Vast application of ITS and the availability of numerous on-road detection devices has resulted in variety of alternative data sources to be exploited and used in the field of traffic modelling. In this thesis, historical travel times, as an alternative data source, is employed on the developed method to perform dynamic network loading. The developed method, referred to as DNLTT, uses the share of each route available in the route choice set from the initial demand, as well as link travel times to perform the network loading. The output of the algorithm is time-dependent link flows. DNLTT is applied on Stockholm transportation network, where it is expected to have variation in link travel times in different time-periods, due to network congestion. In order to calculate the route shares, a time-sliced OD matrix is used. The historical travel times and the routes in the route choice set are extracted from an existing route planning tool. An available logit model, which considers the route travel time as the only logit parameter, is used for the route share calculation and the network loading is performed according to 2 different methods of DNLTT and DL. The evaluation of results is done for a toy network, where there happen different network states in different time-periods. Furthermore, the model output from Stockholm case study is analyzed and evaluated. The dynamic behavior of DNLTT is studied by analysis of link flows in different time-periods. Furthermore, the resulting link flows from both network loading methods are compared against observed link flows from radar sensors and the statistical analysis of link flows is performed accordingly. DNLTT exhibits a better performance on the toy network compared to DL, where the increasing link travel times cause the link flows to decline in different time-periods. However, the output of the developed method does not resemble the observed link flows for the investigated links in Stockholm case study. It is strongly believed, that the performance of DNLTT on the investigated transportation network potentially improves, in case the historical travel times better resemble the network dynamics. In addition to a more reliable data set, an OD adjustment process in all the time-periods is believed to generate better model output.

No description available.

