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

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

Hybrid Satellite-Terrestrial Communication Networks for the Maritime Internet of Things: Key Technologies, Opportunities, and Challenges

With the rapid development of marine activities, there has been an increasing number of maritime mobile terminals, as well as a growing demand for high-speed and ultra-reliable maritime communications to keep them connected. Traditionally, the maritime Internet of Things (IoT) is enabled by maritime satellites. However, satellites are seriously restricted by their high latency and relatively low data rate. As an alternative, shore & island-based base stations (BSs) can be built to extend the coverage of terrestrial networks using fourth-generation (4G), fifth-generation (5G), and beyond 5G services. Unmanned aerial vehicles can also be exploited to serve as aerial maritime BSs. Despite of all these approaches, there are still open issues for an efficient maritime communication network (MCN). For example, due to the complicated electromagnetic propagation environment, the limited geometrically available BS sites, and rigorous service demands from mission-critical applications, conventional communication and networking theories and methods should be tailored for maritime scenarios. Towards this end, we provide a survey on the demand for maritime communications, the state-of-the-art MCNs, and key technologies for enhancing transmission efficiency, extending network coverage, and provisioning maritime-specific services. Future challenges in developing an environment-aware, service-driven, and integrated satellite-air-ground MCN to be smart enough to utilize external auxiliary information, e.g., sea state and atmosphere conditions, are also discussed

Ultra Low Power Communication Protocols for UWB Impulse Radio Wireless Sensor Networks

This thesis evaluates the potential of Ultra Wideband Impulse Radio for wireless sensor network applications. Wireless sensor networks are collections of small electronic devices composed of one or more sensors to acquire information on their environment, an energy source (typically a battery), a microcontroller to control the measurements, process the information and communicate with its peers, and a radio transceiver to enable these communications. They are used to regularly collect information within their deployment area, often for very long periods of time (up to several years). The large number of devices often considered, as well as the long deployment durations, makes any manual intervention complex and costly. Therefore, these networks must self-configure, and automatically adapt to changes in their electromagnetic environment (channel variations, interferers) and network topology modifications: some nodes may run out of energy, or suffer from a hardware failure. Ultra Wideband Impulse Radio is a novel wireless technology that, thanks to its extremely large bandwidth, is more robust to frequency dependent propagation effects. Its impulsional nature makes it robust to multipath fading, as the short duration of the pulses leads most multipath components to arrive isolated. This technology should also enable high precision ranging through time of flight measurements, and operate at ultra low power levels. The main challenge is to design a system that reaches the same or higher degree of energy savings as existing narrowband systems considering all the protocol layers. As these radios are not yet widely available, the first part of this thesis presents Maximum Pulse Amplitude Estimation, a novel approach to symbol-level modeling of UWB-IR systems that enabled us to implement the first network simulator of devices compatible with the UWB physical layer of the IEEE 802.15.4A standard for wireless sensor networks. In the second part of this thesis, WideMac, a novel ultra low power MAC protocol specifically designed for UWB-IR devices is presented. It uses asynchronous duty cycling of the radio transceiver to minimize the power consumption, combined with periodic beacon emissions so that devices can learn each other's wake-up patterns and exchange packets. After an analytical study of the protocol, the network simulation tool presented in the first part of the thesis is used to evaluate the performance of WideMac in a medical body area network application. It is compared to two narrowband and an FM-UWB solutions. The protocol stack parameters are optimized for each solution, and it is observed that WideMac combined to UWB-IR is a credible technology for such applications. Similar simulations, considering this time a static multi-hop network are performed. It is found that WideMac and UWB-IR perform as well as a mature and highly optimized narrowband solution (based on the WiseMAC ULP MAC protocol), despite the lack of clear channel assessment functionality on the UWB radio. The last part of this thesis studies analytically a dual mode MAC protocol named WideMac-High Availability. It combines the Ultra Low PowerWideMac with the higher performance Aloha protocol, so that ultra low power consumption and hence long deployment times can be combined with high performance low latency communications when required by the application. The potential of this scheme is quantified, and it is proposed to adapt it to narrowband radio transceivers by combining WiseMAC and CSMA under the name WiseMAC-HA

