Mobile Wireless Body Area Networks Research Articles

Prediction-based channel assignment for minimizing channel switching in mobile WBANs

As the world’s population rises, the healthcare system experiences significant changes. Wireless body area network (WBAN) is an emerging technology that has considerable impact on medical and non-medical applications. However, two crucial challenges in WBANs are interference minimization and channel assignment. High interference may increase collision probability, transmission delay, and energy consumption. Multichannel schemes are proposed to reduce the data transmission latency and improve the system throughput by allowing simultaneous transmission of sensors in coexisting WBANs. When WBAN users move, they need to switch the channels frequently to avoid potential channel conflicts and to maintain the Quality of Service (QoS). However, frequent switching may raise energy consumption and aggravate delay. Existing multichannel assignment schemes failed to perform well in highly dynamic and densely deployed WBANs environments. In contrast to existing studies, this paper proposes a Prediction-based Channel Assignment (PCA) algorithm that selects the channels for WBANs to remain valid for future time instances and thus minimizes the delay and number of channel switches for dynamic and coexisting WBANs. When a WBAN needs to switch a channel, the proposed method predicts the future neighbors of that WBAN based on its history. It explores the channel information of present and future neighbors to select a suitable channel with higher resilience in a dynamic environment. Thus, our algorithm minimizes channel interference by avoiding unnecessary channel switching. We have used machine learning algorithms to predict the future neighbors of a WBAN. Experiment results show that the proposed algorithm performs better than an existing algorithm and random channel assignment in delay and throughput.

A game theory‐based approach for the study of inter‐interference in coexisting wireless body area networks

SummaryA wireless body area network (WBAN) enables the continuous monitoring of health conditions including heart rate, temperature, and glucose levels. It is composed of several sensors that are placed on the body. The network's performance is significantly affected by the unpredictable movements of the human body. Due to the varying proximities between them, the existence of several WBANs creates a challenge when mobility is involved. In this fictitious scenario, we consider a park area with both mobile and static WBANs or WBAN‐equipped individuals passing through the park who have varying degrees of mobility. When a mobile WBAN passes a static WBAN and is within a minimum distance of the static WBAN, they pair up and immediately interfere. Inter‐interference caused by WBANs operating in a limited area causes packet loss and performance deterioration. In this work, static WBAN locations are optimised to minimise interference and system inter‐interference problems are addressed by a game theoretic method. This paper formulates a flexible game theoretic framework to study WBAN coexistence using the expected pay‐off function considering a two‐player game. It is observed from the results obtained that the probability of interference caused by fast mobile WBANs is reduced to a maximum of 50% compared with that caused by slow mobile WBANs thereby reducing the need for relocation of static WBANs.

Spectrum Allocation Scheme for Intelligent Partition Based on Machine Learning for Inter-WBAN Interference

A wireless body area network (WBAN) is a physical network system with functions such as information collection and data transmission, and provides a key means for real-time health detection and medical services. However, if WBANs deployed in a dense environment lack internetwork coordination, it can cause high interference. In addition, WBANs have the characteristics of social mobility, and regular frequency changes will increase energy consumption. In this article, the co-frequency interference between coexisting WBANs in dense environments is analyzed, and the real-time frequency of mobile WBANs is studied emphatically to alleviate these problems. A spectrum allocation scheme for intelligent partition based on machine learning is proposed as a mixed scheduling scheme that combines graph coloring and partitioning ideas. WBANs' self-organized dynamic clustering forms multiple cells according to location, and the cells use a vertex coloring algorithm of self-generating topological graphs to coordinate their frequency bands and assign different colors to coexisting cells. When a new user joins the area, it will self-organize and cluster to a divided cell, and the cell will divide frequency bands for the new user. No other bands need to be changed, and the experiments conducted in this research demonstrate that the proposed arithmetic can adapt well to the fast-changing WBANs of the topology, and the system anti-interference performance, frequency resource utilization, and system stability are favorable.

A novel nest-based scheduling method for mobile wireless body area networks

Wireless Body Area Networks (WBANs) comprise various sensors to monitor and collect various vital signals, such as blood pressure, pulse, heartbeat, body temperature, and blood sugar. A dense and mobile WBAN often suffers from interference, which causes serious problems, such as wasting energy and degrading throughput. In reality, not all of the sensors in WBAN need to be active at the same time. Therefore, they can be divided into different groups so that each group works in turn to avoid interference. In this paper, a Nest-Based WBAN Scheduling (NBWS) algorithm is proposed to cluster sensors of the same types in a single or multiple WBANs into different groups to avoid interference. Particularly, we borrow the graph coloring theory to schedule all groups to work using a Time Division for Multimodal Sensor (TDMS) group scheduling model. Both theoretical analysis and experimental results demonstrate that the proposed NBWS algorithm performs better in terms of frequency of collisions, transmission delay, system throughput, and energy consumption compared to the counterpart methods.

