In the vision of Ambient Intelligence, people are assisted in their everyday activities through the proactive, opportunistic support of non-intrusive computing devices offering intuitive interaction modalities. The usefulness and quality of delivered services can be improved considerably if the devices are able to adapt their behaviour according to sensed changes in their surrounding environment, both at the physical and logical levels. This interplay between context-awareness and dynamic software adaptability is key to the construction of applications that are smart with respect to user needs. Unfortunately, most current applications do not reach this level of adaptability, due to a lack of appropriate programming technology. Most applications exhibit fixed functionality and seldom do they sense their environment and adapt their services in a context-aware fashion. Many chances of delivering improved services to users and network peers are thus missed. This dissertation presents a programming model to ease the construction of applications that can react to changes in their execution context by adapting their behaviour dynamically. The starting point of our research is the development of novel language abstractions and the adaptation of existing abstractions to render context-aware, self-adaptable applications easier to develop. We demonstrate that a simple yet powerful computation model readily provides the needed support, leading to straightforward application code that is not concerned with context adaptation, behaviour that can be adapted dynamically to different contexts in a non-intrusive fashion, and context-aware applications with software architectures that are not biased towards context adaptation ---rather, they can be designed freely according to their domain. The proposed computation model is realised through the Ambience programming language, and its underlying open implementation, the Ambient Object System. A small-step operational semantics describes it formally. Much in the vein of prototype-based programming, the model has been designed with simplicity and concreteness in mind. It is highly dynamic, featuring dynamic (multiple) dispatch, dynamic inheritance, dynamic typing, and dynamic method scoping. Application logic adaptation is enabled by means of an intuitive, first-class reification of context that is straightforwardly connected to dynamic behaviour selection. We describe needed management techniques for such context, and a few programming guidelines on how to develop context-aware applications using our approach. The approach is validated by showing its application in a number of scenarios inspired on Ambient Intelligence.

Die "Kontextsensitivität" genannte systematische Berücksichtigung von Umweltinformationen durch Anwendungssysteme kann als Querschnittsfunktion im betrieblichen Umfeld in vielen Bereichen einen Nutzen stiften. Wirklich praxistaugliche kontextsensitive Anwendungssysteme, die sich analog zu einem mitdenkenden menschlichen Assistenten harmonisch in die ablaufenden Vorgänge in der Realwelt einbringen, haben einen enormen Bedarf nach umfassenden, d.h. diverse Aspekte der Realwelt beschreibenden Kontextinformationen, die jedoch prinzipbedingt verteilt in verschiedenen Datenquellen, etwa Kontexterfassungssystemen, Endgeräten sowie prinzipiell auch in beliebigen anderen, z.T. bereits existierenden Anwendungen entstehen. Ziel dieser Arbeit ist die Verringerung der Komplexität des Beschaffungsvorganges von verteilten und heterogenen Kontextinformationen durch Bereitstellung einer einfach verwendbaren Methode zur Darstellung eines umfassenden, aus verteilten und heterogenen Datenquellen zusammengetragenen Kontextmodells. Im Besonderen werden durch diese Arbeit zwei Probleme addressiert, zum einen daß ein Konsument von umfassenden Kontextinformationen mehrere Datenquellen sowohl kennen und zugreifen können und zum anderen über die zwischen den einzelnen Kontextinformationen in verschiedenen Datenquellen existierenden, zunächst nicht modellierten semantischen Verbindungen Bescheid wissen muß. Das dazu entwickelte Kontextinformationsintegrations- und -darstellungsverfahren kombiniert daher ein die Beschaffung und Integration von Kontextinformationen aus diversen Datenquellen modellierendes Informationsintegrationsmodell mit einem Kontextdarstellungsmodell, welches die abzubildende Realweltdomäne basierend auf ontologischen Informationen durch in problemspezifischer Weise erweiterte Verfahren des Semantic Web in einer möglichst intuitiven, wiederverwendbaren und modularen Weise modelliert. Nach einer fundierten Anforderungsanalyse des entwickelten Prinzips wird dessen Verwendung