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

Distance Aware Relaying Energy-efficient: DARE to Monitor Patients in Multi-hop Body Area Sensor Networks

In recent years, interests in the applications of Wireless Body Area Sensor Network (WBASN) is noticeably developed. WBASN is playing a significant role to get the real time and precise data with reduced level of energy consumption. It comprises of tiny, lightweight and energy restricted sensors, placed in/on the human body, to monitor any ambiguity in body organs and measure various biomedical parameters. In this study, a protocol named Distance Aware Relaying Energy-efficient (DARE) to monitor patients in multi-hop Body Area Sensor Networks (BASNs) is proposed. The protocol operates by investigating the ward of a hospital comprising of eight patients, under different topologies by positioning the sink at different locations or making it static or mobile. Seven sensors are attached to each patient, measuring different parameters of Electrocardiogram (ECG), pulse rate, heart rate, temperature level, glucose level, toxins level and motion. To reduce the energy consumption, these sensors communicate with the sink via an on-body relay, affixed on the chest of each patient. The body relay possesses higher energy resources as compared to the body sensors as, they perform aggregation and relaying of data to the sink node. A comparison is also conducted conducted with another protocol of BAN named, Mobility-supporting Adaptive Threshold-based Thermal-aware Energy-efficient Multi-hop ProTocol (M-ATTEMPT). The simulation results show that, the proposed protocol achieves increased network lifetime and efficiently reduces the energy consumption, in relative to M-ATTEMPT protocol.Comment: IEEE 8th International Conference on Broadband and Wireless Computing, Communication and Applications (BWCCA'13), Compiegne, Franc

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

Multi-hop Cooperative Relaying for Energy Efficient In Vivo Communications

This paper investigates cooperative relaying to support energy efficient in vivo communications. In such a network, the in vivo source nodes transmit their sensing information to an on-body destination node either via direct communications or by employing on-body cooperative relay nodes in order to promote energy efficiency. Two relay modes are investigated, namely single-hop and multi-hop (two-hop) relaying. In this context, the paper objective is to select the optimal transmission mode (direct, single-hop, or two-hop relaying) and relay assignment (if cooperative relaying is adopted) for each source node that results in the minimum per bit average energy consumption for the in vivo network. The problem is formulated as a binary program that can be efficiently solved using commercial optimization solvers. Numerical results demonstrate the significant improvement in energy consumption and quality-of-service (QoS) support when multi-hop communication is adopted

THE-FAME: THreshold based Energy-efficient FAtigue MEasurment for Wireless Body Area Sensor Networks using Multiple Sinks

Wireless Body Area Sensor Network (WBASN) is a technology employed mainly for patient health monitoring. New research is being done to take the technology to the next level i.e. player's fatigue monitoring in sports. Muscle fatigue is the main cause of player's performance degradation. This type of fatigue can be measured by sensing the accumulation of lactic acid in muscles. Excess of lactic acid makes muscles feel lethargic. Keeping this in mind we propose a protocol \underline{TH}reshold based \underline{E}nergy-efficient \underline{FA}tigue \underline{ME}asurement (THE-FAME) for soccer players using WBASN. In THE-FAME protocol, a composite parameter has been used that consists of a threshold parameter for lactic acid accumulation and a parameter for measuring distance covered by a particular player. When any parameters's value in this composite parameter shows an increase beyond threshold, the players is declared to be in a fatigue state. The size of battery and sensor should be very small for the sake of players' best performance. These sensor nodes, implanted inside player's body, are made energy efficient by using multiple sinks instead of a single sink. Matlab simulation results show the effectiveness of THE-FAME.Comment: IEEE 8th International Conference on Broadband and Wireless Computing, Communication and Applications (BWCCA'13), Compiegne, Franc

A low-power opportunistic communication protocol for wearable applications

© 2015 IEEE.Recent trends in wearable applications demand flexible architectures being able to monitor people while they move in free-living environments. Current solutions use either store-download-offline processing or simple communication schemes with real-time streaming of sensor data. This limits the applicability of wearable applications to controlled environments (e.g, clinics, homes, or laboratories), because they need to maintain connectivity with the base station throughout the monitoring process. In this paper, we present the design and implementation of an opportunistic communication framework that simplifies the general use of wearable devices in free-living environments. It relies on a low-power data collection protocol that allows the end user to opportunistically, yet seamlessly manage the transmission of sensor data. We validate the feasibility of the framework by demonstrating its use for swimming, where the normal wireless communication is constantly interfered by the environment

An Efficient Uplink Multi-Connectivity Scheme for 5G mmWave Control Plane Applications

The millimeter wave (mmWave) frequencies offer the potential of orders of magnitude increases in capacity for next-generation cellular systems. However, links in mmWave networks are susceptible to blockage and may suffer from rapid variations in quality. Connectivity to multiple cells - at mmWave and/or traditional frequencies - is considered essential for robust communication. One of the challenges in supporting multi-connectivity in mmWaves is the requirement for the network to track the direction of each link in addition to its power and timing. To address this challenge, we implement a novel uplink measurement system that, with the joint help of a local coordinator operating in the legacy band, guarantees continuous monitoring of the channel propagation conditions and allows for the design of efficient control plane applications, including handover, beam tracking and initial access. We show that an uplink-based multi-connectivity approach enables less consuming, better performing, faster and more stable cell selection and scheduling decisions with respect to a traditional downlink-based standalone scheme. Moreover, we argue that the presented framework guarantees (i) efficient tracking of the user in the presence of the channel dynamics expected at mmWaves, and (ii) fast reaction to situations in which the primary propagation path is blocked or not available.Comment: Submitted for publication in IEEE Transactions on Wireless Communications (TWC

Wearable Communications in 5G: Challenges and Enabling Technologies

As wearable devices become more ingrained in our daily lives, traditional communication networks primarily designed for human being-oriented applications are facing tremendous challenges. The upcoming 5G wireless system aims to support unprecedented high capacity, low latency, and massive connectivity. In this article, we evaluate key challenges in wearable communications. A cloud/edge communication architecture that integrates the cloud radio access network, software defined network, device to device communications, and cloud/edge technologies is presented. Computation offloading enabled by this multi-layer communications architecture can offload computation-excessive and latency-stringent applications to nearby devices through device to device communications or to nearby edge nodes through cellular or other wireless technologies. Critical issues faced by wearable communications such as short battery life, limited computing capability, and stringent latency can be greatly alleviated by this cloud/edge architecture. Together with the presented architecture, current transmission and networking technologies, including non-orthogonal multiple access, mobile edge computing, and energy harvesting, can greatly enhance the performance of wearable communication in terms of spectral efficiency, energy efficiency, latency, and connectivity.Comment: This work has been accepted by IEEE Vehicular Technology Magazin