Handling Emergent Conflicts in Adaptable Rule-based Sensor Networks

This thesis presents a study into conflicts that emerge amongst sensor device rules when such devices are formed into networks. It describes conflicting patterns of communication and computation that can disturb the monitoring of subjects, and lower the quality of service. Such conflicts can negatively affect the lifetimes of the devices and cause incorrect information to be reported. A novel approach to detecting and resolving conflicts is presented. The approach is considered within the context of home-based psychiatric Ambulatory Assessment (AA). Rules are considered that can be used to control the behaviours of devices in a sensor network for AA. The research provides examples of rule conflict that can be found for AA sensor networks. Sensor networks and AA are active areas of research and many questions remain open regarding collaboration amongst collections of heterogeneous devices to collect data, process information in-network, and report personalised findings. This thesis presents an investigation into reliable rule-based service provisioning for a variety of stakeholders, including care providers, patients and technicians. It contributes a collection of rules for controlling AA sensor networks. This research makes a number of contributions to the field of rule-based sensor networks, including areas of knowledge representation, heterogeneous device support, system personalisation, and in particular, system reliability. This thesis provides evidence to support the conclusion that conflicts can be detected and resolved in adaptable rule-based sensor networks

An improved locator identifier split architecture (ILISA) to enhance mobility

The increased use of mobile devices has prompted the need for efficient mobility management protocols to ensure continuity of communication sessions as users switch connection between available wireless access networks in an area. Locator/Identifier (LOC/ID) split architectures are designed to, among other functions, enable the mobility of nodes on the Internet. The protocols based on these architectures enable mobility by ensuring that the identifier (IP address) used for creating a communication session is maintained throughout the lifetime of the session and only the location of a mobile node (MN) is updated as the device moves. While the LOC/ID protocols ensure session continuity during handover, they experience packet loss and long service disruption times as the MN moves from one access network to another. The mobility event causes degradation of throughput, poor network utilisation, and affects the stability of some applications, such as video players. This poor performance was confirmed from the experiments we conducted on a laboratory testbed running Locator Identifier Separation Protocol MN (LISP-MN) and Mobile IPv6 (MIPv6). The MIPv6, as the standardised IETF mobility protocol, was used to benchmark the performance of LISP-MN. The poor performance recorded is owed to the design of the LISP-MN’s architecture, with no specific way of handling packets that arrive during handover events. Our main aim in this thesis is to introduce an Improved Locator/Identifier Split Architecture (ILISA) designed to enhance the mobility of nodes running a LOC/ID protocol by mitigating packet loss and reducing service disruption in handovers. A new network node, Loc-server, is central to the new architecture with the task of buffering incoming packets during handover and forwarding the packets to the MN on the completion of the node’s movement process. We implemented ILISA with LISP-MN on a laboratory testbed to evaluate its performance in different mobility scenarios. Our experimental results show a significant improvement in the mobility performance of MNs as reflected by the different network parameters investigated

Using spatiotemporal patterns to qualitatively represent and manage dynamic situations of interest : a cognitive and integrative approach

Les situations spatio-temporelles dynamiques sont des situations qui évoluent dans l’espace et dans le temps. L’être humain peut identifier des configurations de situations dans son environnement et les utilise pour prendre des décisions. Ces configurations de situations peuvent aussi être appelées « situations d’intérêt » ou encore « patrons spatio-temporels ». En informatique, les situations sont obtenues par des systèmes d’acquisition de données souvent présents dans diverses industries grâce aux récents développements technologiques et qui génèrent des bases de données de plus en plus volumineuses. On relève un problème important dans la littérature lié au fait que les formalismes de représentation utilisés sont souvent incapables de représenter des phénomènes spatiotemporels dynamiques et complexes qui reflètent la réalité. De plus, ils ne prennent pas en considération l’appréhension cognitive (modèle mental) que l’humain peut avoir de son environnement. Ces facteurs rendent difficile la mise en œuvre de tels modèles par des agents logiciels. Dans cette thèse, nous proposons un nouveau modèle de représentation des situations d’intérêt s’appuyant sur la notion des patrons spatiotemporels. Notre approche utilise les graphes conceptuels pour offrir un aspect qualitatif au modèle de représentation. Le modèle se base sur les notions d’événement et d’état pour représenter des phénomènes spatiotemporels dynamiques. Il intègre la notion de contexte pour permettre aux agents logiciels de raisonner avec les instances de patrons détectés. Nous proposons aussi un outil de génération automatisée des relations qualitatives de proximité spatiale en utilisant un classificateur flou. Finalement, nous proposons une plateforme de gestion des patrons spatiotemporels pour faciliter l’intégration de notre modèle dans des applications industrielles réelles. Ainsi, les contributions principales de notre travail sont : Un formalisme de représentation qualitative des situations spatiotemporelles dynamiques en utilisant des graphes conceptuels. ; Une approche cognitive pour la définition des patrons spatio-temporels basée sur l’intégration de l’information contextuelle. ; Un outil de génération automatique des relations spatiales qualitatives de proximité basé sur les classificateurs neuronaux flous. ; Une plateforme de gestion et de détection des patrons spatiotemporels basée sur l’extension d’un moteur de traitement des événements complexes (Complex Event Processing).Dynamic spatiotemporal situations are situations that evolve in space and time. They are part of humans’ daily life. One can be interested in a configuration of situations occurred in the environment and can use it to make decisions. In the literature, such configurations are referred to as “situations of interests” or “spatiotemporal patterns”. In Computer Science, dynamic situations are generated by large scale data acquisition systems which are deployed everywhere thanks to recent technological advances. Spatiotemporal pattern representation is a research subject which gained a lot of attraction from two main research areas. In spatiotemporal analysis, various works extended query languages to represent patterns and to query them from voluminous databases. In Artificial Intelligence, predicate-based models represent spatiotemporal patterns and detect their instances using rule-based mechanisms. Both approaches suffer several shortcomings. For example, they do not allow for representing dynamic and complex spatiotemporal phenomena due to their limited expressiveness. Furthermore, they do not take into account the human’s mental model of the environment in their representation formalisms. This limits the potential of building agent-based solutions to reason about these patterns. In this thesis, we propose a novel approach to represent situations of interest using the concept of spatiotemporal patterns. We use Conceptual Graphs to offer a qualitative representation model of these patterns. Our model is based on the concepts of spatiotemporal events and states to represent dynamic spatiotemporal phenomena. It also incorporates contextual information in order to facilitate building the knowledge base of software agents. Besides, we propose an intelligent proximity tool based on a neuro-fuzzy classifier to support qualitative spatial relations in the pattern model. Finally, we propose a framework to manage spatiotemporal patterns in order to facilitate the integration of our pattern representation model to existing applications in the industry. The main contributions of this thesis are as follows: A qualitative approach to model dynamic spatiotemporal situations of interest using Conceptual Graphs. ; A cognitive approach to represent spatiotemporal patterns by integrating contextual information. ; An automated tool to generate qualitative spatial proximity relations based on a neuro-fuzzy classifier. ; A platform for detection and management of spatiotemporal patterns using an extension of a Complex Event Processing engine

