IntroductionSensorNetworks-part 1(1)

IntroductionSensorNetworks-part 1(1) - Introduction to...

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Unformatted text preview: Introduction to Wireless Sensor Networks -System Architecture of Networked Sensor Platforms and Applications Sensor Networks Wireless sensor networks consists of group of sensor nodes Wireless to perform distributed sensing task using wireless medium. Characteristics - low-cost, low-power, lightweight - densely deployed - prone to failures prone - two ways of deployment: randomly, pre-determined or engineered two deployment Objectives Objectives - Monitor activities Monitor - Gather and fuse information - Communicate with global data processing unit Communicate Sensor Networks Application Areas [Akyildiz+ 2002] [Akyildiz+ 1. Military: 1. Monitoring equipment and ammunition Battlefield surveillance and damage assessment Nuclear, biological, chemical attack detection and reconnaissance 1. Environmental: Forest fire / flood detection 1. Health: Tracking and monitoring doctors and patients inside a hospital Drug administration in hospitals Sensor Networks Application Areas [Akyildiz+ 2002] [Akyildiz+ 1. Home: 1. Home automation Smart environment 1. Other Commercial Applications: Environmental control in office buildings Detecting and monitoring car thefts Managing inventory control Vehicle tracking and detection Sensor Networks Preliminaries – For large scale environment monitoring applications, dense For sensor networks are mainly used – Sensing capabilities should be distributed and coordinated Sensing amongst the sensor nodes amongst – Algorithms deployed should be localized since transmissions Algorithms between large distances are expensive and lowers networks life time time – These networks should be self-configuring, scalable, redundant These and robust during topology changes and Research Problems in Sensor Networks Clustering – Partitioning of the network Partitioning – Identification of vital nodes (clusterheads) Routing – – – Discovering routes from source to destination Maintaining the routes Rediscovery and repair of routes Topology management – Maintain the links – Minimize the changes in underlying graph Security Research Problems in Ad hoc and Sensor Networks Medium Access Control Protocols Sensor data management Power conservation/energy consumption Data fusion and dissemination of sensor data New applications for ad hoc and sensor networks Why Sensor Platforms? – Compared to analysis and simulation techniques, designing a system Compared platform has the following advantages: platform Provides genuine executive environment: various proposed Provides algorithms can be exactly evaluated; good way to examine existing design principles and discover new ones under different configurations configurations More attention can be focused on the application-layer A real system platform can accelerate the pace of research and real development development General WSN System Architecture – Constructing a platform for WSN falls into the area of embedded system Constructing development which usually consists of developing environment, hardware and software platforms. hardware 1. Hardware Platform Consists of the following four components: a) Processing Unit Associates with small storage unit (tens of kilo bytes order) and Associates manages the procedures to collaborate with other nodes to carry out the manages assigned sensing task b) Transceiver Unit Connects the node to the network via various possible transmission medias such as infra, light, radio and so on General WSN System Architecture 1. 1. Hardware Platform c) Power Unit Supplies power to the system by small size batteries which makes the Supplies energy a scarce resource energy d) Sensing Units Usually composed of two subunits: sensors and analog-to-digital Converters (ADCs). The analog signal produced by the sensors are converted to digital signals by the ADC, and fed into the processing unit e) Other Application Dependent Components Location finding system is needed to determine the location of sensor Location nodes with high accuracy; mobilizer may be needed to move sensor nodes when it is required to carry out the task nodes General WSN System Architecture 1. 1. Software Platform Consists of the following four components: a) Embedded Operating System (EOS) Manages the hardware capability efficiently as well as supports concurrency-intense operations. Apart from traditional OS tasks such as processor, memory and I/O management, it must be real-time to rapidly respond the hardware triggered events, multi-threading to handle respond concurrent flows b) Application Programming Interface (API) b) A series of functions provided by OS and other system-level components series for assisting developers to build applications upon itself for General WSN System Architecture 1. 