Reconfigurable middleware architectures for large scale sensor networks

Wireless sensor networks, in an effort to be energy efficient, typically lack the high-level abstractions of advanced programming languages. Though strong, the dichotomy between these two paradigms can be overcome. The SENSIX software framework, described in this dissertation, uniquely integrates constraint-dominated wireless sensor networks with the flexibility of object-oriented programming models, without violating the principles of either. Though these two computing paradigms are contradictory in many ways, SENSIX bridges them to yield a dynamic middleware abstraction unifying low-level resource-aware task reconfiguration and high-level object recomposition. Through the layered approach of SENSIX, the software developer creates a domain-specific sensing architecture by defining a customized task specification and utilizing object inheritance. In addition, SENSIX performs better at large scales (on the order of 1000 nodes or more) than other sensor network middleware which do not include such unified facilities for vertical integration

FPGA-Based Wireless Sensor Node Architecture for High Performance Applications

While for years traditional wireless sensor nodes have been based on ultra-low power microcontrollers with sufficient but limited computing power, the complexity and number of tasks of today’s applications are constantly increasing. Increasing the node duty cycle is not feasible in all cases, so in many cases more computing power is required. This extra computing power may be achieved by either more powerful microcontrollers, though more power consumption or, in general, any solution capable of accelerating task execution. At this point, the use of hardware based, and in particular FPGA solutions, might appear as a candidate technology, since though power use is higher compared with lower power devices, execution time is reduced, so energy could be reduced overall. In order to demonstrate this, an innovative WSN node architecture is proposed. This architecture is based on a high performance high capacity state-of-the-art FPGA, which combines the advantages of the intrinsic acceleration provided by the parallelism of hardware devices, the use of partial reconfiguration capabilities, as well as a careful power-aware management system, to show that energy savings for certain higher-end applications can be achieved. Finally, comprehensive tests have been done to validate the platform in terms of performance and power consumption, to proof that better energy efficiency compared to processor based solutions can be achieved, for instance, when encryption is imposed by the application requirements

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

Analysis of current and potential sensor network technologies and their incorporation as embedded structural system

This document provides a brief overview of the actual wireless ad hoc sensor networks technologies and standards available, especially in view of their possible implementation for shipping container protection and monitoring within the framework of the STEC Action aiming at analyzing possible technical solutions to improve the security of the millions of containers moving in and out of Europe. Examples of applications and research projects are reported from the literature to give insights on the possibility of implementation of wireless sensor networks in real world scenarios.JRC.G.5-European laboratory for structural assessmen

Towards Efficient Wireless Video Sensor Networks: A Survey of Existing Node Architectures and Proposal for A Flexi-WVSNP Design

Wireless sensor networks (WSNs) capable of capturing video at distributed video sensor nodes and transmitting the video via multiple wireless hops to sink nodes have received significan

A comprehensive survey of wireless body area networks on PHY, MAC, and network layers solutions

Recent advances in microelectronics and integrated circuits, system-on-chip design, wireless communication and intelligent low-power sensors have allowed the realization of a Wireless Body Area Network (WBAN). A WBAN is a collection of low-power, miniaturized, invasive/non-invasive lightweight wireless sensor nodes that monitor the human body functions and the surrounding environment. In addition, it supports a number of innovative and interesting applications such as ubiquitous healthcare, entertainment, interactive gaming, and military applications. In this paper, the fundamental mechanisms of WBAN including architecture and topology, wireless implant communication, low-power Medium Access Control (MAC) and routing protocols are reviewed. A comprehensive study of the proposed technologies for WBAN at Physical (PHY), MAC, and Network layers is presented and many useful solutions are discussed for each layer. Finally, numerous WBAN applications are highlighted

Leveraging software-defined networking for modular management in wireless sensor networks

Thesis (PhD (Electronics))--University of Pretoria, 2019.Wireless sensor networks (WSNs) are becoming increasingly popular with the advent of the internet of things (IoT). Various real-world applications of WSNs such as in smart grids, smart farming, and smart health would require a potential deployment of thousands or maybe hundreds of thousands of sensor nodes/actuators. To ensure the proper working order and network efficiency of such a network of sensor nodes, an effective WSN management system has to be integrated. However, the inherent challenges of WSNs such as sensor/actuator heterogeneity, application dependency, and resource constraints have led to challenges in implementing effective traditional WSN management. This difficulty in management increases as the WSN becomes larger. Software-defined networking (SDN) provides a promising solution for flexible management of WSNs by allowing the separation of the control logic from the sensor nodes/actuators. The advantage with this SDN-based management in WSNs is that it enables centralized control of the entire WSN making it simpler to deploy network-wide management protocols and applications on demand. Therefore in a comprehensive literature review, this study highlights some of the recent work on traditional WSN management in brief and reviews SDN-based management techniques for WSNs in greater detail. All this while drawing attention towards the advantages that SDN brings to traditional WSN management. This study also investigates open research challenges in coming up with mechanisms for flexible and easier SDN-based WSN configuration and management. A profound research challenge uncovered in the literature review is the need for an SDN-based system that would provide an opportunity for rapid testing and implementation of management modules. Therefore, this study proposes SDNMM, a generic and modular WSN management system based on SDN. SDNMM introduces the concept of management modularity using a management service interface (MSI) that enables management entities to be added as modules. The system leverages the use of SDN in WSNs and by being modular it also allows for rapid development and implementation of IoT applications. The system has been built on an open-source platform to support its generic aspect and a sample resource management module implemented and evaluated to support the proposed modular management approach. Results showed how adding a resource management module via the MSI improved packet delivery, delay, control traffic and energy consumption over comparable frameworks. However, SDN-based implementation comes at a cost of control overhead traffic which is a performance bottleneck in WSNs due to the limited in-band traffic channel bandwidth associated with WSNs. This has driven the research community to look into methods of effectively reducing the overhead control traffic in a process known as control message quenching (CMQ). In this study, a state of the art overview of control traffic reduction techniques available and being implemented for SDN-based WSNs is also presented. It provides an insight on benefits, challenges and open research areas available in the field of control message quenching for SDN-based WSNs. This study opens the door to this widely unexplored research area in its current form. Additionally, this study introduces a neighbour discovery control message quenching (ND-CMQ) algorithm to aid the reduction of neighbour reports in an SDN-based 6LoWPAN framework. The algorithm produces a significant decrease in control traffic and as a result shows improvements in packet delivery rate, packet delay, and energy efficiency compared to not implementing any CMQ algorithm and also compared to an alternative FR-CMQ algorithm based on flow setup requests.Copperbelt University under the ministry of higher education in ZambiaCouncil for Scientific and Industrial Research (CSIR)Electrical, Electronic and Computer EngineeringPhD (Electronics)Unrestricte