Shared Sensor Networks Fundamentals, Challenges, Opportunities, Virtualization Techniques, Comparative Analysis, Novel Architecture and Taxonomy
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A Comparative Study on Operating System for Wireless Sensor Networks
ICACSIS 2011 ISBN: 978-979-1421-11-9 A Comparative Study on Operating System for Wireless Sensor Networks Thang Vu Chien, Hung Nguyen Chan, and Thanh Nguyen Huu Thai Nguyen University of Information and Communication Technology Quyet Thang Commune, Thai Nguyen City, Vietnam E-mail: [email protected], [email protected], [email protected] Abstract—Wireless Sensor Networks (WSNs) them work correctly and effectively without a conflict have been the subject of intensive research over the in support of the specific applications for which they last years. WSNs consist of a large number of are designed. Each sensor node needs an OS that can sensor nodes, and are used for various applications control the hardware, provide hardware abstraction to such as building monitoring, environment control, application software, and fill in the gap between wild-life habitat monitoring, forest fire detection, applications and the underlying hardware. industry automation, military, security, and health- The basic functionalities of an OS include resource care. Operating system (OS) support for WSNs abstractions for various hardware devices, interrupt plays a central role in building scalable distributed management and task scheduling, concurrency control, applications that are efficient and reliable. Over and networking support. Based on the services the years, we have seen a variety of operating provided by the OS, application programmers can systems (OSes) emerging in the sensor network conveniently use high-level application programming community to facilitate developing WSN interfaces (APIs) independent of the underlying applications. In this paper, we present OS for WSNs. We begin by presenting the major issues for hardware. -
Key Infection: Smart Trust for Smart Dust
Key Infection: Smart Trust for Smart Dust Ross Anderson Haowen Chan Adrian Perrig University of Cambridge Carnegie Mellon University Carnegie Mellon University [email protected] [email protected] [email protected] Abstract and building safety. As sensor networks become cheaper and more commoditised, they will become attractive to Future distributed systems may include large self- home users and small businesses, and for other new appli- organizing networks of locally communicating sen- cations. sor nodes, any small number of which may be sub- A typical sensor network consists of a large number of verted by an adversary. Providing security for these small, low-cost nodes that use wireless peer-to-peer com- sensor networks is important, but the problem is compli- munication to form a self-organized network. They use cated by the fact that managing cryptographic key ma- multi-hop routing algorithms based on dynamic network terial is hard: low-cost nodes are neither tamper-proof and resource discovery protocols. To keep costs down and nor capable of performing public key cryptography effi- to deal with limited battery energy, nodes have fairly min- ciently. imal computation, communication, and storage resources. In this paper, we show how the key distribution problem They do not have tamper-proof hardware. We can thus ex- can be dealt with in environments with a partially present, pect that some small fraction of nodes in a network may be passive adversary: a node wishing to communicate securely compromised by an adversary over time. with other nodes simply generates a symmetric key and An interesting example of a sensor network technology sends it in the clear to its neighbours. -
Tinyos Meets Wireless Mesh Networks
TinyOS Meets Wireless Mesh Networks Muhammad Hamad Alizai, Bernhard Kirchen, Jo´ Agila´ Bitsch Link, Hanno Wirtz, Klaus Wehrle Communication and Distributed Systems, RWTH Aachen University, Germany [email protected] Abstract 2 TinyWifi We present TinyWifi, a nesC code base extending TinyOS The goal of TinyWifi is to enable direct execution of to support Linux powered network nodes. It enables devel- TinyOS applications and protocols on Linux driven network opers to build arbitrary TinyOS applications and protocols nodes with no additional effort. To achieve this, the Tiny- and execute them directly on Linux by compiling for the Wifi platform extends the existing TinyOS core to provide new TinyWifi platform. Using TinyWifi as a TinyOS plat- the exact same hardware independent functionality as any form, we expand the applicability and means of evaluation of other platform (see Figure 1). At the same time, it exploits wireless protocols originally designed for sensornets towards the customary advantages of typical Linux driven network inherently similar Linux driven ad hoc and mesh networks. devices such as large memory, more processing power and higher communication bandwidth. In the following we de- 1 Motivation scribe the architecture of each component of our TinyWifi Implementation. Although different in their applications and resource con- straints, sensornets and Wi-Fi based multihop networks share 2.1 Timers inherent similarities: (1) They operate on the same frequency The TinyOS timing functionality is based on the hardware band, (2) experience highly dynamic and bursty links due to timers present in current microcontrollers. A sensor-node radio interferences and other physical influences resulting in platform provides multiple realtime hardware timers to spe- unreliable routing paths, (3) each node can only communi- cific TinyOS components at the HAL layer - such as alarms, cate with nodes within its radio range forming a mesh topol- counters, and virtualization. -
