Towards reliable communication in low-power wireless body area networks

Es wird zunehmend die Ansicht vertreten, dass tragbare Computer und Sensoren neue Anwendungen in den Bereichen Gesundheitswesen, personalisierte Fitness oder erweiterte Realität ermöglichen werden. Die am Körper getragenen Geräte sind dabei mithilfe eines Wireless Body Area Network (WBAN) verbunden, d.h. es wird drahtlose Kommunikation statt eines drahtgebundenen Kanals eingesetzt. Der drahtlose Kanal ist jedoch typischerweise ein eher instabiles Kommunikationsmedium und die Einsatzbedingungen von WBANs sind besonders schwierig: Einerseits wird die Kanalqualität stark von den physischen Bewegungen der Person beeinflusst, andererseits werden WBANs häufig in lizenzfreien Funkbändern eingesetzt und sind daher Störungen von anderen drahtlosen Geräten ausgesetzt. Oft benötigen WBAN Anwendungen aber eine zuverlässige Datenübertragung. Das erste Ziel dieser Arbeit ist es, ein besseres Verständnis dafür zu schaffen, wie sich die spezifischen Einsatzbedingungen von WBANs auf die intra-WBAN Kommunikation auswirken. So wird zum Beispiel analysiert, welchen Einfluss die Platzierung der Geräte auf der Oberfläche des menschlichen Körpers und die Mobilität des Benutzers haben. Es wird nachgewiesen, dass während regelmäßiger Aktivitäten wie Laufen die empfangene Signalstärke stark schwankt, gleichzeitig aber Signalstärke-Spitzen oft einem regulären Muster folgen. Außerdem wird gezeigt, dass in urbanen Umgebungen die Effekte von 2.4 GHz Radio Frequency (RF) Interferenz im Vergleich zu den Auswirkungen von fading (Schwankungen der empfangenen Signalstärke) eher gering sind. Allerdings führt RF Interferenz dazu, dass häufiger Bündelfehler auftreten, d.h. Fehler zeitlich korrelieren. Dies kann insbesondere in Anwendungen, die eine geringe Übertragungslatenz benötigen, problematisch sein. Der zweite Teil dieser Arbeit beschäftigt sich mit der Analyse von Verfahren, die potentiell die Zuverlässigkeit der Kommunikation in WBANs erhöhen, ohne dass wesentlich mehr Energie verbraucht wird. Zunächst wird der Trade-off zwischen Übertragungslatenz und der Zuverlässigkeit der Kommunikation analysiert. Diese Analyse basiert auf einem neuen Paket-Scheduling Algorithmus, der einen Beschleunigungssensor nutzt, um die WBAN Kommunikation auf die physischen Bewegungen der Person abzustimmen. Die Analyse zeigt, dass unzuverlässige Kommunikationsverbindungen oft zuverlässig werden, wenn Pakete während vorhergesagter Signalstärke-Spitzen gesendet werden. Ferner wird analysiert, inwiefern die Robustheit gegen 2.4 GHz RF Interferenz verbessert werden kann. Dazu werden zwei Verfahren betrachtet: Ein bereits existierendes Verfahren, das periodisch einen Wechsel der Übertragungsfrequenz durchführt (channel hopping) und ein neues Verfahren, das durch RF Interferenz entstandene Bitfehler reparieren kann, indem der Inhalt mehrerer fehlerhafter Pakete kombiniert wird (packet combining). Eine Schlussfolgerung ist, dass Frequenzdiversität zwar das Auftreten von Bündelfehlern reduzieren kann, dass jedoch die statische Auswahl eines Kanals am oberen Ende des 2.4 GHz Bandes häufig schon eine akzeptable Abhilfe gegen RF Interferenz darstellt.There is a growing belief that wearable computers and sensors will enable new applications in areas such as healthcare, personal fitness or augmented reality. The devices are attached to a person and connected through a Wireless Body Area Network (WBAN), which replaces the wires of traditional monitoring systems by wireless communication. This comes, however, at the cost of turning a reliable communication channel into an unreliable one. The wireless channel is typically a rather unstable medium for communication and the conditions under which WBANs have to operate are particularly harsh: not only is the channel strongly influenced by the movements of the person, but WBANs also often operate in unlicensed frequency bands and may therefore be exposed to a significant amount of interference from other wireless devices. Yet, many envisioned WBAN applications require reliable data transmission. The goals of this thesis are twofold: first, we aim at establishing a better understanding of how the specific WBAN operating conditions, such as node placement on the human body surface and user mobility, impact intra-WBAN communication. We show that during periodic activities like walking the received signal strength on an on-body communication link fluctuates strongly, but signal strength peaks often follow a regular pattern. Furthermore, we find that in comparison to the effects of fading 2.4 GHz Radio Frequency (RF) interference causes relatively little packet loss - however, urban 2.4 GHz RF noise is bursty (correlated in time), which may be problematic for applications with low latency bounds. The second goal of this thesis is to analyze how communication reliability in WBANs can be improved without sacrificing a significant amount of additional energy. To this end, we first explore the trade-off between communication latency and communication reliability. This analysis is based on a novel packet scheduling algorithm, which makes use of an accelerometer to couple WBAN communication with the movement patterns of the user. The analysis shows that unreliable links can often be made reliable if packets are transmitted at predicted signal strength peaks. In addition, we analyze to what extent two mechanisms can improve robustness against 2.4 GHz RF interference when adopted in a WBAN context: we analyze the benefits of channel hopping, and we examine how the packet retransmission process can be made more efficient by using a novel packet combining algorithm that allows to repair packets corrupted by RF interference. One of the conclusions is that while frequency agility may decrease "burstiness" of errors the static selection of a channel at the upper end of the 2.4 GHz band often already represents a good remedy against RF interference

