431 research outputs found

    Machine learning based lightweight interference mitigation scheme for wireless sensor network

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    The interference issue is most vibrant on low-powered networks like wireless sensor network (WSN). In some cases, the heavy interference on WSN from different technologies and devices result in life threatening situations. In this paper, a machine learning (ML) based lightweight interference mitigation scheme for WSN is proposed. The scheme detects and identifies heterogeneous interference like Wifi, bluetooth and microwave oven using a lightweight feature extraction method and ML lightweight decision tree. It also provides WSN an adaptive interference mitigation solution by helping to choose packet scheduling, Acknowledgement (ACK)-retransmission or channel switching as the best countermeasure. The scheme is simulated with test data to evaluate the accuracy performance and the memory consumption. Evaluation of the proposed scheme’s memory profile shows a 14% memory saving compared to a fast fourier transform (FFT) based periodicity estimation technique and 3% less memory compared to logistic regression-based ML model, hence proving the scheme is lightweight. The validation test shows the scheme has a high accuracy at 95.24%. It shows a precision of 100% in detecting WiFi and microwave oven interference while a 90% precision in detecting bluetooth interference

    Wireless body sensor networks for health-monitoring applications

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    This is an author-created, un-copyedited version of an article accepted for publication in Physiological Measurement. The publisher is not responsible for any errors or omissions in this version of the manuscript or any version derived from it. The Version of Record is available online at http://dx.doi.org/10.1088/0967-3334/29/11/R01

    JAG: Reliable and Predictable Wireless Agreement under External Radio Interference

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    Wireless low-power transceivers used in sensor networks typically operate in unlicensed frequency bands that are subject to external radio interference caused by devices transmitting at much higher power.communication protocols should therefore be designed to be robust against such interference. A critical building block of many protocols at all layers is agreement on a piece of information among a set of nodes. At the MAC layer, nodes may need to agree on a new time slot or frequency channel, at the application layer nodes may need to agree on handing over a leader role from one node to another. Message loss caused by interference may break agreement in two different ways: none of the nodes uses the new information (time slot, channel, leader) and sticks with the previous assignment, or-even worse-some nodes use the new information and some do not. This may lead to reduced performance or failures. In this paper, we investigate the problem of agreement under external radio interference and point out the limitations of traditional message-based approaches. We propose JAG, a novel protocol that uses jamming instead of message transmissions to make sure that two neighbouring nodes agree, and show that it outperforms message-based approaches in terms of agreement probability, energy consumption, and time-to-completion. We further show that JAG can be used to obtain performance guarantees and meet the requirements of applications with real-time constraints.CONETReSens

    Wireless Sensor Networking in Challenging Environments

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    Recent years have witnessed growing interest in deploying wireless sensing applications in real-world environments. For example, home automation systems provide fine-grained metering and control of home appliances in residential settings. Similarly, assisted living applications employ wireless sensors to provide continuous health and wellness monitoring in homes. However, real deployments of Wireless Sensor Networks (WSNs) pose significant challenges due to their low-power radios and uncontrolled ambient environments. Our empirical study in over 15 real-world apartments shows that low-power WSNs based on the IEEE 802.15.4 standard are highly susceptible to external interference beyond user control, such as Wi-Fi access points, Bluetooth peripherals, cordless phones, and numerous other devices prevalent in residential environments that share the unlicensed 2.4 GHz ISM band with IEEE 802.15.4 radios. To address these real-world challenges, we developed two practical wireless network protocols including the Adaptive and Robust Channel Hopping (ARCH) protocol and the Adaptive Energy Detection Protocol (AEDP). ARCH enhances network reliability through opportunistically changing radio\u27s frequency to avoid interference and environmental noise and AEDP reduces false wakeups in noisy wireless environments by dynamically adjusting the wakeup threshold of low-power radios. Another major trend in WSNs is the convergence with smart phones. To deal with the dynamic wireless conditions and varying application requirements of mobile users, we developed the Self-Adapting MAC Layer (SAML) to support adaptive communication between smart phones and wireless sensors. SAML dynamically selects and switches Medium Access Control protocols to accommodate changes in ambient conditions and application requirements. Compared with the residential and personal wireless systems, industrial applications pose unique challenges due to their critical demands on reliability and real-time performance. We developed an experimental testbed by realizing key network mechanisms of industrial Wireless Sensor and Actuator Networks (WSANs) and conducted an empirical study that revealed the limitations and potential enhancements of those mechanisms. Our study shows that graph routing is more resilient to interference and its backup routes may be heavily used in noisy environments, which demonstrate the necessity of path diversity for reliable WSANs. Our study also suggests that combining channel diversity with retransmission may effectively reduce the burstiness of transmission failures and judicious allocation of multiple transmissions in a shared slot can effectively improve network capacity without significantly impacting reliability

