Given the continuing advancement of networking applications and our increased dependence upon software-based systems, there is a pressing need to develop improved security techniques for defending modern information technology (IT) systems from malicious cyber-attacks. Indeed, anyone can be impacted by such activities, including individuals, corporations, and governments. Furthermore, the sustained expansion of the network user base and its associated set of applications is also introducing additional vulnerabilities which can lead to criminal breaches and loss of critical data. As a result, the broader cybersecurity problem area has emerged as a significant concern, with many solution strategies being proposed for both intrusion detection and prevention. Now in general, the cybersecurity dilemma can be treated as a conflict-resolution setup entailing a security system and minimum of two decision agents with competing goals (e.g., the attacker and the defender). Namely, on the one hand, the defender is focused on guaranteeing that the system operates at or above an adequate (specified) level. Conversely, the attacker is focused on trying to interrupt or corrupt the system’s operation. In light of the above, this dissertation introduces novel methodologies to build appropriate strategies for system administrators (defenders). In particular, detailed mathematical models of security systems are developed to analyze overall performance and predict the likely behavior of the key decision makers influencing the protection structure. The initial objective here is to create a reliable intrusion detection mechanism to help identify malicious attacks at a very early stage, i.e., in order to minimize potentially critical consequences and damage to system privacy and stability. Furthermore, another key objective is also to develop effective intrusion prevention (response) mechanisms. Along these lines, a machine learning based solution framework is developed consisting of two modules. Specifically, the first module prepares the system for analysis and detects whether or not there is a cyber-attack. Meanwhile, the second module analyzes the type of the breach and formulates an adequate response. Namely, a decision agent is used in the latter module to investigate the environment and make appropriate decisions in the case of uncertainty. This agent starts by conducting its analysis in a completely unknown milieu but continually learns to adjust its decision making based upon the provided feedback. The overall system is designed to operate in an automated manner without any intervention from administrators or other cybersecurity personnel. Human input is essentially only required to modify some key model (system) parameters and settings. Overall, the framework developed in this dissertation provides a solid foundation from which to develop improved threat detection and protection mechanisms for static setups, with further extensibility for handling streaming data.

Acoustic wave sensors have proven useful in many fields as primarily mass sensitive devices capable of responding to small environmental perturbations. The focus of this dissertation is the development of a new type of surface acoustic wave device with application to material property measurement, and biological and chemical sensing. This device is a combination of three independent acoustic wave devices with these waves propagated across the same area, while retaining independence of actuation and sensor function. The development of a complete sensor system, and its use and operation are presented for several example cases of chemical and biomarker sensing, and sample manipulation. These include experimental and theoretical studies for organic vapor sensing, biological moiety sensing, acoustic streaming to remove loosely bound material, and optimization of designs for these applications.