1. Software Platform c) Device Drivers A series of routines that determine how the upper layer entities series communicate with the peripheral devices communicate d) Hardware Abstract Layer (HAL) Intermediate layer between the hardware and the OS. Provides uniform interfaces to the upper layer while its implementation is highly dependent on the lower layer hardware. With the use of HAL, the OS and on applications easily transplant from one hardware platform to another applications Berkeley Motes [Hill+ 2000] – Motes are tiny, self-contained, battery powered computers with radio Motes links, which enable them to communicate and exchange data with one another, and to self-organize into ad hoc networks another, – Motes form the building blocks of wireless sensor networks – TinyOS [TinyOS], component-based runtime environment, is designed to TinyOS [TinyOS] component-based provide support for these motes which require concurrency intensive operations while constrained by minimal hardware resources operations Figure 3: Berkeley Mote Wireless Sensor Networks for Habitat Monitoring [Mainwaring+ 2002] Introduction Introduction – Habitat and environmental monitoring represent essential class of sensor Habitat network applications by placing numerous networked micro-sensors in an environment where long-term data collection can be achieved environment – The sensor nodes perform filtering and triggering functions as well as The application-specific or sensor-specific data compression algorithms thru the integration of local processing and storage the – The ability to communicate allows nodes to cooperate in performing The tasks such as statistical sampling, data aggregation, and system health and status monitoring and – Increased power efficiency assists in resolving fundamental design Increased tradeoffs, e.g., between sampling rates and battery lifetimes tradeoffs, Wireless Sensor Networks for Habitat Monitoring [Mainwaring+ 2002] Introduction Introduction – The sensor nodes can be reprogrammed or retasked after deployment in The the field by the networking and computing capabilities provided the – Nodes can adapt their operation over time in response to changes in the Nodes environment environment – The application context helps to differentiate problems with simple and The concrete solutions from open research areas concrete – An effective sensor network architecture and general solutions should be An developed for the domain developed – The impact of sensor networks for habitat and environmental monitoring The is measured by their ability to enable new applications and produce new results results Wireless Sensor Networks for Habitat Monitoring [Mainwaring+ 2002] Introduction Introduction – This paper develops a specific habitat monitoring application, but yet a This representative of the domain representative – It presents a collection of requirements, constraints and guidelines that It serve as a basis for general sensor network architecture serve – It describes the core components of the sensor network for this domain– It hardware and sensor platforms, the distinct networks involved, their interconnection, and the data management facilities interconnection, – The design and implementation of the essential network services – The power management, communications, re-tasking, and node management can be evaluated in this context can Wireless Sensor Networks for Habitat Monitoring [Mainwaring+ 2002] Habitat Monitoring Habitat – Researchers in the Life Sciences are concerned about the impacts of Researchers human presence in monitoring plants and animals in the field conditions human – It is possible that chronic human disturbance may adversely effect results It by changing behavioral patterns or distributions by – Disturbance effects are of concern in small island situations where it may Disturbance be physically impossible for researchers to avoid some impact on an entire population entire – Seabird colonies are extreme sensitive to human disturbance – Research in Maine [Anderson 1995], suggests that a 15 minute visit to a Research cormorant colony can result in up to 20% mortality among eggs and chicks in a given breeding year. Repeated disturbance can lead to the end of the colony end Wireless Sensor Networks for Habitat Monitoring [Mainwaring+ 2002] Habitat Monitoring Habitat – On Kent Island, Nova Scotia, research learned that Leach’s Storm Petrels On are likely to desert their nesting burrows in case of disturbance during the first two weeks of incubation first – Sensor networks advances the monitoring methods over the traditional Sensor invasive ones invasive – Sensors