由於競爭環境的變化，使得供應鏈中製造廠商與供應廠商雙方的交易關係(supplier-manufacturer relationship)有了重大的改變，由過去競爭的對立關係，轉變為合作的夥伴關係；中心廠與諸多零配件的供應商形成了一個合作的群聚，來共同滿足買方客戶的需求。台灣中小企業組成的綿密產業網絡便是一個相當好的例證，台灣產業網絡的「彈性」和「速度」特質，使台灣企業能夠在市場急速變化、壓力陡增的情況下，及時進行靈活調適，並整合體系內各種可用的資源，創造特有的競爭優勢。 本研究以個案研究的方式，選擇具動態合作網絡特性的營造業作為母體，來瞭解台灣的營造廠如何建立與維繫一個動態性合作網絡？如何進行網絡成員的分工與連結管理？本研究透過兩個實務個案分析，來瞭解動態合作網絡的分工與連結管理的前因與後果，建立觀念性架構與命題，以作為企業經營業者的參考。 營造廠的「價值活動調整」的取決會受到「環境系絡」、「技術系絡」的影響，當營造廠決定其價值活動涵蓋範疇後，將會面臨價值活動劃分的問題，要在諸多的承包商中選擇合適的對象來負責各式專業工項的執行工作，也就是要進行其「委外對象選擇」的安排，接下來最後就是依據承包商的類型的不同，於此稱之為「網絡關係管理類型」，進行分類管理，最後導致不同的「利潤模式」的選擇。 整體而言，個案公司多年來能在環境景氣循環與競爭壓力的衝擊下，不斷地成長茁壯，核心的概念在於其價值活動涵蓋範疇的動態調整彈性，方能擁有足夠的利潤，持續地追求公司的成長。當環境競爭態勢激烈的時候，就擴大價值活動的涵蓋範圍，將工程進行細部的切割，一方面可以跨過大包商直接發包給小包商，自己進行溝通協調的工作，以降低成本，一方面則可以將專業工項的設計規劃、採購活動等納入公司內部執行，減少外包佔比，提升工程利潤；當環境景氣好，訂單旺的時候，就降低價值活動的涵蓋範圍，發大包給承包商來執行，辛苦費時的整合者利潤讓給承包商，雖然單一工程的整合者利潤降低，但是由於可以承接的工程數目變多了，所以在仲介者利潤的擴大下，獲得利潤的成長。 營造廠的策略彈性，來自於其自身的價值活動調整彈性與承包商網絡的建立與維繫。該價值活動調整的彈性來自於自身能力的強弱與完備性，能力越強越完備的廠商，其價值活動調整的彈性越高；營造廠的能力可以分為整合能力與操作能力兩類，整合能力佳的廠商在價值活動細切給小包商的時候，或者在跨專業工項的承包商間的溝通協調上，會有比較好的績效，如期完成工程，減少成本支出；操作能力好的營造商，除了可以選擇性地決定是否要將專業工項相關的價值活動內製外，增加議價能力外，還可以掌握該相關工項的成本結構，控制成本支出。在承包商網絡的建立與維繫上，多元化承包商網絡的存在，除了可以讓營造廠能夠視工程需要找到合適的承包商外，還可以透過創造群與群間的承包商的相互競爭性，來降低對於單一承包商的依賴程度，也增加了承包商間的選擇彈性。 由於工程設計的差異，工程技術的變遷，營造商必需不斷地透過工程案件的執行，向具夥伴關係的廠商學習特定工項的操作知識與技能，提昇自身的能力，也將該操作知識與技能傳授給具團隊關係的廠商，也帶動整體承包商網絡能力的增長。因而，讓營造廠得以在環境競爭與技術變遷的衝擊下，獲得不斷成長的機會，也創造了與承包商網絡同步成長的機會，而得以避免整體策略彈性喪失的可能性。 最後，不同的網絡關係類型的管理代表著不同的利潤模式的創造思維，營造廠對於會員關係類型的承包商將採取採購成本最小化的模式，之於團隊關係類型的承包商將採取交易成本最小化的模式，夥伴關係類型的承包商則採最大化綜效的模式。 / Duing to the changing of the competitive environment, make the relationship between the manufacturing firm and their suppliers from competitive to cooperative. The manufacturing firm and its suppliers form a cooperative cluster to satisfy the buyer’s requirement. The cooperative network manufacturing firms build become one of the important sources of competitive advantage, therefore it’s a significant issue to the management of the cooperative network. From the practical view, the intensive industrial network organizes by the small and medium size enterprise is the important source of the Taiwan’s manufacturing advantage. The nature of flexibility and speed of Taiwan’s industrial network makes the firms could deal with the fast changing environment, and integrate the available resources of the network to create the unique competitive advantages. The industrial network also play a major role for hundred billion of the foreign exchange reserves in Taiwan, no matter what the traditional industry, such as tailoring, shoes, and machine tool industries or high-tech industry as computer, integrated circuit and electronic industries, the specialization and cooperation between industries is more significant in Taiwan than in other Asia countries, such as in Japan and Korea. Therefore, it’s an important issue to know the manufacturing firms how to build up and maintain their dynamic cooperative network and how to do the job assign and the leakage management among members of network. From the theatrical view, the early researches in the intra-organizational cooperative relationships is focus on the dyadic relationship to explain how the power and trust influence the cooperation, maybe how to gain the competitive advantage based on the relationship further. As we know manufacturing firms will exchange their resources with many suppliers, they always make the strategic decision from the holistic view of the network, not the dyadic view. Miles and Snow (1984) argue that the traditional organization will be disaggregated vertically, the way of integrating all the functions in a single organization will be instead of dividing into many independent firms to execute coordinately. They said that a successful company should integrate and coordinate their network members dynamically to achieve the customer’s need. Recently Bovet and Martha (2000) emphasize the important of building the value creating system to support the customer’s need agilely, the network of value system is different from the production line relationship of traditional supply chain, it start by the customer’s need, the manufacturing firms which interconnected with their suppliers, strategic partners, customers, exchange with the network member to acquire the resources they need, such as economic assets, knowledge, intangible benefits, to satisfy the need of customer (Allee, 2000). This study tries to figure out how the manufacturing firm build up and maintain their network dynamically, how they do the job assignment and linkage management, by case study. The two cases selected from construction industry are suitable to present the dynamic network management, by cooperating the two cases, this study establish the conceptual framework and propositions for the reference of managers.