Resource Management in E-health Systems

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

Congestion control mechanism for sensor-cloud Infrastructure

 This thesis has developed a sensor-Cloud system that integrates WBANs with Cloud computing to enable real-time sensor data collection, storage, processing, sharing and management. As the main contribution of this study, a congestion detection and control protocol is proposed to ensure acceptable data flows are maintained during the network lifetime

A Priority-based Fair Queuing (PFQ) Model for Wireless Healthcare System

Healthcare is a very active research area, primarily due to the increase in the elderly population that leads to increasing number of emergency situations that require urgent actions. In recent years some of wireless networked medical devices were equipped with different sensors to measure and report on vital signs of patient remotely. The most important sensors are Heart Beat Rate (ECG), Pressure and Glucose sensors. However, the strict requirements and real-time nature of medical applications dictate the extreme importance and need for appropriate Quality of Service (QoS), fast and accurate delivery of a patient’s measurements in reliable e-Health ecosystem. As the elderly age and older adult population is increasing (65 years and above) due to the advancement in medicine and medical care in the last two decades; high QoS and reliable e-health ecosystem has become a major challenge in Healthcare especially for patients who require continuous monitoring and attention. Nevertheless, predictions have indicated that elderly population will be approximately 2 billion in developing countries by 2050 where availability of medical staff shall be unable to cope with this growth and emergency cases that need immediate intervention. On the other side, limitations in communication networks capacity, congestions and the humongous increase of devices, applications and IOT using the available communication networks add extra layer of challenges on E-health ecosystem such as time constraints, quality of measurements and signals reaching healthcare centres. Hence this research has tackled the delay and jitter parameters in E-health M2M wireless communication and succeeded in reducing them in comparison to current available models. The novelty of this research has succeeded in developing a new Priority Queuing model ‘’Priority Based-Fair Queuing’’ (PFQ) where a new priority level and concept of ‘’Patient’s Health Record’’ (PHR) has been developed and integrated with the Priority Parameters (PP) values of each sensor to add a second level of priority. The results and data analysis performed on the PFQ model under different scenarios simulating real M2M E-health environment have revealed that the PFQ has outperformed the results obtained from simulating the widely used current models such as First in First Out (FIFO) and Weight Fair Queuing (WFQ). PFQ model has improved transmission of ECG sensor data by decreasing delay and jitter in emergency cases by 83.32% and 75.88% respectively in comparison to FIFO and 46.65% and 60.13% with respect to WFQ model. Similarly, in pressure sensor the improvements were 82.41% and 71.5% and 68.43% and 73.36% in comparison to FIFO and WFQ respectively. Data transmission were also improved in the Glucose sensor by 80.85% and 64.7% and 92.1% and 83.17% in comparison to FIFO and WFQ respectively. However, non-emergency cases data transmission using PFQ model was negatively impacted and scored higher rates than FIFO and WFQ since PFQ tends to give higher priority to emergency cases. Thus, a derivative from the PFQ model has been developed to create a new version namely “Priority Based-Fair Queuing-Tolerated Delay” (PFQ-TD) to balance the data transmission between emergency and non-emergency cases where tolerated delay in emergency cases has been considered. PFQ-TD has succeeded in balancing fairly this issue and reducing the total average delay and jitter of emergency and non-emergency cases in all sensors and keep them within the acceptable allowable standards. PFQ-TD has improved the overall average delay and jitter in emergency and non-emergency cases among all sensors by 41% and 84% respectively in comparison to PFQ model

Analysis of a batch-service queue with variable service capacity, correlated customer types and generally distributed class-dependent service times

Queueing models with batch service have been studied frequently, for instance in the domain of telecommunications or manufacturing. Although the batch server's capacity may be variable in practice, only a few authors have included variable capacity in their models. We analyse a batch server with multiple customer classes and a variable service capacity that depends on both the number of waiting customers and their classes. The service times are generally distributed and class-dependent. These features complicate the analysis in a non-trivial way. We tackle it by examining the system state at embedded points, and studying the resulting Markov Chain. We first establish the joint probability generating function (pgf) of the service capacity and the number of customers left behind in the queue immediately after service initiation epochs. From this joint pgf, we extract the pgf for the number of customers in the queue and in the system respectively at service initiation epochs and departure epochs, and the pgf of the actual server capacity. Combined with additional techniques, we also obtain the pgf of the queue and system content at customer arrival epochs and random slot boundaries, and the pgf of the delay of a random customer. In the numerical experiments, we focus on the impact of correlation between the classes of consecutive customers, and on the influence of different service time distributions on the system performance. (C) 2019 Elsevier B.V. All rights reserved

