Boundary node selection algorithms in WSNs

Physical damage and/or node power exhaustion may lead to coverage holes in WSNs. Coverage holes can be directly detected by certain proximate nodes known as boundary nodes (B-nodes). Due to the sensor nodes' redundant deployment and autonomous fault detection, holes are surrounded by a margin of B-nodes (MB-nodes). If all B-nodes in the margin take part in the hole recovery processes, either by increasing their transmission power or by relocating towards region of interest (ROI), the probability of collision, interference, disconnection, and isolation may increase affecting the rest of the network's performance and QoS. Thus, distributed boundary node selection algorithms (BNS-Algorithms) are proposed to address these issues. BNS-algorithms allow B-nodes to self-select based on available 1-hop information extracted from nodes' simple geometrical and statistical features. Our results show that the performance of the proposed distributed BNS-algorithms approaches that of their centralized counterparts. © 2011 IEEE

Balancing the trade-off between cost and reliability for wireless sensor networks: a multi-objective optimized deployment method

The deployment of the sensor nodes (SNs) always plays a decisive role in the system performance of wireless sensor networks (WSNs). In this work, we propose an optimal deployment method for practical heterogeneous WSNs which gives a deep insight into the trade-off between the reliability and deployment cost. Specifically, this work aims to provide the optimal deployment of SNs to maximize the coverage degree and connection degree, and meanwhile minimize the overall deployment cost. In addition, this work fully considers the heterogeneity of SNs (i.e. differentiated sensing range and deployment cost) and three-dimensional (3-D) deployment scenarios. This is a multi-objective optimization problem, non-convex, multimodal and NP-hard. To solve it, we develop a novel swarm-based multi-objective optimization algorithm, known as the competitive multi-objective marine predators algorithm (CMOMPA) whose performance is verified by comprehensive comparative experiments with ten other stateof-the-art multi-objective optimization algorithms. The computational results demonstrate that CMOMPA is superior to others in terms of convergence and accuracy and shows excellent performance on multimodal multiobjective optimization problems. Sufficient simulations are also conducted to evaluate the effectiveness of the CMOMPA based optimal SNs deployment method. The results show that the optimized deployment can balance the trade-off among deployment cost, sensing reliability and network reliability. The source code is available on https://github.com/iNet-WZU/CMOMPA.Comment: 25 page

Internet of Underwater Things and Big Marine Data Analytics -- A Comprehensive Survey

The Internet of Underwater Things (IoUT) is an emerging communication ecosystem developed for connecting underwater objects in maritime and underwater environments. The IoUT technology is intricately linked with intelligent boats and ships, smart shores and oceans, automatic marine transportations, positioning and navigation, underwater exploration, disaster prediction and prevention, as well as with intelligent monitoring and security. The IoUT has an influence at various scales ranging from a small scientific observatory, to a midsized harbor, and to covering global oceanic trade. The network architecture of IoUT is intrinsically heterogeneous and should be sufficiently resilient to operate in harsh environments. This creates major challenges in terms of underwater communications, whilst relying on limited energy resources. Additionally, the volume, velocity, and variety of data produced by sensors, hydrophones, and cameras in IoUT is enormous, giving rise to the concept of Big Marine Data (BMD), which has its own processing challenges. Hence, conventional data processing techniques will falter, and bespoke Machine Learning (ML) solutions have to be employed for automatically learning the specific BMD behavior and features facilitating knowledge extraction and decision support. The motivation of this paper is to comprehensively survey the IoUT, BMD, and their synthesis. It also aims for exploring the nexus of BMD with ML. We set out from underwater data collection and then discuss the family of IoUT data communication techniques with an emphasis on the state-of-the-art research challenges. We then review the suite of ML solutions suitable for BMD handling and analytics. We treat the subject deductively from an educational perspective, critically appraising the material surveyed.Comment: 54 pages, 11 figures, 19 tables, IEEE Communications Surveys & Tutorials, peer-reviewed academic journa

Telecommunications Networks

This book guides readers through the basics of rapidly emerging networks to more advanced concepts and future expectations of Telecommunications Networks. It identifies and examines the most pressing research issues in Telecommunications and it contains chapters written by leading researchers, academics and industry professionals. Telecommunications Networks - Current Status and Future Trends covers surveys of recent publications that investigate key areas of interest such as: IMS, eTOM, 3G/4G, optimization problems, modeling, simulation, quality of service, etc. This book, that is suitable for both PhD and master students, is organized into six sections: New Generation Networks, Quality of Services, Sensor Networks, Telecommunications, Traffic Engineering and Routing

