DOCSLIB.ORG

Real-Time Control Over Wireless Networks

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Real-Time Control Over Wireless Networks REAL-TIME CONTROL OVER WIRELESS NETWORKS by VENKATA PRASHANT MODEKURTHY DISSERTATION Submitted to the Graduate School of Wayne State University, Detroit, Michigan in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY 2020 MAJOR: COMPUTER SCIENCE Approved By: Advisor Date arXiv:2011.03169v1 [cs.NI] 6 Nov 2020 DEDICATION To Venkata Sita Rama Murthy Modekurthy, Vijaya Kumari Modekurthy, Venkata Pavan Kumar Modekurthy, and Kalianne Kinsey Modekurthy. ii ACKNOWLEDGEMENTS I would like to sincerely thank my advisor, Dr. Abusayeed Saifullah, for his guidance, cooper- ation, ideas and most-importantly time. I would not be graduating if not for his advice over the last 5 years. I extend my thanks to my co-advisor Dr. Sanjay Madria for his guidance and motivation. I would like to thank Dr. Nathan Fisher, Dr. Zhishan Guo, and Dr. Marco Brocanelli with whom I had wonderful opportunities for collaboration. These collaborations have made my Ph.D. experience productive and inspiring. I would also like to thank my lab mates from the CRI lab at Wayne State University and then Advanced Networking Lab at Missouri S&T. My hearty gratitude for Dr. Corey Tessler and Dr. Amartya Sen for both the personal and professional time which lead to stimulating discussions and collaborations. I am greatly indebted to the the faculty members and staff at both Wayne State for their helping hands in every step of my Ph.D. and notably for making the transfer from Missouri S&T effortless. Most importantly, I would like to thank my parents and wife for their perpetual support and love. I acknowledge the financial support from Dr. Abusayeed Saifullah and Dr. Sanjay Madria in the form of research assistantship through NSF grants, and from Department of Computer Science at Wayne State in the form of research assistantship from internal grants and teaching assistantship. Last but not least, I thank all committee members for their time, suggestions, and service. iii TABLE OF CONTENTS Dedication . ii Acknowledgements . iii List of Tables . x List of Figures . xi Chapter 1 Introduction . 1 Chapter 2 Distributed Graph Routing for WirelessHART Networks . 4 2.1 Introduction . 5 2.2 Related Work . 8 2.3 Network Model . 9 2.4 An Overview of Graph Routing . 11 2.5 Distributed Graph Routing . 12 2.5.1 Protocol Description . 14 2.5.2 Example . 17 2.6 Theoretical Analysis . 19 2.6.1 Convergence and Sub-optimality . 19 2.6.2 Performance Analysis . 20 2.7 Evaluation . 23 2.7.1 Experiment . 23 iv 2.7.2 Simulation Setup . 25 2.7.3 Simulation Results . 26 2.8 Summary . 36 Chapter 3 A Distributed Real-Time Scheduling System for Industrial Wireless Networks . 38 3.1 Introduction . 39 3.2 Related Work . 42 3.3 Background and System Model . 44 3.4 The Design of DistributedHART . 47 3.4.1 Distributed Scheduling . 48 3.4.2 Scheduling Policy . 55 3.4.3 Online Scheduling as Dedicated and Shared Slots . 56 3.5 End-to-end Delay Analysis for DistributedHART . 60 3.6 Non-Uniform Time Window Assignment in DistributedHART . 67 3.6.1 Algorithm to Select Non-Uniform Time Window Length . 67 3.6.2 Non-Uniform Time Window Allocation: . 