can be deployed prior to the breeding season or other sensitive Sensors period or while plants are dormant or the ground is frozen on small islets where it would be unsafe or unwise to repeatedly attempt field studies where – Sensor network deployment may be more economical method for Sensor conducting long-term studies than traditional personnel-rich methods conducting – A “deploy ‘em and leave ‘em” strategy of wireless sensor usage would “deploy decrease the logistical needs to initial placement and occasional servicing decrease Wireless Sensor Networks for Habitat Monitoring [Mainwaring+ 2002] Great Duck Island Great – The College of Atlantic (COA) is field testing in-situ sensor networks for The habitat monitoring habitat – Great Duck Island (GDI) is a 237 acre island located 15 km south of Great Mount Desert Island, Maine Mount – At GDI, three major questions in monitoring the Leach’s Storm Petrel At [Anderson 1995]: [Anderson 1. What is the usage pattern of nesting burrows over the 24-72 hour What cycle when one or both members of a breeding pair may alternate incubation duties with feeding at sea? incubation 2. What changes can be observed in the burrow and surface What environmental parameters during the course of the approximately 7 month breeding season (April-October)? month Wireless Sensor Networks for Habitat Monitoring [Mainwaring+ 2002] Great Duck Island Great 1. What are the differences in the micro-environments with and without What large numbers of nesting petrels? large – Presence/absence data is obtained through occupancy detection and Presence/absence temperature differentials between burrows with adult birds and burrows that contain eggs, chicks, or are empty that – Petrels will most likely enter or leave during the daytime; however, 5-10 Petrels minutes during late evening and early morning measurements are needed to capture the entry and exit timings needed – More general environmental differentials between burrow and surface More conditions can be captured by records every 2-4 hours during the extended breeding season; whereas, the differences between “popular” and “unpopular” sites benefit from hourly sampling and Wireless Sensor Networks for Habitat Monitoring [Mainwaring+ 2002] Great Duck Island Requirements Great 1. Internet Access – The sensor networks at GDI must be accessible via the Internet since the The ability to support remote interactions with in-situ networks is essential ability 1. Hierarchical Network – Habitats of interest are located up to several kilometers away. A second Habitats tier of wireless networking provides connectivity to multiple patches of sensor networks deployed at each of the areas. sensor 1. Sensor Network Longevity – Sensor networks that runs for several month from non-rechargeable Sensor power sources would be desirable since studies at GDI can span multiple field seasons field Wireless Sensor Networks for Habitat Monitoring [Mainwaring+ 2002] Great Duck Island Requirements Great 1. Operating off-the grid – Every level of the network must operate with bounded energy supplies – Renewable energy such as solar power may be available some locations, Renewable disconnected operation is a possibility disconnected – GDI has enough solar power that run the application 24x7 with small GDI probabilities of service interruptions due to power loss probabilities 1. Management at-a-distance – Remoteness of the field sites requires the ability to monitor and manage Remoteness sensor networks over the Internet. The goal is no on-site presence for maintenance and administration during the field season, except for installation and removal of nodes installation Wireless Sensor Networks for Habitat Monitoring [Mainwaring+ 2002] Great Duck Island Requirements Great 1. Inconspicuous operation – It should not disrupt the natural processes or behaviors under study – Removing human presence from the study areas would eliminate a Removing source of error and variation in data collection and source of disturbance source 1. System behavior – Sensor networks should present stable, predictable, and repeatable Sensor behavior at all times since unpredictable system is difficult to debug and maintain maintain – Predictability is essential in developing trust in these new technologies Predictability for life scientists for Wireless Sensor Networks for Habitat Monitoring [Mainwaring+ 2002] Great Duck Island Requirements Great 1. In-situ interactions – Local interactions are required during initial development, maintenance Local and on-site visits – PDAs can be useful in accomplishing these tasks – they may directly PDAs query a sensor, adjust operational parameters and so on query 1. Sensors and sampling – The ability to sense light, temperature, infrared, relative