<p>With accelerating urbanization it is crucial to understand how urban ecosystems play a part in generating ecosystem services for urban dwellers, such as clean water, spaces for recreation, stress relief and improved air quality. An equally important question relate to who gets to enjoy these benefits, i.e. the distribution of ecosystem services, and how issues of power and equity influence the management of ecosystems. Through case studies from the urban landscape of Stockholm, this doctoral thesis engages with these perspectives through combining ecological theory with social theory, including social network analysis, actor-network theory and social movement theory. Strategies for how to improve urban ecosystem management are presented along with frameworks for how to analyze issues of power and equity in relation to natural resource management.</p><p><b>Paper I </b>shows that ecosystem management can be studied through analyzing the structure of social networks, i.e. the patterns of relations between agencies, stake-holders and user groups. <b>Paper II</b> and <b>Paper III</b> analyze, based on a network survey of 62 civil society organizations and in-depth interviews, a transformational process of how an urban local movement managed to protect a large urban green area from exploitation (The Stockholm National Urban Park). <b>Paper IV</b> discusses, based on several case studies from Stockholm, a conducive network structure for linking managers and user groups (e.g. allotment gardens, cemetery managers, and urban planners) across spatial ecological scales so as to improve urban green area management. <b>Paper V</b> presents a framework to analyze the social-ecological dynamics behind the generation and distribution of ecosystem services in urban landscapes.</p><p>The thesis points towards the notion of "a social production of ecosystem services" and argues for deeper engagement with urban political ecology and critical geography to inform governance and collective action in relation to urban ecosystems.</p>

With accelerating urbanization it is crucial to understand how urban ecosystems play a part in generating ecosystem services for urban dwellers, such as clean water, spaces for recreation, stress relief and improved air quality. An equally important question relate to who gets to enjoy these benefits, i.e. the distribution of ecosystem services, and how issues of power and equity influence the management of ecosystems. Through case studies from the urban landscape of Stockholm, this doctoral thesis engages with these perspectives through combining ecological theory with social theory, including social network analysis, actor-network theory and social movement theory. Strategies for how to improve urban ecosystem management are presented along with frameworks for how to analyze issues of power and equity in relation to natural resource management. <b>Paper I </b>shows that ecosystem management can be studied through analyzing the structure of social networks, i.e. the patterns of relations between agencies, stake-holders and user groups. <b>Paper II</b> and <b>Paper III</b> analyze, based on a network survey of 62 civil society organizations and in-depth interviews, a transformational process of how an urban local movement managed to protect a large urban green area from exploitation (The Stockholm National Urban Park). <b>Paper IV</b> discusses, based on several case studies from Stockholm, a conducive network structure for linking managers and user groups (e.g. allotment gardens, cemetery managers, and urban planners) across spatial ecological scales so as to improve urban green area management. <b>Paper V</b> presents a framework to analyze the social-ecological dynamics behind the generation and distribution of ecosystem services in urban landscapes. The thesis points towards the notion of "a social production of ecosystem services" and argues for deeper engagement with urban political ecology and critical geography to inform governance and collective action in relation to urban ecosystems.

Wireless sensor networks (WSNs) have a wide variety of applications in civilian, medical and military applications. However, the nodes in such a network are limited to one type of action: sensing the environment. With increasing requirements for intelligent interaction with the environment, there is a need to not only perceive but also control the monitored environment. This has led to the emergence of a new class of networks, referred to as wireless sensor and actor networks (WSANs), capable of performing both sensing and acting tasks on the environment. The evolution from WSNs, which can be thought of as performing only read operations, to WSANs, which can perform both read and write operations, introduces unique and new challenges that need to be addressed. In this research, the fundamental challenges required for effective operation of WSANs are analyzed from the following three different perspectives: (i) operation correctness, (ii) resource optimality, and (iii) operation performance. The solutions proposed to address the challenges are evaluated with the optimal solution and other competing approaches through analytical and simulation results. The feasibility of the proposed solutions is demonstrated through a testbed implementation.