68 3.6.3 End-to-End Delay Analysis for Non-Uniform Time Window Assignment . 69 3.6.4 Performance Evaluation of Non-Uniform Time Window Assignment . 70 3.7 Latency under DistributedHART . 71 3.8 Testbed Experiments . 75 3.8.1 Evaluation Metrics . 75 3.8.2 Results . 76 v 3.9 Simulation . 79 3.9.1 Simulation Setup . 79 3.9.2 Performance under Varying Window Lengths . 80 3.9.3 Performance under Varying Number of Control Loops considering Har- monic Periods . 81 3.9.4 Performance under Varying Number of Control Loops considering Non- Harmonic Periods . 83 3.9.5 Performance under Varying Number of Nodes . 85 3.9.6 Performance under Varying Hyper-Periods . 87 3.9.7 Performance under Varying Workload Dynamics . 88 3.9.8 Performance of End-to-End Delay Analysis . 90 3.9.9 Comparison in terms of Percentage of Idle Slots . 91 3.9.10 Performance Comparison between DistributedHART and Centralized Sched- uler with Compact Schedules . 93 3.10 Summary . 94 Chapter 4 Low-Latency In-Band Integration of Multiple Low-Power Wide-Area Networks 95 4.1 Introduction . 96 4.2 The SNOW Architecture . 100 4.3 Integrating Multiple SNOWs: An Overview of the Proposed Approach . 101 4.3.1 Related Work and New Challenges . 104 4.3.2 Formulation . 104 4.4 Description of the Low-Latency Integration of Multiple SNOWs . 108 vi 4.4.1 Deriving an Expression of Latency . 109 4.4.2 Deriving a Latency Expression for a special case . 120 4.4.3 Latency and Traffic aware Spectrum Allocation for SNOW Integration (LT- SASI) . 121 4.5 Experiment . 123 4.6 Simulation . 125 4.6.1 Maximum and Average Latencies for Each SNOW . 126 4.6.2 Performance of LT-SASI under Scalability of Number of Nodes . 127 4.6.3 Performance of LT-SASI under Scalability of Number of Base Station . 128 4.7 Summary . 129 Chapter 5 A Utilization-Based Approach for Schedulability Analysis in Wireless Control Systems . 131 5.1 Introduction . 132 5.2 Background . 134 5.3 Related Work . 135 5.4 System Model . 136 5.5 Problem Formulation . 138 5.6 Utilization-Based Schedulability Analysis . 139 5.6.1 Establishing a Utilization Bound Analysis . 139 5.6.2 Transmission Conflict Delay Computation . 143 5.7 Extending the Utilization Bound Analysis to Graph Routing and Hierarchical Net- working . 146 vii 5.7.1 Transmission Conflict Delay Computation for Graph Routing Algorithms . 147 5.7.2 Adopting the Utilization Based Analysis through Hierarchical Networking . 151 5.8 Evaluation . 153 5.8.1 Simulation Setup . 153 5.8.2 Results . 154 5.9 Summary . 157 Chapter 6 Online Period Selection for Wireless Control Systems . 158 6.1 Introduction . 159 6.2 Related Work . 162 6.3 System Model . 163 6.3.1 Network Model . 163 6.3.2 Control System Model . 164 6.4 Link Quality Based Autonomous Scheduler . 166 6.4.1 Link Quality Prediction . 167 6.4.2 Game Formulation for Autonomous Scheduler . 169 6.4.3 Single Time Slot Game . 171 6.4.4 Multiple Time Slot Game . 173 6.4.5 Schedulability Analysis . 174 6.5 Online Sampling Period Selection . 175 6.5.1 Formulation of a Centralized Online Sampling Period Selection Problem . 175 6.5.2 Sampling Period Acclimation . 176 viii 6.5.3 Initial Sampling Period Assignment . 178 6.5.4 State Estimation and Correction . 179 6.5.5 Segregating the Flows . ..
