43 research outputs found

    A CSMA/CA Based MAC Layer Solution for Inter-WBAN Interference and Starvation

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    With the advancement in wireless communication technologies, E-healthcare system has been proposed to deal with the issues such as inefficiency, high cost, and degradations in service quality in traditional health-care systems. Wireless Body Area Network (WBAN) is widely used in E-healthcare system as it provides continuous monitoring on physiological parameters. However, when two or more WBANs overlap with each other, there exists inter-WBAN interference. The inter-WBAN interference may cause transmission failures, which result in packet losses, throughput degradations, and energy wastes for energy limited sensors. This motivates us to develop a distributed CSMA/CA-based MAC protocol for inter-WBAN interference management. There are three challenges, namely, power optimization, protocol response time, and starvation in designing such a protocol. In this thesis, the power optimization challenge is overcome by an innovative WBAN system. To deal with the challenges in protocol response time and starvation, the proposed MAC protocol extends the CSMA/CA protocol with an adaptive transmission probability that uses frozen time as the adjustment criterion and a back-off counter adjustment mechanism that prioritizes the starving nodes. The proposed protocol achieves throughput improvement, starvation mitigation, and energy efficiency for sensors. Simulation results demonstrate the effectiveness of the proposed MAC protocol for health-care applications in scenarios such as having dinner at a round table or sitting in a hospital waiting room

    Interference in wireless networks : a game theory approach

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    A Survey on Modality Characteristics, Performance Evaluation Metrics, and Security for Traditional and Wearable Biometric Systems

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    Biometric research is directed increasingly towards Wearable Biometric Systems (WBS) for user authentication and identification. However, prior to engaging in WBS research, how their operational dynamics and design considerations differ from those of Traditional Biometric Systems (TBS) must be understood. While the current literature is cognizant of those differences, there is no effective work that summarizes the factors where TBS and WBS differ, namely, their modality characteristics, performance, security and privacy. To bridge the gap, this paper accordingly reviews and compares the key characteristics of modalities, contrasts the metrics used to evaluate system performance, and highlights the divergence in critical vulnerabilities, attacks and defenses for TBS and WBS. It further discusses how these factors affect the design considerations for WBS, the open challenges and future directions of research in these areas. In doing so, the paper provides a big-picture overview of the important avenues of challenges and potential solutions that researchers entering the field should be aware of. Hence, this survey aims to be a starting point for researchers in comprehending the fundamental differences between TBS and WBS before understanding the core challenges associated with WBS and its design

    The Internet of Humans: Optimal Resource Allocation and Wireless Channel Prediction

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    Recent advances in information and communications technologies (ICT) have accelerated the realization of the Internet of Humans (IoH). Among the many IoH applications, Wireless Body Area Networks (BANs) are a remarkable solution that are revolutionising the health care industry. However, many challenges must be addressed, including: a) unavoidable inter-BAN interference severely degrading system performance. b) The non-stationarity and atypical dynamics of BAN channels make it extremely challenging to apply predictive transmit power control that improves the energy efficiency of the network. In this context, this thesis investigates the use of intelligent and adaptive resource allocation algorithms and effective channel prediction to achieve reliable, energy-efficient communications in BAN-enabled IoH. Firstly, we investigate the problem of co-channel interference amongst coexisting BANs by proposing a socially optimal finite repeated non-cooperative transmit power control game. The proposed method improves throughput, reduces overall power consumption and suppress interference. The game is shown to have a unique Nash equilibrium. We also prove that the aggregate outcome of the game is socially efficient across all players at the unique Nash equilibrium, given reasonable constraints for both static and slowly time-varying channels. Secondly, we address the problem of overlapping transmissions among non-coordinated BANs with multiple access schemes through intelligent link resource allocation methods. We present two non-cooperative games, employed with a time-division multiple access (TDMA) based MAC layer scheme that has a novel back-off mechanism. The Link Adaptation game jointly adjusts the sensor node's transmit power and data rate, which provides robust transmission under strong inter-BAN interference. Moreover, by adaptively tuning contention windows size an alternative game, namely a Contention Window game is developed, which significantly reduces latency. The uniqueness and existence of the games' Nash Equilibrium (NE) over the action space are proved using discrete concavity. The NE solution is further analysed and shown to be socially efficient. Motivated by the emergence of deep learning technology, we address the challenge of long-term channel predictions in BANs by using neural networks. Specifically, we propose Long Short-term Memory (LSTM)-based neural network (NN) prediction methods that provide long-term accurate channel gain prediction of up to 2s over non-stationary BAN on-body channels. An incremental learning scheme, which provides continuous and robust predictions, is also developed. We also propose a lightweight NN predictor, namely 'LiteLSTM', that has a compact structure and higher computational efficiency. When implemented on hand-held devices, 'LiteLSTM' remains functional with comparable performance. Finally, we explore the theoretical connections between BAN on-body channels' characteristics and the performance of NN-based power control. To analyse wide-sense stationarity (WSS) characteristics, different stationarity tests are performed for a range of window lengths for on-body channels. Following from this, we develop test benches for NN-based methods at corresponding window lengths using empirical channel measurements. It is observed that WSS characteristics of the BAN on-body channels have a significant impact on the performance of NN-based methods