It is widely accepted that modern computer networks (often presented as a heterogeneous collection of functioning organisations, applications, software, and hardware) contain vulnerabilities. This research proposes a new methodology to compute a dynamic severity cost for each state. Here a state refers to the behaviour of a system during an attack; an example of a state is where an attacker could influence the information on an application to alter the credentials. This is performed by utilising a modified variant of the Common Vulnerability Scoring System (CVSS), referred to as a Dynamic Vulnerability Scoring System (DVSS). This calculates scores of intrinsic, time-based, and ecological metrics by combining related sub-scores and modelling the problem’s parameters into a mathematical framework to develop a unique severity cost. The individual static nature of CVSS affects the scoring value, so the author has adapted a novel model to produce a DVSS metric that is more precise and efficient. In this approach, different parameters are used to compute the final scores determined from a number of parameters including network architecture, device setting, and the impact of vulnerability interactions. An attack graph (AG) is a security model representing the chains of vulnerability exploits in a network. A number of researchers have acknowledged the attack graph visual complexity and a lack of in-depth understanding. Current attack graph tools are constrained to only limited attributes or even rely on hand-generated input. The automatic formation of vulnerability information has been troublesome and vulnerability descriptions are frequently created by hand, or based on limited data. The network architectures and configurations along with the interactions between the individual vulnerabilities are considered in the method of computing the Cost using the DVSS and a dynamic cost-centric framework. A new methodology was built up to present an attack graph with a dynamic cost metric based on DVSS and also a novel methodology to estimate and represent the cost-centric approach for each host’ states was followed out. A framework is carried out on a test network, using the Nessus scanner to detect known vulnerabilities, implement these results and to build and represent the dynamic cost centric attack graph using ranking algorithms (in a standardised fashion to Mehta et al. 2006 and Kijsanayothin, 2010). However, instead of using vulnerabilities for each host, a CostRank Markov Model has developed utilising a novel cost-centric approach, thereby reducing the complexity in the attack graph and reducing the problem of visibility. An analogous parallel algorithm is developed to implement CostRank. The reason for developing a parallel CostRank Algorithm is to expedite the states ranking calculations for the increasing number of hosts and/or vulnerabilities. In the same way, the author intends to secure large scale networks that require fast and reliable computing to calculate the ranking of enormous graphs with thousands of vertices (states) and millions of arcs (representing an action to move from one state to another). In this proposed approach, the focus on a parallel CostRank computational architecture to appraise the enhancement in CostRank calculations and scalability of of the algorithm. In particular, a partitioning of input data, graph files and ranking vectors with a load balancing technique can enhance the performance and scalability of CostRank computations in parallel. A practical model of analogous CostRank parallel calculation is undertaken, resulting in a substantial decrease in calculations communication levels and in iteration time. The results are presented in an analytical approach in terms of scalability, efficiency, memory usage, speed up and input/output rates. Finally, a countermeasures model is developed to protect against network attacks by using a Dynamic Countermeasures Attack Tree (DCAT). The following scheme is used to build DCAT tree (i) using scalable parallel CostRank Algorithm to determine the critical asset, that system administrators need to protect; (ii) Track the Nessus scanner to determine the vulnerabilities associated with the asset using the dynamic cost centric framework and DVSS; (iii) Check out all published mitigations for all vulnerabilities. (iv) Assess how well the security solution mitigates those risks; (v) Assess DCAT algorithm in terms of effective security cost, probability and cost/benefit analysis to reduce the total impact of a specific vulnerability.

Les travaux présentés dans cette thèse visent à proposer des méthodes de routage d’une population de masse à travers un réseau perturbé dont les données varient dans le temps pour l’aide à la conception de plan d’évacuation. Ce problème s’illustre parfaitement en cas de catastrophe d’origine humaine ou naturelle où les populations (potentiellement) impactées par ces sinistres doivent quitter leur lieux de vie pour une période pouvant aller d’un à plusieurs jours. Dans la littérature, ces routages de masse sont souvent modélisés comme des problèmes de flots dynamiques dont l’objectif est de minimiser la durée globale du transfert des individus depuis un certain nombre de points de départs dangereux vers des points d’arrivé sûrs. Toutefois, peu de travaux prennent en compte la notion de sécurité durant ce routage et encore moins le déploiement d’agents (policiers, sapeur-pompiers, ambulanciers,...) pouvant sécuriser et/ou faciliter le déplacement des personnes. / The work presented in this thesis aims to propose methods for routing a mass population through a disturbed network whose data vary over time. This problem can be illustrated by disasters due to humans or natural events where people (potentially) affected have to leave their living places for a period of one to several days. In the literature, mass routing are often modeled as dynamic flow problems whose objective is to minimize the overall duration of the evacuation process from a set of gathering points towards another set of shelter locations. However few papers take into account the concept of safety during this routing nor deploying task forces that can secure or facilitate this process. In this context, the safety security can be seen as a danger affecting the quality of life of people we organize the trip. In this context, the safety can be seen as a danger that influence the health of the people we are trying to evacuate. Indeed, this hazardous event can be related to a radioactive cloud, a fire, a tsunami, an earthquake or a flooding which make some of paths becoming dangerous or less usable by evacuees.

