Modeling of Duty-Cycled MAC Protocols for Heterogeneous WSN with Priorities

[EN] Wireless Sensor Networks (WSN) have experienced an important revitalization, particularly with the arrival of Internet of Things applications. In a general sense, a WSN can be composed of different classes of nodes, having different characteristics or requirements (heterogeneity). Duty-cycling is a popular technique used in WSN, that allows nodes to sleep and wake up periodically in order to save energy. We believe that the modeling and performance evaluation of heterogeneous WSN with priorities operating in duty-cycling, being of capital importance for their correct design and successful deployment, have not been sufficiently explored. The present work presents a performance evaluation study of a WSN with these features. For a scenario with two classes of nodes composing the network, each with a different channel access priority, an approximate analytical model is developed with a pair of two-dimensional discrete-time Markov chains. Note that the same modeling approach can be used to analyze networks with a larger number of classes. Performance parameters such as average packet delay, throughput and average energy consumption are obtained. Analytical results are validated by simulation, showing accurate results. Furthermore, a new procedure to determine the energy consumption of nodes is proposed that significantly improves the accuracy of previous proposals. We provide quantitative evidence showing that the energy consumption accuracy improvement can be up to two orders of magnitudeThis work is part of the project PGC2018-094151-B-I00, which is financed by the Ministerio de Ciencia, Innovacion y Universidades (MCIU), Agencia Estatal de Investigacion (AEI) and Fondo Europeo de Desarrollo Regional (FEDER) (MCIU/AEI/FEDER.UE). C. Portillo acknowledges the funding received from the European Union under the program Erasmus Mundus Partnerships, project EuroinkaNet, GRANT AGREEMENT NUMBER -2014 -0870/001/001, and the support received from SEP-SES (DSA/103.5/15/6629)Portillo, C.; Martínez Bauset, J.; Pla, V.; Casares-Giner, V. (2020). Modeling of Duty-Cycled MAC Protocols for Heterogeneous WSN with Priorities. Electronics. 9(3):1-16. https://doi.org/10.3390/electronics9030467S11693Gomes, D. A., & Bianchini, D. (2016). Interconnecting Wireless Sensor Networks with the Internet Using Web Services. IEEE Latin America Transactions, 14(4), 1937-1942. doi:10.1109/tla.2016.7483537Libo, Z., Tian, H., & Chunyun, G. (2019). Wireless multimedia sensor network for rape disease detections. EURASIP Journal on Wireless Communications and Networking, 2019(1). doi:10.1186/s13638-019-1468-3Shi, X., An, X., Zhao, Q., Liu, H., Xia, L., Sun, X., & Guo, Y. (2019). State-of-the-Art Internet of Things in Protected Agriculture. 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Design of a Wireless Sensor Network-Based IoT Platform for Wide Area and Heterogeneous Applications. IEEE Sensors Journal, 18(12), 5187-5197. doi:10.1109/jsen.2018.2832664He, X., Liu, S., Yang, G., & Xiong, N. (2018). Achieving Efficient Data Collection in Heterogeneous Sensing WSNs. IEEE Access, 6, 63187-63199. doi:10.1109/access.2018.2876552Ortin, J., Cesana, M., Redondi, A. E. C., Canales, M., & Gallego, J. R. (2019). Analysis of Unslotted IEEE 802.15.4 Networks With Heterogeneous Traffic Classes. IEEE Wireless Communications Letters, 8(2), 380-383. doi:10.1109/lwc.2018.2873347Bianchi, G. (2000). Performance analysis of the IEEE 802.11 distributed coordination function. IEEE Journal on Selected Areas in Communications, 18(3), 535-547. doi:10.1109/49.840210Liu, R. P., Sutton, G. J., & Collings, I. B. (2010). A New Queueing Model for QoS Analysis of IEEE 802.11 DCF with Finite Buffer and Load. IEEE Transactions on Wireless Communications, 9(8), 2664-2675. doi:10.1109/twc.2010.061010.091803Ou Yang, & Heinzelman, W. (2012). Modeling and Performance Analysis for Duty-Cycled MAC Protocols with Applications to S-MAC and X-MAC. IEEE Transactions on Mobile Computing, 11(6), 905-921. doi:10.1109/tmc.2011.121Martinez-Bauset, J., Guntupalli, L., & Li, F. Y. (2015). Performance Analysis of Synchronous Duty-Cycled MAC Protocols. IEEE Wireless Communications Letters, 4(5), 469-472. doi:10.1109/lwc.2015.2439267Guntupalli, L., Martinez-Bauset, J., Li, F. Y., & Weitnauer, M. A. (2017). Aggregated Packet Transmission in Duty-Cycled WSNs: Modeling and Performance Evaluation. IEEE Transactions on Vehicular Technology, 66(1), 563-579. doi:10.1109/tvt.2016.2536686Zhang, R., Moungla, H., Yu, J., & Mehaoua, A. (2017). Medium Access for Concurrent Traffic in Wireless Body Area Networks: Protocol Design and Analysis. IEEE Transactions on Vehicular Technology, 66(3), 2586-2599. doi:10.1109/tvt.2016.2573718Guntupalli, L., Martinez-Bauset, J., & Li, F. Y. (2018). Performance of frame transmissions and event-triggered sleeping in duty-cycled WSNs with error-prone wireless links. Computer Networks, 134, 215-227. doi:10.1016/j.comnet.2018.01.047(July, 2019). The State Transition Probabilities of the Two 2D-DTMC. Technical Report http://personales.upv.es/jmartine/public/2DDTMC.pdfCrossbow Technology Incorporated, San Jose, CA, USA http://www.openautomation.net/uploadsproductos/micaz-datasheet.pd

