數據分析中，我們將DADS和其他方法如MSCDL、PF、TDPSS以及AMLWDF進行公平性、產能、延遲以及抖動率等效能優劣的比較與分析。最後在總結與未來研究方向，我們歸納與整理了DADS與PF、MSCDL、TDPSS以及AMLWDF等演算法的效能優劣。實驗結果顯示，在延遲上，DADS勝過PF和TDPSS，但略輸MSCDL及AMLWDF；在抖動率及產能上，DADS均較其它四者為差；公平性上則是劣於TDPSS、PF及MSCDL但優於AMLWDF。雖然DADS在整體的表現並非最好，但在特別重視延遲時間的Category1類別(包含QCI級別為1、2及5的應用服務)的延遲效能僅輸AMLWDF些許，而產能卻明顯勝過AMLWDF，由此可見DADS在Category1的表現最佳。 / With the concept and technology of smart homes becoming more and more mature and popular, Internet service provider (ISP) must face managing large set of various applications from smart homes which competing for bandwidth resources. In order to enhance Quality of Services (QoS) of a lot of various applications while they are competing bandwidth resources of both smart homes (home internal) and Internet service provider (home external), we propose a QoS aware bandwidth allocation criterion to optimize Quality of user Experience (QoE). Since ISP has to manage bandwidth resources of large set of smart homes, in the proposed criterion each ISP separates the bandwidth resources for home external bandwidth and system bandwidth of ISP, respectively. Then, aggregates bandwidth requests of large number of smart homes according to distinct service classes. This thesis focuses on the performance index of delay. We proposed to classify bandwidth requests from smart homes and put them into different queues, finally, calculate priority values by DADS (Delay Aware Dynamical Scheduling) algorithm. The proposed method is able to effectively reduce delay time with certain degree of fairness guarantee by dynamically allocate bandwidth resources for services with distinct service priorities. In the experiments, we compared DADS with other algorithms such as MSCDL (Mac Scheduler), PF (Proportional Fair), TDPSS (Time Domain Priority Set Scheduler) and AMLWDF (Adaptive Modified Largest Weighted Delay First), etc. in terms of fairness, throughput, delay and jitter. The experiments results show that DADS performs much better than PF and TDPSS but a bit worse than MSCDL and AMLWDF in terms of delay. However, DADS shows no better performance than all other algorithms in terms of jitter and throughput. In fairness comparison, DADS is worse than PF, TDPSS and MSCDL but is better than AMLWDF. Though DADS has no superior performance on overall indices, it is a bit worse than AMLWDF in delay of Category1 (including QCI 1, 2 and 5), its throughput is better than AMLWDF. Therefore, DADS’s performance is the best on Category1 considering overall indices.

隨著智慧家庭技術及物聯網的裝置大幅度地成長，智慧家庭的網路流量亦隨之升高。當大量成長的智慧家庭流量造成網路壅塞時，可能使緊急服務的警告機制失效，或是造成某些應用服務品質低劣而不堪使用。這些問題恐阻礙智慧家庭未來的發展性。 為改善上述問題，本文提出創新的物聯網智慧家庭頻寬配置管理架構。以ISP業者管理數以千計的物聯網智慧家庭為情境，針對智慧家庭多樣化的應用服務，利用具前瞻性的軟體定義網路，提供ISP業者對智慧家庭外部網路頻寬做最佳化的配置。 本研究依改良後的3GPP LTE QoS Class Identifier (QCI)，分類智慧家庭的服務，並考量服務的優先權及延遲程度，提出BASH演算法。透過本研究，ISP業者能依定義好的服務類別，將匯集後的智慧家庭服務流量藉由配置訊務流(traffic flow)的權重，計算出不同服務的最佳頻寬分配量，達到提升QoS及使用者QoE的目的。 為確認本論文所提出之方法的有效性，實驗設計是利用Linux伺服器架設OpenvSwitch、Ryu控制器及Mininet模擬器，建構SDN網路環境。實驗結果顯示，本研究所提出的BASH與ISP所用的傳統頻寬分配方法相比，能有效提高30%的throughput，降低159%的delay time及967%的 jitter time。 / With the increasing number of IoT (Internet of Things) devices and advance of smart home technology, the network traffic of smart home is also raising rapidly. When network congestion occurs due to massive traffic, some emergent alert mechanisms might become invalid or cause some application services performance degraded. All kinds of these will dramatically hamper the future development of smart homes. In order to resolve these problems, we propose an innovative bandwidth allocation smart home management framework for IoT enabled smart homes. The application scope of this research assumes a scenario that an ISP (Internet Service Provider) should support thousands of IoT enabled smart homes for a variety of services. The proposed bandwidth allocation framework is based on the promising software defined networking (SDN) architecture and is responsible for optimizing bandwidth allocation on external Internet traffic. We modify the 3GPP LTE QoS Class Identifier (QCI) to adaptive to the services suitable for smart homes. The proposed bandwidth allocation smart home (BASH) algorithm considers service priority and delay at the same time. With this framework, ISP is able to optimize bandwidth allocation by aggregating thousands of classified services of smart homes and thus effectively enhance Quality of Service (QoS) and user experience (QoE). In order to verify the proposed methods, we implement a SDN environment by using Linux Ubuntu servers with Mininet, Open vSwitch and Ryu controller. The experiment results show that BASH outperforms ISP traditional method in increasing the throughput by 30%, reducing delay and jitter by 159% and 967%, respectively.

