This thesis proposes a convex network utility maximization (NUM) problem that can be solved to optimize a cross-layer network based on user and system defined requirements for quality and link capacity of multimedia applications. The problem can also be converged to a distributed solution using dual decomposition. Current techniques do not address the changing system's requirements for the network in addition to the user's requirements for an application when optimizing a cross-layer network, but rather focus on optimizing a dynamic network to conform to a real-time application or for a specific performance. Optimizing the cross-layer network for the changing system and user requirements allows a more accurate optimization of the overall cross-layer network of any given multi-node, ad-hoc wireless application for data transmission quality and link capacity to meet overall mission demands.

Wireless mobile internet market is still an unprecedented, uncaptured territory for cellular service providers. The shortage and high cost of downlink data bandwidth in a cellular network has remained a huge factor for the slow growth of data services in mobile devices. Although there has been a significant evolution in telephony infrastructures in form of 3G and 4G systems, the potential of high speed ad hoc network for sharing cellular spectrum have not been realized to its full potential. Like (e.g. Verizon) users can share voice minutes with friends, there is a potential for sharing the unutilized cellular bandwidth among friends to increase net data speed. In a scenario like a football stadium where people visit in groups, although a lone phone cannot stream a high quality replay video, unused cellular bandwidth of proximate friend’s devices can automatically be used in real time to view the replays. An available secondary ad hoc network such as Wi-Fi or Bluetooth in phone can be used for sharing this cellular bandwidth. Thus, we propose BuddyShare, a novel social-based automatic bandwidth sharing overlay platform on short range ad hoc devices to increase net data speed. The motivation stems from the fact that the location of mobile users tends to be clustered to form “people hotspots” such as conferences, stadiums, stations, buses and trains. For example, in a scenario like a football stadium where people visit in groups, although a lone phone cannot stream a high quality replay video, unused cellular bandwidth of proximate friends’ devices can automatically be used in real time to view the replays. Our work creates an overlay on horizontal ad hoc network to enable users to form a group among socially trusted members who can collaboratively share their data connections. Social trust is automatically derived from social relationships obtained by mining mobile-phone behavior pattern. This work aims to improve the overall utilization of the data connection, and increase the data rate of individual users without compromising their privacy and unauthenticated usage. The user privacy is preserved by using the bandwidth resources of only socially trusted member of the user, which also guarantees against unauthenticated exploitation of expensive bandwidth. Our proposed work promises to deliver win-win situation to users, content providers and service providers. The advantages of users are: 1) Increased data rate for the same cost.2) Secure and trusted overlay based communication for sharing resources. The advantages for the service providers are manifold: 1) Customer increase: More customers will avail the data plan due to social influence. 2) Customer retention: [18] Customers part of the social-cum-adhoc network are least likely to leave the network.3) Group subscription: Service provider can get bulk subscriptions as collaborative groups increase data rate. In this work, we address some key technical issues of developing a socially aware overlay collaborating medium. Some of the addressed functionalities associated with the overlay formations are group discovery, creation, management and actual data distribution. This proposal also accounts the computation of social trustworthiness by using standard social networking analytics. We also account the several key technical challenges associated with management of overlay on mobile nodes and trust computation using abstract social network. In order to verify the usefulness of BuddyShare, we collected realistic datasets from various sources (questionnaires, mobile device logs, social networking portal) and conducted analyses and simulations on it. The analyses concluded that sample users from the dataset shared sufficient social trustworthiness. The real events from the datasets were captured in the simulations. These simulations showed that, by using Bluetooth as a horizontal ad hoc medium, an user can scale his data speed three times on average for sufficient duration per day. This thesis achieves the following objectives: 1) It presents a comprehensive design for an overlaid social based internet sharing platform called BuddyShare. 2) It presents a social analysis to validate the concept of social trust among users. 3) It delivers a flexible simulation platform to realistically simulate mobile phones with dual interfaces. 4) It presents the results of simulations of real events captured from the device logs of sample users. These results conclude the usefulness of BuddyShare work.