und Nutzen basierend auf der Skizzierung der wichtigsten allgemeinen Verwendungsmöglichkeiten von Kontextinformationen im betrieblichen Umfeld anhand eines komplexen betrieblichen Anwendungsszenarios demonstriert. Dieses beinhaltet ein Nutzerprofil, das von diversen Anwendungen, u.a. einem kontextsensitiven KFZ-Navigationssystem, einer Restaurantsuchanwendung sowie einem Touristenführer verwendet wird. Probleme hinsichtlich des Datenschutzes, der Integration in existierende Umgebungen und Abläufe sowie der Skalierbarkeit und Leistungsfähigkeit des Verfahrens werden ebenfalls diskutiert. / Context-awareness, which is the systematic consideration of information from the environment of applications, can provide significant benefits in the area of business and technology. To be really useful, i.e. harmonically support real-world processes as human assistants do it, practical applications need a comprehensive and detailed contextual information base that describes all relevant aspects of the real world. As a matter of principle, comprehensive contextual information arises in many places and data sources, e.g. in context-aware infrastructures as well as in "normal" applications, which may have knowledge about the context based on their functionality to support a certain process in the real world. This thesis facilitates the use of contextual information by reducing the complexity of the procurement process of distributed and heterogenous contextual information. Particularly, it addresses the two problems that a consumer of comprehensive contextual information needs to be aware of and able to access several different data sources and must know how to combine the contextual information taken from different and isolated data sources into a meaningful representation of the context. Especially the latter information cannot be modelled using the current state of the art. These problems are addressed by the development of an integration and representation model for contextual information that allows to compose comprehensive context models using information inside distributed and heterogeneous data sources. This model combines an information integration model for distributed and heterogenous information (which consists of an access model for heterogeneous data sources, an integration model and an information relation model) with a representation model for context that formalizes the representation of the respective real world domain, i.e. of the real world objects and their semantic relations in an intuitive, reusable and modular way based on ontologies. The resulting model consists of five layers that represent different aspects of the information integration solution. The achievement of the objectives is rated based on a requirement analysis of the problem domain. The technical feasibility and usefulness of the model is demonstrated by the implementation of an engine to support the approach as well as a complex application scenario consisting of a user profile that integrates information from several data sources and a couple of context-aware applications, e.g. a context-aware navigation system, a restaurant finder application as well as an enhanced tourist guide that use the user profile. Problems regarding security and social effects, the integration of this solution into existing environments and infrastructures as well as technical issues like the scalability and performance of this model are discussed too.

Im Vergleich zu einer stichwortbasierten Suche ermöglicht die semantische Suche ein präziseres und anspruchsvolleres Durchsuchen von (Web)-Dokumenten, weil durch die explizite Semantik Mehrdeutigkeiten von natürlicher Sprache vermieden und semantische Beziehungen in das Suchergebnis einbezogen werden können. Eine semantische, Entitäten-basierte Suche geht von einer Anfrage mit festgelegter Bedeutung aus und liefert nur Dokumente, die mit dieser Entität annotiert sind als Suchergebnis. Die wichtigste Voraussetzung für eine Entitäten-zentrierte Suche stellt die Annotation der Dokumente im Archiv mit Entitäten und Kategorien dar. Textuelle Informationen werden analysiert und mit den entsprechenden Entitäten und Kategorien versehen, um den Inhalt semantisch erschließen zu können. Eine manuelle Annotation erfordert Domänenwissen und ist sehr zeitaufwendig. Die semantische Annotation von Videodokumenten erfordert besondere Aufmerksamkeit, da inhaltsbasierte Metadaten von Videos aus verschiedenen Quellen stammen, verschiedene Eigenschaften und Zuverlässigkeiten besitzen und daher nicht wie Fließtext behandelt werden können. Die vorliegende Arbeit stellt einen semantischen Analyseprozess für Video-Metadaten vor. Die