This thesis deals with detection of dynamic network applications. It describes some of the existing protocols and methods of their identification from IP flow and packet contents. It constitues a design of a detection system based on the automatic creation of regular expressions and describes its implementation. It presents the created regular expressions for BitTorrent and eDonkey protocol. It compares their quality with the solution of L7-filter.

Mobile data traffic is expected to increase substantially in the coming years, with data rates 1000 times higher by 2020, having media and content as the main drivers together with a plethora of new end-user services that will challenge existing networks. Concepts and visions associated with the ICT evolution like the network society, 50 billion connected devices, Industrial Internet, Tactile Internet, etc., exemplifies the range of new services that the networks will have to handle. These new services impose extreme requirement to the network like high capacity, low latency, reliability, security, seamless connectivity, etc. In order to face these challenges, the whole end-to-end network has to evolve and adapt, pushing for advances in different areas, such as transport, cloud, core, and radio access networks. This work investigates the impact of envisioned 2020 society scenarios on transport links for mobile backhaul, emphasizing the need for an integrated and flexible/adaptive network as the way to meet the 2020 networks demands. The evolution of heterogeneous networks and ultra-dense network deployments shall also comprise the introduction of adaptive network features, such as dynamic network resource allocation, automatic integration of access nodes, etc. In order to achieve such self-management features in mobile networks, new mechanisms have to be investigated for an integrated backhaul management. First, this thesis performs a feasibility study on the mobile backhaul dimensioning for 2020 5G wireless ultra-dense networks scenarios, aiming to analyze the gap in capacity demand between 4G and 5G networks. Secondly, the concept of an integrated backhaul management is analyzed as a combination of node attachment procedures, in the context of moving networks. In addition, the dynamic network resource allocation concept, based on DWDM-centric transport architecture, was explored for 5G scenarios assuming traffic variation both in time and between different geographical areas. Finally, a short view on techno-economics and network deployments in the 2020 time frame is provided.

This research is concerned with the modeling and development of algorithmic approaches for solving airport operational problems that arise in Air Traffic Control (ATC) systems within the terminal area at hub airports. Specifically, the problems addressed include the Aircraft Sequencing Problem (ASP) for runway operations, the Network Assignment Problem (NAP) for taxiway operations, and a simulation model for the evaluation of current or proposed ATC system in detail. For the ASP, we develop a mathematical model and apply the Reformulation-Linearization-Technique (RLT) of Sherali and Adams to construct an enhanced tightened version of the proposed model. Since ASP is NP-Hard and in fact, it is a variation of the well-known Traveling Salesman Problem with time-windows, sub-optimal solutions are usually derived to accommodate the real-time constraints of ATC systems. Nevertheless, we exhibit a significant advancement in this challenging class of problem. Also for the purpose of solving relatively large sized problems in practice, we develop and test suitable heuristic procedures. For the NAP, we propose a quasi-dynamic assignment scheme which is based on the incremental assignment technique. This quasi-dynamic assignment method assumes that the current aircraft route is influenced only by the previous aircraft assigned to the network. This simplified assumption obviates the need for iterative rerouting procedures to reach a pure equilibrium state which might not be achievable in practical taxiway operations. To evaluate the overall system, we develop a microscopic simulation model. The simulation model is designed to have the capability for reproducing not only the dynamic behavior of aircraft, but also incorporates communication activities between controllers and pilots. These activities are critical in ATC operations, and in some instances, might limit the capacity of the facility. Finally, using the developed simulation model named Virginia Tech Airport Simulation Model (VTASM) in concert with ASP and NAP, we compare the overall efficiencies of several control strategies, including that of the existing control system as well as of the proposed advanced control system. / Ph. D.

No description available.

