Energy Saving and Reliability for Wireless Body Sensor Networks (WBSN)

Wireless network of wearable biomedical sensors by human body shows great potential to enhance the biometrics performance significantly. Meanwhile, it poses prominent characteristics and challenges to physicians and engineers for its particular medical application as compared to other application of wireless sensor networks (WSN). Mobility pattern plays an important role in designing the wireless body sensor networks (WBSN) and will also affect the accuracy of modeling WBSN in health care application. Much of the mobility scenarios generated in current work of wireless body sensor networks has used fairly simple models to generate the mobile topological graph, which bear little resemblance to the actual mobility patterns. This paper is the first attempt to investigate the mobility model in WBSN based on the existing mobility models in wireless data networks and ad hoc networks. We first briefly review the existing mobility models in related research areas such as wireless ad hoc network and cellular networks. Further on, we propose a dedicated and more realistic mobility model named BAMM (Body Area Mobility Model) for wireless body sensor networks by concentrating on the unique characteristics of WBSN and finally study the effects of mobility on the performance of WBSN by simulation experiments.

The miniaturization of biomedical sensor nodes has paved the way for remote patient monitoring using wearable wireless sensor nodes. The network of such invasive and non-invasive sensor nodes is most commonly known as Wireless Body Sensor Network (WBSN). The healthcare applications of WBSN are delay sensitive and of critical nature, therefore, it require reliable and timely dissemination of patients’ critical data to the remote location to ensure Quality of Service (QoS). However, poor link quality (LQ) may affect QoS and result in higher transmission delay, loss of critical data packets data corruption, packet retransmissions, thereby, degrading network performance and compromising the patient’s privacy and confidentiality. Furthermore, the in-vivo wireless sensor node produces electromagnetic radiations which are absorbed by the human body thereby, causing temperature rise around the implanted sensor node. The prolonged communication of such in-vivo nodes creates a hotspot node that results in sensitive tissue damage. Therefore, ensuring hotspot-free communication is a necessity in WBSN. Considering such issues, we propose a Reliable, Link Quality and Temperature aware routing protocol (RLTD) for delay-sensitive application of WBSNs that route data through reliable nodes and good quality links to the destination node. The efficacy of the proposed (RLTD) routing protocol is confirmed by comparing results with the well-known thermal-aware protocols for WBSN.

<p>A wireless network composed of wearable sensing along with computing systems connected via a wireless communication channel is termed Wireless Body Sensor Network (WBSN). It enables continuous monitoring through sensors for medical and nonmedical applications. WBSN faces several security problems such as loss of information, access control, and authentication. As WBSN collects vital information and operates in an unfriendly environment, severe security mechanisms are needed in order to prevent the network from anonymous interactions. The different security threats are evaluated with the support of the data transmitted via the sensor networks amongst smart wearable devices. The whole network lifetime together with the Data Transmission (DT) quality is mitigated whilst performing DT utilizing sensor networks, which consume more energy. Hence, in this paper, an energy-efficient secure data transmission mechanism is proposed in WBSN using a novel authentication id-based group signature model and SECC technique. At first, the Group Manager (GM) is selected from the sensors in the remote body sensor system using Normalized Opposition Based Learning BAT Optimization Algorithm (NOBL-BOA). Afterward, clustering with Information Entropy induced K-Means Algorithm (IEKMA) takes place to improve energy efficiency. Next, to provide security to the WBSN, message authentication is carried out based on novel authentication ID-based group signature protocol. Finally, Secret key induced Elliptic Curve Cryptography (SECC) is used to encrypt the message for secure transmission. The simulation results reveal that in comparison with existing works, the proposed work achieves improved security and energy efficiency.</p> <p> </p>

Securing an individual’s privacy in a proficient manner is an important task for critical infrastructures like Wireless Body Sensor Networks (WBSN). WBSNs provide real-time monitoring of patients. By protecting the WBSN, lives of patients or soldiers on battleground is secured. This paper gives a comparative study of electrocardiogram (ECG)-based key agreement schemes in WBSNs. The usage of ECG aims to bring plug-and-play capability in WBSNs, i.e., the deployment of sensors on the human body will enable wireless and secure communication for exchanging information. The schemes use Fast Fourier Transform (FFT) and Discrete Wavelet Transform (DWT) for feature extraction. The process is made secure by adding watermark. The watermarking technique does the locking and unlocking technique at the sender and receiver’s side improving the security while not affecting the plug-and-play paradigm. The simulation and analysis is done by using ECG signal taken from MIT PhysioBank database.