Wireless sensor networks (WSNs) is a virtual layer in the paradigm of the Internet of Things (IoT). It inter-relates information associated with the physical domain to the IoT drove computational systems. WSN provides an ubiquitous access to location, the status of different entities of the environment, and data acquisition for long-term IoT monitoring. Since energy is a major constraint in the design process of a WSN, recent advances have led to project various energy-efficient protocols. Routing of data involves energy expenditure in considerable amount. In recent times, various heuristic clustering protocols have been discussed to solve the purpose. This article is an improvement of the existing stable election protocol (SEP) that implements a threshold-based cluster head (CH) selection for a heterogeneous network. The threshold maintains uniform energy distribution between member and CH nodes. The sensor nodes are also categorized into three different types called normal, intermediate, and advanced depending on the initial energy supply to distribute the network load evenly. The simulation result shows that the proposed scheme outperforms SEP and DEEC protocols with an improvement of 300% in network lifetime and 56% in throughput.

This dissertation addresses Internet background traffic generation and network intrusion detection. It is organized in two parts. Part one introduces a method to model realistic Internet background traffic and demonstrates how the models are used both in a simulation environment and in a lab environment. Part two introduces two different NID (Network Intrusion Detection) techniques and evaluates them using the modeled background traffic. To demonstrate the approach we modeled five major application layer protocols: HTTP, FTP, SSH, SMTP and POP3. The model of each protocol includes an empirical probability distribution plus estimates of application-specific parameters. Due to the complexity of the traffic, hybrid distributions (called mixture distributions) were sometimes required. The traffic models are demonstrated in two environments: NS-2 (a simulator) and HONEST (a lab environment). The simulation results are compared against the original captured data sets. Users of HONEST have the option of adding network attacks to the background. The dissertation also introduces two new template-based techniques for network intrusion detection. One is based on a template of autocorrelations of the investigated traffic, while the other uses a template of correlation integrals. Detection experiments have been performed on real traffic and attacks; the results show that the two techniques can achieve high detection probability and low false alarm in certain instances.

Most used security mechanisms in high-speed networks have been adopted without adequate quantification of their impact on performance degradation. Appropriate quantitative network models may be employed for the evaluation and prediction of ¿optimal¿ performance vs. security trade-offs. Several quantitative models introduced in the literature are based on queueing networks (QNs) and generalised stochastic Petri nets (GSPNs). However, these models do not take into consideration Performance Engineering Principles (PEPs) and the adverse impact of traffic burstiness and security protocols on performance. The contributions of this thesis are based on the development of an effective quantitative methodology for the analysis of arbitrary QN models and GSPNs through discrete-event simulation (DES) and extended applications into performance vs. security trade-offs involving infrastructure and infrastructure-less high-speed networks under bursty traffic conditions. Specifically, investigations are carried out focusing, for illustration purposes, on high-speed network routers subject to Access Control List (ACL) and also Robotic Ad Hoc Networks (RANETs) with Wired Equivalent Privacy (WEP) and Selective Security (SS) protocols, respectively. The Generalised Exponential (GE) distribution is used to model inter-arrival and service times at each node in order to capture the traffic burstiness of the network and predict pessimistic ¿upper bounds¿ of network performance. In the context of a router with ACL mechanism representing an infrastructure network node, performance degradation is caused due to high-speed incoming traffic in conjunction with ACL security computations making the router a bottleneck in the network. To quantify and predict the trade-off of this degradation, the proposed quantitative methodology employs a suitable QN model consisting of two queues connected in a tandem configuration. These queues have single or quad-core CPUs with multiple-classes and correspond to a security processing node and a transmission forwarding node. First-Come-First-Served (FCFS) and Head-of-the-Line (HoL) are the adopted service disciplines together with Complete Buffer Sharing (CBS) and Partial Buffer Sharing (PBS) buffer management schemes. The mean response time and packet loss probability at each queue are employed as typical performance metrics. Numerical experiments are carried out, based on DES, in order to establish a balanced trade-off between security and performance towards the design and development of efficient router architectures under bursty traffic conditions. The proposed methodology is also applied into the evaluation of performance vs. security trade-offs of robotic ad hoc networks (RANETs) with mobility subject to Wired Equivalent Privacy (WEP) and Selective Security (SS) protocols. WEP protocol is engaged to provide confidentiality and integrity to exchanged data amongst robotic nodes of a RANET and thus, to prevent data capturing by unauthorised users. WEP security mechanisms in RANETs, as infrastructure-less networks, are performed at each individual robotic node subject to traffic burstiness as well as nodal mobility. In this context, the proposed quantitative methodology is extended to incorporate an open QN model of a RANET with Gated queues (G-Queues), arbitrary topology and multiple classes of data packets with FCFS and HoL disciplines under bursty arrival traffic flows characterised by an Interrupted Compound Poisson Process (ICPP). SS is included in the Gated-QN (G-QN) model in order to establish an ¿optimal¿ performance vs. security trade-off. For this purpose, PEPs, such as the provision of multiple classes with HoL priorities and the availability of dual CPUs, are complemented by the inclusion of robot¿s mobility, enabling realistic decisions in mitigating the performance of mobile robotic nodes in the presence of security. The mean marginal end-to-end delay was adopted as the performance metric that gives indication on the security improvement. The proposed quantitative methodology is further enhanced by formulating an advanced hybrid framework for capturing ¿optimal¿ performance vs. security trade-offs for each node of a RANET by taking more explicitly into consideration security control and battery life. Specifically, each robotic node is represented by a hybrid Gated GSPN (G-GSPN) and a QN model. In this context, the G-GSPN incorporates bursty multiple class traffic flows, nodal mobility, security processing and control whilst the QN model has, generally, an arbitrary configuration with finite capacity channel queues reflecting ¿intra¿-robot (component-to-component) communication and ¿inter¿-robot transmissions. Two theoretical case studies from the literature are adapted to illustrate the utility of the QN towards modelling ¿intra¿ and ¿inter¿ robot communications. Extensions of the combined performance and security metrics (CPSMs) proposed in the literature are suggested to facilitate investigating and optimising RANET¿s performance vs. security trade-offs. This framework has a promising potential modelling more meaningfully and explicitly the behaviour of security processing and control mechanisms as well as capturing the robot¿s heterogeneity (in terms of the robot architecture and application/task context) in the near future (c.f. [1]. Moreover, this framework should enable testing robot¿s configurations during design and development stages of RANETs as well as modifying and tuning existing configurations of RANETs towards enhanced ¿optimal¿ performance and security trade-offs. / Ministry of Higher Education in Libya and the Libyan Cultural Attaché bureau in London

