Wireless Sensor Networks for Habitat Monitoring Reviewed by Li Zhang Courtesy: Prof. Parashar, Rutgers University.

Slides:



Advertisements
Similar presentations
GDI Sensor Net RIP GDI Data Analysis Robert Szewczyk December 20, 2002.
Advertisements

2 Introduction A central issue in supporting interoperability is achieving type compatibility. Type compatibility allows (a) entities developed by various.
Robot Sensor Networks. Introduction For the current sensor network the topography and stability of the environment is uncertain and of course time is.
Introduction to Wireless Sensor Networks
CSE 5392By Dr. Donggang Liu1 CSE 5392 Sensor Network Security Introduction to Sensor Networks.
Fresh from the boat: Great Duck Island habitat monitoring
Mobile and Wireless Computing Institute for Computer Science, University of Freiburg Western Australian Interactive Virtual Environments Centre (IVEC)
Wireless Sensor Networks for Habitat Monitoring
What is a Wireless Sensor Network (WSN)? An autonomous, ad hoc system consisting of a collective of networked sensor nodes designed to intercommunicate.
Wireless Sensor Networks for Habitat Monitoring
Wireless Sensor Networks for Habitat Monitoring
1 ITC242 – Introduction to Data Communications Week 12 Topic 18 Chapter 19 Network Management.
Networking Theory (Part 1). Introduction Overview of the basic concepts of networking Also discusses essential topics of networking theory.
A New Household Security Robot System Based on Wireless Sensor Network Reporter :Wei-Qin Du.
4/30/031 Wireless Sensor Networks for Habitat Monitoring CS843 Gangalam Vinaya Bhaskar Rao.
GDI Environmental monitoring app Data & lessons learned Robert Szewczyk Joe Polastre Alan Mainwaring David Culler January 15, 2002.
1 Ultra-Low Duty Cycle MAC with Scheduled Channel Polling Wei Ye Fabio Silva John Heidemann Presented by: Ronak Bhuta Date: 4 th December 2007.
Wireless Distributed Sensor Networks Special Thanks to: Jasvinder Singh Hitesh Nama.
Wireless Sensor Networks for Habitat Monitoring Jennifer Yick Network Seminar October 10, 2003.
Wireless Video Sensor Networks Vijaya S Malla Harish Reddy Kottam Kirankumar Srilanka.
A Guide to major network components
Cross Strait Quad-Regional Radio Science and Wireless Technology Conference, Vol. 2, p.p. 980 – 984, July 2011 Cross Strait Quad-Regional Radio Science.
ZIGBEE PROTOCOL FOR WIRLEESS SENSOR NETWORK ZIGBEE PROTOCOL FOR WIRLEESS SENSOR NETWORK Research paper Lina kazem
Fault Tolerance in ZigBee Wireless Sensor Networks
INTRUSION DETECTION SYSTEMS Tristan Walters Rayce West.
Remote Monitoring and Desktop Management Week-7. SNMP designed for management of a limited range of devices and a limited range of functions Monitoring.
Network Topologies.
SCADA and Telemetry Presented By:.
MICA: A Wireless Platform for Deeply Embedded Networks
Presented by Amira Ahmed El-Sharkawy Ibrahim.  There are six of eight turtle species in Ontario are listed as endangered, threatened or of special concern.
FOREST MONITERING APPLICATION USING WSN
Common Devices Used In Computer Networks
WSN Done By: 3bdulRa7man Al7arthi Mo7mad AlHudaib Moh7amad Ba7emed Wireless Sensors Network.