Pemodelan Background Traffic Pada Jaringan Berkapasitas Terbatas

Rapid technological developments influence various aspects of life. And that makes the use of Internet technology as a part of carrying out daily activities. But the need for adequate Internet networks is hampered by limited bandwidth capacity in the network. Measurements made on limited capacity testing networks aim to determine the characteristics of the testing network and the rate of traffic in the network. In the testing network, the average bandwidth capacity was 3.61 Mbps, and the average rate of traffic was 1,428 Mbps. The rate of traffic that occurs in the testing network is worth 1/3 of the highest bandwidth capacity on the testing network which is 4,76 Mbps. With the characteristics of continuous packet delivery of 70%, and bulk packet delivery by 30%. Through the results of the characteristics of the package delivery, the background traffic model that is constructed describing the transmission of bulk packets will be transmitted after 7 continuous packets sent. Background traffic modeling can be a reference in conducting content delivery simulations in network simulations application that resemble the characteristics of testing networkPerkembangan teknologi yang begitu cepat mempengaruhi berbagai aspek dalam kehidupan. Dan hal tersebut yang menjadikan penggunaan teknologi Internet menjadi bagian dalam menjalankan kegiatan sehari-hari. Namun kebutuhan atas jaringan Internet yang memadai terhambat dengan terbatasnya kapasitas bandwidth dalam jaringan. Pengukuran yang dilakukan pada jaringan pengujian berkapasitas terbatas bertujuan untuk mengetahui karakteristik dari jaringan pengujian dan tingkat laju traffic dalam jaringan tersebut. Pada jaringan pengujian didapati rata-rata kapasitas bandwidth sebesar 3,61 Mbps, dan rata-rata tingkat laju traffic sebesar 1,428 Mbps. Tingkat laju traffic yang terjadi dalam jaringan pengujian bernilai 1/3 dari kapasitas bandwidth tertinggi pada jaringan pengujian yaitu 4,76 Mbps. Dengan karakteristik penyampaian paket yang bersifat continuous sebesar 70%, dan paket yang bersifat bulk sebesar 30%. Melalui hasil karakteristik penyampaian paket tersebut, pemodelan background traffic yang dibangun menggambarkan transmisi paket yang bersifat bulk akan ditransmisikan setelah 7 paket yang bersifat continuous terkirim. Pemodelan background traffic ini dapat menjadi acuan dalam melakukan simulasi penyampaian konten dalam aplikasi simulasi jaringan yang dibangun menyerupai karakteristik jaringan pengujia

Design and Empirical Validation of a Bluetooth 5 Fog Computing Based Industrial CPS Architecture for Intelligent Industry 4.0 Shipyard Workshops