京都大学 / 新制・課程博士 / 博士(情報学) / 甲第24940号 / 情博第851号 / 新制||情||142(附属図書館) / 京都大学大学院情報学研究科通信情報システム専攻 / (主査)教授 大木 英司, 教授 原田 博司, 教授 伊藤 孝行 / 学位規則第4条第1項該当 / Doctor of Informatics / Kyoto University / DFAM

5G is an enabler to several new use cases. To support all of them, the network infrastructure must be flexible and it should adapt to the different situations. This feature is powered by SDN, NFV, and Automation, three of the main pillars on which the 5G network is built.Traditional network management approaches may not be suitable for the 5G Core Network User Plane, which holds strict requirements in terms of latency and throughput. Therefore, Artificial Intelligence agents have been proposed to manage the 5G in a more efficient manner, delivering a more optimized allocation of the resources. This approach requires real-time monitoring of the data passing by the Core Network, a feature not standardized by the current protocols. In this thesis, the design of a monitoring protocol for the 5G Core Network User Plane has been studied, focusing on precise measurement of latencies. Then, a In-band Network Telemetry (INT) framework has been implemented on top of a User Plane Function prototype. The prototype is built on top of a novel User Plane implementation, based on chaining of atomic functions called micro-UPFs (µUPFs).While the main focus of this work has been latency measurement, packet counters, byte counters and Inter Packet Gap values can be collected from the framework, proving the main KPIs of a 5G User Plane. The INT framework has been implemented through two new µUPFs, one for updating the INT metadata and one for collecting them. These metadata are attached to the user packets as GTP-U extended header, maintaining compatibility with the standard protocol. Moreover, the implemented framework allows high flexibility through dynamic tuning of the parameters, providing mechanisms to reduce the amount of telemetry data generated and, thus, the system overhead.The framework has been tested on a physical setup of four server machines, abstracting a Core Network User Plane, connected with 10 Gbps NICs. In all the tests performed, the performances of the User Plane are affected by the new functionalities only when INT metadata are inserted very frequently. The results show that is possible to monitor the three main KPIs of a 5G User Plane without heavily limiting the system performances. / 5G är en möjliggörare för flera nya användningsfall: för att stödja dem alla måste nätverksinfrastrukturen vara flexibel och den ska anpassa sig till de olika situationerna. Denna funktion drivs av SDN, NFV och Automation, tre av de viktigaste pelarna som 5G-nätverket är byggt på.Traditionella nätverkshanteringsstrategier kanske inte passar för 5G Core Network, som har strikta krav när det gäller latens och genomströmning. Därför har Artificial Intelligence-agenter föreslagits att hantera 5G på ett mer effektivt sätt, vilket ger en mer optimerad fördelning av resurserna. Detta tillvägagångssätt kräver realtidsövervakning av data som passerar via Core Network, en funktion som inte standardiseras med de aktuella protokollen.I denna avhandling har utformningen av ett övervakningsprotokoll för 5G Core Network User Plane studerats med fokus på exakt mätning av latenser. Sedan har ett in-band Network Telemetry (INT) -ramverk implementerats ovanpå en prototyp för User Plane Function. Denna prototyp utnyttjade Chain Controllerarkitekturen, en ny användarplan-implementering baserad på kedjan av atomfunktioner som kallas µUPF.Medan huvudfokuset för detta arbete har varit latensmätning, kan paketräknare, byttäknare och Inter Packet Gap-värden samlas in från ramverket, vilket bevisar de viktigaste KPI: erna i ett 5G-nätverk. INT-ramverket har implementerats genom två nya µUPF, en för att uppdatera INT-metadata och en för att samla dem. Dessa metadata är anslutna till användarpaketen som GTP-U utökad rubrik, bibehållande kompatibilitet med standardprotokollet. Dessutom tillåter det implementerade ramverket hög flexibilitet som tillåter dynamisk inställning av parametrarna, tillhandahåller mekanismer för att minska mängden telemetri-data som genereras och därmed systemomkostnaderna.Ramverket har testats på en fysisk installation av fyra servermaskiner som abstraherar ett Core Network User Plane, anslutet med 10 Gbps NIC. I samtliga tester påverkas testbäddens prestationer av de nya funktionerna först när INT-metadata sätts in mycket ofta. Resultaten visar att det är möjligt att övervaka de tre huvudsakliga KPI: erna i ett 5G-nätverk utan att starkt begränsa systemprestanda.