An energy-saving routing architecture with a uniform clustering algorithm for wireless body sensor networks

Wireless body sensor network (WBSN) allows remote monitoring for different types of applications in security, healthcare and medical domains. Medical applications involve monitoring a large number of patients in real-time environments. The WBSNs in such environments have to be efficient and reliable in terms of data transfer rate, accuracy, latency, and power consumption. This work focuses on studying the slotted access protocol variables in the Contention Access Period (CAP) with the acknowledged uplink traffic (nodes-to-coordinator) under the WBSN channel. This paper proposes a Markov Chain model in WBSN (MC-WBSN) for improving the efficiency and reliability of patients’ remote monitoring systems. The application of the model includes propagating human arm sensory data and analyzing the latency, power consumption, throughput, and higher path loss channel of the WBSN. The results show that the hidden nodes have a great impact on WBSNs performance and throughput. This issue is highly associated with the capacity of the transmitted power.

This study concerns security issues of the emerging Wireless Body Sensor Network (WBSN) formed by biomedical sensors worn on or implanted in the human body for mobile healthcare applications. A novel authenticated symmetric-key establishment scheme is proposed for WBSN, which fully exploits the physiological features obtained by network entities via the body channel available in WBSN but not other wireless networks. The self-defined Intrinsic Shared Secret (ISS) is used to replace the pre-deployment of secrets among network entities, which thus eliminates centralized services or authorities essential in existing protocols, and resolves the key transport problem in the pure symmetric-key cryptosystem for WBSN as well. The security properties of the proposed scheme are demonstrated in terms of its attack complexity and the types of attacks it can resist. Besides, the scheme can be implemented under a light-weight way in WBSN systems. Due to the importance of the ISS concept, the analysis on using false acceptance/false rejection method to evaluate the performance of ISS for its usage in the scheme is also demonstrated.

Wireless body sensor networks (WBSNs) that offer various medical applications have received considerable attention in recent years. Due to limited energy of sensors, duty-cycling technique is employed to prolong the network lifetime. However, it results in long delivery delay and suffers from reliability issues. In this chapter, we introduce an energy-efficient and reliable sleep scheduling scheme from the perspective of constructing m-fold dominating set (DS), where m is the number of links from a node outside DS to those in DS. The key idea is to activate partial nodes at each frame to form a DS which can guarantee the network reliability such that the other nodes can fall asleep to save energy. Technically, we formulate the sleep scheduling in a WBSN as a problem of constructing minimum weighted m-fold dominating set (MWmDS) which is proven NP-hard. We first design an H(m + δ)-approximation algorithm, namely GAA, by globally picking the optimal node based on a polymatroid function, where H(⋅) is the harmonic number and δ is the maximum node degree. Then, we propose a simplified \(1+\ln (m\delta )\)-approximation algorithm, referred to as LAA, to reduce computational complexity and execution rounds. We further conduct extensive simulations to confirm the superiority of our proposed algorithms.

BackgroundHuman life can be further improved if diseases and disorders can be predicted before they become dangerous, by correctly recognizing signals from the human body, so in order to make disease detection more precise, various body-signals need to be measured simultaneously in a synchronized manner.ObjectThis research aims at developing an integrated system for measuring four signals (EEG, ECG, respiration, and PPG) and simultaneously producing synchronous signals on a Wireless Body Sensor Network.DesignWe designed and implemented a platform for multiple bio-signals using Bluetooth communication.ResultsFirst, we developed a prototype board and verified the signals from the sensor platform using frequency responses and quantities. Next, we designed and implemented a lightweight, ultra-compact, low cost, low power-consumption Printed Circuit Board.ConclusionA synchronous multi-body sensor platform is expected to be very useful in telemedicine and emergency rescue scenarios. Furthermore, this system is expected to be able to analyze the mutual effects among body signals.

The Wireless Sensors Network (WSN) is an emergent technology resulting from progress of various fields. Many applications of networks WSN are born. One of the applications which have an operational effectiveness relates to the field of health and allows a medical remote support. Miniature wireless sensors, strategically placed on the human body, create a Wireless Body Sensor Network (WBSN) which allows supervising various essential biological signals (rate of heartbeat, pressure, etc). The sensitivity of medical information requires mechanisms of safety. This performance constitutes a challenge for WBSN because of their limitation in resources energy and data-processing. In this paper we propose a new approach to symmetric cryptographic key establishment, based on biometrics physiology. This approach takes into account WBSN constraints and its topology.