Road traffic congestion causes several problems. For instance, slow moving traffic in congested regions poses a safety hazard to vehicles approaching the congested region and increased commuting times lead to higher transportation costs and increased pollution.The work carried out in this thesis aims to detect and track road traffic congestion in real time. Real-time road congestion detection is important to allow for mechanisms to e.g. improve traffic safety by sending advanced warnings to drivers approaching a congested region and to mitigate congestion by controlling adaptive speed limits. In addition, the tracking of the evolution of congestion in time and space can be a valuable input to the development of the road network. Traffic sensors in Stockholm’s road network are represented as a directed weighted graph and the congestion detection problem is formulated as a streaming graph processing problem. The connected components algorithm and existing graph processing algorithms originally used for community detection in social network graphs are adapted for the task of road congestion detection. The results indicate that a congestion detection method based on the streaming connected components algorithm and the incremental Dengraph community detection algorithm can detect congestion with accuracy at best up to 94% for connected components and up to 88% for Dengraph. A method based on hierarchical clustering is able to detect congestion while missing details such as shockwaves, and the Louvain modularity algorithm for community detection fails to detect congested regions in the traffic sensor graph.Finally, the performance of the implemented streaming algorithms is evaluated with respect to the real-time requirements of the system, their throughput and memory footprint. / Vägtrafikstockningar orsakar flera problem. Till exempel utgör långsam trafik i överbelastade områden en säkerhetsrisk för fordon som närmar sig den överbelastade regionen och ökade pendeltider leder till ökade transportkostnader och ökad förorening.Arbetet i denna avhandling syftar till att upptäcka och spåra trafikstockningar i realtid. Detektering av vägtrafiken i realtid är viktigt för att möjliggöra mekanismer för att t.ex. förbättra trafiksäkerheten genom att skicka avancerade varningar till förare som närmar sig en överbelastad region och för att mildra trängsel genom att kontrollera adaptiva hastighetsgränser. Dessutom kan spårningen av trängselutveckling i tid och rum vara en värdefull inverkan på utvecklingen av vägnätet. Trafikavkännare i Stockholms vägnät representeras som en riktad vägd graf och problemet med överbelastningsdetektering är formulerat som ett problem med behandling av flödesgrafer. Den anslutna komponentalgoritmen och befintliga grafbehandlingsalgoritmer som ursprungligen användes för communitydetektering i sociala nätgravar är anpassade för uppgiften att detektera vägtäthet. Resultaten indikerar att en överbelastningsdetekteringsmetod baserad på den strömmande anslutna komponentalgoritmen och den inkrementella Dengraph communitydetekteringsalgoritmen kan upptäcka överbelastning med noggrannhet i bästa fall upp till 94% för anslutna komponenter och upp till 88% för Dengraph. En metod baserad på hierarkisk klustring kan detektera överbelastning men saknar detaljer som shockwaves, och Louvain modularitetsalgoritmen för communitydetektering misslyckas med att detektera överbelastade områden i trafiksensorns graf.Slutligen utvärderas prestandan hos de implementerade strömmalgoritmerna med hänsyn till systemets realtidskrav, deras genomströmning och minnesfotavtryck.

Streaming video has strong availability requirements, while for livestreamed video low latency becomes an additional significant factor. For large-scale video streaming the streaming service must be able to scale in and out in order to conform to the interchanging demands of users. Video streaming demonstrates heavily fluctuating load, where number of viewers may increase exponentially within a few minutes. In combination with the high availability guarantees suggests that the problem is non-trivial.This thesis covers the issues of providing a cost-effective distributed live video streaming application that guarantees a seamless user experience. For instance, there are multiple channels, in the order of hundred, where each has an ever changing popularity and furthermore, users are able to watch content which was streamed for some number of hours ago. Thus, the system must both provide cached streams as well as the live-stream.In this thesis, an elasticity-providing solution for live video streaming is presented. The solution is a combination of rule-based reactive algorithm for channel distribution and a predictive method for VM instance provisioning. The results show that the algorithm, when simulating 15 channels with 80000 viewers and 50 instances, keeps underallocation of channels at less than 1% while achieving significant reduction of about 125% for channel occurrences and thereby bandwidth consumption compared to the previous channel distribution solution. As the video streaming service scales in terms of number of channels and VM instances, the reduction factor increases. / Videoströmmingstjänster har starka krav på tillgänglighet, medan för live-strömmad video blir låg latens också signifikant. För storskalig videoströmmning måste tjänsten kunna skala in och ut för att överensstämma med användarnas växlande krav. Videoströmmning visar starkt varierande belastning, där antalet tittare kan öka exponentiellt inom några minuter. I kombination med de höga tillgänglighetsgarantierna antyder att problemet inte är trivialt.Denna avhandling täcker problemen med att tillhandahålla en kostnadseffektiv distribuerad live-videoströmmningstjänst som garanterar en sömlös användarupplevelse. Till exempel finns det flera kanaler, i storleksordningen hundra, där var och en har en ständigt förändrande popularitet. Därtill tillkommer dessutom att användare har möjligheten titta på innehåll som strömmats för några timmar sedan. Således måste systemet både tillhandahålla cachade strömmar såväl som direktsändning.I denna avhandling presenteras en elasticitetslösning för live video streaming. Lösningen är en kombination av en regelbaserad reaktiv algorithm för kanaldistribution och en prediktiv metod för VM-instans allokering. Resultaten visar att algoritmen, vid en simulering med 15 kanaler, 80000 tittare och 50 instanser, klarar att hålla underallokering av kanaler lägre än 1% samtidigt som totala antalet kanalinstanser reduceras med ungefär 125% jämfört med den tidigare kanaldistributionslösningen. Allteftersom videostreamingstjänsten skalar i antal kanaler och VM-instanser ökar reduktionsfaktorn ytterligare.