Load more

Recommended publications
  • A DASH7-Based Power Metering System
    A DASH7-based Power Metering System Oktay Cetinkaya Ozgur B. Akan Next-generation and Wireless Communications Laboratory Department of Electrical and Electronics Engineering Koc University, Istanbul, Turkey Email: fokcetinkaya13, [email protected] Abstract—Considering the inability of the existing energy non-embedded structure. When considering the cost of HEMS, resources to satisfy the current needs, the right and efficient use power meters can be defined as cheap and cost effective of the energy has become compulsory. To make energy sustain- products, undoubtedly. ability permanent, management and planning activities should be carried out by arranging the working hours and decreasing There are several wireless communication protocols in liter- the energy wasting. For all these, power metering, managing ature to actualize the remote control of plugged gadgets. The and controlling systems or plugs has been proposed in recent communication between ‘master and slave’ or equivalently efforts. Starting from this point, a new DASH7-based Smart Plug ‘user and device’ is realized over any of these wireless (D7SP) is designed and implemented to achieve a better structure communication protocols based modules. 2.4 GHz frequency compared to ZigBee equipped models and reduce the drawbacks of current applications. DASH7 technology reaches nearly 6 times is frequently preferred for this goal and ZigBee can be referred farther distances in comparison with 2.4 GHz based protocols and as the most popular member of this band. With a brief provides multi-year battery life as a result of using limited energy definition, ZigBee is a low cost and high reliable technology during transmission. Performing in the 433 MHz band prevents based on IEEE 802.15.4 [1].
    [Show full text]
  • Internet of Underground Things in Precision Agriculture: Architecture and Technology Aspects Mehmet C
    University of Nebraska - Lincoln DigitalCommons@University of Nebraska - Lincoln CSE Journal Articles Computer Science and Engineering, Department of 2018 Internet of underground things in precision agriculture: Architecture and technology aspects Mehmet C. Vuran University of Nebraska-Lincoln, [email protected] Abdul Salam Purdue University, [email protected] Rigoberto Wong University of Nebraska-Lincoln, [email protected] Suat Irmak University of Nebraska - Lincoln, [email protected] Follow this and additional works at: https://digitalcommons.unl.edu/csearticles Part of the Bioresource and Agricultural Engineering Commons, Computer and Systems Architecture Commons, Operations Research, Systems Engineering and Industrial Engineering Commons, and the Robotics Commons Vuran, Mehmet C.; Salam, Abdul; Wong, Rigoberto; and Irmak, Suat, "Internet of underground things in precision agriculture: Architecture and technology aspects" (2018). CSE Journal Articles. 189. https://digitalcommons.unl.edu/csearticles/189 This Article is brought to you for free and open access by the Computer Science and Engineering, Department of at DigitalCommons@University of Nebraska - Lincoln. It has been accepted for inclusion in CSE Journal Articles by an authorized administrator of DigitalCommons@University of Nebraska - Lincoln. digitalcommons.unl.edu Internet of underground things in precision agriculture: Architecture and technology aspects Mehmet C. Vuran,1 Abdul Salam,2 Rigoberto Wong,1 and Suat Irmak 3 1 Cyber-physical Networking Laboratory, Computer Science and Engineering, University of Nebraska–Lincoln, Lincoln, NE, USA 2 Department of Computer and Information Technology, Purdue University, West Lafayette, IN 47907, USA 3 Department of Biological Systems Engineering, University of Nebraska–Lincoln, Lincoln, NE 68583, USA Corresponding author — A. Salam, [email protected] Email addresses: [email protected] (M.C.
    [Show full text]
  • A Changing Landscape: the Internet of Things (Iot)
    A Changing Landscape: the Internet of Things (IoT) Prof Sanjay Jha Deputy Director, Australian Center for Cyber Security, UNSW Director of Cyber Security and Privacy Laboratory, School of Computer Science and Engineering University Of New South Wales [email protected] http://www.cse.unsw.edu.au/~sanjay SecureCanberra@MilCIS 2014, Australia 13th Nov 2014 Internet of Things • Connected devices • Smoke alarms, light bulbs, power switches, motion sensors, door locks etc. 2 Outline • Introduction to IoT • History of IoT (and M2M) and Wireless Sensor Networks • Security Challenges in IoT • Sample Research Projects at UNSW History (IoT) • Early 90s or prior: SCADA systems, Telemetry applications • Late 90s- Products/services from mobile operators (Siemens) to connect devices via cellular network – Primarily automotive telematics • Mid- 2000s – Many tailored products for logistics, fleet management, car safety, healthcare, and smart metering of electricity consumption • Since 2010 – A large number of consortiums mushrooming up to bid for a large market share – ABI Projects US$198M by 2018 – Berg Insight US$187M by 2014…… History of Wireless Sensor Net • 1999: Kahn, Katz,Pister: Vision for Smart Dust • 2002 Sensys CFP: Wireless Sensor Network research as being composed of ”distributed systems of numerous smart sensors and actuators connecting computational capabilities to the physical world have the potential to revolutionise a wide array of application areas by providing an unprecedented density and fidelity of instrumentation”. Typical Application Roadmap to IoT • Supply Chain Applications – Routing, inventory, loss prevention. • Vertical Market Helpers – Healthcare, Transport, Energy, Agriculture, Security, Home Network. • Ubiquitous Position – Location of people and objects and possible tailored services • Teleoperations/Telepresence - Ability to interact/control with remote objects.
