1,362 research outputs found
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
Initial Phase Proximity for Reachback Firefly Synchronicity in WSNs: Node Clustering
Synchronicity is one of the essential basic services to support the main duties of Wireless Sensor Networks (WSNs). Synchronicity is the ability to arrange simultaneously collective actions in WSNs. A high-rate data sampling to analyze the seismic structure and volcanic monitoring is the important applications requiring a synchronicity. However, most of the existing synchronicity algorithm is still executed in a flat network, so that it requires a long time to achieve a synchronous condition. To increase the convergence rate, the synchronicity can be executed concurrently through a clustering scheme approach. In this work, the such scheme is called as the Node Clustering based on Initial Phase Proximity for Reachback Firefly Synchronicity (NCIPP-RFS). The NCIPP-RFS solves in three steps: (1) constructing the node clustering, (2) intra-cluster synchronicity, and (3) inter-cluster synchronicity. The NCIPP-RFS method is based on the firefly-inspired algorithm. The fireflies are a species in the natural system, which are able to manage their flashing for synchronicity in a distributed manner. The NCIPP-RFS was implemented in NS-3 and evaluated and compared with Reachback Firefly Algorithm (RFA). The simulation results show a significant increase in the convergence rate. The NCIPP-RFS can reach a convergence time shorter than the RFA. In addition, the NCIPP-RFS was compared in the various numbers of clusters, where the least number of clusters can reach the fastest convergence rate. Finally, it can also contribute significantly to the increase of the convergence rate if the number of nodes is greater than or equal to 50 nodes
Data Acquisition Applications
Data acquisition systems have numerous applications. This book has a total of 13 chapters and is divided into three sections: Industrial applications, Medical applications and Scientific experiments. The chapters are written by experts from around the world, while the targeted audience for this book includes professionals who are designers or researchers in the field of data acquisition systems. Faculty members and graduate students could also benefit from the book
Security and Privacy Issues in Wireless Mesh Networks: A Survey
This book chapter identifies various security threats in wireless mesh
network (WMN). Keeping in mind the critical requirement of security and user
privacy in WMNs, this chapter provides a comprehensive overview of various
possible attacks on different layers of the communication protocol stack for
WMNs and their corresponding defense mechanisms. First, it identifies the
security vulnerabilities in the physical, link, network, transport, application
layers. Furthermore, various possible attacks on the key management protocols,
user authentication and access control protocols, and user privacy preservation
protocols are presented. After enumerating various possible attacks, the
chapter provides a detailed discussion on various existing security mechanisms
and protocols to defend against and wherever possible prevent the possible
attacks. Comparative analyses are also presented on the security schemes with
regards to the cryptographic schemes used, key management strategies deployed,
use of any trusted third party, computation and communication overhead involved
etc. The chapter then presents a brief discussion on various trust management
approaches for WMNs since trust and reputation-based schemes are increasingly
becoming popular for enforcing security in wireless networks. A number of open
problems in security and privacy issues for WMNs are subsequently discussed
before the chapter is finally concluded.Comment: 62 pages, 12 figures, 6 tables. This chapter is an extension of the
author's previous submission in arXiv submission: arXiv:1102.1226. There are
some text overlaps with the previous submissio
Techniques for Decentralized and Dynamic Resource Allocation
abstract: This thesis investigates three different resource allocation problems, aiming to achieve two common goals: i) adaptivity to a fast-changing environment, ii) distribution of the computation tasks to achieve a favorable solution. The motivation for this work relies on the modern-era proliferation of sensors and devices, in the Data Acquisition Systems (DAS) layer of the Internet of Things (IoT) architecture. To avoid congestion and enable low-latency services, limits have to be imposed on the amount of decisions that can be centralized (i.e. solved in the ``cloud") and/or amount of control information that devices can exchange. This has been the motivation to develop i) a lightweight PHY Layer protocol for time synchronization and scheduling in Wireless Sensor Networks (WSNs), ii) an adaptive receiver that enables Sub-Nyquist sampling, for efficient spectrum sensing at high frequencies, and iii) an SDN-scheme for resource-sharing across different technologies and operators, to harmoniously and holistically respond to fluctuations in demands at the eNodeB' s layer.
The proposed solution for time synchronization and scheduling is a new protocol, called PulseSS, which is completely event-driven and is inspired by biological networks. The results on convergence and accuracy for locally connected networks, presented in this thesis, constitute the theoretical foundation for the protocol in terms of performance guarantee. The derived limits provided guidelines for ad-hoc solutions in the actual implementation of the protocol.
The proposed receiver for Compressive Spectrum Sensing (CSS) aims at tackling the noise folding phenomenon, e.g., the accumulation of noise from different sub-bands that are folded, prior to sampling and baseband processing, when an analog front-end aliasing mixer is utilized.
The sensing phase design has been conducted via a utility maximization approach, thus the scheme derived has been called Cognitive Utility Maximization Multiple Access (CUMMA).
The framework described in the last part of the thesis is inspired by stochastic network optimization tools and dynamics.
While convergence of the proposed approach remains an open problem, the numerical results here presented suggest the capability of the algorithm to handle traffic fluctuations across operators, while respecting different time and economic constraints.