[Abstract] Navantia, one of largest European shipbuilders, is creating a fog computing based Industrial Cyber-Physical System (ICPS) for monitoring in real-time its pipe workshops in order to track pipes and keep their traceability. The deployment of the ICPS is a unique industrial challenge in terms of communications, since in a pipe workshop there is a significant number of metallic objects with heterogeneous typologies. There are multiple technologies that can be used to track pipes, but this article focuses on Bluetooth 5, which is a relatively new technology that represents a cost-effective solution to cope with harsh environments, since it has been significantly enhanced in terms of low power consumption, range, speed and broadcasting capacity. Thus, it is proposed a Bluetooth 5 fog computing based ICPS architecture that is designed to support physically-distributed and low-latency Industry 4.0 applications that off-load network traffic and computational resources from the cloud. In order to validate the proposed ICPS design, one of the Navantia’s pipe workshops was modeled through an in-house developed 3D-ray launching radio planning simulator that allows for estimating the coverage provided by the deployed Bluetooth 5 fog computing nodes and Bluetooth 5 tags. The experiments described in this article show that the radio propagation results obtained by the simulation tool are really close to the ones obtained through empirical measurements. As a consequence, the simulation tool is able to reduce ICPS design and deployment time and provide guidelines to future developers when deploying Bluetooth 5 fog computing nodes and tags in complex industrial scenarios.Auto-ID for Intelligent Products research line of the Navantia-UDC Joint Research Unit (Grant Number: IN853B-2018/02) 10.13039/100014440-Ministerio de Ciencia, Innovaci??n y Universidades (Grant Number: RTI2018-095499-B-C31

Apoio à Definição de Arquiteturas IIoT Inteligentes

As plataformas IIoT (Industrial Internet-of-Things) são um facilitador na transformação digital, no âmbito da indústria 4.0, promovendo a flexibilidade, para uma adaptação mais rápida às necessidades do mercado, e permitindo às organizações ter uma visão clara sobre o seu estado atual. No entanto, as PMEs (Pequenas e Médias Empresas) estão a encontrar dificuldades na mudança para este novo paradigma, devido à falta de: i) recursos qualificados que são necessários para desenvolver e implementar as suas próprias soluções de digitalização; ii) um entendimento claro sobre a reengenharia necessária que envolve a digitalização, na adoção de soluções IIoT, e iii) modelos adequados para a especificação de soluções IIoT orientadas às PMEs. Com intuito de ultrapassar estes desafios, discute-se uma solução numa dupla perspetiva, em que: i) por um lado, procura-se a automatização da especificação das arquiteturas de plataformas IIoT, de acordo com as necessidades específicas do negócio, reduzindo o investimento necessário para desenvolver este tipo de facilitadores I4.0, e; ii) por outro lado, fomentar o entendimento partilhado do IIoT, entre os especialistas do domínio e as organizações, promovendo o envolvimento de ambas as partes neste processo de especificação. Neste contexto, a semântica desempenha um papel importante, permitindo a acomodação do conhecimento multidisciplinar das arquiteturas IIoT num modelo semântico alavancado por capacidades de raciocínio. Esta solução foi avaliada num caso de estudo, em que a arquitetura produzida pela solução foi comparada, em termos de utilidade, com a arquitetura implementada. O resultado foi que a arquitetura produzida correspondia aos requisitos impostos, pelo que esta foi aprovada pelos especialistas do domínio do caso de estudo, validando a solução.IIoT (Industrial Internet-of-Things) platforms are an enabler for the digital transformation in the scope of industry 4.0, promoting flexibility for a faster adjustment to market and allowing organisations to have a clear vision over its current status. However, SMEs (Small and Medium Enterprises) are struggling to shift into this new paradigm, due to the lack of: i) qualified resources needed to develop and implement their digitalization solutions; ii) a clear understanding about the digitalisation reengineering related IIoT adoption, and; iii) suitable models for SME-oriented IIoT solutions specification. In order to overcome these challenges, a solution is discussed within a twofold perspective: i) on one hand, it looks for the automation of the specification of IIoT platform’s architectures, according to the specific business needs, reducing the investment needed to develop these kind of I4.0 digital enablers, and; ii) on the other hand, it fosters a shared understanding of the IIoT between the domain expert’s and the organisations, promoting the involvement of both parties in this specification process. In this context, semantics plays an impacting role, allowing the accommodation of the multidisciplinary knowledge of IIoT architectures in a semantic model leveraged by reasoning capabilities. This solution was evaluated in a case study, where the architecture produced by the solution was compared, utility wise, with the implemented architecture. The result was that the produced architecture matched the imposed requirements, and so, it was approved by the case study’s domain experts, validating the solution