Mobile Ad Hoc Networks

Guiding readers through the basics of these rapidly emerging networks to more advanced concepts and future expectations, Mobile Ad hoc Networks: Current Status and Future Trends identifies and examines the most pressing research issues in Mobile Ad hoc Networks (MANETs). Containing the contributions of leading researchers, industry professionals, and academics, this forward-looking reference provides an authoritative perspective of the state of the art in MANETs. The book includes surveys of recent publications that investigate key areas of interest such as limited resources and the mobility of mobile nodes. It considers routing, multicast, energy, security, channel assignment, and ensuring quality of service. Also suitable as a text for graduate students, the book is organized into three sections: Fundamentals of MANET Modeling and Simulation—Describes how MANETs operate and perform through simulations and models Communication Protocols of MANETs—Presents cutting-edge research on key issues, including MAC layer issues and routing in high mobility Future Networks Inspired By MANETs—Tackles open research issues and emerging trends Illustrating the role MANETs are likely to play in future networks, this book supplies the foundation and insight you will need to make your own contributions to the field. It includes coverage of routing protocols, modeling and simulations tools, intelligent optimization techniques to multicriteria routing, security issues in FHAMIPv6, connecting moving smart objects to the Internet, underwater sensor networks, wireless mesh network architecture and protocols, adaptive routing provision using Bayesian inference, and adaptive flow control in transport layer using genetic algorithms

Fuzzy Logic

The capability of Fuzzy Logic in the development of emerging technologies is introduced in this book. The book consists of sixteen chapters showing various applications in the field of Bioinformatics, Health, Security, Communications, Transportations, Financial Management, Energy and Environment Systems. This book is a major reference source for all those concerned with applied intelligent systems. The intended readers are researchers, engineers, medical practitioners, and graduate students interested in fuzzy logic systems

Deep learning for internet of underwater things and ocean data analytics

The Internet of Underwater Things (IoUT) is an emerging technological ecosystem developed for connecting objects in maritime and underwater environments. IoUT technologies are empowered by an extreme number of deployed sensors and actuators. In this thesis, multiple IoUT sensory data are augmented with machine intelligence for forecasting purposes

Mobile Ad Hoc Networks

Guiding readers through the basics of these rapidly emerging networks to more advanced concepts and future expectations, Mobile Ad hoc Networks: Current Status and Future Trends identifies and examines the most pressing research issues in Mobile Ad hoc Networks (MANETs). Containing the contributions of leading researchers, industry professionals, and academics, this forward-looking reference provides an authoritative perspective of the state of the art in MANETs. The book includes surveys of recent publications that investigate key areas of interest such as limited resources and the mobility of mobile nodes. It considers routing, multicast, energy, security, channel assignment, and ensuring quality of service. Also suitable as a text for graduate students, the book is organized into three sections: Fundamentals of MANET Modeling and Simulation—Describes how MANETs operate and perform through simulations and models Communication Protocols of MANETs—Presents cutting-edge research on key issues, including MAC layer issues and routing in high mobility Future Networks Inspired By MANETs—Tackles open research issues and emerging trends Illustrating the role MANETs are likely to play in future networks, this book supplies the foundation and insight you will need to make your own contributions to the field. It includes coverage of routing protocols, modeling and simulations tools, intelligent optimization techniques to multicriteria routing, security issues in FHAMIPv6, connecting moving smart objects to the Internet, underwater sensor networks, wireless mesh network architecture and protocols, adaptive routing provision using Bayesian inference, and adaptive flow control in transport layer using genetic algorithms

On a wildlife tracking and telemetry system : a wireless network approach

Includes abstract.Includes bibliographical references (p. 239-261).Motivated by the diversity of animals, a hybrid wildlife tracking system, EcoLocate, is proposed, with lightweight VHF-like tags and high performance GPS enabled tags, bound by a common wireless network design. Tags transfer information amongst one another in a multi-hop store-and-forward fashion, and can also monitor the presence of one another, enabling social behaviour studies to be conducted. Information can be gathered from any sensor variable of interest (such as temperature, water level, activity and so on) and forwarded through the network, thus leading to more effective game reserve monitoring. Six classes of tracking tags are presented, varying in weight and functionality, but derived from a common set of code, which facilitates modular tag design and deployment. The link between the tags means that tags can dynamically choose their class based on their remaining energy, prolonging lifetime in the network at the cost of a reduction in function. Lightweight, low functionality tags (that can be placed on small animals) use the capabilities of heavier, high functionality devices (placed on larger animals) to transfer their information. EcoLocate is a modular approach to animal tracking and sensing and it is shown how the same common technology can be used for diverse studies, from simple VHF-like activity research to full social and behavioural research using wireless networks to relay data to the end user. The network is not restricted to only tracking animals – environmental variables, people and vehicles can all be monitored, allowing for rich wildlife tracking studies