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The growing need for a trustworthy Future Internet demands evolutionary approaches unfettered by legacy constrains and concepts. The networking community is calling for new network architectural proposals that address the deficiencies identified in present network realizations, acknowledge the need for a trustworthy IT infrastructure, and satisfy the society's emerging and future requirements. Proposed architectures need to be founded on well-articulated design principles, account for network operational and management complexities, embrace technology and application heterogeneity, regulate network-inherent emergent behavior, and overcome shortcomings attributed to present network realizations. This dissertation presents our proposed clean-slate Concern-Oriented Reference Model (CORM) for architecting future computer networks. CORM stands as a guiding framework from which network architectures can be derived according to specific functional, contextual, and operational requirements or constraints. CORM represents a pioneering attempt within the network realm, and to our knowledge, CORM is the first reference model that is bio-inspired and derived in accordance with the Function-Behavior-Structure (FBS) engineering framework. CORM conceives a computer network as a software-dependent complex system whose design needs to be attempted in a concern-oriented bottom-up approach along two main dimensions: a vertical dimension addressing structure and configuration of network building blocks; and a horizontal dimension addressing communication and interactions among the previously formulated building blocks. For each network dimension, CORM factors the design space into function, structure, and behavior, applying to each the principle of separation of concerns for further systematic decomposition. In CORM, the network-building block is referred to as the Network Cell (NC), which represents CORM's first basic abstraction. An NC's structure and inherent behavior are bio-inspired, imitating a bacterium cell in a bacteria colony, thus it is capable of adaptation, self-organization and evolution. An NC's functional operation is defined by CORM second basic abstraction; the ACRF framework. The ACRF framework is a conceptual framework for network-concerns derived according to our interpretation of computer network requirement specifications. CORM networks are recursively synthesized in a bottom-up fashion out of CORM NCs. CORM addresses the multi-dimensionality of computer networks by modeling the network structure and behavior using a network structural template (NST), and an information flow model (IFM), respectively. Being developed according to a complex system paradigm, CORM refutes the long endorsed concept of layering, intrinsically accounts for emergent behavior, and ensures system integrity and stability. As a reference model, CORM is more typical of conventional engineering. Therefore it was validated using the FBS engineering framework. However, the behavior to be realized in CORM-based networks was substantiated and evaluated by deriving CellNet, our proposed CORM-based network architecture. CellNet-compliant protocols' behavioral adaptation and modification were illustrated and evaluated through simulation. CORM will have a profound impact on the operation and behavior of computer networks composing the Internet. By introducing awareness adaptability and evolvability as network intrinsic features, CORM-based Internet will proactively respond to changes in operational contexts, underlying technologies, and end user requirements. A major direction in CORM future work would be to detail the IFM component. / Ph. D.