Wireless Sensor and Actor Networks (WSANs) are composed of heterogeneous nodes referred to as sensors and actors. Sensors are low-cost, low-power, multi-functional devices that communicate untethered in short distances. Actors collect and process sensor data and perform appropriate actions on the environment. Hence, actors are resource-rich devices equipped with higher processing and transmission capabilities, and longer battery life. In WSANs, the collaborative operation of the sensors enables the distributed sensing of a physical phenomenon. After sensors detect an event in the deployment field, the event data is distributively processed and transmitted to the actors, which gather, process, and eventually reconstruct the event data. WSANs can be considered a distributed control system designed to react to sensor information with an effective and timely action. For this reason, in WSANs it is important to provide real-time coordination and communication to guarantee timely execution of the right actions. The energy efficiency of the networking protocols is also a major concern, since sensors are resource-constrained devices. Hence, the unique characteristics and challenges coupled with the limitations of wireless environments call for novel networking protocols for WSANs. The objective of this research is to develop new communication protocols to support real-time and reliable event data delivery with minimum energy consumption in WSANs. The proposed solutions dynamically adjust their protocol configurations to adapt to the heterogeneous characteristics of WSANs. Specifically, the interactions between contention resolution and congestion control mechanisms as well as the physical layer effects in WSANs are investigated. Next, a real-time and reliable transport protocol is proposed to achieve reliable and timely event detection with congestion avoidance in WSANs. In addition, a resource-aware and link-quality-based routing protocol is presented to address energy limitations and link quality variations in WSANs. Finally, the electric utility automation applications of WSANs are presented and the propagation characteristics of wireless channel in different utility environments are investigated.

In Wireless Sensor Actor Networks (WSANs), sensor nodes perform the sensing task and actor nodes take action based on the sensed phenomenon. The presence of actors in this configuration can not be benefited from, unless they are able to execute actions at right place and right time in the event region. The right place can be related to the accurate position of the sensor nodes. While, the right time is related to delivering the packets directly to the appropriate actors within the event specific response times. Hence, the efficient localization of sensor nodes, sensor-actor/actor-actor coordination and real-time routing is indispensable in WSANs. Furthermore, the limited energy levels and bandwidth of the state of art sensor nodes currently impose stringent requirements for low-complexity, low-energy, distributed coordination and cooperation protocols and their implementation. In this study, we propose an integrated framework which addresses the issues of sensors localization, network configuration, data aggregation, real-time data delivery, sensor-actor/actor-actor coordination and energy saving mechanisms. The proposal incorporates novel approaches on three fronts / (1) timing-based sensors localization (TSL) algorithm to localize the sensor nodes relative to actors, (2) real-time coordination and routing protocols and (3) energy conservation. The distributed real-time coordination and routing is implemented in addressing and greedy modes routing. A cluster-based real-time coordination and routing (RCR) protocol operates in addressing mode. The greedy mode routing approach (Routing by Adaptive Targeting, RAT) is a stateless shortest path routing. In dense deployment, it performs well in terms of delay and energy consumption as compared to RCR. To keep the traffic volume under control, the framework incorporates a novel real-time data aggregation (RDA) approach in RCR such that the packets deadlines are not affected. RDA is adaptive to the traffic conditions and provides fairness among the farther and nearer cluster-heads. Finally, framework incorporates a power management scheme that eliminates data redundancy by exploiting the spatial correlation of sensor nodes. Simulation results prove that the framework provides the real-time guarantees up to 95 % of the packets with lesser energy consumption of up to 33 % achieved using MEAC as compared to LEACH and SEP. The packet delivery ratio is also 60 % higher than that of semi-automated architecture. Furthermore the action accuracy is supported by TSL which restricts the localization errors less than 1 meter by tuning it according to the expected velocity of nodes and required accuracy.

