Maximize Body Node’s Lifetime Through Conditional Re-transmission

Problem statement: The Wireless Body Area Sensor Networks (WBASNs) is a wireless network used for communication among sensor nodes operating on or inside the human body in order to monitor vital body parameters and movements. This study surveys the state-of-the-art on Wireless Body Area Networks, discussing the major components of research in this area including physiological sensing and preprocessing, WBASNs communication techniques and data fusion for gathering data from sensors. In addition, data analysis and feedback will be presented including feature extraction, detection and classification of human related phenomena. Approach: Comparative studies of the technologies and techniques used in such systems will be provided in this study, using qualitative comparisons and use case analysis to give insight on potential uses for different techniques. Results and Conclusion: Wireless Sensor Networks (WSNs) technologies are considered as one of the key of the research areas in computer science and healthcare application industries. Sensor supply chain and communication technologies used within the system and power consumption therein, depend largely on the use case and the characteristics of the application. Authors conclude that Life-saving applications and thorough studies and tests should be conducted before WBANs can be widely applied to humans, particularly to address the challenges related to robust techniques for detection and classification to increase the accuracy and hence the confidence of applying such techniques without physician intervention.

One of the most promising fields is Wireless Body Area Sensor network (WBASN) which consists of a large number of wearable or implantable sensor nodes for collecting physiological data from the patients. The healthcare data is most sensitive digital data which contains high, delicate private data, and it needs to be shared among the peoples such as health specialists, pharmacist, family members, insurance companies, hospitals, etc. Due to the openness of wireless network, WBASN is vulnerable to a different variety of attacks; it needs high-security mechanisms to secure the data. The breach of healthcare information is one of the most crucial concern nowadays. In this paper, we mainly emphasise the general outlook of wireless body area sensor networks, which includes the architecture of healthcare system, various research domain, need of security and privacy of WBASNs. Further, the pro and cons of different security mechanism for WBASNs are discussed.

In today’s world, the increasing cost of healthcare and tremendous growth of elderly population introduced a major issue for medical monitoring and healthcare applications. A tiny sensor attached outside/inside the human body in Wireless Body Area Sensor Network (WBASN) monitors the surrounding environment and function of human body. Meanwhile, the heat dissipated from antenna and sensor node’s circuitry and antenna deteriorates human tissue. Thus it is very important to design a routing protocol in WBASN by incorporating the effect of temperature into routing metrics. A WBASN consists of heterogeneous nodes; therefore, the routing protocols must be designed to balance traffic among these sensor nodes. Vital signals of human body require different quality of service for different data types. Thus designing QoS aware routing protocols is a challenging task. In this paper, conventional temperature and QoS aware routing protocols are compared and open issues in routing protocol design are discussed.

In this survey, we review the current research on Wireless Body Area Sensor Networks (WBASNs). This technology is playing key role in different aspects of life such as entertainment, emergency services, sports and medical health care applications. We identify the issues of WBASNs for medical and health care services. Different techniques and several algorithms are designed to handle the problems of energy consumption, delay and route selection in WBASNs. This study also discusses how different algorithms use different techniques to minimize energy consumption, delay, path selection cost and computational complexity. A detailed hierarchy of existing algorithms is included in this work to better understand the emerging issues in WBASN. MATLAB simulations for different algorithms are performed to analyze the path loss and energy consumption of disconnected nodes. We also check the connectivity between employ nodes and out body server on LOS and NLOS due to frequent human body movements. We see some connections break due to absorption of cloths and human body, and also take time to setup a connection, which causes delay and energy utilization. From this study we found that the algorithms designed to tackle the problem of emergency should be priority-base, thermal-aware and easily manage its energy range for sending data when disconnection occurs due to partitioning.

In this paper, a random access protocol for quality of service (QoS) support targeted for medical wireless body area sensor networks (WBASNs) is proposed. In this proposal, the sensor nodes are classified into nodes of life-critical health information, and nodes of non-critical health information. The proposed QoS-based MAC protocol prioritizes the critical packets access to the transmission medium by cutting of the number of retransmissions of the collided non critical packets. Therefore, the critical traffic throughput is increased and its rejection rate is decreased while maintaining the non critical traffic QoS parameters above a minimum provisioned level. The proposed protocol is evaluated analytically and through simulation. The obtained results demonstrate a dramatic increase in the critical traffic throughput.

Wireless body area sensor networks will revolutionize health care services by remote, continuous and non-invasive monitoring. Body area sensor networks (BASN) should monitor various physiological parameters of a person for a long period of time. Thus, efficient energy usage in sensor nodes is essential in order to provide a long life time for the network. This paper investigates the effect of adding a relay network to the network of body sensors to reduce energy consumption of sensor nodes when transmitting data to the sink.

Recent advances in Wireless Body Area Sensor Network (WBASN) technology has become a leading approach for several promising applications in the medical field. WBASN is the network is built with different kinds of physiological sensors which measures different vital parameters on the human body for the purpose of monitoring the patients. Prediction and modeling are very two important issues which are required to address while building a WBASN. To enhance the long-term critical health monitoring, a robust predictive approach should be incorporated in every WBASN system and it leads to saving computation time and increasing the energy.In this paper, we describe the use of polynomial regression for predicting and modeling biological functions. We also describe how effective different orders of polynomials can be. There are four functions that we use for this purpose: blood pressure, scalp EEG signals, the walking gait of people with neurodegenerative disorders, and lastly motor movement signals. We have also used two different degrees of polynomial functions to determine the predictive value.

