1 Achieving Long-Term Surveillance in VigilNet Tian He, Pascal Vicaire, Ting Yan, Qing Cao, Gang Zhou, Lin Gu, Liqian Luo, Radu Stoleru, John A. Stankovic,

Slides:



Advertisements
Similar presentations
A 2 -MAC: An Adaptive, Anycast MAC Protocol for Wireless Sensor Networks Hwee-Xian TAN and Mun Choon CHAN Department of Computer Science, School of Computing.
Advertisements

1 MMSN: Multi-Frequency Media Access Control for Wireless Sensor Networks Gang Zhou, Chengdu Huang, Ting Yan, Tian He John. A. Stankovic, Tarek F. Abdelzaher.
SELF-ORGANIZING MEDIA ACCESS MECHANISM OF A WIRELESS SENSOR NETWORK AHM QUAMRUZZAMAN.
Bidding Protocols for Deploying Mobile Sensors Reporter: Po-Chung Shih Computer Science and Information Engineering Department Fu-Jen Catholic University.
Decentralized Reactive Clustering in Sensor Networks Yingyue Xu April 26, 2015.
Integrated Coverage and Connectivity Configuration in Wireless Sensor Networks Xiaorui Wang, Guoliang Xing, Yuanfang Zhang*, Chenyang Lu, Robert Pless,
Routing Protocols for Sensor Networks Presented by Siva Desaraju Computer Science WMU An Application Specific Protocol Architecture for Wireless Microsensor.
Introduction to Wireless Sensor Networks
A High-Accuracy, Low-Cost Localization System for Wireless Sensor Networks Radu Stoleru, Tian He, John A. Stankovic, David Luebke University of Virginia.
1 Prediction-based Strategies for Energy Saving in Object Tracking Sensor Networks Yingqi Xu, Wang-Chien Lee Proceedings of the 2004 IEEE International.
Differentiated Surveillance for Sensor Networks Ting Yan, Tian He, John A. Stankovic CS294-1 Jonathan Hui November 20, 2003.
PEDS September 18, 2006 Power Efficient System for Sensor Networks1 S. Coleri, A. Puri and P. Varaiya UC Berkeley Eighth IEEE International Symposium on.
Localized Techniques for Power Minimization and Information Gathering in Sensor Networks EE249 Final Presentation David Tong Nguyen Abhijit Davare Mentor:
Impact of Radio Irregularity on Wireless Sensor Networks
A Survey of Energy-Efficient Scheduling Mechanisms in Sensor Networks Author : Lan Wang·Yang Xiao(2006) Presented by Yi Cheng Lin.
Results Showing the potential of the method for arbitrary networks The following diagram show the increase of networks’ lifetime in which SR I =CR I versus.
A Hierarchical Energy-Efficient Framework for Data Aggregation in Wireless Sensor Networks IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, VOL. 55, NO. 3, MAY.
IEEE INFOCOM 2005, Miami, FL RID: Radio Interference Detection in Wireless Sensor Networks Gang Zhou, Tian He, John A. Stankovic, Tarek F. Abdelzaher Computer.
Range-free Localization Schemes for Large Scale Sensor Networks
LPT for Data Aggregation in Wireless Sensor networks Marc Lee and Vincent W.S Wong Department of Electrical and Computer Engineering, University of British.
Extending Network Lifetime for Precision-Constrained Data Aggregation in Wireless Sensor Networks Xueyan Tang School of Computer Engineering Nanyang Technological.
USense: A Unified Asymmetric Sensing Architecture for Wireless Sensor Networks Yu Gu, Joengmin Hwang, Tian He and David Du Minnesota Embedded Sensor System.
University of Virginia1 TMMAC: An Energy Efficient Multi- Channel MAC Protocol for Ad Hoc Networks Jingbin Zhang †, Gang Zhou †, Chengdu Huang ‡, Sang.
Maximum Network lifetime in Wireless Sensor Networks with Adjustable Sensing Ranges Mihaela Cardei, Jie Wu, Mingming Lu, and Mohammad O. Pervaiz Department.
Radio-Triggered Wake-Up Capability for Sensor Networks Soji Sajuyigbe Duke University Slides adapted from: Wireless Sensor Networks Power Management Prof.
Talha Naeem Qureshi Joint work with Tauseef Shah and Nadeem Javaid
Achieving Long-Term Surveillance in VigilNet Pascal A. Vicaire Department of Computer Science University of Virginia Charlottesville, USA.
1 Energy Efficient Communication in Wireless Sensor Networks Yingyue Xu 8/14/2015.
December 3, 2009 Yu (Jason) RTSS ‘09 Spatiotemporal Delay Control for Low-Duty-Cycle Sensor Networks Yu (Jason) Gu 1, Tian He 1, Mingen Lin 2 and.
Lifetime and Coverage Guarantees Through Distributed Coordinate- Free Sensor Activation ACM MOBICOM 2009.
University of Virginia Wireless Sensor Networks August, 2006 University of Virginia Jack Stankovic.
Dynamic Clustering for Acoustic Target Tracking in Wireless Sensor Network Wei-Peng Chen, Jennifer C. Hou, Lui Sha.
Stochastic sleep scheduling (SSS) for large scale wireless sensor networks Yaxiong Zhao Jie Wu Computer and Information Sciences Temple University.
2015/10/1 A color-theory-based energy efficient routing algorithm for mobile wireless sensor networks Tai-Jung Chang, Kuochen Wang, Yi-Ling Hsieh Department.