    [Show full text]
  • Wireless Sensor Networks
    White Paper ® Internet of Things: Wireless Sensor Networks Executive summary Today, smart grid, smart homes, smart water Section 2 starts with the historical background of networks, intelligent transportation, are infrastruc- IoT and WSNs, then provides an example from the ture systems that connect our world more than we power industry which is now undergoing power ever thought possible. The common vision of such grid upgrading. WSN technologies are playing systems is usually associated with one single con- an important role in safety monitoring over power cept, the internet of things (IoT), where through the transmission and transformation equipment and use of sensors, the entire physical infrastructure is the deployment of billions of smart meters. closely coupled with information and communica- Section 3 assesses the technology and charac- tion technologies; where intelligent monitoring and teristics of WSNs and the worldwide application management can be achieved via the usage of net- needs for them, including data aggregation and worked embedded devices. In such a sophisticat- security. ed dynamic system, devices are interconnected to transmit useful measurement information and con- Section 4 addresses the challenges and future trol instructions via distributed sensor networks. trends of WSNs in a wide range of applications in various domains, including ultra large sensing A wireless sensor network (WSN) is a network device access, trust security and privacy, and formed by a large number of sensor nodes where service architectures to name a few. each node is equipped with a sensor to detect physical phenomena such as light, heat, pressure, Section 5 provides information on applications. etc. WSNs are regarded as a revolutionary The variety of possible applications of WSNs to the information gathering method to build the real world is practically unlimited.
    [Show full text]
  • Security Vulnerabilities in Lpwans—An Attack Vector Analysis for the Iot Ecosystem
    applied sciences Article Security Vulnerabilities in LPWANs—An Attack Vector Analysis for the IoT Ecosystem Nuno Torres 1 , Pedro Pinto 1,2,3 and Sérgio Ivan Lopes 1,4,* 1 ADiT—Instituto Politécnico de Viana do Castelo, 4900-347 Viana do Castelo, Portugal; [email protected] (N.T.); [email protected] (P.P.) 2 Instituto Universitário da Maia, 4475-690 Maia, Portugal 3 INESC TEC, 4200-465 Porto, Portugal 4 IT—Instituto de Telecomunicações, Campus Universitário de Santiago, 3810-193 Aveiro, Portugal * Correspondence: [email protected] Abstract: Due to its pervasive nature, the Internet of Things (IoT) is demanding for Low Power Wide Area Networks (LPWAN) since wirelessly connected devices need battery-efficient and long-range communications. Due to its low-cost and high availability (regional/city level scale), this type of network has been widely used in several IoT applications, such as Smart Metering, Smart Grids, Smart Buildings, Intelligent Transportation Systems (ITS), SCADA Systems. By using LPWAN technologies, the IoT devices are less dependent on common and existing infrastructure, can operate using small, inexpensive, and long-lasting batteries (up to 10 years), and can be easily deployed within wide areas, typically above 2 km in urban zones. The starting point of this work was an overview of the security vulnerabilities that exist in LPWANs, followed by a literature review with the main goal of substantiating an attack vector analysis specifically designed for the IoT ecosystem. This methodological approach resulted in three main contributions: (i) a systematic review regarding cybersecurity in LPWANs with a focus on vulnerabilities, threats, and typical defense strategies; (ii) a Citation: Torres, N.; Pinto, P.; Lopes, state-of-the-art review on the most prominent results that have been found in the systematic review, S.L.