Large-scale graph-structured datasets are growing at an increasing rate. Social network graphs are an example of these datasets. Processing large-scale graphstructured datasets are central to many applications ranging from telecommunication to biology and has led to the development of many parallel graph algorithms. Performance of parallel graph algorithms largely depends on how the underlying graph is partitioned. In this work, we focus on studying streaming vertex-cut graph partitioning algorithms where partitioners receive a graph as a stream of vertices and edges and assign partitions to them on their arrival once and for all. Some of these algorithms maintain a state during partitioning. In some cases, the size of the state is so huge that it cannot be kept in a single machine memory. In many real world scenarios, several instances of a streaming graph partitioning algorithm are run simultaneously to improve the system throughput. However, running several instances of a partitioner drops the partitioning quality considerably due to the incomplete information of partitioners. Even frequently sharing states and its combination with buffering mechanisms does not completely solves the problem because of the heavy communication overhead produced by partitioners. In this thesis, we propose an algorithm which tackles the problem of low scalability and performance of existing streaming graph partitioning algorithms by providing an efficient way of sharing states and its combination with windowing mechanism. We compare state-of-the-art streaming graph partitioning algorithms with our proposed solution concerning performance and efficiency. Our solution combines a batch processing method with a shared-state mechanism to achieve both an outstanding performance and a high partitioning quality. Shared state mechanism is used for sharing states of partitioners. We provide a robust implementation of our method in a PowerGraph framework. Furthermore, we empirically evaluate the impact of partitioning quality on how graph algorithms perform in a real cloud environment. The results show that our proposed method outperforms other algorithms in terms of partitioning quality and resource consumption and improves partitioning time considerably. On average our method improves partitioning time by 23%, decreases communication load by 15% and increase memory consumption by only 5% compared to the state-of-the-art streaming graph partitioning.

This study deals with the writing of senior students in the subject English from two ACT secondary colleges. Whilst the written work analysed is from students enrolled in courses accredited for tertiary entrance, the ACT'S high retention rate and students' tendency to avoid 'non-tertiary' courses, ensures that the scripts analysed are wide-ranging. Broadly, this study rests on the theoretical approach to language and learning that came out of Dartmouth: that which is associated with James Britton. Its focus is twofold. In Volume I it presents a heuristic, describing its development and discussing the thinking, and learning students appear to do - and the writing they do - as a result of using it. The heuristic is called 'streaming' by the students who use it and is based on Vygotsky's notion of 'Inner Speech'. A key phrase that expresses a powerful or rich idea about the subject being studied is used as a starting point for student thinking. Students explore the layers of cognitive and affective meaning encapsulated in the idea, and perhaps extend the idea, in writing. The writing is very rough, and an act of thought whereby the meaning of the phrase is accommodated, rather than a communication to others. Students are asked NOT to think prior to setting pen to paper, but to let their writing 'bring their thought out of the shadows' by giving words to it. This avoids superficial or cliched response because the process of 'thinking out loud in writing' allows an interplay of cognitive and affective meaning that seems to lead students in to abstract thinking, generally by way of poetic abstraction. The 'streaming' that students do becomes the basis for further discussion or writing in a variety of forms. Volume II is given over to an explication, and use, of Graham Little's development and refinement of an analytical model for investigating language use. Based on the variables of situation, function and form, it enables the empirical analysis of 237 examples of writing from students who had used the heuristic presented in Volume I. The analysis indicates that students who use the heuristic write differently from students who do not. Their writing shows a wide range of function and form and achieves unusually high levels of abstraction. The thinking and writing that students do when using the heuristic is usually realised poetically and used as a basis for further writing. The range within the student writing indicates a high degree of language competence whereby students are able to write in different forms. Little's analytical model is a simple and powerful means of quantifying elements of school language in order to make qualitative judgements that are sensitive to the complex and holistic nature of language development and use.