Abstract With the current technological advancements, stage is being set for new ultra-responsive and robust 5G-enabled applications (e.g., virtual reality, Tactile Internet,…) to deliver critical real-time traffic. The emergence of such critical applications requires new networking models that can handle more connected devices with super high reliability and low latency communications. In the view of these research challenges, this thesis aims to propose new techno-economic models and networking paradigms needed in the redesign of wireless network architectures and protocols to support the connectivity requirements by which operators and users effectively benefit from new opportunities introduced by 5G-enabled applications. In this thesis, new paradigms in wireless network access are presented and analyzed. First, dynamic network architecture (DNA) is introduced, where certain classes of wireless terminals can be turned temporarily into an access point (AP) anytime while connected to the Internet. In this concept, a framework is proposed to optimize different aspects of this architecture. Furthermore, to dynamically reconfigure an optimum topology and adjust it to the traffic variations, a new specific encoding of genetic algorithm (GA) is presented. Then, a distributed user-centric spectrum sharing is developed based on DNA networks to enable user-provided access points pervasively share the unused resources. Next, a flexible cloud-based radio access network (FRAN) is proposed to offload traffic to DNA networks in order to provide low latency communications. In the sequel of the thesis, as a new paradigm, a context-aware resource allocation scheme based on adaptive spatial beamforming and reinforcement learning is proposed. In addition, semi-cognitive radio network (SCRN) as a new spectrum sharing model is developed to improve the utility of primary and secondary owners. / Tiivistelmä Nykyaikaisilla teknologisilla edistysaskeleilla mahdollistetaan uusien 5G-pohjaisien erittäin lyhyen vasteajan ja suuren luotettavuuden sovelluksien ilmestyminen kriittisen reaaliaikaisen informaation välittämiseen (esim. taktiiliset ja virtuaalitodellisuus-sovellukset). Näiden kaltaiset sovellukset vaativat uudenlaisia verkottumismalleja, jotka kykenevät käsittelemään enemmän laitteita suurella toimintavarmuudella ja matalalla latenssilla. Tämä väitöskirja ehdottaa näiden haasteiden valossa uusia teknis-taloudellisia malleja ja verkottumisparadigmoja, joita tarvitaan verkkoarkkitehtuurien ja -protokollien uudelleensuunnittelussa tulevaisuuden sovelluksien tarpeet huomioiden, joiden kautta operaattorit ja käyttäjät voivat hyödyntää tulevien 5G-sovelluksien tuomat mahdollisuudet. Tässä väitöskirjassa esitetään ja analysoidaan uusia paradigmoja langattomaan verkkoliityntään. Ensimmäisenä esitellään dynaaminen verkkoarkkitehtuuri (dynamic network architecture, DNA), missä tietyt langattomat terminaalit voidaan väliaikaisesti muuttaa liityntäpisteiksi milloin vain internetyhteyden ollessa käytettävissä. Tämän konseptin puitteissa ehdotetaan viitekehys sen eri osa-alueiden optimoimiseksi. Tämän lisäksi esitetään uusi spesifinen geneettisen algoritmin (GA) koodaus optimaalisen topologian dynaamiseen konfigurointiin ja sen säätämiseen tietoliikenteen määrän mukaan. Tämän jälkeen esitellään kehitetty hajautettu käyttäjäkeskeinen spektrinjako, joka perustuu DNA-verkkoihin ja joka mahdollistaa käyttämättömien resurssien kokonaisvaltaisen jakamisen käyttäjien kautta. Seuraavaksi työssä ehdotetaan joustavaa pilvipalvelu-pohjaista liityntäverkkoa (flexible cloud-based radio access network, FRAN) käyttäjädatan purkamiseksi DNA-verkoille matalalatenssisen tietoliikenteen tarjoamiseksi. Edellä mainittujen menetelmien seurauksena ehdotetaan uutta paradigmaa: Kontekstiriippuvaista resurssien allokointia perustuen adaptiiviseen spatiaaliseen keilanmuodostukseen ja vahvistusoppimiseen. Näiden lisäksi kehitetään uusi spektrinjakomalli puolikognitiivisille radioverkoille (semi-cognitive radio network, SCRN) ensisijaisien ja toissijaisien käyttäjien utiliteetin parantamiseksi.