    [Show full text]
  • Overview and Measurement of Mobility in DASH7 Wael Ayoub, Fabienne Nouvel, Abed Ellatif Samhat, Jean-Christophe Prévotet, Mohamad Mroue
    Overview and Measurement of Mobility in DASH7 Wael Ayoub, Fabienne Nouvel, Abed Ellatif Samhat, Jean-Christophe Prévotet, Mohamad Mroue To cite this version: Wael Ayoub, Fabienne Nouvel, Abed Ellatif Samhat, Jean-Christophe Prévotet, Mohamad Mroue. Overview and Measurement of Mobility in DASH7. 2018 25th International Conference on Telecommu- nications (ICT), Jun 2018, St. Malo, France. pp.532-536, 10.1109/ICT.2018.8464846. hal-01991725 HAL Id: hal-01991725 https://hal.archives-ouvertes.fr/hal-01991725 Submitted on 4 Feb 2019 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Overview and Measurement of Mobility in DASH7 Wael Ayoub∗y, Fabienne Nouvel∗, Abed Ellatif Samhaty, Jean-christophe Prevotet´ ∗,and Mohamad Mrouey ∗Institut National des Sciences Appliquees´ de Rennes — IETR-INSA, Rennes, France. y Faculty of Engineering - CRSI, Lebanese University, Hadath Campus, Hadath, Lebanon Email∗: fi[email protected] Emaily: [email protected], [email protected] Abstract—Recently, the evolution of low-power wide area net- TABLE I works (LPWANs) provides Internet of Things (IoT) with an D7A PROTOCOL SPECIFICATIONS approach between the short range multi-hop technology and the long-range single-hop cellular network technology.
    [Show full text]
  • Networking Layer Protocols for Internet of Things: 6Lowpan And
    NetworkingNetworking LayerLayer ProtocolsProtocols forfor InternetInternet ofof Things:Things: . 6LoWPAN6LoWPAN andand RPLRPL Raj Jain Washington University in Saint Louis Saint Louis, MO 63130 [email protected] These slides and audio/video recordings of this class lecture are at: http://www.cse.wustl.edu/~jain/cse570-15/ Washington University in St. Louis http://www.cse.wustl.edu/~jain/cse570-15/ ©2015 Raj Jain 13-1 OverviewOverview 6LowPAN Adaptation Layer Address Formation Compression RPL RPL Concepts RPL Control Messages RPL Data Forwarding Note: This is part 3 of a series of class lectures on IoT. Washington University in St. Louis http://www.cse.wustl.edu/~jain/cse570-15/ ©2015 Raj Jain 13-2 IoTIoT EcosystemEcosystem Applications Smart Health, Smart Home, Smart Grid Security Management Smart Transport, Smart Workspaces, … TCG, Session MQTT, CoRE, DDS, AMQP , … IEEE 1905, Oath 2.0, IEEE 1451, Routing 6LowPAN, RPL, 6Lo, 6tsch, Thread, SMACK, … 6-to-nonIP , … SASL, ISASecure, Datalink WiFi, Bluetooth Smart, Zigbee Smart, ace, Z-Wave, DECT/ULE, 3G/LTE, NFC, CoAP, Weightless, HomePlug GP, 802.11ah, DTLS, 802.15.4, G.9959, WirelessHART, Dice DASH7, ANT+ , LoRaWAN, … Software Mbed, Homekit, AllSeen, IoTvity, ThingWorks, EVRYTHNG , … Operating Systems Linux, Android, Contiki-OS, TinyOS, … Hardware ARM, Arduino, Raspberry Pi, ARC-EM4, Mote, Smart Dust, Tmote Sky, … Washington University in St. Louis http://www.cse.wustl.edu/~jain/cse570-15/ ©2015 Raj Jain 13-3 IEEEIEEE 802.15.4802.15.4 Wireless Personal Area Network (WPAN) Allows mesh networking. Full function nodes can forward packets to other nodes. A PAN coordinator (like WiFi Access Point) allows nodes to join the network.