QoS in Body Area Networks: A survey

Body Area Networks (BANs) are becoming increasingly popular and have shown great potential in real-time monitoring of the human body. With the promise of being cost-effective and unobtrusive and facilitating continuous monitoring, BANs have attracted a wide range of monitoring applications, including medical and healthcare, sports, and rehabilitation systems. Most of these applications are real time and life critical and require a strict guarantee of Quality of Service (QoS) in terms of timeliness, reliability, and so on. Recently, there has been a number of proposals describing diverse approaches or frameworks to achieve QoS in BANs (i.e., for different layers or tiers and different protocols). This survey put these individual efforts into perspective and presents a more holistic view of the area. In this regard, this article identifies a set of QoS requirements for BAN applications and shows how these requirements are linked in a three-tier BAN system and presents a comprehensive review of the existing proposals against those requirements. In addition, open research issues, challenges, and future research directions in achieving these QoS in BANs are highlighted.</jats:p

Cognitive Security Framework For Heterogeneous Sensor Network Using Swarm Intelligence

Rapid development of sensor technology has led to applications ranging from academic to military in a short time span. These tiny sensors are deployed in environments where security for data or hardware cannot be guaranteed. Due to resource constraints, traditional security schemes cannot be directly applied. Unfortunately, due to minimal or no communication security schemes, the data, link and the sensor node can be easily tampered by intruder attacks. This dissertation presents a security framework applied to a sensor network that can be managed by a cohesive sensor manager. A simple framework that can support security based on situation assessment is best suited for chaotic and harsh environments. The objective of this research is designing an evolutionary algorithm with controllable parameters to solve existing and new security threats in a heterogeneous communication network. An in-depth analysis of the different threats and the security measures applied considering the resource constrained network is explored. Any framework works best, if the correlated or orthogonal performance parameters are carefully considered based on system goals and functions. Hence, a trade-off between the different performance parameters based on weights from partially ordered sets is applied to satisfy application specific requirements and security measures. The proposed novel framework controls heterogeneous sensor network requirements,and balance the resources optimally and efficiently while communicating securely using a multi-objection function. In addition, the framework can measure the affect of single or combined denial of service attacks and also predict new attacks under both cooperative and non-cooperative sensor nodes. The cognitive intuition of the framework is evaluated under different simulated real time scenarios such as Health-care monitoring, Emergency Responder, VANET, Biometric security access system, and Battlefield monitoring. The proposed three-tiered Cognitive Security Framework is capable of performing situation assessment and performs the appropriate security measures to maintain reliability and security of the system. The first tier of the proposed framework, a crosslayer cognitive security protocol defends the communication link between nodes during denial-of-Service attacks by re-routing data through secure nodes. The cognitive nature of the protocol balances resources and security making optimal decisions to obtain reachable and reliable solutions. The versatility and robustness of the protocol is justified by the results obtained in simulating health-care and emergency responder applications under Sybil and Wormhole attacks. The protocol considers metrics from each layer of the network model to obtain an optimal and feasible resource efficient solution. In the second tier, the emergent behavior of the protocol is further extended to mine information from the nodes to defend the network against denial-of-service attack using Bayesian models. The jammer attack is considered the most vulnerable attack, and therefore simulated vehicular ad-hoc network is experimented with varied types of jammer. Classification of the jammer under various attack scenarios is formulated to predict the genuineness of the attacks on the sensor nodes using receiver operating characteristics. In addition to detecting the jammer attack, a simple technique of locating the jammer under cooperative nodes is implemented. This feature enables the network in isolating the jammer or the reputation of node is affected, thus removing the malicious node from participating in future routes. Finally, a intrusion detection system using `bait\u27 architecture is analyzed where resources is traded-off for the sake of security due to sensitivity of the application. The architecture strategically enables ant agents to detect and track the intruders threateningthe network. The proposed framework is evaluated based on accuracy and speed of intrusion detection before the network is compromised. This process of detecting the intrusion earlier helps learn future attacks, but also serves as a defense countermeasure. The simulated scenarios of this dissertation show that Cognitive Security Framework isbest suited for both homogeneous and heterogeneous sensor networks