Designing Flexible, Energy Efficient and Secure Wireless Solutions for the Internet of Things

The Internet of Things (IoT) is an emerging concept where ubiquitous physical objects (things) consisting of sensor, transceiver, processing hardware and software are interconnected via the Internet. The information collected by individual IoT nodes is shared among other often heterogeneous devices and over the Internet. This dissertation presents flexible, energy efficient and secure wireless solutions in the IoT application domain. System design and architecture designs are discussed envisioning a near-future world where wireless communication among heterogeneous IoT devices are seamlessly enabled. Firstly, an energy-autonomous wireless communication system for ultra-small, ultra-low power IoT platforms is presented. To achieve orders of magnitude energy efficiency improvement, a comprehensive system-level framework that jointly optimizes various system parameters is developed. A new synchronization protocol and modulation schemes are specified for energy-scarce ultra-small IoT nodes. The dynamic link adaptation is proposed to guarantee the ultra-small node to always operate in the most energy efficiency mode, given an operating scenario. The outcome is a truly energy-optimized wireless communication system to enable various new applications such as implanted smart-dust devices. Secondly, a configurable Software Defined Radio (SDR) baseband processor is designed and shown to be an efficient platform on which to execute several IoT wireless standards. It is a custom SIMD execution model coupled with a scalar unit and several architectural optimizations: streaming registers, variable bitwidth, dedicated ALUs, and an optimized reduction network. Voltage scaling and clock gating are employed to further reduce the power, with a more than a 100% time margin reserved for reliable operation in the near-threshold region. Two upper bound systems are evaluated. A comprehensive power/area estimation indicates that the overhead of realizing SDR flexibility is insignificant. The benefit of baseband SDR is quantified and evaluated. To further augment the benefits of a flexible baseband solution and to address the security issue of IoT connectivity, a light-weight Galois Field (GF) processor is proposed. This processor enables both energy-efficient block coding and symmetric/asymmetric cryptography kernel processing for a wide range of GF sizes (2^m, m = 2, 3, ..., 233) and arbitrary irreducible polynomials. Program directed connections among primitive GF arithmetic units enable dynamically configured parallelism to efficiently perform either four-way SIMD GF operations, including multiplicative inverse, or a long bit-width GF product in a single cycle. This demonstrates the feasibility of a unified architecture to enable error correction coding flexibility and secure wireless communication in the low power IoT domain.PHDComputer Science & EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/137164/1/yajchen_1.pd

IEEE 802.15.4e: a Survey

Several studies have highlighted that the IEEE 802.15.4 standard presents a number of limitations such as low reliability, unbounded packet delays and no protection against interference/fading, that prevent its adoption in applications with stringent requirements in terms of reliability and latency. Recently, the IEEE has released the 802.15.4e amendment that introduces a number of enhancements/modifications to the MAC layer of the original standard in order to overcome such limitations. In this paper we provide a clear and structured overview of all the new 802.15.4e mechanisms. After a general introduction to the 802.15.4e standard, we describe the details of the main 802.15.4e MAC behavior modes, namely Time Slotted Channel Hopping (TSCH), Deterministic and Synchronous Multi-channel Extension (DSME), and Low Latency Deterministic Network (LLDN). For each of them, we provide a detailed description and highlight the main features and possible application domains. Also, we survey the current literature and summarize open research issues

Security protocols suite for machine-to-machine systems

Nowadays, the great diffusion of advanced devices, such as smart-phones, has shown that there is a growing trend to rely on new technologies to generate and/or support progress; the society is clearly ready to trust on next-generation communication systems to face today’s concerns on economic and social fields. The reason for this sociological change is represented by the fact that the technologies have been open to all users, even if the latter do not necessarily have a specific knowledge in this field, and therefore the introduction of new user-friendly applications has now appeared as a business opportunity and a key factor to increase the general cohesion among all citizens. Within the actors of this technological evolution, wireless machine-to-machine (M2M) networks are becoming of great importance. These wireless networks are made up of interconnected low-power devices that are able to provide a great variety of services with little or even no user intervention. Examples of these services can be fleet management, fire detection, utilities consumption (water and energy distribution, etc.) or patients monitoring. However, since any arising technology goes together with its security threats, which have to be faced, further studies are necessary to secure wireless M2M technology. In this context, main threats are those related to attacks to the services availability and to the privacy of both the subscribers’ and the services providers’ data. Taking into account the often limited resources of the M2M devices at the hardware level, ensuring the availability and privacy requirements in the range of M2M applications while minimizing the waste of valuable resources is even more challenging. Based on the above facts, this Ph. D. thesis is aimed at providing efficient security solutions for wireless M2M networks that effectively reduce energy consumption of the network while not affecting the overall security services of the system. With this goal, we first propose a coherent taxonomy of M2M network that allows us to identify which security topics deserve special attention and which entities or specific services are particularly threatened. Second, we define an efficient, secure-data aggregation scheme that is able to increase the network lifetime by optimizing the energy consumption of the devices. Third, we propose a novel physical authenticator or frame checker that minimizes the communication costs in wireless channels and that successfully faces exhaustion attacks. Fourth, we study specific aspects of typical key management schemes to provide a novel protocol which ensures the distribution of secret keys for all the cryptographic methods used in this system. Fifth, we describe the collaboration with the WAVE2M community in order to define a proper frame format actually able to support the necessary security services, including the ones that we have already proposed; WAVE2M was funded to promote the global use of an emerging wireless communication technology for ultra-low and long-range services. And finally sixth, we provide with an accurate analysis of privacy solutions that actually fit M2M-networks services’ requirements. All the analyses along this thesis are corroborated by simulations that confirm significant improvements in terms of efficiency while supporting the necessary security requirements for M2M networks