Overview of Wireless Sensor Network (WSN) Security
Overview of Wireless Sensor Network (WSN) Security Aparicio Carranza Heesang Kim Xiao Lin Chen NYC College of Technology NYC College of Technology NYC College of Technology 186 Jay Street – V626 186 Jay Street 186 Jay Street Brooklyn, NY, USA Brooklyn, NY, USA Brooklyn NY, USA 718 – 260 – 5897 703 – 232 – 2001 917 – 285 - 5155 [email protected] [email protected] xiaolin,[email protected] ABSTRACT of different transmission schemes, allowing the connection Our civilization has entered an era of big data networking. to be made between different models. A router is a good Massive amounts of data is being converted into bits for example of a gateway. There are two common Wireless transmitting over the Internet and shared all over the world network topologies commonly used in WSN systems, they every second. The concept of “smart” devices has are “relay nodes” and “leaf nodes”. The relay network is a conquered preconceived notions of daily routines. broad network topology where the source and destination Smartphones and wearable device technologies have made are interconnected through some node. In these networks, humans to be continuously interconnected, making distance the source and destination cannot communicate directly a factor of no limitation. “Smart” systems are based on a with each other because the distance between the source single concept called the Internet of Things (IoT). IoT is a and destination is greater than the transmission range, due web of wirelessly networked devices embedded with to this an intermediate node needs to relay. The advantage electronic components and sensors that monitors physical of using the relay nodes is that the information can travel and environmental conditions and acquires data to be long distances even when the caller and recipient are far shared with other systems. -
Contemporary Developments in Wireless Sensor Networks
I.J.Modern Education and Computer Science, 2012, 3, 1-13 Published Online April 2012 in MECS (http://www.mecs-press.org/) DOI: 10.5815/ijmecs.2012.03.01 Contemporary Developments in Wireless Sensor Networks Sangeeta Mittal Department of Computer Science & Information Technology, Jaypee Institute of Information Technology, Noida, India Email: [email protected] Alok Aggarwal Department of Computer Science & Information Technology, Jaypee Institute of Information Technology, Noida, India Email: [email protected] S.L. Maskara G2W - Soura Niloy. 1 - Kailash Ghosh Road.Kolkata - 700 008. ( WB ). India Email: [email protected] Abstract—Wireless Sensor Networks (WSN) since their made a tremendous progress. An analysis of inception, a decade ago, have grown well in research and contemporary developments in these sub areas of WSN is implementation. In this work the developments in WSNs are the subject matter of this paper and we elaborate on these reported in three sub areas of wireless sensor networks that aspects. The applications of WSN encompass many areas is, wireless sensor node (hardware and software), like healthcare, environmental monitoring, smart Communication & Networking issues in WSNs and application areas. WSNs are characterized by huge data dwellings and civil & battle field security. Still challenges hence research work in aggregation & mining is also such as design of new sensor devices to sense & calibrate discussed. Contemporary issues of integration of WSNs with phenomenon of new interests, integration of WSNs with other prevalent networks, sensor enabled smartness and co existing networks and meaningful interpretation of role of artificial intelligence methods is elaborated. Insight sensor data has to be addressed [4][5]. -
Low Power Or High Performance? a Tradeoff Whose Time
Low Power or High Performance? ATradeoffWhoseTimeHasCome(andNearlyGone) JeongGil Ko1,KevinKlues2,ChristianRichter3,WanjaHofer4, Branislav Kusy3,MichaelBruenig3,ThomasSchmid5,QiangWang6, Prabal Dutta7,andAndreasTerzis1 1 Department of Computer Science, Johns Hopkins University 2 Computer Science Division, University of California, Berkeley 3 Australian Commonwealth Scientific and Research Organization (CSIRO) 4 Department of Computer Science, Friedrich–Alexander University Erlangen–Nuremberg 5 Department Computer Science, University of Utah 6 Department of Control Science and Engineering, Harbin Institute of Technology 7 Division of Computer Science and Engineering, University of Michigan, Ann Arbor Abstract. Some have argued that the dichotomy between high-performance op- eration and low resource utilization is false – an artifact that will soon succumb to Moore’s Law and careful engineering. If such claims prove to be true, then the traditional 8/16- vs. 32-bit power-performance tradeoffs become irrelevant, at least for some low-power embedded systems. We explore the veracity of this the- sis using the 32-bit ARM Cortex-M3 microprocessor and find quite substantial progress but not deliverance. The Cortex-M3, compared to 8/16-bit microcon- trollers, reduces latency and energy consumption for computationally intensive tasks as well as achieves near parity on code density. However, it still incurs a 2 overhead in power draw for “traditional” sense-store-send-sleep applica- tions.∼ × These results suggest that while 32-bit processors are not yet ready for applications with very tight power requirements, they are poised for adoption ev- erywhere else. Moore’s Law may yet prevail. 1Introduction The desire to operate unattended for long periods of time has been a driving force in de- signing wireless sensor networks (WSNs) over the past decade. -