The network coding capacity of a single multicast traffic is characterized by the min-cut/max-flow (mcMF) theorem, which can be achieved by random linear network coding (RLNC). Nonetheless, the graph-theoretic characterization for multiple unicast/multicast traffic remains an open problem. This paper proposes and studies a new class of intersession-network-coding schemes: RLNC with selective cancelling (SC), which inherits the complexity advantage of RLNC once the set of selective cancelling edges is decided. A graph-theoretic characterization is provided for the achievable rates of RLNC with SC for the general multiple multicast setting. The findings contain most existing achievability results as special cases, including the mcMF theorem of the single multicast traffic and the existing characterization of pairwise intersession network coding. One prominent feature of the proposed approach is its focus on the achievability analysis with arbitrary network topology, arbitrary inter-session packet-mixing capability, and arbitrary traffic demands, which distinguishes the results from the special case analysis, capacity outer bound constructions, and the pattern-based (butterfly-based) superposition arguments.

In order to improve the throughput and transmission reliability in wireless sensor network with limited resources, multicast network coding technology is imported in. On this basis, through random linear network coding by nodes' cooperation to make improvement in delayed and expense. The simulation results show that the transmission, to the opportunity routing, by cooperation network coding strategies is improved in making full use of space-time reusability, reducing the delay and enhancing the throughput and transmission reliability of wireless sensor network.

Passive network tomography uses end-to-end observations of network communication to characterize the network, for instance to estimate the network topology and to localize random or adversarial glitches. Under the setting of linear network coding this work provides a comprehensive study of passive network tomography in the presence of network (random or adversarial) glitches. To be concrete, this work is developed along two directions: 1. Tomographic upper and lower bounds (i.e., the most adverse conditions in each problem setting under which network tomography is possible, and corresponding schemes (computationally efficient, if possible) that achieve this performance) are presented for random linear network coding (RLNC). We consider RLNC designed with common randomness, i.e., the receiver knows the random code-books all nodes. (To justify this, we show an upper bound for the problem of topology estimation in networks using RLNC without common randomness.) In this setting we present the first set of algorithms that characterize the network topology exactly. Our algorithm for topology estimation with random network errors has time complexity that is polynomial in network parameters. For the problem of network error localization given the topology information, we present the first computationally tractable algorithm to localize random errors, and prove it is computationally intractable to localize adversarial errors. 2. New network coding schemes are designed that improve the tomographic performance of RLNC while maintaining the desirable low-complexity, throughput-optimal, distributed linear network coding properties of RLNC. In particular, we design network codes based on Reed-Solomon codes so that a maximal number of adversarial errors can be localized in a computationally efficient manner even without the information of network topology.

Random linear network coding (RLNC) has the potential to improve the performance of current and future Internet of Things (IoT) communication systems, but is computationally demanding due to matrix multiplications and inversions. Some single-core RLNC implementations achieve already sufficient coding speeds for contemporary multimedia streaming formats. However, advances in multimedia streaming formats and IoT applications will require the exploitation of heterogeneous multicore architectures, which are becoming common for a wide range of IoT nodes, including smartphones. In this paper, we introduce and evaluate efficient RLNC computing strategies for IoT node architectures, including the emerging heterogeneous big.LITTLE multicore architectures with multiple big (fast) cores and multiple LITTLE (slow) cores. In contrast to existing RLNC implementation strategies, we build on and adapt highly optimized dense matrix operations from the high performance computing field to RLNC on heterogeneous multicore IoT nodes. Our approach includes the optimization of RLNC matrix operations through optimized operations on matrix blocks with single instruction multiple data instructions. We schedule block operations on the heterogeneous cores through a directed acyclic graph that avoids artificial synchronization points while ensuring the data dependencies. We examine priority scheduling according to the number of outgoing dependencies of a task and data locality of cached blocks. Our extensive measurements with several heterogeneous big.LITTLE multicore IoT node and smartphone processor boards demonstrate higher RLNC encoding and decoding throughputs than existing approaches. Moreover, our measurements indicate that the utilization of more cores decreases energy consumption, which is an important goal for IoT nodes.

Random linear network coding with ladder-shaped global coding matrix for robust video transmission