Sensor Network Applications. Introduction –Habitat and environmental monitoring represent essential class of sensor network applications by placing numerous.
IEEE R lmap 23 Feb 2015.
Low-Power Wireless Sensor Networks
DCE (distributed computing environment) DCE (distributed computing environment)
한국기술교육대학교 컴퓨터 공학 김홍연 Habitat Monitoring with Sensor Networks DKE.
Wireless Sensor Networks for Habitat Monitoring Intel Research Lab EECS UC at Berkeley College of the Atlantic.
Lan F.Akyildiz,Weilian Su, Erdal Cayirci,and Yogesh sankarasubramaniam IEEE Communications Magazine 2002 Speaker:earl A Survey on Sensor Networks.
SENSOR NETWORKS BY Umesh Shah Mayuresh Patil G P Reddy GUIDES Prof U.B.Desai Prof S.N.Merchant.
1 REED: Robust, Efficient Filtering and Event Detection in Sensor Networks Daniel Abadi, Samuel Madden, Wolfgang Lindner MIT United States VLDB 2005.
Lecture 6 Page 1 Advanced Network Security Review of Networking Basics Advanced Network Security Peter Reiher August, 2014.
Chapter2 Networking Fundamentals
11 CLUSTERING AND AVAILABILITY Chapter 11. Chapter 11: CLUSTERING AND AVAILABILITY2 OVERVIEW  Describe the clustering capabilities of Microsoft Windows.
Network Operating Systems : Tasks and Examples Instructor: Dr. Najla Al-Nabhan
NETWORKING FUNDAMENTALS. Network+ Guide to Networks, 4e2.
SATIRE: A Software Architecture for Smart AtTIRE R. Ganti, P. Jayachandran, T. F. Abdelzaher, J. A. Stankovic (Presented by Linda Deng)
Internet of Things. IoT Novel paradigm – Rapidly gaining ground in the wireless scenario Basic idea – Pervasive presence around us a variety of things.
Adaptive Sleep Scheduling for Energy-efficient Movement-predicted Wireless Communication David K. Y. Yau Purdue University Department of Computer Science.
SEA-MAC: A Simple Energy Aware MAC Protocol for Wireless Sensor Networks for Environmental Monitoring Applications By: Miguel A. Erazo and Yi Qian International.
Sensor Network Applications
Link Layer Support for Unified Radio Power Management in Wireless Sensor Networks IPSN 2007 Kevin Klues, Guoliang Xing and Chenyang Lu Database Lab.
Wireless Sensor Networks
ARM and GPS Based Transformer monitoring system with area Identification Student Name USN NO Guide Name H.O.D Name Name Of The College & Dept.
Projekt „ESSNBS“ Niš, November 4 th – 7 th, DAAD Wireless Measurement System for Environmental Monitoring and Control MM. Srbinovska, V. Dimcev,
Wireless Sensor Networks: A Survey I. F. Akyildiz, W. Su, Y. Sankarasubramaniam and E. Cayirci.
- Pritam Kumat - TE(2) 1.  Introduction  Architecture  Routing Techniques  Node Components  Hardware Specification  Application 2.
Introduction to Mobile-Cloud Computing. What is Mobile Cloud Computing? an infrastructure where both the data storage and processing happen outside of.
UNIT II –Part 2.
How SCADA Systems Work?.
Introduction to Wireless Sensor Networks
Trickle: Code Propagation and Maintenance
Chapter 16: Distributed System Structures
Bluetooth Based Smart Sensor Network
Review: Analysis of Wireless Sensor Networks for Habitat Monitoring Polastre, Szewczyk, Mainwaring, Culler Review by Nate Ota CS294 8/28/03.
Sensor Networks – Motes, Smart Spaces, and Beyond
REED : Robust, Efficient Filtering and Event Detection
Protocols.
Protocols.
Presentation transcript:

Wireless Sensor Networks for Habitat Monitoring Reviewed by Li Zhang Courtesy: Prof. Parashar, Rutgers University

Outline Introduction Motivation and requirement analysis System architecture System implementation Current results Discussion Conclusion

Introduction long-term data collection at scales and resolutions Habitat and environmental monitoring can enable long-term data collection at scales and resolutions that are difficult, or even impossible, to obtain. local processing and storage Integration of local processing and storage  allows sensor nodes to perform complex filtering and triggering functions, as well as to apply application-specific or sensor-specific data compression algorithms. communicate Ability to communicate  allows information and control to be communicated across the network of nodes; nodes cooperate in performing more complex tasks. power efficiency Increased power efficiency

Introduction (cont.) Application-driven approach Separates actual problems from potential ones, relevant issues from irrelevant ones; helps to differentiate problems with simple, concrete solutions from open research areas. general solutions However, general solutions should be seeked from this. Collaboration with scientists in other fields helps to define a broader application space. largely representative The paper develops a specific habitat monitoring application, which is a largely representative of the domain. A collection of requirements, constraints and guidelines

Motivation The potential impact of human presence in monitoring plants and animals in field conditions Disturbance effects Disturbance effects are of particular concern in small island situations Sensor networks represent a significant advance over traditional invasive methods of monitoring. more economical Sensor network deployment may represent a substantially more economical method for conducting long-term studies than traditional personnel-rich methods.

Requirement Analysis for GDI Great Duck Island (GDI) major interested questions: What is the usage pattern of nesting burrows over the hour cycle when one or both members of a breeding pair may alternate incubation duties with feeding at sea? What changes can be observed in the burrow and surface environmental parameters during the course of the approximately 7 month breeding season? What are the differences in the micro-environments with and without large numbers of nesting petrels? unique data needs suitable data acquisition rates Each of these questions has unique data needs and suitable data acquisition rates.

Requirement Analysis for GDI Internet access  To support remote interactions with in-situ networks Hierarchical network  Needs sufficient resources to host internet connectivity and database system. However, the habitat of scientific interest are several kilometres further away.  A second tier of wireless network provides connectivity to multiple patches of sensor networks deployed at each of the areas of interest. Sensor network longevity  Individual field seasons typically vary from 9~12 months

Requirement Analysis for GDI Operating off-the-grid  Every level of the network must operate with bounded energy supplies. Management at-a-distance  To zero on-site presence for maintenance and administration during the field season Inconspicuous operating  It should not disrupt the natural processes or behaviors under study. System behaviour  sensor networks should present stable, predictable, and repeatable behaviour whenever possible.

Requirement Analysis for GDI In-situ interactions  Local interactions are required during initial deployment, during maintenance tasks, as well as during on-site visits. Sensors and sampling  The ability to sense light, temperature, ingrared, relative humidity, and barometric pressure is essential. Data archiving  Archiving sensor readings for off-line data mining and analysis is essential

System Architecture Tiered architecture Database replicas: store data retrievable by scientists Base station: connects to database replicas across the internet Gateway: transmit sensor data from the sensor patch through a local transit network to the remote base station that provides WAN connectivity and data logging Sensor nodes: general purpose computing and networking, application-specific sensing

System Architecture: sensor nodes Sensors are small, battery-powered devices that can collect environmental data primarily about its immediate surroundings. small and inexpensive individual sensors dense deployment They use small and inexpensive individual sensors and dense deployment of sensor nodes higher robustness Compared with traditional approaches, which use a few high quality sensors with sophisticated signal processing, this architecture provides higher robustness against occlusions and component failures.

System Architecture: sensor nodes Computational module + sensor module Computational module is a programmable unit that provides computation, storage, and bidirectional communication with other nodes in the system. Networked sensors offer two major advantages: They can be re-tasked in the field. They can easily communicate with the rest of the system.

System Architecture connectivity to the transit network Each sensor patch is equipped with a gateway which can communicate with the sensor network and provides connectivity to the transit network. WAN connectivity and persistent data storage Base station includes WAN connectivity and persistent data storage for the collection of sensor patches. Wireless WAN connection will be wireless (two-way satellite) Reliable components enclosed in environmentally protected housing, and provided with adequate power  For example, a ranger station

System Architecture The architecture needs to address the possibility of disconnection at every level. Each layer (sensor nodes, gateways, base stations) has some persistent storage which protects against data loss in case of power outage. Each layer also provides data management services  Sensor level: data logging  Base station: full-fledged relational database service  Gateways: some database services over limited window of data System prefers long-latency of data transfer to data loss  Uses “custody transfer” model, which is similar to SMTP messages or bundles

