282 research outputs found

    Embracing corruption burstiness: Fast error recovery for ZigBee under wi-Fi interference

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    This is the author accepted manuscript. The final version is available from the publisher via the DOI in this record.The ZigBee communication can be easily and severely interfered by Wi-Fi traffic. Error recovery, as an important means for ZigBee to survive Wi-Fi interference, has been extensively studied in recent years. The existing works add upfront redundancy to in-packet blocks for recovering a certain number of random corruptions. Therefore the bursty nature of ZigBee in-packet corruptions under Wi-Fi interference is often considered harmful, since some blocks are full of errors which cannot be recovered and some blocks have no errors but still requiring redundancy. As a result, they often use interleaving to reshape the bursty errors, before applying complex FEC codes to recover the re-shaped random distributed errors. In this paper, we take a different view that burstiness may be helpful. With burstiness, the in-packet corruptions are often consecutive and the requirement for error recovery is reduced as ”recovering any k consecutive errors” instead of ”recovering any random k errors”. This lowered requirement allows us to design far more efficient code than the existing FEC codes. Motivated by this implication, we exploit the corruption burstiness to design a simple yet effective error recovery code using XOR operations (called ZiXOR). ZiXOR uses XOR code and the delay is significantly reduced. More, ZiXOR uses RSSI-hinted approach to detect in packet corruptions without CRC, incurring almost no extra transmission overhead. The testbed evaluation results show that ZiXOR outperforms the state-of-the-art works in terms of the throughput (by 47%) and latency (by 22%)This work was supported by the National Natural Science Foundation of China (No. 61602095 and No. 61472360), the Fundamental Research Funds for the Central Universities (No. ZYGX2016KYQD098 and No. 2016FZA5010), National Key Technology R&D Program (Grant No. 2014BAK15B02), CCFIntel Young Faculty Researcher Program, CCF-Tencent Open Research Fund, China Ministry of Education—China Mobile Joint Project under Grant No. MCM20150401 and the EU FP7 CLIMBER project under Grant Agreement No. PIRSES-GA- 2012-318939. Wei Dong is the corresponding author

    Facilitating wireless coexistence research

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    Secure Data Collection and Analysis in Smart Health Monitoring

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    Smart health monitoring uses real-time monitored data to support diagnosis, treatment, and health decision-making in modern smart healthcare systems and benefit our daily life. The accurate health monitoring and prompt transmission of health data are facilitated by the ever-evolving on-body sensors, wireless communication technologies, and wireless sensing techniques. Although the users have witnessed the convenience of smart health monitoring, severe privacy and security concerns on the valuable and sensitive collected data come along with the merit. The data collection, transmission, and analysis are vulnerable to various attacks, e.g., eavesdropping, due to the open nature of wireless media, the resource constraints of sensing devices, and the lack of security protocols. These deficiencies not only make conventional cryptographic methods not applicable in smart health monitoring but also put many obstacles in the path of designing privacy protection mechanisms. In this dissertation, we design dedicated schemes to achieve secure data collection and analysis in smart health monitoring. The first two works propose two robust and secure authentication schemes based on Electrocardiogram (ECG), which outperform traditional user identity authentication schemes in health monitoring, to restrict the access to collected data to legitimate users. To improve the practicality of ECG-based authentication, we address the nonuniformity and sensitivity of ECG signals, as well as the noise contamination issue. The next work investigates an extended authentication goal, denoted as wearable-user pair authentication. It simultaneously authenticates the user identity and device identity to provide further protection. We exploit the uniqueness of the interference between different wireless protocols, which is common in health monitoring due to devices\u27 varying sensing and transmission demands, and design a wearable-user pair authentication scheme based on the interference. However, the harm of this interference is also outstanding. Thus, in the fourth work, we use wireless human activity recognition in health monitoring as an example and analyze how this interference may jeopardize it. We identify a new attack that can produce false recognition result and discuss potential countermeasures against this attack. In the end, we move to a broader scenario and protect the statistics of distributed data reported in mobile crowd sensing, a common practice used in public health monitoring for data collection. We deploy differential privacy to enable the indistinguishability of workers\u27 locations and sensing data without the help of a trusted entity while meeting the accuracy demands of crowd sensing tasks

    Enhanced collision avoidance mechanisms for wireless sensor networks through high accuracy collision modeling