防火牆是現今網路中的重要設備，負責區隔內部網路和公共網路，維護內部網路安全。然而防火牆也存在幾個重要的問題，首先，防火牆的規則是由網管人員設定，近年來隨著網路科技蓬勃發展、虛擬技術大量應用，此項工作已帶給網管人員龐大的負擔。其次，防火牆雖可隔離外部網路，阻擋有害流量，但對內部網路的防範卻毫無用武之地。目前市面上普遍使用入侵偵測系統(IDS)進行偵測，但僅能在發現攻擊行為後發出警告訊息，無法即時處理。最後，企業在連外網路部分，通常採用多條線路進行備援，並倚賴多路頻寬負載平衡器(Multi-WAN load balancer)增加頻寬的使用率，但在線路數量上卻受限於廠商所制定之規格，無法彈性調整。而在負載平衡演算法方面，也只能基於網路特徵(IP位置)、權重比例(weight)或是輪詢機制(round robin)，無法依據目前網路狀況做出更好判斷。 為改善上述問題，本論文在軟體定義網路(SDN)環境下，使用交換機取代傳統防火牆設備，透過封包分析與信任觀測區間達到規則學習，並整合Snort入侵偵測系統，透過特徵比對，找出危害網路環境之封包，即時阻擋該危險流量。本論文也提出基於隨需(on demand)概念，動態調整防火牆規則，降低管理人員負擔。最後利用交換機擁有多個實體通訊埠的概念 ，依需求可自由調整對外及對內線路數量，不再受限於廠商規格，取代傳統多路寬頻負載平衡器，建構更彈性的架構。並透過收集交換機上的實體埠與資料流表中的資訊，即時評估網路狀況，加強負載平衡。為驗證本論文所提出之⽅法的有效性，我們使用Linux伺服器架設KVM、OpenvSwitch以及POX控制器實際建構SDN網路環境，透過發送封包對防火牆提出請求，以驗證實驗方法的正確性。 根據實驗結果顯示，本論文所提出之概念均能正確運作，有效降低調整防火牆所需之人工作業。在多路寬頻負載平衡器部分，本研究所提出之負載平衡方法，與round robin負載平衡方法相較之下，在最佳情況下，能有效提升約25%平均頻寬使用率，並降低約17.5%封包遺失率。 / Firewall is an important device that is responsible for securing internal network by separating Internet from Intranet, but here are several existing issues about the firewall. First, the firewall rules are set by the network admistrator manually. Along with the vigorous development of Internet technologies and great amount of applications of virtual technology in recent years. This work burdens the network adminstrator with a heavy workload. Second, the firewall is able to isolate the external network from harmful traffic, however, it can do nothing to the internal network. The common situation is to use IDS to detect the harmful packet, but it can only send an alert message to the adminstrater, no more actions can be done. Finally, most companies use several ISP connections to assure fault tolerance and use Multi-WAN load balancer to integrate those connections to enhance bandwidth utilization. But the number of WAN/LAN ports is set by the manufacturer, and the load balance algorithm is also limited by the manufacturer. It offers only a few algorithms (network-based features, round-robin, etc.), and there is no other way to provide more efficient algorithms. In order to resolve the mentioned problems, we propose an automatic firewall based Software Defined Network (SDN). We use Openflow switches to replace traditional firewalls, the system is able to learn the rules automaticlly by packet analysis during an observation interval. We aslo integrate Snort Intrusion Detection System (IDS) to localize the dangerous packets and block them immediately. Next, we propose an on-demand based dynamic firewall rules adjustment mechanism which is able to reduce management workload. Finally, we implement a Multi-WAN load balancer architecture and provide a more efficient load balance algorithm by collecting port usage and firewall rule information. In order to verify the proposed methods, we implement a SDN environment by using Linux Ubuntu servers with KVM, Open vSwitch and POX controller. According to the experiment result, it proves that the proposed method is able to reduce the firewall configuration effectively. In the Multi-WAN load balancer, experiment results show that our method outperforms round-robin argrithom in terms of average bandwidth utilization and packet loss rate by 25% and 17.5%, respectively.