System Architecture Users interact with the sensor network data in two ways Remote: users access the replica of the base station database  Allows for easy integration with data analysis and mining tools  Provides remote control of the network On-site: users use small PDA-sized device (gizmo) to directly communicate with the sensor patch  Provides the users with a fresh set of readings about the environments and monitors the network  Allows users to interactively control the network parameters by adjusting the sampling rates, power management parameters and other network parameters.  Is especially useful during the initial deployment and during re- tasking of the network

Implementation Strategy Sensor network node Uses UC Berkeley motes Sensor Board Mica weather board provides sensors that monitor changing environmental conditions Mica weather board includes temperature, photoresistor, barometric pressure, humidity, and passive infrared sensors The sensors are chosen based on  high interchangeability and high accuracy  shorter startup time The unique combination of sensors in Mica can be used for a variety of aggregate operations Mica considers Interoperability

Implementation Strategy Energy budget Many habitat monitoring applications need to run for nine months—the length of a single field season Since different nodes have different power requirements, we need to budget power with respect to the energy bottleneck of the network The baseline life time of the node is determined by the current draw in the sleep state --minimize power in sleep mode

Implementation Strategy Sensor deployment To withstand the variable weather conditions on DGI, environmental protective packaging that minimally obstructs sensing functionality is used Patch gateways Using different gateway nodes directly affects the underlying transit network available Current two designs  An b single hop with an embedded Linux system  A single hop mote-to-mote network These two designs differ in communication frequency, power requirements, and software component. Currently, only mote solution is used

Implementation Strategy Base-station installation To provide remote access to the habitat monitoring networks The collection of sensor network patches is connected to the Internet through a wide-area link---a two way satellite connection Database management system Uses Postgres SQL database Stores time-stamped readings from the sensors Is replicated every 15 minutes over the wide-area satellite link to Postgres database in Berkeley

Implementation Strategy User interface Many user interfaces will be implemented on top of the sensor network database Gizmo design for local users is not well developed yet

Results The sensor network has been deployed for four weeks as of the writing of this paper Occupancy data are down in the figure

Discussions All system components must operate in accordance with the system’s power budget In a running system, the energy budget must be divided amongst several system services Data sampling and collection Communications Network re-tasking Health and status monitoring Data sampling and collection By analyzing the requirements we can place a bound on the energy spent on data acquisition Trade the cost of data processing and compression against the cost of data transmission

Discussions (cont.) Communications Power efficient communication paradigms for habitat monitoring must include a set of routing algorithms, media access algorithms, and managed hardware access.  The routing algorithms must be tailored for efficient network communication while maintaining connectivity when required to source or relay packets Most efficient for low duty cycle sensor networks is to simply broadcasting data to a gateway during scheduled communication period. (single hop) Multi-hop scheduled protocol must be used for hard to reach research locations that are beyond the range of a single wireless broadcast from mote to gateway Scheduled communication Low power MAC protocol

Discussion (cont.) Network re-tasking Adjust the functionality of individual nodes  Simple parameter, such as scalar parameters, may be adjusted through the application manager  Complex functionality adjustment may be implemented through virtual machines like Mate or reprogramming Health and status monitoring Health and status messages sent to the gateway can be used to infer the validity of the mote’s sensor reading Including battery voltage level in transmitted sensor reading helps remote analysis of node failures

Conclusion Habitat and environmental monitoring represent an important class of sensor network applications Sensor network system must deliver the data of interest in a confidence-inspiring manner Tight energy bounds and the need for predictable operation guide the development of application architecture and services

Further Discussion The authors claimed in the paper that the work is largely representative of the domain. Do you think so after reading the paper? Health and status monitoring is important. Battery voltage seems to provide limited information for inferring the validity of the mote’s sensor readings. No other methods are brought up in the paper. Difference between scheduled communication and low power MAC protocols?