    A critical analysis of research potential, challenges and future directives in industrial wireless sensor networks

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    In recent years, Industrial Wireless Sensor Networks (IWSNs) have emerged as an important research theme with applications spanning a wide range of industries including automation, monitoring, process control, feedback systems and automotive. Wide scope of IWSNs applications ranging from small production units, large oil and gas industries to nuclear fission control, enables a fast-paced research in this field. Though IWSNs offer advantages of low cost, flexibility, scalability, self-healing, easy deployment and reformation, yet they pose certain limitations on available potential and introduce challenges on multiple fronts due to their susceptibility to highly complex and uncertain industrial environments. In this paper a detailed discussion on design objectives, challenges and solutions, for IWSNs, are presented. A careful evaluation of industrial systems, deadlines and possible hazards in industrial atmosphere are discussed. The paper also presents a thorough review of the existing standards and industrial protocols and gives a critical evaluation of potential of these standards and protocols along with a detailed discussion on available hardware platforms, specific industrial energy harvesting techniques and their capabilities. The paper lists main service providers for IWSNs solutions and gives insight of future trends and research gaps in the field of IWSNs

    Sub-GHz LPWAN network coexistence, management and virtualization : an overview and open research challenges

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    The IoT domain is characterized by many applications that require low-bandwidth communications over a long range, at a low cost and at low power. Low power wide area networks (LPWANs) fulfill these requirements by using sub-GHz radio frequencies (typically 433 or 868 MHz) with typical transmission ranges in the order of 1 up to 50 km. As a result, a single base station can cover large areas and can support high numbers of connected devices (> 1000 per base station). Notorious initiatives in this domain are LoRa, Sigfox and the upcoming IEEE 802.11ah (or "HaLow") standard. Although these new technologies have the potential to significantly impact many IoT deployments, the current market is very fragmented and many challenges exists related to deployment, scalability, management and coexistence aspects, making adoption of these technologies difficult for many companies. To remedy this, this paper proposes a conceptual framework to improve the performance of LPWAN networks through in-network optimization, cross-technology coexistence and cooperation and virtualization of management functions. In addition, the paper gives an overview of state of the art solutions and identifies open challenges for each of these aspects

    Machine Learning Aided Methods for Resilient Industrial Wireless Sensor Network

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    Le Wireless Sensor Network (WSN) possono essere definite come un’ infrastruttura composta da sensori/dispositivi in grado di calcolare comunicare e effettuare sensing sul ambiente che gli circonda processando e analizzando i dati in modo da reagire a eventi e fenomeni che possono occorrere durante la comunicazione. Questo motiva un enorme effort nella ricerca, standardizzazione e investimento industriale in questo campo, nell’ultimo decennio. L’uso delle WSN nell’ambiente industriale ù soggetto a diverse problematiche, dovuto all’ostilità dell’ambiente, come rumore, shadwoing, multi-percorso e interferenze. Nel nostro progetto, proponiamo un meccanismo basato sulle condizioni di propagazione del canale e algoritmi di machine learning che ci permettono di classificare lo stato del canale (LOS o NLOS) e migliorare qualità, sicurezza e in particolar modo l’affidabilità del sistema radio link da noi esaminato in differenti ambienti

    A real-time packet scheduling system for a 6LoWPAN industrial application

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    Nowadays, the industrial Wireless Sensor Networks (WSN) are crucial for the monitoring and control of the modern smart factory floor that is relying on them for critical applications and tasks that were performed by wired systems in the past. For this reason, it is required that the transmission mechanisms of wireless sensor networks are efficient and robust and that they guarantee realtime responses with low data losses. Furthermore, it is required that they utilize common networking standards, such as the Internet Protocol (IP), that provides interoperability with already existing infrastructures and offers widely tested security and transmission control protocols. The theoretical part of this document focuses on the description of the current panorama of the industrial WSN, its applications, design challenges and standardizations. It describes the 6LoWPAN standard and the wireless transmission technology that it uses for its lower layers, the IEEE 802.15.4 protocol. Later, it describes the principles behind the wireless scheduling, a state-of-the-art in the IEEE 802.15.4 scheduled channel access and the features of the most used operating systems for WSN. The practical part presents the real-time packet scheduling system for a 6LoWPAN industrial application proposed by this thesis work that adapts the HSDPA scheduling mechanisms to the IEEE 802.15.4 beacon-enabled mode. The system implemented manages the channel access by allocating Guaranteed Time Slots to sensor nodes according to the priority given by three scheduling algorithms that can be selected according to the traffic condition of the network. The system proposed was programmed using Contiki OS. It is based on the eSONIA 6LoWPAN firmware developed for the European Research Project and it was deployed on the FAST WSN for testing. The results, discussion and conclusions are documented at the final sections of this part
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