Wireless sensor networks

Wireless sensor networks promise an unprecedented fine-grained interface between the virtual and the physical world. They are one of the most rapidly developing new information technologies, with applications in a wide range of fields including industrial process control, security and surveillance, environmental sensing, and structural health monitoring. The subject of this project is motivated by the urgent need to provide a comprehensive and organized survey of the field. It shows how the core challenges of energy efficiency, robustness, and autonomy are addressed in these systems by networking techniques across multiple layers. The topics covered include network deployment, wireless characteristics, time synchronization, congestion and error control, medium access, standards, topology control, routing, security, data transfer, transport protocols and new technologies and materials in fabricating sensors

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

Intelligent Sensor Networks

In the last decade, wireless or wired sensor networks have attracted much attention. However, most designs target general sensor network issues including protocol stack (routing, MAC, etc.) and security issues. This book focuses on the close integration of sensing, networking, and smart signal processing via machine learning. Based on their world-class research, the authors present the fundamentals of intelligent sensor networks. They cover sensing and sampling, distributed signal processing, and intelligent signal learning. In addition, they present cutting-edge research results from leading experts

Applications

Volume 3 describes how resource-aware machine learning methods and techniques are used to successfully solve real-world problems. The book provides numerous specific application examples: in health and medicine for risk modelling, diagnosis, and treatment selection for diseases in electronics, steel production and milling for quality control during manufacturing processes in traffic, logistics for smart cities and for mobile communications

Applications

Volume 3 describes how resource-aware machine learning methods and techniques are used to successfully solve real-world problems. The book provides numerous specific application examples: in health and medicine for risk modelling, diagnosis, and treatment selection for diseases in electronics, steel production and milling for quality control during manufacturing processes in traffic, logistics for smart cities and for mobile communications

Use of Inferential Statistics to Design Effective Communication Protocols for Wireless Sensor Networks

This thesis explores the issues and techniques associated with employing the principles of inferential statistics to design effective Medium Access Control (MAC), routing and duty cycle management strategies for multihop Wireless Sensor Networks (WSNs). The main objective of these protocols are to maximise the throughput of the network, to prolong the lifetime of nodes and to reduce the end-to-end delay of packets over a general network scenario without particular considerations for specific topology configurations, traffic patterns or routing policies. WSNs represent one of the leading-edge technologies that have received substantial research efforts due to their prominent roles in many applications. However, to design effective communication protocols for WSNs is particularly challenging due to the scarce resources of these networks and the requirement for large-scale deployment. The MAC, routing and duty cycle management protocols are amongst the important strategies that are required to ensure correct operations of WSNs. This thesis makes use of the inferential statistics field to design these protocols; inferential statistics was selected as it provides a rich design space with powerful approaches and methods. The MAC protocol proposed in this thesis exploits the statistical characteristics of the Gamma distribution to enable each node to adjust its contention parameters dynamically based on its inference for the channel occupancy. This technique reduces the service time of packets and leverages the throughput by improving the channel utilisation. Reducing the service time minimises the energy consumed in contention to access the channel which in turn prolongs the lifetime of nodes. The proposed duty cycle management scheme uses non-parametric Bayesian inference to enable each node to determine the best times and durations for its sleeping durations without posing overheads on the network. Hence the lifetime of node is prolonged by mitigating the amount of energy wasted in overhearing and idle listening. Prolonging the lifetime of nodes increases the throughput of the network and reduces the end-to-end delay as it allows nodes to route their packets over optimal paths for longer periods. The proposed routing protocol uses one of the state-of-the-art inference techniques dubbed spatial reasoning that enables each node to figure out the spatial relationships between nodes without overwhelming the network with control packets. As a result, the end-to-end delay is reduced while the throughput and lifetime are increased. Besides the proposed protocols, this thesis utilises the analytical aspects of statistics to develop rigorous analytical models that can accurately predict the queuing and medium access delay and energy consumption over multihop networks. Moreover, this thesis provides a broader perspective for design of communication protocols for WSNs by casting the operations of these networks in the domains of the artificial chemistry discipline and the harmony search optimisation algorithm