In Automotive Industries, to be confident regarding the success of a planned operation, performing accurate methods in order to detect abnormal operating conditions, known as faults, is crucial. An effective method for diagnosis and fault recognition ensures the safety of the operation, reduces manufacturing cost and any other potential impacts. In addition, mobile solutions have been widely adopted among automotive manufactures during recent years and they have taken full advantage of mobile strategies. Accordingly, it is necessary for there to be a future-proof plan to control the diagnostic operations in advance. In this thesis, the immediate objective has been to offer a future-proof and user-friendly solution to assist engineers and service technicians in the monitoring, detecting, and diagnosing of faults on Toyota/BT/CESAB branded trucks. A mobile cross-platform framework is used to develop the diagnostic mobile solution which is not only able to be deployed on Android and iOS mobile platforms, but also provides wireless communication between truck machines and mobile devices through Bluetooth and Wi-Fi ad hoc technologies. The diagnostic mobile tool is capable of processing real-time controller area network messages and visualizing the condition of different sensors in a more user-friendly way through rich hybrid and client-side web user interfaces. The experience of evaluating a cross-platform diagnostic tool on different mobile operating systems proved that cross-platform mobile development methodology can be a reliable technique for developing projects that essentially require real-time data processing. In addition, it indicates that Apple iOS offers a better runtime performance than Google Android for the current tool.

In recent years, Internet and IP technologies have made inroads into almost every commu- nication market ranging from best-effort services such as email and Web, to soft real-time applications such as VoIP, IPTV, and video. However, providing a transport service over IP that meets the timeliness and availability requirements of soft real-time applications has turned out to be a complex task. Although network solutions such as IntServ, DiffServ, MPLS, and VRRP have been suggested, these solutions many times fail to provide a trans- port service for soft real-time applications end to end. Additionally, they have so far only been modestly deployed. In light of this, this thesis considers transport protocols for soft real-time applications. Part I of the thesis focuses on the design and analysis of transport protocols for soft real- time multimedia applications with lax deadlines such as image-intensive Web applications. Many of these applications do not need a completely reliable transport service, and to this end Part I studies so-called partially reliable transport protocols, i.e., transport protocols that enable applications to explicitly trade reliability for improved timeliness. Specifically, Part I investigates the feasibility of designing retransmission-based, partially reliable transport protocols that are congestion aware and fair to competing traffic. Two transport protocols are presented in Part I, PRTP and PRTP-ECN, which are both extensions to TCP for partial reliability. Simulations and theoretical analysis suggest that these transport protocols could give a substantial improvement in throughput and jitter as compared to TCP. Additionally, the simulations indicate that PRTP-ECN is TCP friendly and fair against competing congestion- aware traffic such as TCP flows. Part I also presents a taxonomy for retransmission-based, partially reliable transport protocols. Part II of the thesis considers the Stream Control Transmission Protocol (SCTP), which was developed by the IETF to transfer telephony signaling traffic over IP. The main focus of Part II is on evaluating the SCTP failover mechanism. Through extensive experiments, it is suggested that in order to meet the availability requirements of telephony signaling, SCTP has to be configured much more aggressively than is currently recommended by IETF. Fur- thermore, ways to improve the transport service provided by SCTP, especially with regards to the failover mechanism, are suggested. Part II also studies the effects of Head-of-Line Blocking (HoLB) on SCTP transmission delays. HoLB occurs when packets in one flow block packets in another, independent, flow. The study suggests that the short-term effects of HoLB could be substantial, but that the long-term effects are marginal.

This thesis describes novel machine learning techniques specifically designed for use in real-time embedded systems. The techniques directly address three major requirements of such learning systems. Firstly, learning must be capable of being achieved incrementally, since many applications do not have a representative training set available at the outset. Secondly, to guarantee real-time performance, the techniques must be able to operate within a deterministic and limited time bound. Thirdly, the memory requirement must be limited and known a priori to ensure the limited memory available to hold data in embedded systems will not be exceeded. The work described here has three principal contributions. The frequency table is a data structure specifically designed to reduce the memory requirements of incremental learning in embedded systems. The frequency table facilitates a compact representation of received data that is sufficient for decision tree generation. The frequency table decision tree (FTDT) learning method provides classification performance similar to existing decision tree approaches, but extends these to incremental learning while substantially reducing memory usage for practical problems. The incremental decision path (IDP) method is able to efficiently induce, from the frequency table of observations, the path through a decision tree that is necessary for the classification of a single instance. The classification performance of IDP is equivalent to that of existing decision tree algorithms, but since IDP allows the maximum number of partial decision tree nodes to be determined prior to the generation of the path, both the memory requirement and the execution time are deterministic. In this work, the viability of the techniques is demonstrated through application to realtime mobile robot navigation.