Monitoring High Voltage Power Lines Using Efficient WSN
Advances in Energy and Power 7(1): 10-19, 2020 http://www.hrpub.org DOI: 10.13189/aep.2020.070102 Monitoring High Voltage Power Lines Using Efficient WSN Khaled Al-Maitah, Batool Al-Khriesat, Abdullah Al-Odienat* Department of Electrical Engineering, Faculty of Engineering, Mutah University, Jordan Received March 13, 2020; Revised April 22, 2020; Accepted April 27, 2020 Copyright©2020 by authors, all rights reserved. Authors agree that this article remains permanently open access under the terms of the Creative Commons Attribution License 4.0 International License Abstract The power transmission line is one of most [1]. Moreover, power systems are now highly critical components in electrical power system. In order to interconnected which allows the transfer of a large enhance the reliability of the large power systems, an electrical energy over long distances far from the source of advanced and efficient Wireless Sensor Network (WSN) generation to locations suffer of lack in electrical energy [2] must be employed along power transmission line. However, [3]. time delay has emerged as one of the most critical issues in In power systems, transmission lines are critical the design of WSN-based monitoring network of components from the reliability and stability view point. transmission lines. This paper proposes a new model for There is a real need for an efficient monitoring system of WSN for monitoring High Voltage Transmission Line the transmission lines to enhance the normal operation of (HVTL) which improves the needed time delay to transmit the power system and avoid the major disconnections and the measured quantity from transmission line towers to the blackouts [4]. -
System Architecture Directions for Post-Soc/32-Bit Networked Sensors Hyung-Sin Kim, Michael P Andersen, Kaifei Chen, Sam Kumar, William J
System Architecture Directions for Post-SoC/32-bit Networked Sensors Hyung-Sin Kim, Michael P Andersen, Kaifei Chen, Sam Kumar, William J. Zhao, Kevin Ma, and David E. Culler Department of Electrical Engineering and Computer Sciences, University of California, Berkeley (hs.kim,m.andersen,kaifei,samkumar,william_zhao,kevinma.sd,culler)@berkeley.edu ABSTRACT those that have guided design over the past 20 years, since the The emergence of low-power 32-bit Systems-on-Chip (SoCs), which emergence of the field [31, 37]. While it is easy to observe high- integrate a 32-bit MCU, radio, and flash, presents an opportunity level trends and infer that at some point conventional concurrency to re-examine design points and trade-offs at all levels of the sys- models and networking stacks will fit on this class of computing tem architecture of networked sensors. To this end, we develop a platform, when dealing with low power embedded operation, the post-SoC/32-bit design point called Hamilton, showing that using devil is always in the details. integrated components enables a ∼$7 core and shifts hardware mod- The datasheets for modern 32-bit System-on-Chip units (SoCs) ularity to design time. We study the interaction between hardware with an integrated microcontroller (MCU) and radio are truly im- and embedded operating systems, identifying that (1) post-SoC pressive [10, 43]. Thread-based OSes have reemerged (e.g., RIOT motes provide lower idle current (5.9 µA) than traditional 16-bit [14]), and commercially-driven IPv6 network protocols have arrived motes, (2) 32-bit MCUs are a major energy consumer (e.g., tick (e.g., OpenThread [71]). -
Concepts General Concepts Wireless Sensor Networks (WSN)
Wireless Sensor Networks – Concepts General Concepts Wireless Sensor Networks (WSN) are built based on a combination of multiple sensors placed in diverse locations, wireless communication network infrastructure and software data processing to monitor and record multiple parameters. Commonly monitored parameters are temperature, atmospheric pressure, humidity, vibration, illuminance, sound level, power consumption, chemical concentration, body health signals and many others, dependant on the selected available sensors. The WSN are used in multiple fields, ranging from remote environment monitoring, medical health, to home surveillance and industrial machines monitoring. In some cases, WSN can also be additionally used for control functions, apart from monitoring functions. Typically a WSN is made of sensor nodes that are wirelessly connected to a gateway that is then connected to a main computer (Fig. 1). In some WSN the sensor nodes can also be connected to each other, so that is possible to implement multi-hop wireless mesh networks. The gateway connects to the main computer through a cabled or wireless connection. Figure 1 – Wireless sensor network The wireless communications used in WSN depend on the application requirements, taking into consideration the needs in terms of transmission distance, sensor data bandwidth, energy source and power consumption. Common communications include standard protocols such as 2.4 GHz radio based on either IEEE802.15.4 (ZigBee, ISA 100, WirelessHart, MiWi) or IEEE802.11 (WiFi) standards. Each sensor node typically includes an embedded microcontroller system with adequate electronic interface with a sensor (or set of sensors), a radio transceiver with antenna (internal or external) and an energy source, usually a battery, or in some cases an energy harvesting circuit. -