A comprehensive survey on Fog Computing: State-of-the-art and research challenges

Cloud computing with its three key facets (i.e., Infrastructure-as-a-Service, Platform-as-a-Service, and Softwareas- a-Service) and its inherent advantages (e.g., elasticity and scalability) still faces several challenges. The distance between the cloud and the end devices might be an issue for latencysensitive applications such as disaster management and content delivery applications. Service level agreements (SLAs) may also impose processing at locations where the cloud provider does not have data centers. Fog computing is a novel paradigm to address such issues. It enables provisioning resources and services outside the cloud, at the edge of the network, closer to end devices, or eventually, at locations stipulated by SLAs. Fog computing is not a substitute for cloud computing but a powerful complement. It enables processing at the edge while still offering the possibility to interact with the cloud. This paper presents a comprehensive survey on fog computing. It critically reviews the state of the art in the light of a concise set of evaluation criteria. We cover both the architectures and the algorithms that make fog systems. Challenges and research directions are also introduced. In addition, the lessons learned are reviewed and the prospects are discussed in terms of the key role fog is likely to play in emerging technologies such as tactile Internet

Interconectando sensores com transparência numa rede de sensores sem fio segura dividida em clusters

Dissertação (mestrado) - Universidade Federal de Santa Catarina, Centro Tecnológico. Programa de Pós-Graduação em Ciência da ComputaçãoUma rede de sensores sem fio é uma coleção de dispositivos limitados em poder de processamento e alcance de transmissão, com baixa disponibilidade de memória e de energia. Devido a estas limitações, a maioria das soluções de segurança de redes cabeadas, tais como baseadas em ICP pura, não se aplicam diretamente neste tipo de ambiente. Este trabalho apresenta um protocolo híbrido que trata do esquema de gerenciamento de chaves e da interconexão transparente de clusters. Também é tratado o problema de captura de nós, oferecendo uma solução para a proteção da chave de grupo. Simulações mostram que aumentando o número de sensores na rede, o desempenho da comunicação entre dois clusters quaisquer permanece o mesm

Data Collection in Two-Tier IoT Networks with Radio Frequency (RF) Energy Harvesting Devices and Tags

The Internet of things (IoT) is expected to connect physical objects and end-users using technologies such as wireless sensor networks and radio frequency identification (RFID). In addition, it will employ a wireless multi-hop backhaul to transfer data collected by a myriad of devices to users or applications such as digital twins operating in a Metaverse. A critical issue is that the number of packets collected and transferred to the Internet is bounded by limited network resources such as bandwidth and energy. In this respect, IoT networks have adopted technologies such as time division multiple access (TDMA), signal interference cancellation (SIC) and multiple-input multiple-output (MIMO) in order to increase network capacity. Another fundamental issue is energy. To this end, researchers have exploited radio frequency (RF) energy-harvesting technologies to prolong the lifetime of energy constrained sensors and smart devices. Specifically, devices with RF energy harvesting capabilities can rely on ambient RF sources such as access points, television towers, and base stations. Further, an operator may deploy dedicated power beacons that serve as RF-energy sources. Apart from that, in order to reduce energy consumption, devices can adopt ambient backscattering communication technologies. Advantageously, backscattering allows devices to communicate using negligible amount of energy by modulating ambient RF signals. To address the aforementioned issues, this thesis first considers data collection in a two-tier MIMO ambient RF energy-harvesting network. The first tier consists of routers with MIMO capability and a set of source-destination pairs/flows. The second tier consists of energy harvesting devices that rely on RF transmissions from routers for energy supply. The problem is to determine a minimum-length TDMA link schedule that satisfies the traffic demand of source-destination pairs and energy demand of energy harvesting devices. It formulates the problem as a linear program (LP), and outlines a heuristic to construct transmission sets that are then used by the said LP. In addition, it outlines a new routing metric that considers the energy demand of energy harvesting devices to cope with routing requirements of IoT networks. The simulation results show that the proposed algorithm on average achieves 31.25% shorter schedules as compared to competing schemes. In addition, the said routing metric results in link schedules that are at most 24.75% longer than those computed by the LP