Performance Analysis of IEEE 802.15.6-Based Coexisting Mobile WBANs With Prioritized Traffic and Dynamic Interference

Intelligent wireless body area networks (WBANs) have entered into an incredible explosive popularization stage. WBAN technologies facilitate real-time and reliable health monitoring in e-healthcare and creative applications in other fields. However, due to the limited space and medical resources, deeply deployed WBANs are suffering severe interference problems. The interference affects the reliability and timeliness of data transmissions, and the impacts of interference become more serious in mobile WBANs because of the uncertainty of human movement. In this paper, we analyze the dynamic interference taking human mobility into consideration. The dynamic interference is investigated in different situations for WBANs coexistence. To guarantee the performance of different traffic types, a health critical index is proposed to ensure the transmission privilege of emergency data for intra- and inter-WBANs. Furthermore, the performance of the target WBAN, i.e., normalized throughput and average access delay, under different interference intensity are evaluated using a developed three-dimensional Markov chain model. Extensive numerical results show that the interference generated by mobile neighbor WBANs results in 70% throughput decrease for general medical data and doubles the packet delay experienced by the target WBAN for emergency data compared with single WBAN. The evaluation results greatly benefit the network design and management as well as the interference mitigation protocols design.

Link Scheduling Algorithm with Interference Prediction for Multiple Mobile WBANs

As wireless body area networks (WBANs) become a key element in electronic healthcare (e-healthcare) systems, the coexistence of multiple mobile WBANs is becoming an issue. The network performance is negatively affected by the unpredictable movement of the human body. In such an environment, inter-WBAN interference can be caused by the overlapping transmission range of nearby WBANs. We propose a link scheduling algorithm with interference prediction (LSIP) for multiple mobile WBANs, which allows multiple mobile WBANs to transmit at the same time without causing inter-WBAN interference. In the LSIP, a superframe includes the contention access phase using carrier sense multiple access with collision avoidance (CSMA/CA) and the scheduled phase using time division multiple access (TDMA) for non-interfering nodes and interfering nodes, respectively. For interference prediction, we define a parameter called interference duration as the duration during which disparate WBANs interfere with each other. The Bayesian model is used to estimate and classify the interference using a signal to interference plus noise ratio (SINR) and the number of neighboring WBANs. The simulation results show that the proposed LSIP algorithm improves the packet delivery ratio and throughput significantly with acceptable delay.

A two-stage game theoretical approach for interference mitigation in Body-to-Body Networks

In this paper, we identify and exploit opportunities for cooperation between a group of mobile Wireless Body Area Networks (WBANs), forming a Body-to-Body Network (BBN), through inter-body interference detection and subsequent mitigation. Thus, we consider a dynamic system composed of several BBNs and we analyze the joint mutual and cross-technology interference problem due to the utilization of a limited number of channels by different transmission technologies (i.e., ZigBee and WiFi) sharing the same radio spectrum. To this end, we propose a game theoretical approach to address the problem of Socially-aware Interference Mitigation (SIM) in BBNs, where WBANs are “social” and interact with each other. Our approach considers a two-stage channel allocation scheme: a BBN-stage for inter-WBANs’ communications and a WBAN-stage for intra-WBAN communications. We demonstrate that the proposed BBN-stage and WBAN-stage games admit exact potential functions, and we develop a Best-Response (BR-SIM) algorithm that converges to Nash Equilibrium points. A second algorithm, named Sub-Optimal Randomized Trials (SORT-SIM), is then proposed and compared to BR-SIM in terms of efficiency and computation time. series We further compare the BR-SIM and SORT-SIM algorithms to two power control algorithms in terms of signal-to-interference ratio and aggregate interference, and show that they outperform the power control schemes in several cases. Numerical results, obtained in several realistic mobile scenarios, show that the proposed schemes are indeed efficient in optimizing the channel allocation in medium-to-large-scale BBNs.

A mobile wireless body area network platform

This paper aims to propose a system architecture for a mobile health-monitoring platform based on a wireless body area network (WBAN). We detail the WBAN features from either hardware and software point of view. The system architecture of this platform is three-tier system. Each tier is detailed. We have designed a flowchart of a use of the WBANs to illustrate the functioning of such platforms. We show the use of this platform in a wide area to detect and to track disease movement in the case of epidemic situation. Indeed, tracking epidemic disease is a very challenging issue. The success of such process could help medical administration to stop diseases quicker than usual. In this study, WBANs deployed over volunteers who agree to carry a light wireless sensor network. Sensors over the body will monitor some health parameters (temperature, pressure, etc) and will run some light classification algorithms to help disease diagnosis. Finally, the WBAN will send aggregated data about the disease to some base stations which collect the results. Our platform will run an on-line disease tracking program and to detect some information about how the disease is propagated.