We develop and test a probabilistic real-time streamflow-forecasting platform, Multimodel and Multiproduct Streamflow Forecasting (MMSF), that uses information provided by a suite of hydrologic models and satellite precipitation products (SPPs). The SPPs are bias-corrected before being used as inputs to the hydrologic models, and model calibration is carried out independently for each of the model-product combinations (MPCs). Forecasts generated from the calibrated models are further bias-corrected to compensate for the deficiencies within the models, and then probabilistically merged using a variety of model averaging techniques. Use of bias-corrected SPPs in streamflow forecasting applications can overcome several issues associated with sparsely gauged basins and enable robust forecasting capabilities. Bias correction of streamflow significantly improves the forecasts in terms of accuracy and precision for all different cases considered. Results show that the merging of individual forecasts from different MPCs provides additional improvements. All the merging techniques applied in this study produce similar results, however, the Inverse Weighted Averaging (IVA) proves to be slightly superior in most cases. We demonstrate the implementation of the MMSF platform for real-time streamflow monitoring and forecasting in the Mara River basin of Africa (Kenya & Tanzania) in order to provide improved monitoring and forecasting tools to inform water management decisions.

Real-Time Strategy (RTS) is a sub-genre of strategy games which is running in real-time, typically in a war setting. The player use workers to gather resources, which in turn is used for creating new buildings, training combat units and build upgrades and research. The game is won when all buildings of the opponents have been destroyed. The numerous tasks that need to be handled in real-time can be very demanding for a player. Computer players (bots) for RTS games face the same challenges, and also have to navigate units in highly dynamic game worlds and deal with other low-level tasks such as attacking enemy units within fire range. This thesis is a compilation of nine papers. The first four papers deal with navigation in dynamic game worlds, which can be very complex and resource demanding. Typically it is solved by using pathfinding algorithms. We investigate an alternative approach based on Artificial Potential Fields and show how a PF based navigation system can be used without any need of pathfinding algorithms. In RTS games players usually have a limited visibility of the game world, known as Fog of War. Bots on the other hand often have complete visibility to aid the AI in making better decisions. In a paper we show that a Multi-Agent PF based bot with limited visibility can match and even surpass bots with complete visibility in some RTS scenarios. In the sixth paper we show how the bot can be extended and used in a full RTS scenario with base building and unit construction. This is followed by a paper where we propose a flexible and expandable RTS game architecture that can be modified at several levels of abstraction to test different techniques and ideas. The proposed architecture is implemented in the famous RTS game StarCraft, and we show how the high-level architecture goals of flexibility and expandability can be achieved. The last two papers present two studies related to gameplay experience in RTS games. In games players usually have to select a static difficulty level when playing against computer opponents. In the first study we use a bot that during runtime can adapt the difficulty level depending on the skills of the opponent, and study how it affects the perceived enjoyment and variation in playing against the bot. To create bots that are interesting and challenging for human players a goal is often to create bots that play more human-like. In the second study we asked participants to watch replays of recorded RTS games between bots and human players. The participants were asked to guess and motivate if a player was controlled by a human or a bot. This information was then used to identify human-like and bot-like characteristics for RTS game players.

International Telemetering Conference Proceedings / October 17-20, 1994 / Town & Country Hotel and Conference Center, San Diego, California / A demonstration of near real-time performance assessment for the Program Executive Officer for Cruise Missiles Project and Unmanned Aerial Vehicles, Cruise Test Directorate, PEO(CU)-CT, was conducted between 22 March 1994 through 4 May 1994. The demonstration involved the temporary installation of a portable TOMAHAWK telemetry recording and telecommunications capability at the Air Force Development Test Center range at Eglin Air Force Base, Florida and a receiving telecommunications capability at the Naval Warfare Assessment Division (NWAD), Corona, California. The system was successfully used on 4 May 1994 to record TOMAHAWK missile telemetry data in real-time in support of Operational Test Launch (OTL)-163 and to transfer that data to the weapons system performance analysts at NWAD in near real-time. The one hour and three minutes of flight data was compressed in real-time as it was recorded, then, after completion of the flight, the data was transferred to NWAD in about 12 minutes using the switched 56 kbps network. Additional transfers using the Defense Commercial Telecommunications Network (DCTN) were also conducted. All transfers were secured using ethernet encryptors. The data was processed by both the NWAD telemetry ground station and the TOMAHAWK workstation complex. This paper quantifies the results and documents the lessons learned from this demonstration and proposes a standardized system design for possible implementation at TOMAHAWK test range sites in the future. A position is taken that for situations where the remote site (e.g. other range or data analysis site) does not exercise direct operational control over the test/host range, near real-time data relay solutions are not only as adequate, but in many cases are preferable to real-time solutions.

International Telemetering Conference Proceedings / October 26-29, 1992 / Town and Country Hotel and Convention Center, San Diego, California / The parallel processing technology has been widely applied to many science and engineering technical fields, also to telemetry. In particular, telemetry develops towards the trend of large capacity, high rate, several data streams and programmable formats. This sets a still higher demand on processing for real-time multilexing telemetry data. On the basis of analyzing of the characteristics of telemetry data processing (TDP), the parallel processing conception and methods are adopted, countering multiiple-channel data streams of different objects, several architectures of parallel processing for real-time multiplexing telemetry data are presented. It makes better use of the concurrency during the process of TDP and handles the telemetry information effectively in every processing level of the whole telemetering information processing system. The paper shows the property comparison of these parallel processing architectures and main features too. Experiments have indicated that it is an economical and effective method to improve the performance of telemetry information processing system by using paralle processing architecture which is based on concurrency of telemetry data processing.