Eigenschaften der verschiedenen Metadatentypen werden analysiert und ein Konfidenzwert ermittelt. Dieser Wert spiegelt die Korrektheit und die wahrscheinliche Mehrdeutigkeit eines Metadatums wieder. Beginnend mit dem Metadatum mit dem höchsten Konfidenzwert wird der Analyseprozess innerhalb eines Kontexts in absteigender Reihenfolge des Konfidenzwerts durchgeführt. Die bereits analysierten Metadaten dienen als Referenzpunkt für die weiteren Analysen. So kann eine möglichst korrekte Analyse der heterogen strukturierten Daten eines Kontexts sichergestellt werden. Am Ende der Analyse eines Metadatums wird die für den Kontext relevanteste Entität aus einer Liste von Kandidaten identifiziert - das Metadatum wird disambiguiert. Hierfür wurden verschiedene Disambiguierungsalgorithmen entwickelt, die Beschreibungstexte und semantische Beziehungen der Entitätenkandidaten zum gegebenen Kontext in Betracht ziehen. Der Kontext für die Disambiguierung wird für jedes Metadatum anhand der Eigenschaften und Konfidenzwerte zusammengestellt. Der vorgestellte Analyseprozess ist an zwei Hypothesen angelehnt: Um die Analyseergebnisse verbessern zu können, sollten die Metadaten eines Kontexts in absteigender Reihenfolge ihres Konfidenzwertes verarbeitet werden und die Kontextgrenzen von Videometadaten sollten durch Segmentgrenzen definiert werden, um möglichst Kontexte mit kohärentem Inhalt zu erhalten. Durch ausführliche Evaluationen konnten die gestellten Hypothesen bestätigt werden. Der Analyseprozess wurden gegen mehrere State-of-the-Art Methoden verglichen und erzielt verbesserte Ergebnisse in Bezug auf Recall und Precision, besonders für Metadaten, die aus weniger zuverlässigen Quellen stammen. Der Analyseprozess ist Teil eines Videoanalyse-Frameworks und wurde bereits erfolgreich in verschiedenen Projekten eingesetzt. / The Semantic Web provides information contained in the World Wide Web as machine-readable facts. In comparison to a keyword-based inquiry, semantic search enables a more sophisticated exploration of web documents. By clarifying the meaning behind entities, search results are more precise and the semantics simultaneously enable an exploration of semantic relationships. However, unlike keyword searches, a semantic entity-focused search requires that web documents are annotated with semantic representations of common words and named entities. Manual semantic annotation of (web) documents is time-consuming; in response, automatic annotation services have emerged in recent years. These annotation services take continuous text as input, detect important key terms and named entities and annotate them with semantic entities contained in widely used semantic knowledge bases, such as Freebase or DBpedia. Metadata of video documents require special attention. Semantic analysis approaches for continuous text cannot be applied, because information of a context in video documents originates from multiple sources possessing different reliabilities and characteristics. This thesis presents a semantic analysis approach consisting of a context model and a disambiguation algorithm for video metadata. The context model takes into account the characteristics of video metadata and derives a confidence value for each metadata item. The confidence value represents the level of correctness and ambiguity of the textual information of the metadata item. The lower the ambiguity and the higher the prospective correctness, the higher the confidence value. The metadata items derived from the video metadata are analyzed in a specific order from high to low confidence level. Previously analyzed metadata are used as reference points in the context for subsequent disambiguation. The contextually most relevant entity is identified by means of descriptive texts and semantic relationships to the context. The context is created dynamically for each metadata item, taking into account the confidence value and other characteristics. The proposed semantic analysis follows two hypotheses: metadata items of a context should be processed in descendent order of their confidence value, and the metadata that pertains to a context should be limited by content-based segmentation boundaries. The evaluation results support the proposed hypotheses and show increased recall and precision for annotated entities, especially for metadata that originates from sources with low reliability. The algorithms have been evaluated against several state-of-the-art annotation approaches. The presented semantic analysis process is integrated into a video analysis framework and has been successfully applied in several projects for the purpose of semantic video exploration of videos.

