1,093 research outputs found
Exploiting web technologies to build autonomic wireless sensor networks
Most of the current wireless sensor networks are built for specific applications, with a tight coupling between them and the underlying communication protocols. We present a more flexible architectural approach for building WSNs, in which application-specific features are decoupled from the underlying communication infrastructure, although affecting the network behavior. We propose a framework based on Web technologies that provides a standard interface for accessing the network and configurable service components tailored to meet different application requirements, while optimizing the network scarce resources. Also, a set of ontologies is defined as part of the framework for representing shared knowledge of the WSN domain.8th IFIP/IEEE International conference on Mobile and Wireless CommunicationRed de Universidades con Carreras en Informática (RedUNCI
Machine Learning in Wireless Sensor Networks: Algorithms, Strategies, and Applications
Wireless sensor networks monitor dynamic environments that change rapidly
over time. This dynamic behavior is either caused by external factors or
initiated by the system designers themselves. To adapt to such conditions,
sensor networks often adopt machine learning techniques to eliminate the need
for unnecessary redesign. Machine learning also inspires many practical
solutions that maximize resource utilization and prolong the lifespan of the
network. In this paper, we present an extensive literature review over the
period 2002-2013 of machine learning methods that were used to address common
issues in wireless sensor networks (WSNs). The advantages and disadvantages of
each proposed algorithm are evaluated against the corresponding problem. We
also provide a comparative guide to aid WSN designers in developing suitable
machine learning solutions for their specific application challenges.Comment: Accepted for publication in IEEE Communications Surveys and Tutorial
A COGNITIVE ARCHITECTURE FOR AMBIENT INTELLIGENCE
L’Ambient Intelligence (AmI) è caratterizzata dall’uso di sistemi pervasivi per
monitorare l’ambiente e modificarlo secondo le esigenze degli utenti e rispettando
vincoli definiti globalmente. Questi sistemi non possono prescindere da requisiti
come la scalabilità e la trasparenza per l’utente. Una tecnologia che consente di
raggiungere questi obiettivi è rappresentata dalle reti di sensori wireless (WSN),
caratterizzate da bassi costi e bassa intrusività. Tuttavia, sebbene in grado di
effettuare elaborazioni a bordo dei singoli nodi, le WSN non hanno da sole le capacità
di elaborazione necessarie a supportare un sistema intelligente; d’altra parte
senza questa attività di pre-elaborazione la mole di dati sensoriali può facilmente
sopraffare un sistema centralizzato con un’eccessiva quantità di dettagli superflui.
Questo lavoro presenta un’architettura cognitiva in grado di percepire e controllare
l’ambiente di cui fa parte, basata su un nuovo approccio per l’estrazione
di conoscenza a partire dai dati grezzi, attraverso livelli crescenti di astrazione.
Le WSN sono utilizzate come strumento sensoriale pervasivo, le cui capacità computazionali
vengono utilizzate per pre-elaborare i dati rilevati, in modo da consentire
ad un sistema centralizzato intelligente di effettuare ragionamenti di alto
livello.
L’architettura proposta è stata utilizzata per sviluppare un testbed dotato degli
strumenti hardware e software necessari allo sviluppo e alla gestione di applicazioni
di AmI basate su WSN, il cui obiettivo principale sia il risparmio energetico. Per
fare in modo che le applicazioni di AmI siano in grado di comunicare con il mondo
esterno in maniera affidabile, per richiedere servizi ad agenti esterni, l’architettura
è stata arricchita con un protocollo di gestione distribuita della reputazione.
È stata inoltre sviluppata un’applicazione di esempio che sfrutta le caratteristiche
del testbed, con l’obiettivo di controllare la temperatura in un ambiente
lavorativo. Quest’applicazione rileva la presenza dell’utente attraverso un modulo
per la fusione di dati multi-sensoriali basato su reti bayesiane, e sfrutta questa
informazione in un controllore fuzzy multi-obiettivo che controlla gli attuatori sulla
base delle preferenze dell’utente e del risparmio energetico.Ambient Intelligence (AmI) systems are characterized by the use of pervasive
equipments for monitoring and modifying the environment according to users’
needs, and to globally defined constraints. Furthermore, such systems cannot ignore
requirements about ubiquity, scalability, and transparency to the user. An
enabling technology capable of accomplishing these goals is represented by Wireless
Sensor Networks (WSNs), characterized by low-costs and unintrusiveness. However,
although provided of in-network processing capabilities, WSNs do not exhibit
processing features able to support comprehensive intelligent systems; on the other
hand, without this pre-processing activities the wealth of sensory data may easily
overwhelm a centralized AmI system, clogging it with superfluous details.
This work proposes a cognitive architecture able to perceive, decide upon, and
control the environment of which the system is part, based on a new approach to
knowledge extraction from raw data, that addresses this issue at different abstraction
levels. WSNs are used as the pervasive sensory tool, and their computational
capabilities are exploited to remotely perform preliminary data processing. A central
intelligent unit subsequently extracts higher-level concepts in order to carry on
symbolic reasoning. The aim of the reasoning is to plan a sequence of actions that
will lead the environment to a state as close as possible to the users’ desires, taking
into account both implicit and explicit feedbacks from the users, while considering
global system-driven goals, such as energy saving. The proposed conceptual architecture
was exploited to develop a testbed providing the hardware and software
tools for the development and management of AmI applications based on WSNs,
whose main goal is energy saving for global sustainability. In order to make the
AmI system able to communicate with the external world in a reliable way, when
some services are required to external agents, the architecture was enriched with
a distributed reputation management protocol.