Interference‐aware MAC scheduling and admission control for multiple mobile WBANs used in healthcare monitoring

SummaryIn this paper, we address the problem of interference when multiple time division multiple access‐based wireless body area networks (WBANs) come in the proximity of one another. We propose a simple solution that creates common non‐conflicting schedule between these interfering WBANs. Our proposed scheme allows the reuse of maximum possible time slots among WBANs that are two‐hop neighbors of one another. A flow admission control scheme is applied to control the flows during the period of interference. We show that the percentage of flows admitted because of flow control decreases with the increase in the network size and flow rate. We simulated a scenario where WBANs move randomly within a simulation area with a certain speed and meet at a particular point. We show that the signal to interference noise ratio (SINR) value of WBANs changes as long as they are within the transmission range of one another. Also, we show that the exchanges of common schedule (which is dependent on the number of times the SINR value drops below the threshold) are required in order to improve the packet delivery ratio in WBANs. Copyright © 2014 John Wiley & Sons, Ltd.

A Clique-based WBAN Scheduling for Mobile Wireless Body Area Networks

Wireless-body-area-networks (WBAN) that generally comprises different types of sensors are useful to gather multiple parameters together, such as body temperature, blood pressure, pulse, heartbeat and blood sugar. However, a dense and mobile WBAN often suffers from interference, which causes serious problems, such as degrading throughput and wasting energy. So, the sensors in WBAN are not active together at the same time and they can be partitioned to different groups and each group works in turn to avoid interference. In this paper, we provide a Clique-Based WBAN Scheduling (CBWS) algorithm to cluster sensors of a single or multiple WBAN into different groups to avoid interference. Particularly, we propose a coloring based scheduling method to schedule all groups to work in a sequence of time slots. The experimental results demonstrate the performance of the proposed CBWS algorithm in terms of system throughput.

A Distributed Scheme to Manage The Dynamic Coexistence of IEEE 802.15.4-Based Health-Monitoring WBANs

The overlap of transmission ranges between wireless networks as a result of mobility is referred to as dynamic coexistence. The interference caused by coexistence may significantly affect the performance of wireless body area networks (WBANs) where reliability is particularly critical for health monitoring applications. In this paper, we analytically study the effects of dynamic coexistence on the operation of IEEE 802.15.4-based health monitoring WBANs. The current IEEE 802.15.4 standard lacks mechanisms for effectively managing the coexistence of mobile WBANs. Considering the specific characteristics and requirements of health monitoring WBANs, we propose the dynamic coexistence management (DCM) mechanism to make IEEE 802.15.4-based WBANs able to detect and mitigate the harmful effects of coexistence. We assess the effectiveness of this scheme using extensive OPNET simulations. Our results indicate that DCM improves the successful transmission rates of dynamically coexisting WBANs by 20%-25% for typical medical monitoring applications.

Coloring-Based Inter-WBAN Scheduling for Mobile Wireless Body Area Networks

In this study, random incomplete coloring (RIC) with low time-complexity and high spatial reuse is proposed to overcome in-between wireless-body-area-networks (WBAN) interference, which can cause serious throughput degradation and energy waste. Interference-avoidance scheduling of wireless networks can be modeled as a problem of graph coloring. For instance, high spatial-reuse scheduling for a dense sensor network is mapped to high spatial-reuse coloring; fast convergence scheduling for a mobile ad hoc network (MANET) is mapped to low time-complexity coloring. However, for a dense and mobile WBAN, inter-WBAN scheduling (IWS) should simultaneously satisfy both of the following requirements: 1) high spatial-reuse and 2) fast convergence, which are tradeoffs in conventional coloring. By relaxing the coloring rule, the proposed distributed coloring algorithm RIC avoids this tradeoff and satisfies both requirements. Simulation results verify that the proposed coloring algorithm effectively overcomes inter-WBAN interference and invariably supports higher system throughput in various mobile WBAN scenarios compared to conventional colorings.

RACOON: A Multiuser QoS Design for Mobile Wireless Body Area Networks

In this study, Random Contention-based Resource Allocation (RACOON) medium access control (MAC) protocol is proposed to support the quality of service (QoS) for multi-user mobile wireless body area networks (WBANs). Different from existing QoS designs that focus on a single WBAN, a multiuser WBAN QoS should further consider both inter-WBAN interference and inter-WBAN priorities. Similar problems have been studied in both overlapped wireless local area networks (WLANs) and Bluetooth piconets that need QoS supports. However, these solutions are designed for non-medical transmissions that do not consider any priority scheme for medical applications. Most importantly, these studies focus on only static or low mobility networks. Network mobility of WBANs will introduce unnecessary inter-network collisions and energy waste, which are not considered by these solutions. The proposed multiuser-QoS protocol, RACOON, simultaneously satisfies the inter WBAN QoS requirements and overcomes the performance degradation caused by WBAN mobility. Simulation results verify that RACOON provides better latency and energy control, as compared with WBAN QoS protocols without considering the inter-WBAN requirements.