College of Engineering Non-uniform Grid- based Coordinated Routing Priyanka Kadiyala Major Advisor: Dr. Robert Akl Department of Computer Science and Engineering.
1 EnviroStore: A Cooperative Storage System for Disconnected Operation in Sensor Networks Liqian Luo, Chengdu Huang, Tarek Abdelzaher John Stankovic INFOCOM.
Infocom’07 Authors:Liqian Luo, Chengdu Huang, Tarek Abdelzaher John Stankovic Presented By Rohini Kurkal Under Guidance of Dr.Bin Tang.
Maximum Network Lifetime in Wireless Sensor Networks with Adjustable Sensing Ranges Cardei, M.; Jie Wu; Mingming Lu; Pervaiz, M.O.; Wireless And Mobile.
1 A Bidding Protocol for Deploying Mobile Sensors GuilingWang, Guohong Cao, and Tom LaPorta Department of Computer Science & Engineering The Pennsylvania.
Presenter: Abhishek Gupta Dept. of Electrical and Computer Engineering
Efficient Energy Management Protocol for Target Tracking Sensor Networks X. Du, F. Lin Department of Computer Science North Dakota State University Fargo,
MMAC: A Mobility- Adaptive, Collision-Free MAC Protocol for Wireless Sensor Networks Muneeb Ali, Tashfeen Suleman, and Zartash Afzal Uzmi IEEE Performance,
1 VISA: Virtual Scanning Algorithm for Dynamic Protection of Road Networks IEEE Infocom’09, Rio de Janeiro, Brazil Jaehoon Jeong (Paul), Yu Gu, Tian He.
Achieving Long-Term Surveillance in VigilNet Tian He, Pascal Vicaire, Ting Yan, Qing Cao, Gang Zhou, Lin Gu, Liqian Luo, Radu Stoleru, John A. Stankovic,
Copyright © 2011, Scalable and Energy-Efficient Broadcasting in Multi-hop Cluster-Based Wireless Sensor Networks Long Cheng ∗ †, Sajal K. Das†,
University of Virginia Self-Organizing Wireless Sensor Networks in Action A Case Study Computer Science University of Virginia Jack Stankovic.
Low Power, Low Delay: Opportunistic Routing meets Duty Cycling Olaf Landsiedel 1, Euhanna Ghadimi 2, Simon Duquennoy 3, Mikael Johansson 2 1 Chalmers University.
A Wakeup Scheme for Sensor Networks: Achieving Balance between Energy Saving and End-to-end Delay Xue Yang, Nitin H.Vaidya Department of Electrical and.
Yu Gu and Tian He Minnesota Embedded Sensor System (MESS) Department of Computer Science & Engineering This work is supported by.
Ching-Ju Lin Institute of Networking and Multimedia NTU
An Energy-Efficient MAC Protocol for Wireless Sensor Networks Speaker: hsiwei Wei Ye, John Heidemann and Deborah Estrin. IEEE INFOCOM 2002 Page
CS 851 Presentation: Differentiated Surveillance for Sensor Network Presented by Liqian Luo Reference: 1. T. Yan, T. He, and J. A. Stankovic, “Differentiated.
Delivery ratio-maximized wakeup scheduling for ultra-low duty-cycled WSNs under real-time constraints Fei Yang, Isabelle Augé-Blum National Institute of.
Link Layer Support for Unified Radio Power Management in Wireless Sensor Networks IPSN 2007 Kevin Klues, Guoliang Xing and Chenyang Lu Database Lab.
Localized Low-Power Topology Control Algorithms in IEEE based Sensor Networks Jian Ma *, Min Gao *, Qian Zhang +, L. M. Ni *, and Wenwu Zhu +
Energy-Efficient Randomized Switching for Maximizing Lifetime in Tree- Based Wireless Sensor Networks Sk Kajal Arefin Imon, Adnan Khan, Mario Di Francesco,
0.1 IT 601: Mobile Computing Wireless Sensor Network Prof. Anirudha Sahoo IIT Bombay.
SenSys 2003 Differentiated Surveillance for Sensor Networks Ting Yan Tian He John A. Stankovic Department of Computer Science, University of Virginia November.
GholamHossein Ekbatanifard, Reza Monsefi, Mohammad H. Yaghmaee M., Seyed Amin Hosseini S. ELSEVIER Computer Networks 2012 Queen-MAC: A quorum-based energy-efficient.
Toward Reliable and Efficient Reporting in Wireless Sensor Networks Authors: Fatma Bouabdallah Nizar Bouabdallah Raouf Boutaba.
On Mobile Sink Node for Target Tracking in Wireless Sensor Networks Thanh Hai Trinh and Hee Yong Youn Pervasive Computing and Communications Workshops(PerComW'07)
University of Virginia Full Life Cycle Analysis for Wireless Sensor Networks January 10, 2007 Computer Science University of Virginia Jack Stankovic.
Scalable Coverage Maintenance for Dense Wireless Sensor Networks Jun Lu, Jinsu Wang, Tatsuya Suda University of California, Irvine Secon ‘ 06.
MAC Protocols for Sensor Networks
Towards Optimal Sleep Scheduling in Sensor Networks for Rare-Event Detection Qing Cao, Tarek Abdelzaher, Tian He, John Stankovic Department of Computer.
TripWire Section Qiuhua Cao April 23, 2004.
Energy-Efficient Communication Protocol for Wireless Microsensor Networks by Wendi Rabiner Heinzelman, Anantha Chandrakasan, and Hari Balakrishnan Presented.
Distributed Energy Efficient Clustering (DEEC) Routing Protocol
Introduction to Wireless Sensor Networks
Adaptive Topology Control for Ad-hoc Sensor Networks
Presentation transcript:

1 Achieving Long-Term Surveillance in VigilNet Tian He, Pascal Vicaire, Ting Yan, Qing Cao, Gang Zhou, Lin Gu, Liqian Luo, Radu Stoleru, John A. Stankovic, Tarek F. Abdelzaher Department of Computer Science, University of Virginia IEEE Infocom 2006

2 outlines Introduction Power management Power management in VigilNet System implementation System evaluation Conclusion

3 Introduction VigilNet  An Integrated Sensor Network System for Energy-Efficient Surveillance  Goal : to achieve long-term surveillance in a realistic mission deployment. long-term : minimum 3 ~6 months life time  tml tml

4

5 Introduction Energy efficiency  Single protocol : the hardware design 、 coverage 、 MAC 、 routing 、 data dissemination 、 data gathering 、 data aggregation 、 data caching 、 topology management 、 clustering 、 placement...etc.  Our : an integrated multi-dimensional power management system. tripwire service 、 sentry service 、 duty cycle scheduling

6 Introduction Contributions :  1) Our design is validated through an extensive system implementation: VigilNet – a large-scale sensor network system delivered to military agencies.  2) VigilNet takes a systematic approach. We propose a novel tripwire service, integrated with an effective sentry and duty cycle scheduling to increase the system lifetime.  3) We devote considerable effort to evaluate the system with 200 XSM motes in an outdoor environment and an extensive simulation of 10,000 nodes.

