Wireless Sensor and Actor Networks (WSANs) are distributed systems of heterogeneous devices, referred to as sensors and actors, which sense, control, and interact with the physical environment. Sensors are low-cost, low-power, multi-functional devices that communicate untethered in short distances. Actors are resource-rich devices that collect and process sensor data and consequently perform actions on the environment. This thesis is concerned with coordination and communication problems in WSANs, in datacentric and multimedia application scenarios. First, communication and coordination problems are jointly addressed in a unifying framework for the case of static actors. A sensor-actor coordination model is proposed, based on an event-driven partitioning paradigm. Sensors are partitioned into different sets and each set is associated with a different actor. Data delivery trees are created to optimally react to the event and timely deliver event data with minimum energy expenditure. The optimal partitioning strategy is determined bymathematical programming, and a distributed solution is also proposed. Furthermore, the actor-actor coordination problem is formulated as an optimal task assignment problem, and a distributed solution of the problem based on an analogy with a one-shot auction is presented. Application scenarios for WSANs with mobile actors are then studied. A location management scheme is introduced to handle the mobility of actors with minimal energy consumption for resource-constrained sensors. The proposed scheme, which is the first localization scheme specifically designed for WSANs, is shown to consistently reduce the energy consumption with respect to existing localization services for ad hoc and sensor networks. An optimal energy-aware forwarding rule is then derived for sensor-actor communication in fast varying Rayleigh channels. The proposed scheme allows controlling the delay of the data-delivery process based on power control, and reacts to network congestion by diverting traffic from congested to lightly-loaded actors. The mobility of actors is coordinated to optimally accomplish application-specific tasks, based on a nonlinear optimization model that accounts for location and capabilities of heterogeneous actors. The research challenges for delivery of multimedia traffic in wireless sensor and actor networks are then outlined. Finally, a cross-layer communication architecture based on Ultra Wide Band communications is described, whose design objective is to reliably and flexibly deliver QoS to multimedia applications in WSANs, by carefully leveraging and controlling interactions among layers according to application requirements. Performance evaluation shows how the proposed solution achieves the performance objectives of wireless sensor and actor networks.

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Wireless sensor and actor networks (WSANs) are distributed systems of sensor nodes and actors that are interconnected over the wireless medium. Sensor nodes collect information about the physical world and transmit the data to actors by using one-hop or multi-hop communications. Actors collect information from the sensor nodes, process the information, take decisions and react to the events. This dissertation presents contributions to the methods of routing, localization and positioning in WSANs for practical applications. We first propose a routing protocol with service differentiation for WSANs with stationary nodes. In this setting, we also adapt a sports ranking algorithm to dynamically prioritize the events in the environment depending on the collected data. We extend this routing protocol for an application, in which sensor nodes float in a river to gather observations and actors are deployed at accessible points on the coastline. We develop a method with locally acting adaptive overlay network formation to organize the network with actor areas and to collect data by using locality-preserving communication. We also present a multi-hop localization approach for enriching the information collected from the river with the estimated locations of mobile sensor nodes without using positioning adapters. As an extension to this application, we model the movements of sensor nodes by a subsurface meandering current mobility model with random surface motion. Then we adapt the introduced routing and network organization methods to model a complete primate monitoring system. A novel spatial cut-off preferential attachment model and iii center of mass concept are developed according to the characteristics of the primate groups. We also present a role determination algorithm for primates, which uses the collection of spatial-temporal relationships. We apply a similar approach to human social networks to tackle the problem of automatic generation and organization of social networks by analyzing and assessing interaction data. The introduced routing and localization protocols in this dissertation are also extended with a novel three dimensional actor positioning strategy inspired by the molecular geometry. Extensive simulations are conducted in OPNET simulation tool for the performance evaluation of the proposed protocols

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.

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.