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    Wireless channel and multi-hop communications cause a significant number of packet collisions in Wireless Sensor Networks (WSNs). Although a collision may cause packet loss and reduce network performance, low-power wireless transceivers allow packet reception in the presence of collisions if at least one signal can provide a sufficiently high power compared with other signals. Therefore, with respect to the large number of nodes used in WSNs, which necessitates the use of simulation for protocol development, collisions should be addressed at two layers: First, collisions should be modeled at the physical layer through a high-accuracy packet reception algorithm that decides about packet reception in the presence of collisions. Second, collision avoidance mechanisms should be employed at the Medium Access Control (MAC) layer to reduce packet losses caused by collisions. Unfortunately, the existing packet reception algorithms exhibit low accuracy and impede the development of efficient collision avoidance mechanisms. From the collision avoidance perspective, existing contention-based MAC protocols do not provide reliable packet broadcasting, thereby affecting the initialization performance of WSNs. In addition, despite the benefits of schedule-based MAC protocols during the data-gathering phase, the existing mechanisms rely on unrealistic assumptions. The first major contribution of this work is CApture Modeling Algorithm (CAMA), which enables collision modeling with high accuracy and efficiency at the physical layer. The higher accuracy of CAMA against existing approaches is validated through extensive comparisons with empirical experiments. The second major contribution includes mechanisms that improve the reliability of packet broadcasting. In particular, adaptive contention window adjustment mechanisms and the Geowindow algorithm are proposed for collision avoidance during the initialization phases. These mechanisms considerably improve the accuracy of the initialization phases, without violating duration and energy efficiency requirements. As the third major contribution, a distributed and concurrent link-scheduling algorithm (called DICSA) is proposed for collision avoidance during the data-gathering phase. DICSA provides faster slot assignment, higher spatial reuse and lower energy consumption, compared with existing algorithms. Furthermore, evaluating DICSA within a MAC protocol confirms its higher throughput, higher delivery ratio, and lower end-to-end delay

    An approach to understand network challenges of wireless sensor network in real-world environments

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    The demand for large-scale sensing capabilities and scalable communication networks to monitor and control entities within smart buildings have fuelled the exponential growth in Wireless Sensor Network (WSN). WSN proves to be an attractive enabler because of its accurate sensing, low installation cost and flexibility in sensor placement. While WSN offers numerous benefits, it has yet to realise its full potential due to its susceptibility to network challenges in the environment that it is deployed. Particularly, spatial challenges in the indoor environment are known to degrade WSN communication reliability and have led to poor estimations of link quality. Existing WSN solutions often generalise all link failures and tackle them as a single entity. However, under the persistent influence of spatial challenges, failing to provide precise solutions may cause further link failures and higher energy consumption of battery-powered devices. Therefore, it is crucial to identify the causes of spatial- related link failures in order to improve WSN communication reliability. This thesis investigates WSN link failures under the influence of spatial challenges in real-world indoor environments. Novel and effective strategies are developed to evaluate the WSN communication reliability. By distinguishing between spatial challenges such as a poorly deployed environment and human movements, solutions are devised to reduce link failures and improve the lifespans of energy constraint WSN nodes. In this thesis, WSN test beds using proprietary wireless sensor nodes are developed and deployed in both controlled and uncontrolled office environments. These test beds provide diverse platforms for investigation into WSN link quality. In addition, a new data extraction feature called Network Instrumentation (NI) is developed and implemented onto the communication stacks of wireless sensor nodes to collect ZigBee PRO parameters that are under the influence of environmental dynamics. To understand the relationships between WSN and Wi-Fi devices communications, an investigation on frequency spectrum sharing is conducted between IEEE 802.15.4 and IEEE 802.11 bgn standards. It is discovered that the transmission failure of WSN nodes under persistent Wi-Fi interference is largely due to channel access failure rather than corrupted packets. The findings conclude that both technologies can co- exist as long as there is sufficient frequency spacing between Wi-Fi and WSN communication and adequate operating distance between the WSN nodes, and between the WSN nodes and the Wi-Fi interference source. Adaptive Network-based Fuzzy Inference System (ANFIS) models are developed to predict spatial challenges in an indoor environment. These challenges are namely, “no failure”, “failure due to poorly deployed environment” and “failure due to human movement”. A comparison of models has found that the best-produced model represents the properties of signal strength, channel fluctuations, and communication success rates. It is recognised that the interpretability of ANFIS models have reduced due to the “curse of dimensionality”. Hence, Non-Dominated Sorting Genetic Algorithm (NSGA-II) technique is implemented to reduce the complexity of these ANFIS models. This is followed by a Fuzzy rule sensitivity analysis, where the impacts of Fuzzy rules on model accuracy are found to be dependent on factors such as communication range and controlled or uncontrolled environment. Long-term WSN routing stability is measured, taking into account the adaptability and robustness of routing paths in the real-world environments. It is found that routing stability is subjected to the implemented routing protocol, deployed environment and routing options available. More importantly, the probability of link failures can be as high as 29.9% when a next hop’s usage rate falls less than 10%. This suggests that a less dominant next hop is subjected to more link failures and is short-lived. Overall, this thesis brings together diverse WSN test beds in real-world indoor environments and a new data extraction platform to extract link quality parameters from ZigBee PRO stack for a representative assessment of WSN link quality. This produces realistic perspectives of the interactions between WSN communication reliability and the environmental dynamics, particularly spatial challenges. The outcomes of this work include an in-depth system level understanding of real-world deployed applications and an insightful measure of large-scale WSN communication performance. These findings can be used as building blocks for a reliable and sustainable network architecture built on top of resource–constrained WSN