7 Power management Sampling System  regular reporting Ex : Great Duck Island  Predefined sampling schedules Nodes can conserve energy by turning themselves off, according to a predefined schedule.  Synchronized and coordinated operations Once the sampling interval is defined a priori, nodes can communicate in a synchronized fashion.  Data aggregation and compression Since channel media access is costly, especially when the receiver is in a deep-sleep state

8 Power management Surveillance System : event-driven  Coverage control activating only a subset of nodes at a given point of time, waiting for potential targets.  Duty cycle scheduling By coordinating nodes’ sleep schedules, we can conserve energy without noticeably reducing the chance of detection.  Incremental activation First activate only a subset of sensors for the initial detection, then activate other sensors to achieve a higher sensing fidelity.

9 Power management in VigilNet Power management requirements in VigilNet  Continuous surveillance VigilNet is a military surveillance application.  Real-time VigilNet is a real-time online system for target tracking.  Rare and critical event detection VigilNet deals with the rare and critical event model. In this model, the total duration of events is small.  Stealthiness Deployed in hostile environments, miniaturization makes nodes hard to detect.  Flexibility the deployment of VigilNet is under different densities, topologies, sensing and communication capabilities.

10 Power management in VigilNet 3 main power management strategies in VigilNet  tripwire service  sentry service  duty cycle scheduling

11 Tripwire Services Divides the sensor field into multiple sections, called tripwire sections, and applies different working schedules to each tripwire section.  A tripwire section can be either in an active or a dormant state.

12 Tripwire Services Tripwire partition  VigilNet implements its tripwire partition policy based on the Voronoi diagram. Can reduce the energy consumption and the end-to-end delay in data delivery.  A network with n bases is partitioned into n tripwire sections and each tripwire section contains exactly one base i. Every node in the network uniquely belongs to one and only one tripwire section.  The base placement strategy is normally determined by the mission plan and topology.

13 Tripwire Services Tripwire partition mechanism  1) each base broadcasts one initialization beacon to its neighbors with a hop count parameter initialized to one  2) Each receiving node maintains the minimum hop- count value of all beacons it received from the nearest base, in terms of the physical distance.  Supported partition policies  Hop count (currently used)  Distance

14 Data Structure Maintenance TripWire Table Max Num of TripWire Base a node can remember, currently set be 5 TripWire IDHopsstatus (active, dormant)

15 12 Green: Base (active), Blue: Base (dormant), Yellow: Motes Red: example node

16 12 Green: Base (active), Blue: Base (dormant), Yellow: Motes Red: example node

17 12 Green: Base (active), Blue: Base (dormant), Yellow: Motes Red: example node ………... Find min hop, if it choose the first one

18 Tripwire Services

19 Tripwire Services Tripwire scheduling  Configure the state of each tripwire section by setting a 16 bits schedule.  Each bit in the schedule denotes the state of this tripwire section in each round (rotation) up to 16 rounds.  After 16 rounds, the pattern is repeated.  Can assign different schedules to each tripwire and assign 65536^N (N is the number of tripwires.) different schedules to the network.  The schedule can be predetermined or randomly generated. Random scheduling is done by setting the Tripwire Duty Cycle (TDC), which is the percentage of active rounds in the schedule.

20 Sentry service The main purpose of the sentry service is to select a subset of nodes, called sentries. 2 phases  1) Nodes exchange neighboring information through hello messages. a sender attaches its node ID, position, number of neighbors and its own energy readings.  2) each node sets a delay timer Renergy : weighted Energy rank Rcover : weighted Cover rank Our : Renergy = Rcover

21 Sentry service Range of Vicinity (ROV)  The effective range, in physical distance, of a sentry’s declaration message.  1) How to choose ROV? The sentry density is upper bounded by to achieve a 99% detection probability  a sentry density of nodes/m2 (ROV= 6 meters) with 8 meter sensing range  a lower density of nodes/m2 (ROV=8.5 meters) with 14 meters sensing range

22 Sentry service  2) How to enforce ROV ? discard declaration messages from any sentry beyond the distance of ROV. provides a more predictable sentry distribution  Localization[38] is supported in VigilNet.