Heterogeneous system and application communication modeling

With the end of Dennard scaling, high-performance computing increasingly relies on heterogeneous systems with specialized hardware to improve application performance. This trend has driven up the complexity of high-performance software development, as developers must manage multiple programming systems and develop system-tuned code to utilize specialized hardware. In addition, it has exacerbated existing challenges of data placement as the specialized hardware often has local memories to fuel its computational demands. In addition to using appropriate software resources to target application computation at the best hardware for the job, application developers now must manage data movement and placement within their application, which also must be specifically tuned to the target system. Instead of relying on the application developer to have specialized knowledge of system characteristics and specialized expertise in multiple programming systems, this work proposes a heterogeneous system communication library that automatically chooses data location and data movement for high-performance application development and execution on heterogeneous systems. This work presents the foundational components of that library: a systematic approach for characterization of system communication links and application communication demands

Heterogeneous system and application communication modeling

With the end of Dennard scaling, high-performance computing increasingly relies on heterogeneous systems with specialized hardware to improve application performance. This trend has driven up the complexity of high-performance software development, as developers must manage multiple programming systems and develop system-tuned code to utilize specialized hardware. In addition, it has exacerbated existing challenges of data placement as the specialized hardware often has local memories to fuel its computational demands. In addition to using appropriate software resources to target application computation at the best hardware for the job, application developers now must manage data movement and placement within their application, which also must be specifically tuned to the target system. Instead of relying on the application developer to have specialized knowledge of system characteristics and specialized expertise in multiple programming systems, this work proposes a heterogeneous system communication library that automatically chooses data location and data movement for high-performance application development and execution on heterogeneous systems. This work presents the foundational components of that library: a systematic approach for characterization of system communication links and application communication demands

Effectiveness of OPC for systems integration in the process control information architecture

A Process is defined as the progression to some particular end or objective through a logical and orderly sequence of events. Various devices (e.g., actuators, limit switches, motors, sensors, etc.) play a significant role in making sure that the process attains its objective (e.g., maintaining the furnace temperature within an acceptable limit). To do these things effectively, manufacturers need to access data from the plant floor or devices and integrate those into their control applications, which maybe one of the off the shelf tools such as Supervisory Control and Data Acquisition (SCADA), Distributed Control System (DCS), or Programmable Logic Controllers (PLC). A number of vendors have devised their own Data Acquisition Networks or Process Control Architectures (e.g., PROFIBUS, DEVICENET, INTERBUS, ETHERNET I/P, etc.) that claim to be open to or interoperable with a number of third party devices or products that make process data available to the Process or Business Management level. In reality this is far from what it is claimed to be. Due to the problem of interoperability, a manufacturer is forced to be bound, either with the solutions provided by a single vendor or with the writing of a driver for each hardware device that is accessed by a process application. Today\u27s manufacturers are looking for advanced distributed object technologies that allow for seamless exchange of information across plant networks as a means of integrating the islands of automation that exist in their manufacturing operations. OLE for Process Control (OPC) works to significantly reduce the time, cost, and effort required in writing custom interfaces for hundreds of different intelligent devices and networks in use today. The objective of this thesis is to explore the OLE for Process Control (OPC) technology in depth by highlighting its need in industry and by using the OPC technology in an application in which data from a process controlled by Siemens Simatic S7 PLC are shared with a client application running in LabVTEW6i