Leveraging our experience with the traditional approach to ambient assisted living (AAL) which relies on a large spread of heterogeneous technologies in deployments, this thesis studies the possibility of a more "stripped down" and complementary approach, where only a reduced hardware subset is deployed, probing a transfer of complexity towards the software side, and enhancing the large scale deployability of the solution. Focused on the reasoning aspects in AAL systems, this work has allowed the finding of a suitable semantic inference engine for the peculiar use in these systems, responding to a need in this scientific community. Considering the coarse granularity of situational data available, dedicated rule-sets with adapted inference strategies are proposed, implemented, and validated using this engine. A novel semantic reasoning mechanism is proposed based on a cognitively inspired reasoning architecture. Finally, the whole reasoning system is integrated in a fully featured context-aware service framework, powering its context awareness by performing live event processing through complex ontological manipulation. the overall system is validated through in-situ deployments in a nursing home as well as private homes over a few months period, which itself is noticeable in a mainly laboratory-bound research domain

Almost 20 years ago, Marc Weiser envisioned the prospect of computer in 21st century, and proposed the pioneering notion of ubiquitous computing. One of Weiser's primary ideas has recently evolved to a more general paradigm known as context awareness, becoming a central research theme in many other ubiquitous computing programs. From Active Badge considered as the first context-aware application, there are numerous attempts to build effective context-aware systems. However, how to acquire context, how to process context and how to create context-aware applications is still faced with enormous challenges in the both of research and practice. This dissertation investigates deeply some chosen key issues in context awareness and develops a context-aware middleware. The main research contributions are presented in three categories: a spatialtemporal context represent model, a context-aware middleware and an intelligence context inference engine. The spatial-temporal context representation model is proposed to organize context and relations for context-aware system. Ontology-based method is adopted to construct our model, supporting both knowledge sharing and reuse as well as logic inference. This model adopts two-layer hierarchy structure for different situation. The higher layer comes up with the generic common context, while the lower layer focuses on various specific situations. Differing from existing models, besides taking locational factors into account, it supports different historical context service depending on different context resource. These context histories may be used to predict and infer the context. A context-aware middleware is designed as a platform associated with context retrieval and context processing. It is organized in two layers: the low layer provides a solution to integrate sensors and actuators with a standardized data representation; the high layer: versatile context interpreter focuses on context processing, which is made up of four parts: Context Aggregator, Inference Engine, Context Knowledge Base, and Query Engine in charge of context inferences, expressive query, and persistent storage. This middleware provides an environment for rapid prototyping of context aware services in ambient intelligent. The intelligent inference engine is the central and intellectual component of context-aware middleware. We review all the methods on activity context recognition published in three premier conferences in past decade and conclude that activity context recognition is divided into three facets: basic activity inference, dynamic activity analysis and future activity recommendation. Then we propose an intelligent inference engine based on our context-aware middleware. Beside satisfying requirements of checking the context consistency, our inference engine integrates the three most popular methods on activity context recognition: Rules, Decision Tree, and Hide Markov Model. It provides a solution for all facets of activity context recognition based on our context-aware middleware. The individuals' information collecting from their social networks under permission are leveraged to train intelligent inference engine. We finally use two scenarios (applications) to explain the generic process to develop application via our middleware, and compare and analyze the main aspects of our middleware with other five representative context-aware applications. Our middleware profits good features from existing context-aware systems and improve intelligence via supporting activity context recognition. It provides an efficient platform for a rapid developing of new context-aware applications in ambient intelligence.