網路技術發展的日新月異帶領了眾多新網路服務的崛起，例如即時影音串流這類的多媒體服務。但即時影音串流服務所產生的龐大資料流和傳輸延遲時間的嚴格限制也隨之而來的為網路環境帶來許多挑戰，在這些條件下，傳統Server-client拓樸架構將client要求的影音資料以單一鏈結傳輸時，常會因為頻寬不足而面臨嚴重的封包遺失，或是資料流擁擠造成的額外傳輸延遲使得封包無法達到即時性的需求。P2P網路擁有server-client架構所難以達到的規模伸縮性，且對於節點、鏈結失效所引起的傳輸錯誤也較能容忍，更重要的是，它有效的分散了原本負載在少數link上的龐大資料流。因此P2P架構近年來風行於即時影音串流服務。 目前P2P網路的拓樸多是隨意形成，當網路成員規模龐大時，由傳送端出發到遠方的接收端，途中可能經過無數的鏈結，每一個鏈結都會由於頻寬的不足使得資料流遭受某種程度的品質損害，另一方面，對即時影音服務而言，若資料流的累積延遲時間超出可容忍範圍時，無法為使用者接受。 本研究嘗試找出一個較好的拓樸用以傳輸多媒體資料流，使得位於最遠端節點的累積延遲亦能為使用者接受，且資料品質的損害程度最小。我們將之建置成一NP-Complete複雜度的問題模型，名為MLDST。而解法則是修改Dijkstra single-source shortest-path演算法，並加上每個節點承擔下游節點數量及延遲時間限制而來。我們以PlanetLab環境在實際的網路上進行實驗，證實我們的演算法比傳統的Minimum-Spanning Tree及shortest path spanning tree有更好的影像品質。 / Numerous new network services arise with the advanced development of network technologies, such as real-time multimedia streaming services. But challenges to network environment come along with the enormous traffic of data flows and rigorous restriction to transmission delay of real-time multimedia streaming services. Under this circumstance, conventional server-client topology suffers from serious packet loss and packet delay due to the overload of servers and their accessing links. Also, extra transmission delay may make packets fail to meet the requirement of real-timed services. Peer-to-peer network is more scalable than server-client model, and is much more tolerable to the transmission errors caused by node or link failures. More importantly, it effectively distributes load from the server to peers. As a consequence, peer-to-peer service architecture becomes very popular for real-time multimedia streaming services recently. Peer-to-peer networks are mostly formed in random fashion. As the size of network grows, packets may have to travel through numerous links to reach far-end receivers. The quality of data may be damaged by insufficient bandwidth of links. For real-time multimedia services, it is not acceptable to users if the cumulated packet delay exceeds a tolerable limit. Our research is trying to find a better topology to transmit multimedia data flows which makes the cumulated delay of the most-far-end user be tolerable and the damage of data quality is minimized. The problem is modeled as a MLDST problem, which is a NP-Complete problem. To solve the problem, we modified Dijkstra’s single-source shortest-path algorithm by bounding the node degree and adding delay constraint. The experiments were carried out on real network environment through PlanetLab. Experiments show that our algorithm outperforms traditional MST and shortest path spanning tree.

It has been said that the XXI century is the century of people; social media, web2.0 applications and other technology breakthroughs have made the world every single day a smaller place. iChina forum takes advantage of all available existing technology to provide seasoned China experts with a platform that help them share their knowledge with the world. Our purpose is to enhance the mutual understanding between east and west towards and harmonic future. This business plan explains how through the use of open source development tools, a network of partnerships and social media marketing a low cost internet startup is possible.