隨著物聯網這個萬物連網的概念順勢推動智慧家庭在市場裡蓬勃發展，可預期未來ISP(Internet Service Provider)業者勢必面臨大量智慧家庭中各種不同應用服務互相競爭頻寬資源的情況，甚至遇到網路滿載壅塞時造成應用服務不堪使用的情形。 為改善上述問題，本文以ISP業者管理智慧家庭中眾多的物聯網設備為情境，透過軟體定義網路 (Software Defined Network，SDN)進行頻寬排程配置，排程演算法以可兼顧公平性(fairness)、時間延遲(delay)及應用服務優先權(service priority)的A-MLWDF (Adaptive Modified Largest Weighted Delay First) [7]演算法，確保優先配置頻寬給智慧家庭中優先權較高、時效較為急迫的流量，以降低應用服務的延遲來提升智慧家庭網路之服務品質(Quality of Service，QoS)。 本研究透過OMNet++模擬器建構SDN環境與傳統環境中有眾多物聯網設備之智慧家庭。家中物聯網設備包含M2M (Machine to Machine)和非M2M(non Machine to Machine)裝置，以提供各種智慧家庭應用服務。我們透過SDN架構進行頻寬配置，達到集中式管控家中的頻寬資源，其中排程演算法包括PF、MLWDF、A-MLWDF。實驗結果顯示，以上排程演算法雖然於SDN環境下在公平性與抖動率表現並不顯著，公平性約改善1.6%及抖動率約降低1%左右，但在產能與延遲方面表現較為顯著，能有效提高產能約52%，及降低延遲約 52%。 / With the concept of IoT (Internet of Things) spread rapidly, it is the opportunity to promote smart homes in the expanding market. We can see that the future ISP (Internet Service Provider) has to face a large number of smart homes having bandwidth competition in a variety of different applications and causing application services unavailable due to network congestion.     In order to resolve the above problems, we propose that each ISP (Internet Service Provider) has to manage a large number of IoT devices in a smart home to performs bandwidth scheduling through Software Defined Network (SDN). We choose to use A-MLWDF scheduling algorithm (Adaptive Modified Largest Weighted Delay First) [7] which considers fairness, delay and service priority. A-MLWDF is able to ensure services of higher priority and emergent traffic be allocated bandwidth earlier and greatly reduce delay and thus effectively enhance Quality of Service (QoS) of smart homes.     In this research, we implement a SDN environment by using OMNet++ to simulate the bandwidth competition among smart homes with IoT devices. The IoT devices consists of M2M (Machine to Machine) and non-M2M (non Machine to Machine) devices which offer a variety of intelligent home application services. We configure the bandwidth allocation under SDN control. The scheduling algorithms include PF, MLWDF and A-MLWDF. When the network traffic is congested, SDN can significantly increase throughput and reduce latency compared to traditional network management. The experimental results show that above scheduling algorithms using SDN environment having no significant performance improvements in fairness and jitter. The fairness increases around 1.6% and the jitter reduces around 1%. However, it shows significant improvement on throughout and delay. The throughput increases around 52% and the delay reduces around 52%.

當大型災害來臨，通訊系統對救災效益具有不可或缺的重要性。然而，一般公眾通訊系統，如行動通訊網路等，常因各種不同因素導致系統攤瘓，使得協調大批非組織的救災志工，顯得異常困難。現存多個緊急通訊系統的佈建，需仰頼良好的交通運輸。不幸的是，部分道路和橋樑常因大型災害而斷裂或變型，導致災區對外交通運輸中斷，無法快速的將緊急通訊系統的網路元件，運送至災區佈建。我們提出應急行動通訊系統(Contingency Cellular Network, CCN) 以提供災區救災工作的緊急通訊。部分行動基地台雖然結構完整，但因失去與核心網路連線能力或電力供應，而無法提供服務，成為孤立基地台。應急行動通訊網路(CCN) 搭配無線通訊與衛星通訊技術建置一多重跳接無線網路，以恢復孤立基地台與核心網路連線能力；並配備發電機，提供電力，使孤立基地台可提供有限的服務。救災志工和災民無需使用特殊手持設備或額外的訓練，只需使用原有的手機，即可使用CCN的應急通訊服務。CCN可於第一時間，提供大批救災志工和災民通訊服務，以提高救災效益，因而拯救更多寶貴的生命。 本論文主要聚焦在應急行動通訊系統設計所衍生出的相關議題，如 應急網路需求分析、系統架構設計、網路拓樸規劃、網路頻寬規劃、佈署行程規劃等議題。本論文針對網路拓樸規劃、網路頻寬規劃、佈署行程規劃問題以數學模式進行塑模並證明這些問題為NP-Hard問題。因網路拓樸規劃、網路頻寬規劃、佈署行程規劃需緊急完成，我們也提出啟發式算法快速解決這些規劃問題。實驗結果顯示，這些啟發式算法均具良好的效能。 / Communication system is crucial to the efficiency of disaster response operation in the large-scale disaster. However, communication systems, such as cellular networks, usually crashed due to various causes making coordination among disorganized disaster responders extremely difficult. Unfortunately, rapid deployment of many existing emergency communication systems relies on a good transportation system, which is usually not available in a catastrophic natural disaster. We proposed a Contingency Cellular Network (CCN) for emergency communication by connecting disconnected base stations together with wireless links to construct a wireless multi-hop cellular network. CCN can support existing mobile phone users with reduced capability. Such a system can support a large number of disaster responders in the early hours of a catastrophic natural disaster, thus save many lives. Our research addresses the design issues of the network topology of CCN, such as network topology planning, bandwidth management, deployment scheduling and etc., and we take the degree of emergency and population of each stricken area as the priority measure as well as the available resources as the constraint to determine the network topology. Mathematical models of these design issues are proposed and proved as NP-Hard problems. Since the network topology, bandwidth management, deployment scheduling are needed in urgent, we propose heuristic algorithms to solve these problems quickly. Finally, we evaluated the proposed algorithms by simulation. A significant improvement in resiliency is reached.