This thesis presents the design and analysis of Spasiba, a context-aware mobile advisor. We argue that current context-aware mobile applications exhibit significant flaws with respect to (1) limited use of context information, (2) incomplete or irrelevant content generation, and (3) low usability. The proposed model attempts to tackle these limitations by advancing the usage and manipulation of context information, automating the back-end systems in terms of self-management and seamless extensibility, and shifting the logic away from the client side. A distinguishing characteristic of Spasiba is the proactive approach to notifying the user of information of interest. In this proactive approach, the user subscribes to the service and receives content updates as the context changes. This proposed model is realised in a proof-of-concept prototype that uses a Nokia Web Runtime widget as the client application. The widget, which sports an elegant, touch-optimised interface, collects multiple context parameters to deliver high-quality results. The server-side architecture employs the publish/subscribe paradigm for managing the active users and Comet—for proactively notifying the clients of updated information of interest. IRS-III, a Semantic Web Services broker, handles the process of content generation. The prototype employs nine data sources, seven of which are open API web services and two of which are regular web pages, to deliver diverse and complete results. A simple autonomic element, implemented with the help of aspect-oriented programming, ensures partial self-management of the back-end systems. Spasiba is evaluated by means of a case study that involves a tourist couple visiting Victoria. The application assists the tourist couple with finding attractions, relevant stores, and places serving food.

Our society is increasingly demanding situation-aware smarter software (SASS) systems, whose goals change over time and depend on context situations. A system with such properties must sense their dynamic environment and respond to changes quickly, accurately, and reliably, that is, to be context-aware and self-adaptive. The problem addressed in this dissertation is the dynamic management of context information, with the goal of improving the relevance of SASS systems' context-aware capabilities with respect to changes in their requirements and execution environment. Therefore, this dissertation focuses on the investigation of dynamic context management and self-adaptivity to: (i) improve context-awareness and exploit context information to enhance quality of user experience in SASS systems, and (ii) improve the dynamic capabilities of self-adaptivity in SASS systems. Context-awareness and self-adaptivity pose signi cant challenges for the engineering of SASS systems. Regarding context-awareness, the rst challenge addressed in this dissertation is the impossibility of fully specifying environmental entities and the corresponding monitoring requirements at design-time. The second challenge arises from the continuous evolution of monitoring requirements due to changes in the system caused by self-adaptation. As a result, context monitoring strategies must be modeled and managed in such a way that they support the addition and deletion of context types and monitoring conditions at runtime. For this, the user must be integrated into the dynamic context management process. Concerning self-adaptivity, the third challenge is to control the dynamicity of adaptation goals, adaptation mechanisms, and monitoring infrastructures, and the way they a ect each other in the adaptation process. This is to preserve the eff ectiveness of context monitoring requirements and thus self-adaptation. The fourth challenge, related also to self-adaptivity,concerns the assessment of adaptation mechanisms at runtime to prevent undesirable system states as a result of self-adaptation. Given these challenges, to improve context-awareness we made three contributions. First, we proposed the personal context sphere concept to empower users to control the life cycle of personal context information in user-centric SASS systems. Second, we proposed the SmarterContext ontology to model context information and its monitoring requirements supporting changes in these models at runtime. Third, we proposed an effi cient context processing engine to discover implicit contextual facts from context information speci fied in changing context models. To improve self-adaptivity we made three contributions. First, we proposed a framework for the identi cation of adaptation properties and goals, which is useful to evaluate self-adaptivity and to derive monitoring requirements mapped to adaptation goals. Second, we proposed a reference model for designing highly dynamic self-adaptive systems, for which the continuous pertinence between monitoring mechanisms and both changing system goals and context situations is a major concern. Third, we proposed a model with explicit validation and veri cation (V&V) tasks for self-adaptive software, where dynamic context monitoring plays a major role. The seventh contribution of this dissertation, the implementation of Smarter-Context infrastructure, addresses both context-awareness and self-adaptivity. To evaluate our contributions, qualitatively and quantitatively, we conducted several comprehensive literature reviews, a case study on user-centric situation-aware online shopping, and a case study on dynamic governance of service-oriented applications. / Graduate

Weighted granular best matching algorithm is proposed for the operation of context matching in context-aware computing systems. New algorithm deals with the subjective, fuzzy and multidimensional characteristics of contextual information by using weights and a granular structure for contextual information. The proposal is applied on a case: CAPRA &ndash / Context-Aware Personal Reminder Agent tool to show the applicability of the new context matching algorithm. The obtained outputs showed that proposed algorithm produces the results which are more sensitive to the user&rsquo / s intention, more adaptive to the characteristics of the contextual information and applicable to a current Context-aware system.