    [Show full text]
  • LPWAN Technologies: Emerging Application Characteristics, Requirements, and Design Considerations
    future internet Review LPWAN Technologies: Emerging Application Characteristics, Requirements, and Design Considerations Bharat S. Chaudhari *,1, Marco Zennaro 2 and Suresh Borkar 3 1 School of Electronics and Communication Engineering, MIT World Peace University, Pune 411038, India 2 Telecommunications/ICT4D Laboratory, The Abdus Salam International Centre for Theoretical Physics, Strada Costiera, 11-I-34151 Trieste, Italy; [email protected] 3 Department of Electrical and Computer Engineering, Illinois Institute of Technology, Chicago, IL 60616, USA; [email protected] * Correspondence: [email protected] Received: 7 January 2020; Accepted: 4 March 2020; Published: 6 March 2020 Abstract: Low power wide area network (LPWAN) is a promising solution for long range and low power Internet of Things (IoT) and machine to machine (M2M) communication applications. This paper focuses on defining a systematic and powerful approach of identifying the key characteristics of such applications, translating them into explicit requirements, and then deriving the associated design considerations. LPWANs are resource-constrained networks and are primarily characterized by long battery life operation, extended coverage, high capacity, and low device and deployment costs. These characteristics translate into a key set of requirements including M2M traffic management, massive capacity, energy efficiency, low power operations, extended coverage, security, and interworking. The set of corresponding design considerations is identified in terms of two categories, desired or expected ones and enhanced ones, which reflect the wide range of characteristics associated with LPWAN-based applications. Prominent design constructs include admission and user traffic management, interference management, energy saving modes of operation, lightweight media access control (MAC) protocols, accurate location identification, security coverage techniques, and flexible software re-configurability.
    [Show full text]
  • Handling Mobility in Low-Power Wide-Area Network
    Handling Mobility in Low-Power Wide-Area Network Dali Ismail Abusayeed Saifullah Department of Computer Science Department of Computer Science Wayne State University Wayne State University Detroit, Michigan, USA Detroit, Michigan, USA Abstract offering long-range (several miles), low-power, and low- Despite the proliferation of mobile devices in various cost communication [22]. With the fast growth of IoT, wide-area Internet of Things applications (e.g., smart city, multiple LPWAN technologies have emerged recently such smart farming), current Low-Power Wide-Area Networks as LoRa [24, 13], SigFox [46], IQRF [20], RPMA [19], (LPWANs) are not designed to effectively support mobile DASH7 [9], Weightless-N/P [53], Telensa [1] in the ISM nodes. In this paper, we propose to handle mobility in band, and EC-GSM-IoT [17], NB-IoT [33], and LTE Cat SNOW (Sensor Network Over White spaces), an LPWAN M1 [26, 25] in the licensed cellular band. To avoid the that operates in the TV white spaces. SNOW supports mas- crowd in the limited ISM band and the cost of licensed band, sive concurrent communication between a base station (BS) SNOW (Sensor Network Over White spaces) is an LPWAN and numerous low-power nodes through a distributed im- architecture to support scalable wide-area IoT over the TV plementation of OFDM. In SNOW, inter-carrier interference white spaces [44, 42, 43]. White spaces are the allocated (ICI) is more pronounced under mobility due to its OFDM but locally unused TV spectrum (54 - 698 MHz in the US) based design. Geospatial variation of white spaces also [34, 35].
    [Show full text]
  • M2M Protocols, Solutions and Platforms for Smart Home Environments Integrating C.STATUSTM and the Mediasense
    M2M Protocols, Solutions and Platforms for Smart Home Environments Integrating C.STATUSTM and the MediaSense 10/12/2012 MID SWEDEN UNIVERSITY The Department of Information Technology and Media (ITM) Author: Addisu Thomas Lodamo, [email protected] Tutors: Stefan Forsström, Miun,[email protected] Examiner: Prof. Tingting Zhang, [email protected] Medical Monitoring Services Home Security automation Services Services Energy Entertainment Consumption Services services e y t a a W G The Internet M.Sc. Thesis within Computer Engineering AV, 30 Credit Points M2M Protocols, Solutions and Platforms for Smart Home Environments Integrating C.STATUSTM and the MediaSense Addisu Lodamo M2M Protocols, Solutions and Platforms for Smart Home Environments Abstract Addisu Lodamo 2012-11-11 Abstract Digital technological breakthroughs have brought about a huge change in the way the society interacts, responds to the immediate environment and the way that people live. Furthermore, Ubiquitous Computing and dirt cheap sensors have created a new paradigm in digital technology where human beings could control their environment in a different approach. In a number of paradigms of digital technology, multiple proprietary solutions in industry results in a huge cost for the end users to use the technology and thus a very sluggish penetration of the tech- nology into the society. Moreover, such unorganized and vendor ori- ented standards create additional burdens on a person concerned in design and implementation. This thesis presents existing and emerging technologies in relation to smart home environment having an aim to manifest available open standards and platforms. Smart Home Envi- ronment Infrastructures have been presented and discussed.