A sample application exploiting the testbed features was implemented for addressing
temperature control in a work environment. Knowledge about the user’s
presence is obtained through a multi-sensor data fusion module based on Bayesian
networks, and this information is exploited by a multi-objective fuzzy controller
that operates on actuators taking into account users’ preference and energy consumption
constraints
QoS Challenges and Opportunities in Wireless Sensor/Actuator Networks
A wireless sensor/actuator network (WSAN) is a group of sensors and actuators
that are geographically distributed and interconnected by wireless networks.
Sensors gather information about the state of physical world. Actuators react
to this information by performing appropriate actions. WSANs thus enable cyber
systems to monitor and manipulate the behavior of the physical world. WSANs are
growing at a tremendous pace, just like the exploding evolution of Internet.
Supporting quality of service (QoS) will be of critical importance for
pervasive WSANs that serve as the network infrastructure of diverse
applications. To spark new research and development interests in this field,
this paper examines and discusses the requirements, critical challenges, and
open research issues on QoS management in WSANs. A brief overview of recent
progress is given.Comment: 12 pages, 1 figure; revie
Adaptive Duty Cycling MAC Protocols Using Closed-Loop Control for Wireless Sensor Networks
The fundamental design goal of wireless sensor MAC protocols is to minimize unnecessary power consumption of the sensor nodes, because of its stringent resource constraints and ultra-power limitation. In existing MAC protocols in wireless sensor networks (WSNs), duty cycling, in which each node periodically cycles between the active and sleep states, has been introduced to reduce unnecessary energy consumption. Existing MAC schemes, however, use a fixed duty cycling regardless of multi-hop communication and traffic fluctuations. On the other hand, there is a tradeoff between energy efficiency and delay caused by duty cycling mechanism in multi-hop communication and existing MAC approaches only tend to improve energy efficiency with sacrificing data delivery delay. In this paper, we propose two different MAC schemes (ADS-MAC and ELA-MAC) using closed-loop control in order to achieve both energy savings and minimal delay in wireless sensor networks. The two proposed MAC schemes, which are synchronous and asynchronous approaches, respectively, utilize an adaptive timer and a successive preload frame with closed-loop control for adaptive duty cycling. As a result, the analysis and the simulation results show that our schemes outperform existing schemes in terms of energy efficiency and delivery delay
Constraint-based Self-adaptation of Wireless Sensor Networks
International audienceIn recent years, the Wireless Sensor Networks (WSNs) have become a useful mechanism to monitor physical phenomena in environments. The sensors that make part of these long-lived networks have to be reconfigured according to context changes in order to preserve the operation of the network. Such reconfigurations require to consider the distributed nature of the sensor nodes as well as their resource scarceness. Therefore, self-adaptations for WSNs have special requirements comparing with traditional information systems. In particular, the reconfiguration of the WSN requires a trade-off between critical dimensions for this kind of networks and devices, such as resource consumption or reconfiguration cost. Thus, in this paper, we propose to exploit Constraint-Satisfaction Problem (CSP) techniques in order to find a suitable configuration for self-adapting WSNs, modelled using a Dynamic Software Product Line (DSPL), when the context changes. We exploit CSP modeling to find a compromise between contradictory dimensions. To illustrate our approach, we use an Intelligent Transportation System scenario. This case study enables us to show the advantages of obtaining suitable and optimized configurations for self-adapting WSNs
Quality-of-service in wireless sensor networks: state-of-the-art and future directions
Wireless sensor networks (WSNs) are one of today’s most prominent instantiations
of the ubiquituous computing paradigm. In order to achieve high
levels of integration, WSNs need to be conceived considering requirements
beyond the mere system’s functionality. While Quality-of-Service (QoS) is
traditionally associated with bit/data rate, network throughput, message delay
and bit/packet error rate, we believe that this concept is too strict, in
the sense that these properties alone do not reflect the overall quality-ofservice
provided to the user/application. Other non-functional properties
such as scalability, security or energy sustainability must also be considered
in the system design. This paper identifies the most important non-functional
properties that affect the overall quality of the service provided to the users,
outlining their relevance, state-of-the-art and future research directions
From MANET to people-centric networking: Milestones and open research challenges
In this paper, we discuss the state of the art of (mobile) multi-hop ad hoc networking with the aim to present the current status of the research activities and identify the consolidated research areas, with limited research opportunities, and the hot and emerging research areas for which further research is required. We start by briefly discussing the MANET paradigm, and why the research on MANET protocols is now a cold research topic. Then we analyze the active research areas. Specifically, after discussing the wireless-network technologies, we analyze four successful ad hoc networking paradigms, mesh networks, opportunistic networks, vehicular networks, and sensor networks that emerged from the MANET world. We also present an emerging research direction in the multi-hop ad hoc networking field: people centric networking, triggered by the increasing penetration of the smartphones in everyday life, which is generating a people-centric revolution in computing and communications
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