humidity, and The barometric pressure are essential set of measurements barometric – Additional measurements may include acceleration/vibration, weight, Additional chemical vapors, gas concentrations, pH, and noise levels chemical Wireless Sensor Networks for Habitat Monitoring [Mainwaring+ 2002] Great Duck Island Requirements Great 1. Data archiving – Sensor readings must be achieved for off-line data mining and analysis – The reliable offloading of sensor logs to databases in the wired, powered The infrastructure is essential infrastructure – It is desirable to interactively “drill-down” and explore sensors in near It real-time complement log-based studies. In this mode of operation, the timely delivery of sensor data is the key timely – Nodal data summaries and periodic health-and-status monitoring also Nodal requires timely delivery of the data requires Wireless Sensor Networks for Habitat Monitoring [Mainwaring+ 2002] System Architecture System – A tiered architecture is developed – The lowest level consists of the sensor nodes that perform general The sensor purpose computing and networking as well as application-specific sensing purpose – The sensor nodes may be deployed in dense patches and transmit their The data through the sensor network to the sensor network gateway gateway – Gateway is responsible for transmitting sensor data from the sensor patch Gateway sensor through a local transit network to the remote base station that provides transit base WAN connectivity and data logging WAN – The base station connects to database replicas across the internet – At last, the data is displayed to researchers through a user interface Wireless Sensor Networks for Habitat Monitoring [Mainwaring+ 2002] System Architecture System Figure 1: System architecture for habitat monitoring Wireless Sensor Networks for Habitat Monitoring [Mainwaring+ 2002] System Architecture System – The autonomous sensor nodes are placed in the areas of interest where The each sensor node collects environmental data about its immediate surroundings surroundings – Since these sensors are placed close to the area of interest, they can be Since built using small and inexpensive individual sensors – high spatial resolution can be achieved through dense deployment of sensor nodes resolution – This architecture offers higher robustness compared to traditional This approaches which use a few high quality sensors with complex signal processing processing – The computational module is a programmable unit that provides The computation, storage and bidirectional communication with other nodes computation, Wireless Sensor Networks for Habitat Monitoring [Mainwaring+ 2002] System Architecture System – The computational module interfaces with the analog and digital sensors The on the sensor module, performs basic signal processing and dispatches the data according to the needs of the application the – Compared to traditional data logging systems, networked sensors offer Compared two main advantages: they can be re-tasked in the field and they can communicate with the rest of the system communicate – In-situ re-tasking gives researchers the ability to refocus their observations In-situ based on the analysis of the initial results – initially, absolute temperature readings are desired, after a while, only significant temperature changes exceeding a threshold may become more useful exceeding Wireless Sensor Networks for Habitat Monitoring [Mainwaring+ 2002] System Architecture System – Individual sensor nodes communicate and coordinate with one another Individual – These nodes form a multi-hop network by forwarding each other’s These messages and if needed, the network can perform in-network aggregation (e.g., relaying the average temperature across the region) (e.g., – Eventually, data from each sensor needs to be propagated to the Internet – The propagated data may be raw, filtered or processed data – Since direct wide area connectivity cannot be brought to each sensor path Since due to several reasons (e.g., cost of equipment, power, disturbance created by the installation of the equipment in the environment), wide are connectivity is brought to a base station instead base Wireless Sensor Networks for Habitat Monitoring [Mainwaring+ 2002] System Architecture System – The base station may communicate with the sensor patch using a wireless The LAN where each sensor patch is equipped with a gateway that can gateway communicate with the sensor network and provides connectivity to the transit network transit – The transit network may consist of a single hop link or series of networked The wireless nodes and each transit network design has different characteristics with respect to expected robustness, bandwidth, energy