Flexis—A Flexible Sensor Node Platform for the Internet of Things
sensors Article FlexiS—A Flexible Sensor Node Platform for the Internet of Things Duc Minh Pham and Syed Mahfuzul Aziz * UniSA STEM, University of South Australia, Mawson Lakes, SA 5095, Australia; [email protected] * Correspondence: [email protected]; Tel.: +61-08-8302-3643 Abstract: In recent years, significant research and development efforts have been made to transform the Internet of Things (IoT) from a futuristic vision to reality. The IoT is expected to deliver huge economic benefits through improved infrastructure and productivity in almost all sectors. At the core of the IoT are the distributed sensing devices or sensor nodes that collect and communicate information about physical entities in the environment. These sensing platforms have traditionally been developed around off-the-shelf microcontrollers. Field-Programmable Gate Arrays (FPGA) have been used in some of the recent sensor nodes due to their inherent flexibility and high processing capability. FPGAs can be exploited to huge advantage because the sensor nodes can be configured to adapt their functionality and performance to changing requirements. In this paper, FlexiS, a high performance and flexible sensor node platform based on FPGA, is presented. Test results show that FlexiS is suitable for data and computation intensive applications in wireless sensor networks because it offers high performance with low energy profile, easy integration of multiple types of sensors, and flexibility. This type of sensing platforms will therefore be suitable for the distributed data analysis and decision-making capabilities the emerging IoT applications require. Keywords: Internet of Things (IoT); wireless sensor networks (WSN); sensor node; field-programmable Citation: Pham, D.M.; Aziz, S.M. -
A Zigbee-Based Wireless Biomedical Sensor Network
A ZIG BEE -BASED WIRELESS BIOMEDICAL SENSOR NETWORK AS A PRECURSOR TO AN IN-SUIT SYSTEM FOR MONITORING ASTRONAUT STATE OF HEALTH by XIONGJIE DONG B.S., Kansas State University, 2011 A THESIS submitted in partial fulfillment of the requirements for the degree MASTER OF SCIENCE Department of Electrical & Computer Engineering College of Engineering Kansas State University Manhattan, Kansas 2014 Approved by Major Professor Steve Warren ABSTRACT Networks of low-power, in-suit, wired and wireless health sensors offer the potential to track and predict the health of astronauts engaged in extra-vehicular and in-station activities in zero- or reduced- gravity environments. Fundamental research questions exist regarding (a) types and form factors of biomedical sensors best suited for these applications, (b) optimal ways to render wired/wireless on-body networks with the objective to draw little-to-no power, and (c) means to address the wireless transmission challenges offered by a spacesuit constructed from layers of aluminized mylar. This thesis addresses elements of these research questions through the implementation of a collection of ZigBee-based wireless health monitoring devices that can potentially be integrated into a spacesuit, thereby providing continuous information regarding astronaut fatigue and state of health. Wearable biomedical devices investigated for this effort include electrocardiographs, electromyographs, pulse oximeters, inductive plethysmographs, and accelerometers/gyrometers. These ZigBee-enabled sensors will form the nodes of an in-suit ZigBee Pro network that will be used to (1) establish throughput requirements for a functional in-suit network and (2) serve as a performance baseline for future devices that employ ultra-low-power field-programmable gate arrays and micro-transceivers. -
Biology Inspired Approach for Communal Behavior in Sensor Networks
Biology Inspired Approach for Communal Behavior in Sensor Networks K. H. Jones K. N. Lodding NASA Langley Research Center NASA Langley Research Center Hampton, VA 23681 Hampton, VA 23681 [email protected] [email protected] S. Olariu L. Wilson C. Xin Old Dominion University Old Dominion University Norfolk State University Norfolk, VA 23529 Norfolk, VA 23529 Norfolk, VA 23504 [email protected] [email protected] [email protected] Abstract housing, and other necessities. The realization of this dream has progressed for several centuries but has Research in wireless sensor network technology has taken a revolutionary leap through the invention of exploded in the last decade. Promises of complex and electronic computers, which facilitate more ubiquitous control of the physical environment by automation of machines. Futurists have long predicted these networks open avenues for new kinds of science that machines would eventually communicate and and business. Due to the small size and low cost of cooperate with each other to accomplish sensor devices, visionaries promise systems enabled extraordinarily complex tasks without human by deployment of massive numbers of sensors working intervention [20]. in concert. Although the reduction in size has been phenomenal it results in severe limitations on the While futurists long dreamed of machines working computing, communicating, and power capabilities of with other machines, a giant step towards realization these devices. Under these constraints, research of this dream may be credited to a DARPA sponsored efforts have concentrated on developing techniques program, SmartDust, originated in the late 1990’s for performing relatively simple tasks with minimal [11,26].