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Wireless sensor and actor networks are used in situations where interaction is required between a network and the environment in which the network is deployed. This research studies the functioning of a single mobile actor deployed in a sparsely connected network. When deployed in a sparsely connected network, an actor has to do more than acting. It has to perform the additional duties of an event collector - collecting events from the naturally occurring clusters - so that it can fulfill its primary obligation as an actor. The path taken by a mobile actor node is generated by a mobility model. The existing random mobility models are non-intelligent mobility models. While they may bring about a chance meeting between an actor and an event, there is no guarantee that these meetings will actually happen. This motivates the development of intelligent mobility models for the actor node, which will generate paths that are reflective of the network in which the actor is deployed. In this thesis, intelligent mobility models for the actor node were developed using the inherent clustering information of a sparsely connected network. These models were applied to an actor node in networks of varying sparseness and the following conclusions were reached: (i) Existing random mobility models are unsuitable for an actor in a sparsely connected network. (ii) High probability of events can be sensed when a sparsely connected network is used. (iii) 100% event detection by the actor node is possible at higher speeds. (iv) When the single actor functioned both as an event collector and as an actor, the number of events acted upon by the actor was very close to the number of events acted upon by an actor in a fully connected network. (v) The Correlation Theory developed in this research suggests using a combination of the intelligent mobility models to obtain the best performance results under all circumstances. (vi) Early detection of events can be supported where it is required. All of the above conclusions justify the deployment of a single actor and a sparsely connected network, either individually or as a combination.

L’Intelligence Ambiamte (AmI) est un domaine de recherche investigant les techniques d’intelligence artificielle pour créer des environnements réactifs. Les réseaux de capteurs et effecteurs sans-fils sont les supports de communication entre les appareils ménagers, les services installés et les interfaces homme-machine. Cette thèse s’intéresse à la conception d’Environements Réactifs avec des propriétés autonomiques i.e. des systèmes qui ont la capacité de se gérer eux-même. De tels environements sont ouverts, à grande échelle, dynamique et hétérogène, ce qui induit certains problèmes pour leur gestion par des systèmes monolithiques. L’approche proposée est bio-inspirée en considérant chacune des plate-formes comme une cellule indépendente formant un organisme intelligent distribué. Chaque cellule est programmée par un processus ADN-RNA décrit par des règles réactives décrivant leur comportement interne et externe. Ces règles sont modelées par des agents mobiles ayant des capacités d’auto-réécriture et offrant ainsi des possibilités de reprogrammation dynamique. Le framework EMMA est composé d’un middleware modulaire avec une architecture orientée ressource basée sur la technologie 6LoWPAN et d’une architecture MAPE-K pour concevoir des AmI à plusieurs échelles. Les différentes relations entre les problèmes techniques et les besoins théoriques sont discutées dans cette thèse depuis les plate-formes, le réseau, le middleware, les agents mobiles, le déploiement des applications jusqu’au système intelligent. Deux algorithmes pour AmI sont proposés : un modèle de contrôleur neuronal artificiel pour le contrôle automatique des appareils ménagers avec des processus d’apprentissage ainsi qu’une procédure de vote distribuée pour synchroniser les décisions de plusieurs composants systèmes. / AThe Ambient Intelligence (AmI) is a research area investigating AI techniques to create Responsive Environments (RE). Wireless Sensor and Actor Network (WSAN) are the supports for communications between the appliances, the deployed services and Human Computer Interface (HCI). This thesis focuses on the design of RE with autonomic properties i.e. system that have the ability to manage themselves. Such environments are open, large scale, dynamic and heterogeneous which induce some difficulties in their management by monolithic system. The bio-inspired proposal considers all devices like independent cells forming an intelligent distributed organism. Each cell is programmed by a DNA-RNA process composed of reactive rules describing its internal and external behaviour. These rules are modelled by reactive agents with self-rewriting features offering dynamic reprogramming abilities. The EMMA framework is composed of a modular Resource Oriented Architecture (ROA) Middleware based on IPv6 LoW Power Wireless Area Networks (6LoWPAN) technology and a MAPE-K architecture to design multi-scale AmI. The different relations between technical issues and theoretical requirements are discussed through the platforms, the network, the middleware, the mobile agents, the application deployment to the intelligent system. Two algorithms for AmI are proposed: an Artificial Neural Controller (ANC) model for automatic control of appliances with learning processes and a distributed Voting Procedures (VP) to synchronize the decisions of several system components over the WSAN.