efficiency, cost and manageability efficiency, – To provide data to remote end-users, the base station includes WAN To base connectivity and persistent data storage for the collection of sensor patches patches Wireless Sensor Networks for Habitat Monitoring [Mainwaring+ 2002] System Architecture System – It is expected that WAN connection will be wireless – The architecture needs to address the disconnection possibilities – Each layer (sensor nodes, gateways, base stations) has some persistent Each storage to protect against data loss due to power outage as well as data management services management – At the sensor level, these will be primitive, taking the form of data logging – The base station may provide relational database service while the data The management at the gateways falls somewhere in between management – When it comes to data collection, long-latency is preferable to data loss – Users interact with the sensor network in two ways Wireless Sensor Networks for Habitat Monitoring [Mainwaring+ 2002] System Architecture System – Remote users access the replica of the base station database Remote – This approach assists on integration with data analysis and mining tools This while masking the potential wide area disconnections with the base stations stations – On-site users may require direct interaction with the network and this can On-site be accomplished with a small, PDA-sized device, referred to as gizmo gizmo – Gizmo allows the user to interactively control the network parameters by Gizmo adjusting the sampling rates, power management parameters and other network parameters network – The connectivity between any sensor node and gizmo may or may not rely The on functioning on multi-hop sensor network routing on Energy-Efficient Computing for Wildlife Tracking: Design Tradeoffs and Early Experiences with ZebraNet [Juang+ 2002] Introduction Introduction – Focus is on issues related to dynamic sensor networks with mobile Focus nodes and wireless communication between them nodes – In this system, the sensor nodes collars carried by the animals under In study; wireless ad hoc networking techniques are used to swap and store data in a peer-to-peer manner and to pass it towards a mobile base station that sporadically traverses the area to upload data station – Biology and biocomplexity research has been focused on gathering data Biology and observations on a range of species to understand their interactions and influences on each other and – For example, how human development into wilderness areas affects For indigenous species there; understand the migration patterns of wild animals and how they may be affected by changes in weather patterns or plant life, by introduction of non-native species, and by other influences plant Energy-Efficient Computing for Wildlife Tracking: Design Tradeoffs and Early Experiences with ZebraNet [Juang+ 2002] Introduction Introduction – Finding and learning these details require long-term position logs and Finding other biometric data such as heart rate, body temperature, and frequency feeding feeding – Current wildlife tracking studies rely on simple technology, for example, Current many studies rely on collaring a sample subset of animals with simple VHF transmitters VHF – Researchers periodically drive through and/or fly over an area with a Researchers receiver antenna, and listen for pings from previously collared animals receiver – Once animal is found, its behavior can be observed and its observed Once position can be logged; however, there are limits to such studies position – First, data collection is infrequent and can miss many “interesting events” Energy-Efficient Computing for Wildlife Tracking: Design Tradeoffs and Early Experiences with ZebraNet [Juang+ 2002] Introduction Introduction – Second, data collection is mostly limited to daylight hours, but animal Second, behavior and movements in night hours can be different behavior – Third, data collection is impossible or very limited for secluded species Third, that avoid human contact that – The most elegant trackers commercially available use GPS to track The position and use satellite uploads to transfer data to a base station position – These systems also suffer from several limitations – First, at most a log of 3000 position samples can be logged and no First, biometric data biometric – Second, since satellite uploads are slow and uses high power Second, consumption, they are done infrequently – this limits how often position samples can be gathered without overflowing 3000-entry log storage samples Energy-Efficient Computing for Wildlife Tracking: Design Tradeoffs and Early Experiences with ZebraNet [Juang+ 2002] Introduction Introduction – Third, downloads of data