[pt] Aplicações para o monitoramento de frotas de veículos e sistemas de logística, coordenação em situações de emergência, monitoramento ambiental ou de gestão de força de trabalho móvel podem usar redes móveis como meio de comunicação, troca de informações e de coordenação entre um número possivelmente grande de nós móveis interligados por uma rede WAN. A maioria desses sistemas requer o monitoramento em tempo real das informações de contexto dos nós móveis, interação com todos os nós participantes, bem como meios de adaptação num cenário muito dinâmico, onde não é possível prever quando, onde e por quanto tempo os nós permanecerão conectados. As soluções atuais ainda não têm recursos essenciais necessários para a comunicação com os nós móveis, tais como a entrega confiável de mensagens, suporte a handover, resistência a conectividade intermitente, mudanças de endereço IP e firewall transversal. Esta tese propõe um modelo de gestão de dados que permite a implantação de uma rede de componentes de provedores de dados com disseminação e transformação rápida e confiável de informações entre milhares de nós móveis interligados através de internet sem fio. Os testes de desempenho indicam que o nosso modelo consegue escalar para milhares de nós móveis e suporta disseminação confiável, rápida e com alta taxa de transferência da informação entre milhares de provedores de contexto e consumidores de contexto móveis. / [en] Applications such as vehicle fleet monitoring and logistic systems, emergency response coordination, environmental monitoring or mobile workforce management, employ mobile networks as means of communication, information sharing and coordination among a possibly very large set of mobile nodes interconnected by a Wide Area Network (WAN). The majority of those systems thus requires real-time tracking of the mobile nodes context information, interaction with all participant nodes, as well as means of adaptability in a very dynamic scenario, where it is not possible to predict when, where and for how long the nodes will remain connected. Despite being a subject of much research, current solutions still lack essential features required for communication with mobile nodes, such as reliable message delivery, handover support, resilience to intermittent connectivity, IP address changes and firewall transversal. This thesis proposes a data management model that enables deployment of a network of Data Provider components with reliable and on-time dissemination and transformation of information among thousands of mobile nodes interconnected through wireless internet. Performance tests indicate that our model scales to thousands of mobile nodes and supports reliable, high throughput and on-time data dissemination between several thousands of mobile Data Providers and Data Consumers.

Sistemas de vigilância são geralmente empregados no monitoramento de áreas de grandes dimensões nas quais seus usuários visam detectar ou observar fenômenos de seu interesse. O uso de redes de sensores sem fio nesses sistemas apresenta especial interesse, uma vez que essas redes podem apresentar soluções de baixo custo e robustas para cobrir áreas extensas. Neste contexto, novas aplicações têm surgido propondo o uso de redes de sensores sem fio compostas por nós sensores estáticos e móveis. Uma das motivações para esta tendência é a redução do custo de implantação e operação do sistema, além da possibilidade de proporcionar incremento em suas funcionalidades. O foco desta tese se concentra na proposta de soluções para redes de sensores sem fio com uso cooperativo de sensores estáticos e móveis, com particular atenção a sensibilidade ao contexto na configuração e execução de missões de sensoriamento. O objetivo é manter um baixo custo de comunicação associado às soluções propostas. Esta preocupação se dá pelo fato da comunicação aumentar o consumo de energia em redes de sensores, o que é um problema importante para nós sensores com limitada fonte de energia, i.e. baterias. No caso de nós sensores móveis, esta limitação pode não ser relevante, uma vez que seu movimento deve consumir uma quantidade muito mais expressiva de energia do que a comunicação. Neste caso, o problema se relaciona à estabilidade dos enlaces, bem como ao curto intervalo de tempo disponível para transmitir e receber dados. Logo, o melhor é comunicar o menos possível. Com relação à interação entre nós sensores estáticos, os problemas de disseminação e alocação de missões de sensoriamento são estudados e uma solução que explora o uso de informações locais é proposta e avaliada. Esta solução emprega agentes