Enhanced priority-based adaptive energy-aware mechanisms for wireless sensor networks

Wireless Sensor Networks (WSN) continues to find its use in our lives. However, research has shown that it has barely attained an optimal performance, particularly in the aspects of data heterogeneity, data prioritization, data routing, and energy efficiency, all of which affects its operational lifetime. The IEEE 802.15.4 protocol standard, which manages data forwarding across the Data Link Layer (DLL) does not address the impact of heterogeneous data and node Battery-Level (BL) which is an indicator for node battery life. Likewise, mechanisms proposed in the literature – TCP-CSMA/CA, QWL-RPL and SSRA have not proffered optimal solution as they encourage excessive computational overhead which results in shortened operational lifetime. These problems are inherited on the Network Layer (NL) where data routing is implemented. Mitigating these challenges, this research presents an Enhanced Priority-based Adaptive Energy-Aware Mechanisms (EPAEAM) for Wireless Sensor Networks. The first mechanism is the Optimized Backoff Mechanism for Prioritized Data (OBMPD) in Wireless Sensor Networks. This mechanism proposed the Class of Service Traffic Priority-based Medium Access Control (CSTP-MAC). The CSTP-MAC is implemented on the DLL. In this mechanism, unique backoff period expressions compute backoff periods according to the class and priority of the heterogeneous data. This approach improved network performances which enhanced network lifetime. The second mechanism is the Shortest Path Priority-Based Objective Function (SPPB-OF) for Wireless Sensor Networks. SPPB-OF is implemented across the NL. SPPB-OF implements a unique shortest path computation algorithm to generate energy-efficient shortest path between the source and destination nodes. The third mechanism is the Cross-Layer Energy-Efficient Priority-based Data Path (CL-EEPDP) for Wireless Sensor Networks. CL-EEPDP is implemented across the DLL and NL with considerations for node battery-level. A unique mathematical expression, Node Battery-Level Estimator (NBLE) is used to estimate the BL of neighbouring nodes. The knowledge of the BL together with the priority of data are used to decide an energy-efficient next-hop node. Benchmarking the EPAEAM with related mechanisms - TCP-CSMA/CA, QWL-RPL and SSRA, results show that EPAEAM achieved improved network performance with a packet delivery ratio (PDR) of 95.4%, and power-saving of 90.4%. In conclusion, the EPAEAM mechanism proved to be a viable energy-efficient solution for a multi-hop heterogeneous data WSN deployment with support for extended operational lifetime. The limitations and scope of these mechanisms are that their application is restricted to the data-link and network layers, moreover, only two classes of data are considered, that is; High Priority Data (HPD) and Low Priority Data (LPD)

Towards Tactile Internet in Beyond 5G Era: Recent Advances, Current Issues and Future Directions

Tactile Internet (TI) is envisioned to create a paradigm shift from the content-oriented communications to steer/control-based communications by enabling real-time transmission of haptic information (i.e., touch, actuation, motion, vibration, surface texture) over Internet in addition to the conventional audiovisual and data traffics. This emerging TI technology, also considered as the next evolution phase of Internet of Things (IoT), is expected to create numerous opportunities for technology markets in a wide variety of applications ranging from teleoperation systems and Augmented/Virtual Reality (AR/VR) to automotive safety and eHealthcare towards addressing the complex problems of human society. However, the realization of TI over wireless media in the upcoming Fifth Generation (5G) and beyond networks creates various non-conventional communication challenges and stringent requirements in terms of ultra-low latency, ultra-high reliability, high data-rate connectivity, resource allocation, multiple access and quality-latency-rate tradeoff. To this end, this paper aims to provide a holistic view on wireless TI along with a thorough review of the existing state-of-the-art, to identify and analyze the involved technical issues, to highlight potential solutions and to propose future research directions. First, starting with the vision of TI and recent advances and a review of related survey/overview articles, we present a generalized framework for wireless TI in the Beyond 5G Era including a TI architecture, the main technical requirements, the key application areas and potential enabling technologies. Subsequently, we provide a comprehensive review of the existing TI works by broadly categorizing them into three main paradigms; namely, haptic communications, wireless AR/VR, and autonomous, intelligent and cooperative mobility systems. Next, potential enabling technologies across physical/Medium Access Control (MAC) and network layers are identified and discussed in detail. Also, security and privacy issues of TI applications are discussed along with some promising enablers. Finally, we present some open research challenges and recommend promising future research directions