from the satellite to the researchers are both Third, slow and expensive, therefore, constraining the amount of data collected slow – Finally, these systems operate on batteries without recharge – when Finally, power is drained, the system become unusable unless it is retrieved, recharged and re-deployed recharged – ZebraNet project is building tracking nodes that include a low-power miniature GPS system with user-programmable CPU, non-volatile storage for data logs, and radio transceivers for communicating either with other nodes or with a base station with Energy-Efficient Computing for Wildlife Tracking: Design Tradeoffs and Early Experiences with ZebraNet [Juang+ 2002] Introduction Introduction – One of the key principles of ZebraNet is that the system should work in One arbitrary wilderness locations; no assumptions are made about the presence of of fixed antenna towers or cellular phone service presence – The system uses peer-to-peer data swaps to move the data around; The periodic researcher drives bys and/or fly-overs can collect logged data from several animals despite encountering relatively few within range from – Even though ad hoc sensor networks have been heavily studied, not Even much has been published about the characteristics of mobile sensor networks with mobile base stations and very few studies focus on building real systems building Energy-Efficient Computing for Wildlife Tracking: Design Tradeoffs and Early Experiences with ZebraNet [Juang+ 2002] Introduction Introduction – This paper has the following unique contributions: o To the best knowledge of authors, this is the first study of mobile To sensor networks protocols in which the base station is also mobile. It mobile It is presumed that researchers will upload data while driving or flying by the region by o Zebra-tracking is a domain in which the node mobility models are Zebra-tracking unknown which makes it a research goal. Understanding how, when and why zebras undertake long-term migrations is the most essential biological question of this work. o ZebraNet’s data collection has communication patterns in which data ZebraNet’s can be cooperatively passed towards a base station can o Energy tradeoffs are examined in detail using real system energy Energy measurements for ZebraNet prototype hardware in operation measurements Energy-Efficient Computing for Wildlife Tracking: Design Tradeoffs and Early Experiences with ZebraNet [Juang+ 2002] Introduction Introduction – Some of the interesting research questions to be explored are: o o To what extent can we rely on ad hoc, peer-to-peer transfers in a To sparsely-connected spatially-huge sensor network? sparsely-connected o – How to make the communications protocol both effective and powerefficient? How can we provide comprehensive tracking of a collection of How animals, even if some of the animals are reclusive and rarely are close enough to humans to have their data logs updated directly? close This research work gives quantitative explorations of the design This decisions behind some of these questions decisions Energy-Efficient Computing for Wildlife Tracking: Design Tradeoffs and Early Experiences with ZebraNet [Juang+ 2002] ZebraNet Design Goals ZebraNet – The ZebraNet project is a direct and ongoing collaboration between The researchers in experimental computer systems and in wildlife biology researchers – The wildlife biologists have determined the tracker’s overall design goals: o GPS position samples are taken every three minutes o Detailed activity logs taken for three minutes every hour o One year of operation without direct human intervention – that is, not One counting on tranquilizing and re-collaring an animal more than once per year per o No fixed base stations, antennas, or cellular service No o A high success rate for eventually delivering all logged data is high eventually essential while latency is not as critical essential o For a zebra collar, a weight limit of 3-5 lbs is recommended Energy-Efficient Computing for Wildlife Tracking: Design Tradeoffs and Early Experiences with ZebraNet [Juang+ 2002] ZebraNet Design Goals ZebraNet – Ultimately, this detailed information may include several position Ultimately, estimates, temperature information, weather data, environmental data, and body movements that will serve as signatures of behavior; however, in this initial system, the focus is only on position data in – Overall, the key goal is to deliver to researchers a very high fraction of the Overall, data collected over the months or years that the system is in operation data – Therefore, ZebraNet must be power-efficient, designed with appropriate Therefore, data log storage, and must be rugged to ensure reliability under tough environmental