Une définition des systèmes temps réel est que leur correction dépend de la correction fonctionnelle mais aussi du temps d'exécution des différentes opérations. Les propriétés temps réels sont alors exprimées comme des contraintes temporelles sur les opérations du système. Nous proposons dans cette thèse un autre point de vue où la correction est définie relativement à la validité temporelle des valeurs prises par les variables du système et aux flots de données qui parcourent le système. Pour définir ces conditions de validité, nous nous intéressons au rythme de mise à jour des variables mais aussi aux liens entre les valeurs des différentes variables du système. Une relation dite d'observation est utilisée pour modéliser les communications et les calculs du système qui définissent les liens entre les variables. Un ensemble de relations d'observation modélise l'architecture et les flots de données du système en décrivant les chemins de propagation des valeurs dans le système. Les propriétés temps réels sont alors exprimées comme des contraintes sur ces chemins de propagation permettant d'assurer la validité temporelle des valeurs prises par les variables. La validité temporelle d'une valeur est définie selon la validité temporelle des valeurs des autres variables dont elle dépend et selon le décalage temporel logique ou événementiel introduit par les communications ou les calculs le long des chemins de propagation. Afin de prouver la satisfiabilité d'une spécification définie par une telle architecture et de telles propriétés, nous construisons un système de transitions à état fini bisimilaire à la spécification. L'existence de ce système fini est justifiée par des bornes sur le décalage temporel entre les variables du système. Il est alors possible d'explorer les exécutions définies par ce système de transitions afin de prouver l'existence d'exécutions infinies satisfaisant la spécification. / Real time systems are usually defined as systems where the total correctness of an operation depends not only on its logical correctness, but also on the execution time. Under this definition, time constraints are defined according to system operations. Another definition of real time systems is centered on data where the correctness of a system depends on the timed correctness of its data and of the data flows across the system. i.e. we expect the values taken by the variable to be regularly renewed and to be consistent with the environment and the other variables. I propose a modeling framework based on this later definition. This approach allows users to focus on specifying time constraints attached to data and to postpone task and communication scheduling matters. The timed requirements are not expressed as constraints on the implantation mechanism, but on the relations binding the system’s variables. These relations between data are expressed in terms of a so called observation relation which abstracts the relation between the values that are taken by some variables, the set of sources and the image. This relation abstracts the communication as well as the computational operations and a set of observation relations models the system architecture and the data flows by defining the paths along which values of sources are propagated to build the values of an image. The real time properties are expressed as constraints on the propagation paths and state the temporal validity of the values. This temporal validity is defined by the time shift between the source and the image, and specifies the propagation of timely sound values along the path to build temporally correct values of the system outputs. At this level of abstraction, the designer gives a specification of the system based on timed properties about the timeline of data such as their freshness, stability, latency etc. In order to prove the feasibility of an observation-based model, a finite state transition system bi-similar with the specification is built. The existence of a finite bi-similar system is deduced from the bounded time shift between the variables. The existence of an infinite execution in this system proves the feasibility of the specification.

<p>Validerat; 20160705 (global_studentproject_submitter)</p>

Cyber-physical systems (CPS) integrate sensing, computing, communication and actuation capabilities to monitor and control operations in the physical environment. A key requirement of such systems is the need to provide predictable real-time performance: the timing correctness of the system should be analyzable at design time with a quantitative metric and guaranteed at runtime with high assurance. This requirement of predictability is particularly important for safety-critical domains such as automobiles, aerospace, defense, manufacturing and medical devices. The work in this dissertation focuses on the challenges arising from the use of modern multi-core platforms in CPS. Even as of today, multi-core platforms are rarely used in safety-critical applications primarily due to the temporal interference caused by contention on various resources shared among processor cores, such as caches, memory buses, and I/O devices. Such interference is hard to predict and can significantly increase task execution time, e.g., up to 12 commodity quad-core platforms. To address the problem of ensuring timing predictability on multi-core platforms, we develop novel analytical and systems techniques in this dissertation. Our proposed techniques theoretically bound temporal interference that tasks may suffer from when accessing shared resources. Our techniques also involve software primitives and algorithms for real-time operating systems and hypervisors, which significantly reduce the degree of the temporal interference. Specifically, we tackle the issues of cache and memory contention, locking and synchronization, interrupt handling, and access control for computational accelerators such as general-purpose graphics processing units (GPGPUs), all of which are crucial to achieving predictable real-time performance on a modern multi-core platform. Our solutions are readily applicable to commodity multi-core platforms, and can be used not only for developing new systems but also migrating existing applications from single-core to multi-core platforms.