The scheme has been named Decomposition of Infrastructure-based Dynamic Resource Allocation (DIDRA).Dissertation/ThesisDoctoral Dissertation Electrical Engineering 201
A centralized localization algorithm for prolonging the lifetime of wireless sensor networks using particle swarm optimization in the existence of obstacles
The evolution in micro-electro-mechanical systems technology (MEMS) has
triggered the need for the development of wireless sensor network (WSN). These
wireless sensor nodes has been used in many applications at many areas. One of the
main issues in WSN is the energy availability, which is always a constraint. In a
previous research, a relocating algorithm for mobile sensor network had been
introduced and the goal was to save energy and prolong the lifetime of the sensor
networks using Particle Swarm Optimization (PSO) where both of sensing radius and
travelled distance had been optimized in order to save energy in long-term and shortterm.
Yet, the previous research did not take into account obstacles’ existence in the
field and this will cause the sensor nodes to consume more power if obstacles are
exists in the sensing field. In this project, the same centralized relocating algorithm
from the previous research has been used where 15 mobile sensors deployed
randomly in a field of 100 meter by 100 meter where these sensors has been
deployed one time in a field that obstacles does not exist (case 1) and another time in
a field that obstacles existence has been taken into account (case 2), in which these
obstacles has been pre-defined positions, where these two cases applied into two
different algorithms, which are the original algorithm of a previous research and the
modified algorithm of this thesis. Particle Swarm Optimization has been used in the
proposed algorithm to minimize the fitness function. Voronoi diagram has also used
in order to ensure that the mobile sensors cover the whole sensing field. In this
project, the objectives will be mainly focus on the travelling distance, which is the
mobility module, of the mobile sensors in the network because the distance that the
sensor node travels, will consume too much power from this node and this will lead
to shortening the lifetime of the sensor network. So, the travelling distance, power
consumption and lifetime of the network will be calculated in both cases for original
algorithm and modified algorithm, which is a modified deployment algorithm, and compared between them. Moreover, the maximum sensing range is calculated, which
is 30 meter, by using the binary sensing model even though the sensing module does
not consume too much power compared to the mobility module. Finally, the
comparison of the results in the original method will show that this algorithm is not
suitable for an environment where obstacle exist because sensors will consume too
much power compared to the sensors that deployed in environment that free of
obstacles. While the results of the modified algorithm of this research will be more
suitable for both environments, that is environment where obstacles are not exist and
environment where obstacles are exist, because sensors in this algorithm .will
consume almost the same amount of power at both of these environments
Architectures and synchronization techniques for distributed satellite systems: a survey
Cohesive Distributed Satellite Systems (CDSSs) is a key enabling technology for the future of remote sensing and communication missions. However, they have to meet strict synchronization requirements before their use is generalized. When clock or local oscillator signals are generated locally at each of the distributed nodes, achieving exact synchronization in absolute phase, frequency, and time is a complex problem. In addition, satellite systems have significant resource constraints, especially for small satellites, which are envisioned to be part of the future CDSSs. Thus, the development of precise, robust, and resource-efficient synchronization techniques is essential for the advancement of future CDSSs. In this context, this survey aims to summarize and categorize the most relevant results on synchronization techniques for Distributed Satellite Systems (DSSs). First, some important architecture and system concepts are defined. Then, the synchronization methods reported in the literature are reviewed and categorized. This article also provides an extensive list of applications and examples of synchronization techniques for DSSs in addition to the most significant advances in other operations closely related to synchronization, such as inter-satellite ranging and relative position. The survey also provides a discussion on emerging data-driven synchronization techniques based on Machine Learning (ML). Finally, a compilation of current research activities and potential research topics is proposed, identifying problems and open challenges that can be useful for researchers in the field.This work was supported by the Luxembourg National Research Fund (FNR), through the CORE Project COHEsive SATellite (COHESAT): Cognitive Cohesive Networks of Distributed Units for Active and Passive Space Applications, under Grant FNR11689919.Award-winningPostprint (published version
Emerging Communications for Wireless Sensor Networks
Wireless sensor networks are deployed in a rapidly increasing number of arenas, with uses ranging from healthcare monitoring to industrial and environmental safety, as well as new ubiquitous computing devices that are becoming ever more pervasive in our interconnected society. This book presents a range of exciting developments in software communication technologies including some novel applications, such as in high altitude systems, ground heat exchangers and body sensor networks. Authors from leading institutions on four continents present their latest findings in the spirit of exchanging information and stimulating discussion in the WSN community worldwide
Time coordination of standalone measurement instruments by synchronized triggering
A Hardware Interface (HI) to synchronize the operations of standalone Measurement Instruments (MIs) in the absence of networking has been proposed in the recent literature. The synchronization accuracy achieved is one period of the clock equipping the HI. To improve the synchronization accuracy two solutions can be argued on the basis of the mathematical model of the delay between HIs. The first involves increasing the clock frequency; the second concerns the compensation of the phase delay between HI clocks. In this paper the second solution is adopted in order to: (i) reduce the energy consumption, and (ii) not increase the complexity of the hardware architecture. The phase delay compensation is obtained by introducing a programmable delay line after the HI clocks. The phase delay evaluation and the successive tuning of the delay line are performed in the synchronization phase of the HIs. Once synchronized, each HI is moved to the standalone MI to trigger it according to the common sense of time. During the execution of the measurement procedure, networking is not necessary. Experimental tests validate the correct operation of the upgraded HI architecture and indicate that the achievable synchronization accuracy is a low percentage of the HI clock period.</p
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