23 Sentry duty cycle scheduling Ton be the active duration Toff be the inactive duration Sentry Toggle Period (STP) : Ton + Toff Sentry Duty Cycle (SDC) : Ton / STP  lowering the SDC value increases the detection delay and reduces the detection probability Use random duty cycle scheduling, not the sophisticated / optimal scheduling algorithms[33] to coordinate node activities to maximize performance

24 Integrated solution tripwire service controls the network- wide distribution of power consumption among sections  Tripwire Duty Cycle (TDC), the percentage of active time for each tripwire section, to control the network- wide energy burning rate. sentry service controls the power distribution within each section.  use the Range of Vicinity (ROV) parameter to control the energy-burning rate of active sections. duty cycle scheduling controls the energy-burning rate of individual sentry nodes  Sentry Duty Cycle (SDC) parameter is used to control the awareness of sentry nodes, which is the percentage of active time

25 System implementation

26 System implementation OS : TinyOS Language : NesC Code size : about 40,000 lines of code, supporting MICA2 and XSM mote platforms.  83,963 bytes of code memory  3,586 bytes of data memory Nodes are randomly placed roughly 10 meters apart, deployed 200 XSM motes on a dirt T-shape road (200 * 300 meters).

27

28 System evaluation

29 The Voronoi-based tripwire partitioning is very effective and that all nodes attach to the nearest base nodes through the shortest path.

30

31 It is not the case that nodes with high voltages are always selected as sentries. The average minimum distances between sentry- pairs is 9.57 meters with 1.88 meters standard deviation.

32 communication delay < detection report < classification delay < velocity estimations delay

33 SSA (Sentry Service Activation) 1)To reduce the detection delay, choose a sentry toggle period as small as possible. 2)To increase the network lifetime, select a small sentry duty cycle. SDC↓, detection delay↓

34 SDC↓, detection prob↑

35 STP↓, detection delay↓ STP↓, detection prob↑

36 a low tripwire duty cycle(TDC) increases the network lifetime, but increases the detection delay and decreases the detection probability TDC↓, detection prob↓ TDC↓, detection delay↑

37 it takes more time to detect slow targets than faster ones; a high target speed decreases the detection delay Target speed ↑, detection delay↓

38 Conclusions It is a comprehensive case study on power management in a realistic environment with a large testbed. Investigate the power management at the network, section and node level by using a novel tripwire service, sentry service and duty cycle scheduling, respectively.

39 References [7] T. Yan, T. He, and J. Stankovic, “Differentiated Surveillance Service for Sensor Networks,” in SenSys 2003, November [33] Q. Cao, T. Abdelzaher, T. He, and J. Stankovic, “Towards Optimal Sleep Scheduling in Sensor Networks for Rare Event Detection,” in IPSN’05, [37] G.Simon and et. al., “Sensor Network-Based Countersniper System,” in SenSys 2004, November [38] T. He, S. Krishnamurthy, J. A. Stankovic, and T. Abdelzaher, “An Energy-Effi cient Surveillance System Using Wireless Sensor Networks,” in MobiSys’04, June [39] R. Stoleru, T. He, and J. A. Stankovic, “Walking GPS: A Practical Solution for Localization in Manually Deployed Wireless Sensor Networks,” in EmNetS-I, October [41] G. Zhou, T. He, and J. A. Stankovic, “Impact of Radio Irregularity on Wireless Sensor Networks,” in MobiSys’04, June [43] T. He, C. Huang, B. M. Blum, J. A. Stankovic, and T. Abdelzaher, “Range-Free Localization Schemes in Large-Scale Sensor Networks,” in MOBICOM’03, September [44] T. He, B. M. Blum, J. A. Stankovic, and T. F. Abdelzaher, “AIDA: Adaptive Application Independent Data Aggregation in Wireless Sensor Networks,” ACM Transactions on Embedded Computing System, Special issue on Dynamically Adaptable Embedded Systems,

40 References Tian He, Pascal Vicaire, Ting Yan, Qing Cao, Gang Zhou, Lin Gu, Liqian Luo, Radu Stoleru, John A. Stankovic, and Tarek Abdelzaher. Achieving Long-Term Surveillance in VigilNet. IEEE Infocom, April Liqian Luo, Tian He, Gang Zhou, Lin Gu, Tarek Abdelzaher, and John Stankovic. Achieving Repeatability of Asynchronous Events in Wireless Sensor Networks with EnviroLog. IEEE Infocom, April 2006 Qing Cao, Tian He, Lei Fang, Tarek Abdelzaher, John Stankovic, and Sang Son. Efficiency Centric Communication Model for Wireless Sensor Networks. IEEE Infocom, April 2006 Gang Zhou, Chengdu Huang, Ting Yan, Tian He, and John A. Stankovic. MMSN: Multi-Frequency Media Access Control for Wireless Sensor Networks. IEEE Infocom, April 2006