Thermoacoustics is a field of study which includes devices purpose-built to exploit the phenomenal interaction between heat and sound. Thermoacoustics has been demonstrated as an effective technology which can potentially serve a variety of purposes such as cryogenics, cost-effective domestic refrigeration or electricity generation, without adverse environmental impact or commercial drawbacks such as expensive construction or maintenance costs or high part counts. The mechanisms by which thermoacoustic devices operate at low amplitudes have been identified and effective design tools and methods are available, but the precise heat and mass transfer which occurs deep inside the core of thermoacoustic devices at high amplitudes cannot at present be precisely determined experimentally, and to date have been estimated using only relatively simple or one-dimensional computational domains. It is expected that thermoacoustic devices will need to operate at relatively high pressure amplitudes for commercial and practical applications, to achieve power densities similar to competing technologies. Clearly, advancement of these models and the methods used to investigate them will enable a better understanding of the precise heat and mass transfer that occurs within such devices. Previous numerical studies have modelled a ‘thermoacoustic couple’ which consists of a single or several plates (often modelled with zero thickness) and channels within an oscillatory pressure field. In this thesis several improvements to the ‘thermoacoustic couple’ modelspace are introduced and modelled, and compared with published results. Using the commercial CFD software Fluent, a two-dimensional, segregated and second-order implicit numerical model was developed which solves equations for continuity of mass, momentum and energy. These equations were computed using second-order and double-precision discretisation of time, flow variables and energy. A computational domain is presented which is capable of modelling plates of zero or non-zero thickness, is ‘self-resonant’ and able to capture the entrance and exit effects at the stack plate edges. Studies are presented in which the acoustic pressure amplitude, the thickness of the plate (‘blockage ratio’) and the shape of the plate are varied to determine their influence upon the rate of effective heat transfer, flow structure and overall efficiency. The modelling of thermoacoustic couples with finite thickness presented in this thesis demonstrates that the finite thickness produces new results which show significant disturbances to the flow field and changes to the expected rate and distribution of heat flux along the stack plate. Results indicate that the thickness of the plate, t[subscript]s, strongly controls the generation of vortices outside the stack region and perturbs the flow structure and heat flux distribution at the extremities of the plate. Increases in t[subscript]s are also shown to improve the integral of the total heat transfer rate but at the expense of increased entropy generation. Another contribution of this thesis is the study of the effect that leading and trailing edge shapes of stack plates have on the performance of a thermoacoustic couple. In practice, typical parallel or rectangular section stack plates do not have perfectly square edges. The existing literature considers only rectangular or zero-thickness (1-D) plates. Hence a study was performed to evaluate the potential for gains in performance from the use of non-rectangular cross sections, such as rounded, aerofoil or bulbous shaped edges. Consideration of various types of stack plate edges show that performance improvements can be made from certain treatments to the stack plate tips or if possible, stack plate profiles. This thesis also considers the influence of thermophysical properties and phenomena associated with practical thermoacoustic devices to investigate the applicability of the numerical model to experimental outcomes. Comparisons made between results obtained using the numerical model, linear numerical formulations and experimental results suggest that the numerical model allows comparative study of various thermoacoustic systems for design purposes but is not yet of sufficient scope to fully characterise a realistic system and predict absolute levels of performance. However, the presented method of modelling thermoacoustic couples yields increased insight and detail of flow regimes and heat transportation over previous studies. / http://proxy.library.adelaide.edu.au/login?url= http://library.adelaide.edu.au/cgi-bin/Pwebrecon.cgi?BBID=1316904 / Thesis (Ph.D.) -- University of Adelaide, School of Mechanical Engineering, 2008

Dans cette thèse, nous proposons des solutions pour le chargement progressif et le rendu adaptatif de vastes terrains. Cela peut servir notamment à visualiser la Terre en 3D sur un ordinateur en chargeant les données depuis une immense base de données via un réseau. Dans la première partie de cette thèse, nous introduisons une solution générique pour manipuler des cartes d'échantillons de taille quelconque depuis un serveur jusqu'à un système de rendu client. Nos méthodes s'adaptent aux performances du réseau et du rendu et évitent de traiter des données redondantes. Dans une deuxième partie, nous utilisons cette solution pour permettre le rendu 3D temps réel de vastes terrains texturés. De plus, nous supportons des terrains planétaires et réduisons les incohérences visuelles dues à la projection cartographique et à la précision du rendu. Enfin, nous proposons des algorithmes permettant de créer des bases de données serveur à partir d'immenses cartes d'échantillons.