    Resource Management in E-health Systems

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    E-health systems are the information and communication systems deployed to improve quality and efficiency of public health services. Within E-health systems, wearable sensors are deployed to monitor physiology information not only in hospitals, but also in our daily lives under all types of activities; wireless body area networks (WBANs) are adopted to transmit physiology information to smartphones; and cloud servers are utilized for timely diagnose and disease treatment. The integrated services provided by E-health systems could be more convenient, reliable, patient centric and bring more economic healthcare services. Despite of many benefits, e-health systems face challenges among which resource management is the most important one as wearable sensors are energy and computing capability limited, and medical information has stringent quality of service (QoS) requirements in terms of delay and reliability. This thesis presents resource management mechanisms, including transmission power allocation schemes for wearable sensors, Medium Access Control (MAC) for WBANs, and resource sharing schemes among cloud networks, that can efficiently exploit the limited resources to achieve satisfactory QoS. First, we address how wearable sensors could energy efficiently transmit medical information with stringent QoS requirements to a smart phone. We first investigate how to provide worst-case delay provisioning for vital physiology information. Sleep scheduling and opportunistic channel access are exploited to reduce energy consumption in idle listening and increase energy efficiency. Considering dynamic programming suffers from curse of dimensionality, Lyapunov optimization formulation is established to derive a low complexity two-step transmission power allocation algorithm. We analyze the conditions under which the proposed algorithm could guarantee worst-case delay. We then investigate the impacts of peak power constraint and statistical QoS provisioning. An optimal transmission power allocation scheme under a peak power constraint is derived, and followed by an efficient calculation method. Applying duality gap analysis, we characterize the upper bound of the extra average transmission power incurred due a peak power constraint. We demonstrate that when the peak power constraint is stringent, the proposed constant power scheme is suitable for wearable sensors for its performance is close to optimal. Further, we show that the peak power constraint is the bottleneck for wearable sensors to provide stringent statistical QoS provisioning. Second, WBANs can provide low-cost and timely healthcare services and are expected to be widely adopted in hospitals. We develop a centralized MAC layer resource management scheme for WBANs, with a focus on inter-WBAN interference mitigation and sensor power consumption reduction. Based on the channel state and buffer state information reported by smart phones deployed in each WBAN, channel access allocation is performed by a central controller to maximize the network throughput. Note that sensors have insufficient energy and computing capability to timely provide all the necessary information for channel resource management, which deteriorates the network performance. We exploit the temporal correlation of body area channel such that channel state reports from sensors are minimized. We then formulate the MAC design problem as a partially observable optimization problem and develop a myopic policy accordingly. Third, cloud computing is expected to meet the rising computing demands. Both private clouds, which aim at patients in their regions, and public clouds, which serve general public, are adopted. Reliability control and QoS provisioning are the core issues of private clouds and public clouds, respectively. A framework, which exploits the abundant resource of private clouds in time domain, to enable cooperation among private clouds and public clouds, is proposed. Considering the cost of service failure in e-health system, the first time failure probability is adopted as reliability measures for private clouds. An algorithm is proposed to minimize the failure probability, and is proven to be optimal. Then, we propose an e-health monitoring system with minimum service delay and privacy preservation by exploiting geo-distributed clouds. In the system, the resource management scheme enables the distributed cloud servers to cooperatively assign the servers to the requested users under a load balance condition. Thus, the service delay for users is minimized. In addition, a traffic shaping algorithm is proposed, which converts the user health data traffic to the non-health data traffic such that the capability of traffic analysis attacks is largely reduced. In summary, we believe the research results developed in this dissertation can provide insights for efficient transmission power allocation for wearable sensor, can offer practical MAC layer solutions for WBANs in hospital environment, and can improve the QoS provisioning provided by cloud networks in e-health systems

    D13.1 Fundamental issues on energy- and bandwidth-efficient communications and networking

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    Deliverable D13.1 del projecte europeu NEWCOM#The report presents the current status in the research area of energy- and bandwidth-efficient communications and networking and highlights the fundamental issues still open for further investigation. Furthermore, the report presents the Joint Research Activities (JRAs) which will be performed within WP1.3. For each activity there is the description, the identification of the adherence with the identified fundamental open issues, a presentation of the initial results, and a roadmap for the planned joint research work in each topic.Preprin
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