    Supervisory Wireless Control for Critical Industrial Applications

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    Indoor localization utilizing existing infrastructure in smart homes : a thesis by publications presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Computer and Electronics Engineering, Massey University, Albany, New Zealand

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    Listed in 2019 Dean's List of Exceptional ThesesIndoor positioning system (IPS) have received significant interest from the research community over the past decade. However, this has not eventuated into widespread adoption of IPS and few commercial solutions exist. Integration into Smart Homes could allow for secondary services including location-based services, targeted user experiences and intrusion detection, to be enabled using the existing underlying infrastructure. Since New Zealand has an aging population, we must ensure that the elderly are well looked after. An IPS solution could detect whether a person has been immobile for an extended period and alert medical personnel. A major shortcoming of existing IPS is their reliance on end-users to undertake a significant infrastructure investment to facilitate the localization tasks. An IPS that does not require extensive installation and calibration procedures, could potentially see significant uptake from end users. In order to expedite the widespread adoption of IPS technology, this thesis focuses on four major areas of improvement, namely: infrastructure reuse, reduced node density, algorithm improvement and reduced end user calibration requirements. The work presented demonstrates the feasibility of utilizing existing wireless and lighting infrastructure for positioning and implements novel spring-relaxation and potential fields-based localization approaches that allow for robust target tracking, with minimal calibration requirements. The developed novel localization algorithms are benchmarked against the existing state of the art and show superior performance

    Effective Scheduling Algorithms for Cross-Interference Mitigation in Heterogeneous Wireless Networks

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    Wireless networks are making life easier, smarter and more convenient. However, the well-known Carrier-sense multiple access with collision avoidance (CSMA/CA) mechanism is powerless when dealing with Cross-Technology Interference (CTI) between Wi-Fi and Low-Rate Wireless Personal Area Network (LR-WPAN), because of asymmetric transmission power, incompatible Clear Channel Assessment (CCA) and different timing parameters. Plenty of studies have shown that WiFi always has a higher priority to access the wireless medium and even block LR-WPAN transmission in the worst case. Our experiments confirm this point and conclude that Wi-Fi can interrupt LR-WPAN severely even block LR-WPAN traffic, while the interference from LR-WPAN to Wi-Fi is negligible. Different from other studies, this thesis presents a novel centralized scheduling mechanism in the time domain to harmonize coexistence of Wi-Fi and LR-WPAN, also refer to as time-slot based scheduling mechanism. The mechanism is achieved by introducing a new command frame, named Access Notification (AN), into the IEEE802.15.4 Medium Access Control (MAC) layer. Based on this mechanism, a static time-slot based scheduling algorithm is designed and evaluated on both real hardware-based system and NS-3 simulator. The result shows the algorithm improves LR-WPAN Packet Loss Rate (PLR) significantly but at the cost of reducing Wi-Fi throughput. In order to maximize performance, based on slot-based congestion indicator (CI) that is proposed and defined to tell whether an allocated time slot is adequate for data transmission or not, we further design an adaptive time-slot based scheduling algorithm. The evaluation shows that the adaptive algorithm covers the shortage of the static algorithm and offers a distinct improvement on LR-WPAN Packet Transmission Rate (PTR)
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