Smart Monitoring and Control in the Future Internet of Things

The Internet of Things (IoT) and related technologies have the promise of realizing pervasive and smart applications which, in turn, have the potential of improving the quality of life of people living in a connected world. According to the IoT vision, all things can cooperate amongst themselves and be managed from anywhere via the Internet, allowing tight integration between the physical and cyber worlds and thus improving efficiency, promoting usability, and opening up new application opportunities. Nowadays, IoT technologies have successfully been exploited in several domains, providing both social and economic benefits. The realization of the full potential of the next generation of the Internet of Things still needs further research efforts concerning, for instance, the identification of new architectures, methodologies, and infrastructures dealing with distributed and decentralized IoT systems; the integration of IoT with cognitive and social capabilities; the enhancement of the sensing–analysis–control cycle; the integration of consciousness and awareness in IoT environments; and the design of new algorithms and techniques for managing IoT big data. This Special Issue is devoted to advancements in technologies, methodologies, and applications for IoT, together with emerging standards and research topics which would lead to realization of the future Internet of Things

Concevoir des applications internet des objets sémantiques

According to Cisco's predictions, there will be more than 50 billions of devices connected to the Internet by 2020.The devices and produced data are mainly exploited to build domain-specific Internet of Things (IoT) applications. From a data-centric perspective, these applications are not interoperable with each other.To assist users or even machines in building promising inter-domain IoT applications, main challenges are to exploit, reuse, interpret and combine sensor data.To overcome interoperability issues, we designed the Machine-to-Machine Measurement (M3) framework consisting in:(1) generating templates to easily build Semantic Web of Things applications, (2) semantically annotating IoT data to infer high-level knowledge by reusing as much as possible the domain knowledge expertise, and (3) a semantic-based security application to assist users in designing secure IoT applications.Regarding the reasoning part, stemming from the 'Linked Open Data', we propose an innovative idea called the 'Linked Open Rules' to easily share and reuse rules to infer high-level abstractions from sensor data.The M3 framework has been suggested to standardizations and working groups such as ETSI M2M, oneM2M, W3C SSN ontology and W3C Web of Things. Proof-of-concepts of the flexible M3 framework have been developed on the cloud (http://www.sensormeasurement.appspot.com/) and embedded on Android-based constrained devices.Selon les prévisions de Cisco , il y aura plus de 50 milliards d'appareils connectés à Internet d'ici 2020. Les appareils et les données produites sont principalement exploitées pour construire des applications « Internet des Objets (IdO) ». D'un point de vue des données, ces applications ne sont pas interopérables les unes avec les autres. Pour aider les utilisateurs ou même les machines à construire des applications 'Internet des Objets' inter-domaines innovantes, les principaux défis sont l'exploitation, la réutilisation, l'interprétation et la combinaison de ces données produites par les capteurs. Pour surmonter les problèmes d'interopérabilité, nous avons conçu le système Machine-to-Machine Measurement (M3) consistant à: (1) enrichir les données de capteurs avec les technologies du web sémantique pour décrire explicitement leur sens selon le contexte, (2) interpréter les données des capteurs pour en déduire des connaissances supplémentaires en réutilisant autant que possible la connaissance du domaine définie par des experts, et (3) une base de connaissances de sécurité pour assurer la sécurité dès la conception lors de la construction des applications IdO. Concernant la partie raisonnement, inspiré par le « Web de données », nous proposons une idée novatrice appelée le « Web des règles » afin de partager et réutiliser facilement les règles pour interpréter et raisonner sur les données de capteurs. Le système M3 a été suggéré à des normalisations et groupes de travail tels que l'ETSI M2M, oneM2M, W3C SSN et W3C Web of Things. Une preuve de concept de M3 a été implémentée et est disponible sur le web (http://www.sensormeasurement.appspot.com/) mais aussi embarqu