conditions environmental Energy-Efficient Computing for Wildlife Tracking: Design Tradeoffs and Early Experiences with ZebraNet [Juang+ 2002] ZebraNet Problem Statement ZebraNet – The biologists design goals need to be translated into the engineering The task at hand task – Success rate at delivering position data to the researchers –data homing Success rate– should approach 100% rate– – Weight limits on each node translate almost directly to computational Weight energy limits since weight of the battery and solar panel takes bulk of the total weight of a ZebraNet node; therefore, collar and protocol design decisions must manage the number and size of data transmissions required required – System design choices must be made that limit the range of System transmissions since the required transmitter energy increases dramatically with the distance transmitted dramatically Energy-Efficient Computing for Wildlife Tracking: Design Tradeoffs and Early Experiences with ZebraNet [Juang+ 2002] ZebraNet Problem Statement ZebraNet – The amount of storage needed to hold position logs must be limited – if The many redundant copies are stored and swapped, the storage requirements can scale as O(n2) O(n – Although the energy cost of storage is small compared to that of Although transmissions, it is still necessary to develop storage-efficient design transmissions, – Due to limited transceiver, coverage and a base station only sporadically Due available, ZebraNet must forward data through other nodes in peer-toavailable, peer manner and store redundant copies of position logs in other tracking peer nodes nodes – Some of the key challenges in ZebraNet come from the spatial and Some temporal scale of the system temporal Energy-Efficient Computing for Wildlife Tracking: Design Tradeoffs and Early Experiences with ZebraNet [Juang+ 2002] ZebraNet Problem Statement ZebraNet – In terms of temporal scale, keeping a system running autonomously In months at a time is challenging; it requires tremendous design-time attention to both hardware and software reliability attention – In terms of spatial scale, ZebraNet is also aggressive; it is the specific In intent of the system to operate over an area of hundreds or thousands of square square kilometers square – Due to the large distances involved and sparse sensor coverage, energy/ connectivity tradeoffs become key Energy-Efficient Computing for Wildlife Tracking: Design Tradeoffs and Early Experiences with ZebraNet [Juang+ 2002] ZebraNet Problem Statement ZebraNet – These challenges mentioned here tackles several open problems: – ZebraNet protocol promises good communication behavior on mobile ZebraNet sensors forwarding data towards a mobile base station sensors – ZebraNet explores design issues for sensors that are more coarsegrained than many prior sensor proposals. Larger the weight limits grained and storage budgets allow researchers to consider different protocols with improved leverage for sparsely-connected, physicallywith widespread sensors References [Abrach+ 2003] H. Abrach, S. Bhatti, J. Carlson, H. Dai, J. Rose, A. Sheth, B. Shucker, J, Deng and R. Han, MANTIS: System Support for MultimodAl NeTworks of In-Situ Sensors, 2nd ACM International Workshop on Wireless Sensor Networks and Applications (WSNA 2003), September 2003. [Akyildiz+ 2002] I. F. Akyildiz, W. Su, Y. Sankarasubramaniam, and E. Cayirci, A Survey on Sensor Networks, IEEE Communications Magazine, Vol. 40, No. 8, pp. 102-114, August 2002. [Anderson 1995] J.G.T. Anderson, Pilot survey of mid-coast Maine seabird colonies: an evaluation of techniques, Bangor, ME, 1995. Report to the State of Maine Dept. of Inland Fisheries and Wildlife. [Hill+ 2000] J. Hill, R. Szewczyk, A. Woo, S. Hollar, D. Culler, and K. Pister, System Architecture Directions for Networked Sensors, Architectural Support for Programming Languages and Operating Systems (ASPLOS) 2000. [Juang+ 2002] P. Juang, H. Oki, Y. Wang, M. Martonosi, L-S Peh, and D. Rubenstein, EnergyEfficient Computing for Wildlife Tracking: Design Tradeoffs and Early Experiences with ZebraNet, ACM SIGARCH Computer Architecture News, vol. 30, no. 5, December 2002 . [Mainwaring+ 2002] A. Mainwaring, J. Polastre, R. Szewczyk, D. Culler, and J. Anderson, Wireless Sensor Networks for Habitat Monitoring, 1st ACM International Workshop on Wireless Sensor Networks and Applications (WSNA 2002), Atlanta, Georgia, September 28, 2002. [TinyOS] TinyOS: a component-based OS for the networked sensor regime. ...
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This note was uploaded on 08/25/2011 for the course EEL 6788 taught by Professor Boloni,l during the Spring '08 term at University of Central Florida.

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