de software móveis que têm a capacidade de tomar decisões autônomas através do uso de informações de contexto local. Para redes de sensores móveis, o problema estudado se refere a como transferir missões entre os nós sensores de acordo com seu movimento e localização em relação aos locais onde as missões devem ser executadas. Para tratar este problema, uma abordagem baseada em agentes móveis é proposta, na qual os agentes implementam a migração das missões de sensoriamento usando informações de contexto geográfico para decidir a respeito de suas migrações. Para redes de sensores com sensores estáticos e móveis, a cooperação entre eles é abordada através de um mecanismo com inspiração biológica para realizar a realizar a entrega de dados emitidos pelos sensores estáticos aos sensores móveis. Para isto, explora-se uma analogia baseada no comportamento de formigas na construção e seguimento de trilhas. As soluções propostas são flexíveis, sendo aplicáveis a diferentes domínios de aplicação. Resultados experimentais evidenciam sua escalabilidade, avaliando, por exemplo, seu custo em termos de comunicação, além de outras métricas de interesse para cada uma das soluções. Estes resultados são comparados aos atingidos por soluções de referência (solução ótima teórica e baseada em inundação), indicando sua eficiência. Estes resultados são próximos do ótimo teórico e significativamente melhores que aqueles atingidos por soluções baseadas em técnicas de inundação. / Surveillance systems are usually employed to monitor wide areas in which their users are interested in detecting and/or observing events or phenomena of their interest. The use of wireless sensor networks in such systems is of particular interest as these networks can provide a relative low cost and robust solution to cover large areas. Emerging applications in this context are proposing the use of wireless sensor networks composed of both static and mobile sensor nodes. Motivation for this trend is to reduce deployment and operating costs, besides providing enhanced functionalities. This work focuses on the proposal of solutions for wireless sensor networks including static and mobile sensor nodes specifically regarding cooperative and context aware mission setup and performance. The goal is to keep the communication costs as low as possible in the execution of the proposed solutions. This concern comes from the fact that communication increases energy consumption, which is a particular issue for energy constrained sensor nodes often used in wireless sensor networks, especially if battery supplied. In the case of the mobile nodes, this energy constraint may not be valid, since their motion might need much more energy, but links instabilities and short time windows available to receive and transmit data. Therefore, it is better to communicate as little as possible. For the interaction among static sensor nodes, the problems of dissemination and allocation of sensing missions are studied and a solution that explores local information is proposed and evaluated. This solution uses mobile software agents that have capabilities to take autonomous decisions about the mission dissemination and allocation using local context information. For mobile wireless sensor networks, the problem studied is how to perform handover of missions among the nodes according to their movements and locations in relation to the place where the missions have to be performed. To handle this problem, a mobile agent approach is proposed in which the agents implement the sensing missions’ migration from node to node using geographical context information to decide about their migrations. For the networks combining static and mobile sensor nodes, the cooperation among them is approached by a biologically-inspired mechanism to deliver data from the static to the mobile nodes. The data delivery mechanism explores an analogy based on the behaviour of ants building and following trails, inspired by the ant colony algorithm. The proposed solutions are flexible, being able to be applied to different application domains. Obtained experimental results provide evidence of the scalability of these proposed solutions, for example by evaluating their cost in terms of communication, among other metrics of interest for each solution. These results are compared to those achieved by reference solutions (theoretical optimum and floodingbased), providing indications of the proposed solutions’ efficiency. These results are considered close to the theoretical optimum one and significantly better than the ones achieved by flooding-based solutions.