    [Show full text]
  • Introduction to Wireless Technologies
    An Introduction to Wireless Systems – Overview (Part 1) Dr. Farid Farahmand Updated: 9/8/14 Outline o Evolution of wireless technology o Frequency spectrum allocation o Wireless Network Categorization o Wireless Network Technologies Why Go Wireless? Evolution of Wireless RF Technology EM Wave o Practical telecom started with telegraph and Morse code (1837) n tele (τηλε) = far and graphein (γραφειν) = write n Morse code is a type of character encoding that transmits telegraphic information using rhythm. n Created for Samuel F. B. Morse's electric telegraph in the early 1840s o The invention of telephone (1876) later resulted in first switched network n Read The Telephone Gambit by Seth Shulman! o Heinrich Hertz for the first time proved the existence of electromagnetic waves through lab experiment (1887) n RF signals ride on EM waves! o Two major events had critical impact on wireless technology development n Sinking Titanic! n WWII – radar technology and FM o Commercialization of 1-way/2-way radio o Cellular technology in 1970 Wireless Telegraph o The first wireless telegraph goes back to 1872 by Mahlon Loomis (the Dentist) n First to use a complete antenna and ground system n First experimental transmission of wireless telegraph signals. n The first use of balloons to raise an antenna wire. n Formulation of the idea of ‘waves’ traveling out from his antenna. n The first Patent for wireless telegraphy. o Between 1895-1901 Marconi experimented with wireless telegraph systems n In 1901 he was able to send a character wirelessly over 1,600m across the Atlantic ocean n At the time there was no antenna concept or digital systems or even vacuum tube or http://www.smecc.org/mhlon_loomis.htm Wireless Continuous Waves o In 1905 Fessenden in Mass.
    [Show full text]
  • Deployment of Tinyos for Online Water Sensing
    TELKOMNIKA Indonesian Journal of Electrical Engineering Vol.12, No.6, June 2014, pp. 4802 ~ 4807 DOI: 10.11591/telkomnika.v12i6.5525 4802 Deployment of TinyOS for Online Water Sensing Xin Wang*, Pan Xu Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education), Jiangnan University, Wuxi 214122, PR China *Corresponding author, e-mail: [email protected] Abstract Current quality assessment methods of water parameters are mainly laboratory based, require fresh supplies of chemicals, trained staff and are time consuming. Sensor networks are great alternatives for such requirements. We present a practical application of wireless networks: a remote water monitoring system running TinyOS. The contents of several chemicals in the water are sensed and transmitted. The sensor data are collected and transmitted via ZigBee and GPRS. Instead of focusing on theoretic issues such as routing algorithms, network lifetime and so on, we investigate special techniques involved in the implementation of the system while employing TinyOS and its special programming language. Keywords: TinyOS, hierarchical network, embedded operating system, water sensing 1. Introduction TinyOS is an open source, BSD-licensed operating system designed for low-power wireless devices, such as those used in sensor networks, ubiquitous computing, personal area networks, smart buildings, and smart meters. To confront the water pollution, various water monitoring systems based on cellular mobile network have been developed [1, 2]. These systems may assist environmental protection agencies in providing continuous water monitoring with minimum interaction of man interference. But, with such systems, the rare channel resources and hardware are greatly wasted when the monitoring nodes are distributed in higher density.
    [Show full text]