本論文針對隨機數位網路提出一套可行的計算機制，以提供網路管理者進行資源分配與壅塞管理的分析工具。我們研究兩種利潤最佳化模型，探討在預算控制下的頻寬分配方式。因為資源有限，網路管理者無法隨時提供足夠頻寬以滿足隨機的網路需求，而量測網路連結成功與否的阻塞機率(Blocking Probability)為評估此風險之一種指標。我們利用頻寬分配、網路需求量和虛擬端對端路徑的數量等變數，推導阻塞機率函數，並證明阻塞機率的單調性(Monotonicity)和凸性(Convexity)等數學性質。在不失一般性之假設下，我們驗證阻塞機率是(1)隨頻寬增加而變小；(2)在特定的頻寬分配區間內呈凸性；(3)隨網路需求量增加而變大；(4)隨虛擬路徑的數量增加而變小。 本研究探討頻寬分配與阻塞機率之關係，藉由推導單調性和凸性等性質，提供此兩種利潤模型解的最適條件與求解演算法。同時，我們引用經濟學的彈性概念，提出三種模型參數對阻塞機率變化量的彈性定義，並分別進行頻寬分配、網路需求量和虛擬路徑數量對邊際利潤函數的敏感度分析。當網路上的虛擬路徑數量非常大時，阻塞機率的計算將變得複雜難解，因此我們利用高負荷極限理論(Heavy-Traffic Limit Theorem)提供阻塞機率的估計式，並分析其漸近行為(Asymptotic Behavior)。本論文的主要貢獻是分析頻寬分配與阻塞機率之間的關係及其數學性質。網路管理者可應用本研究提出的分析工具，在總預算限制下規劃寬頻網路的資源分配，並根據阻塞機率進行網路參數的調控。 / This thesis considers the problem of bandwidth allocation on communication networks with multiple traffic classes, where bandwidth is determined under the budget constraint. Due to the limited budget, there exists a risk that the network service providers can not assert a 100% guaranteed availability for the stochastic traffic demand at all times. We derive the blocking probabilities of connections as a function of bandwidth, traffic demand and the available number of virtual end-to-end paths for all service classes. Under general assumptions, we prove that the blocking probability is directionally (i) decreasing in bandwidth, (ii) convex in bandwidth for specific regions, (iii) increasing in traffic demand, and (iv) decreasing in the number of virtual paths. We also demonstrate the monotone and convex relations among those model parameters and the expected path occupancy. As the number of virtual paths is huge, we derive a heavy-traffic queueing model, and provide a diffusion approximation and its asymptotic analysis for the blocking probability, where the traffic intensity increases to one from below. Taking the blocking probability into account, two revenue management schemes are introduced to allocate bandwidth under budget control. The revenue/profit functions are studied in this thesis through the monotonicity and convexity of the blocking probability and expected path occupancy. Optimality conditions are derived to obtain an optimal bandwidth allocation for two revenue management schemes, and a solution algorithm is developed to allocate limited budget among competing traffic classes. In addition, we present three elasticities of the blocking probability to study the effect of changing model parameters on the average revenue in analysis of economic models. The sensitivity analysis and economic elasticity notions are proposed to investigate the marginal revenue for a given traffic class by changing bandwidth, traffic demand and the number of virtual paths, respectively. The main contribution of the present work is to prove the relationship between the blocking probability and allocated bandwidth under the budget constraint. Those results are also verified with numerical examples interpreting the blocking probability, utilization level, average revenue, etc. The relationship between blocking probability and bandwidth allocation can be applied in the design and provision of broadband communication networks by optimally choosing model parameters under budget control for sharing bandwidth in terms of blocking/congestion costs.