Remote monitoring of the vital signs of a patient at home is becoming increasingly important. Wireless body area sensor networks (BAN) provide a convenient platform for health monitoring. A typical biomonitoring application running on wireless BAN has stringent timing and energy requirements. In this context, a cycle accurate simulator of biomonitoring application running on wireless BAN network is a critical tool for the developer. In this paper, we present a SystemC-based fast simulator that can provide accurate timing and energy estimated for health monitoring applications on wireless BAN, which is then used to strategize the optimizations towards critical functions and/or components. Our case study with MEMSWear-Biomonitoring application shows the accuracy and utility of our simulator.

The energy efficient Data Timed Sending (DTS) protocol enables information transfer from sensor nodes to sink host by choosing the appropriate transmission time of a short packet without data payload. Wake-up Radio (WuR) devices allow asynchronous communication of Wireless Sensor Networks (WSNs) putting the sensor nodes’ main radio modules in continuous sleep state thus increasing energy efficiency. A common characteristic for the DTS protocol and WuR is that they are designed for applications where sensors take sparse measurements, typically one measurement every few minutes. This paper investigates the combination of the DTS protocol with WuR into a single integrated solution. The analytical analysis shows that the DTS protocol significantly reduces the energy consumption when coupled with WuR making this solution suitable for applications with battery powered WSN (e.g. body area WSN).

Advances in wearable devices and pervasive computing provide unprecedented opportunity for ubiquitous realtime e-Healthcare and patient monitoring by placing wirelessly connected sensors in, on, and around the body of patients. Due to the privacy-sensitive and mission-critical nature of these wireless body area sensor networks (WBASNs), as well as the desire to use them for long-time uninterrupted monitoring of patients' vital physiological signals, the privacy/security and energy efficiency of WBASNs are of primary concerns. In this paper, we propose a novel In-network AES Equivalent (IAE) mechanism to protect the security/privacy and maintain good energy efficiency for WBASNs at the same time. IAE achieves this goal by outsourcing part of the energy-consuming cryptographic operation to other deliberately-selected peer sensor nodes so as to balance the energy consumption of the entire network. An analytical model is proposed to characterize the computation and communication energy consumption of IAE, based on which we optimize the outsourcing under given security constraints. Through extensive simulations, we verify the effectiveness and efficiency of the proposed mechanism in prolonging the network lifetime under given security requirements.

Wireless Body area Sensor Network (WBSN) is a recent concept that can dramatically benefit healthcare applications through advances in wireless technology. Physiological and biokinetic parameters that require continuous monitoring are sensed by small and lightweight body sensors that transmit the values of these parameters over wireless links for monitoring at the other end. The sensors employed in WBSNs are limited in resources, with battery power being at the premium. Conservation of energy used by the network has a direct bearing on the longevity of the network. Therefore, there is no need to send data periodically and need to transmit selectively when needed. This paper presents a dual framework for predicting when to transfer physiological parameters in such a network that could save energy consumption while maintaining error to minimum level. The framework utilizes an artificial neural network (ANN) for prediction that not only saves energy, but also does it with lesser error than popular prediction algorithms. A comparison of performance of five data prediction algorithms in predicting physiological data is presented. The amount of network energy saved as a result of prediction is also considered in detail.

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.

In recent years, wireless body area sensor network (WBASN) has gained a lot of attention from researchers for its potential application in medical care and health care fields. However, previous studies are typically involved in performance of WBASN, and most research has barely considered the details of system design. This paper presents a health care monitoring system. The design of the system is detailedly described. The evaluation result shows that the system can be easily deployed and suitable for health care monitoring.

One of the major issues in Wireless Body Area Sensor Networks (WBASNs) is efficient localization. There are various techniques for indoor and outdoor environments to locate a person. This study evaluating and compares performance of optimization schemes in indoor environments for optimal placement of wireless sensors, where patients can perform their daily activities. In indoor environments, the performance comparison between Distance Vector-Hop algorithm, Ring Overlapping Based on Comparison Received Signal Strength Indicator (ROCRSSI), Particle filtering and Kalman filtering based location tracking techniques, in terms of localization accuracy is estimated. Results show that particle filtering outperforms all. GPS and several techniques based on GSM location tracking schemes are proposed for outdoor environments. Hidden Markov GSM based location tracking scheme efficiently performs among all, in terms of location accuracy and computational overheads.

In this paper, we study the problem of traffic analysis attacks in wireless body area sensor networks. When these networks are used in health-care for remote patient monitoring, traffic analysis can reveal the type of medical sensors mounted on the patient, and this information may be used to infer the patient's health problems. We show that simple signal processing methods can be used effectively for performing traffic analysis attacks and identifying the sensor types in a rather weak adversary model. We then investigate possible traffic obfuscation mechanisms aiming at hiding the regular patterns in the observable wireless traffic. Among the investigated countermeasures, traffic shaping, a mechanism that introduces carefully chosen delays for message transmissions, appears to be the best choice, as it achieves close to optimal protection and incurs no overhead.