Application Specific Large Scale Sensor Networks

Transcription

1 c 2005 Cornell Sensor Network Workshop 1 Application Specific Large Scale Sensor Networks Architecture, Energy Efficient Protocols, and Signal Processing Lang Tong Adaptive Communications and Signal Processing Group School of Electrical and Computer Engineering Cornell University, Ithaca, NY This work is supported in part by the the Army Research Laboratory CTA on Communication and Networks, Army Research Office, Office of Naval Research Office, and National Science Foundation.

2 c 2005 Cornell Sensor Network Workshop 2 The Internet and Layered Architecture WAN PSfrag LAN replacements Application WAN LAN Transport Network Data Link MAC LAN Physical Objectives Millions of users Thousands of applications A growing variety of devices. The need of layered approaches: Partition network functions into layers Design each layer separately

3 c 2005 Cornell Sensor Network Workshop 3 Sensor Networks are Application Specific Weather Environment Military Seismic Network with purposes. Unconventional design metrics Harsh design constraints What should be the appropriate design paradigm?

4 c 2005 Cornell Sensor Network Workshop 4 Large Scale Sensor Networks Applications Target detection and tracking. Surveillance Environmental monitoring Low-power low-cost sensors Random deployment Large number of nodes. Internet Design Challenges Architecture Physical Layer Design Protocols Network Maintenance. Security and Trust.

5 c 2005 Cornell Sensor Network Workshop 5 Outline Architecture Sensor Networks with Mobile Access (SENMA) Experimental Testbed. Energy Efficient Protocols Opportunistic Random Access Energy Efficient Adaptive Routing Communication and Signal Processing How many sensors are alive and for how long? Cooperative network with misinformed nodes Nonparametric event change detection and localization. Target detection and tracking in SENMA.

6 c 2005 Cornell Sensor Network Workshop 6 Sensor Network Architectures Multi-hop Sensor Network Stationary sensors and gateway nodes. Multi-hop to/from gateway nodes. Sensors talk to sensors. Asymmetric and correlated traffic.

7 c 2005 Cornell Sensor Network Workshop 7 Sensor Network Architectures Multi-hop Sensor Network Stationary sensors and gateway nodes. Multi-hop to/from gateway nodes. Sensors talk to sensors. Asymmetric and correlated traffic. Mobile Access Points Sensor Network with Mobile Access Mobile APs + stationary nodes. Sensors talk directly to APs. Stationary sensors driven by mobile APs. Asymmetric resources. Sensor Networks

8 c 2005 Cornell Sensor Network Workshop 8 SENMA: SEnsor Network with Mobile Access Mobile Access Points Sensor Networks Mobile access points can be UAV, UGV, submarine, doves, dogs... Mobile access points are not energy constrained. Suitable for clock-driven and query-driven applications. L. Tong, Q. Zhao, and S. Adireddy, Sensor Networks with Mobile Agents (SENMA), Proc. IEEE MILCOM, Oct., 2003.

9 c 2005 Cornell Sensor Network Workshop 9 Acoustic SENMA: System Configuration Mobile Access Point Sound Processing/ Network Performance Analysis Sensor Field

10 c 2005 Cornell Sensor Network Workshop 10 Outline Architecture Sensor Networks with Mobile Access (SENMA) Experimental Testbed. Energy Efficient Protocols Opportunistic Random Access Energy Efficient Adaptive Routing Communication and Signal Processing How many sensors are alive and for how long? Cooperative network with misinformed nodes Nonparametric event change detection and localization. Target detection and tracking in SENMA.

11 c 2005 Cornell Sensor Network Workshop 11 Opportunistic Communications and Networking γ1(t) γ2(t) γ1 γ2 r t Mobile AP Sensors Only user 1 Only user 2 Opportunistic Communications Design Rationale Mobility of AP induces fading. Fading leads to channel fluctuations. Wait for chances. Save power Act when opportunities arise.

12 c 2005 Cornell Sensor Network Workshop 12 Opportunistic Communications and Networking γ1(t) γ2(t) γ1 γ2 r t Mobile AP Sensors Only user 1 Only user 2 Opportunistic Communications Design Rationale Mobility of AP induces fading. Fading leads to channel fluctuations. Wait for chances. Save power Act when opportunities arise.

13 c 2005 Cornell Sensor Network Workshop 13 Opportunistic Medium Access Control Distributed Opportunistic MAC γ F (γ) Channel Acquisition Estimate γ from beacon. Opportunistic ALOHA Transmit with probability s(γ). Opportunistic CSMA Sense carrier with backoff τ(γ). Slot t Data Advantages Simplicity. Scalability. Beacon Energy Efficiency. P. Venkitasubramaniam, S. Adireddy and L. Tong Sensor Networks with Mobile Access: Optimal Random Access and Coding, To appear in IEEE JSAC: Special Issue on Sensor Networks Q. Zhao and L. Tong, Distributed Opportunistic Information Retrieval in Sensor Networks: CSI-Based Carrier Sensing, ICASSP 04, Also submitted to IEEE Trans. Wireless Communications.

14 c 2005 Cornell Sensor Network Workshop 14 Opportunistic Medium Access Control Distributed Opportunistic MAC γ F (γ) Channel Acquisition Estimate γ from beacon. Opportunistic ALOHA Transmit with probability s(γ). Opportunistic CSMA Sense carrier with backoff τ(γ). Slot t Data Advantages Simplicity. Scalability. Beacon Energy Efficiency. P. Venkitasubramaniam, S. Adireddy and L. Tong Sensor Networks with Mobile Access: Optimal Random Access and Coding, To appear in IEEE JSAC: Special Issue on Sensor Networks Q. Zhao and L. Tong, Distributed Opportunistic Information Retrieval in Sensor Networks: CSI-Based Carrier Sensing, ICASSP 04, also submitted to IEEE Trans. Wireless Communications.

15 c 2005 Cornell Sensor Network Workshop 15 Energy Efficient Adaptive Routing S D R r λ Total energy consumption R=1000,N=30k,Bm=500,τ=300,p o =0.01 proactive reactive hybrid S D R r Q. Zhao and L. Tong, Energy Efficiency of Ad Hoc Networks: An Analysis of Proactive, Reactive, and Hybrid Networking Strategies, submitted to IEEE INFOCOM, July, 2004.

16 c 2005 Cornell Sensor Network Workshop 16 Outline Architecture Sensor Networks with Mobile Access (SENMA) Experimental Testbed. Energy Efficient Protocols Opportunistic Random Access Energy Efficient Adaptive Routing Communication and Signal Processing How many sensors are alive and for how long? Cooperative network with misinformed nodes. Nonparametric event change detection and localization. Target detection and tracking in SENMA.

17 Problem : Estimate the number of operating sensors and the histogram of the energy distribution using the information in the received packets. Power level [%] Number of nodes [%] 5 10 dead hidden observed 15 Power level distribution Operating Sensors and Energy Distribution c 2005 Cornell Sensor Network Workshop 17

18 c 2005 Cornell Sensor Network Workshop 18 Two Approaches in Monitoring Wireless Sensor Networks Counting via Scheduled Interrogation Ask each sensor transmit and count the number of successes Central scheduling is needed. Mobile AP must address sensors individually. Requiring at least O(N) and more if channel has fading and interferences. Counting via Random Collection Collect packets randomly and count the number of successes. Distributed transmission with simple medium access. For such a method to be effective, it requires N log N + O(N) successfully received transmissions. Example: N = 1000, on the order of 10, 000 successful receptions are needed.

19 c 2005 Cornell Sensor Network Workshop 19 Two Approaches in Monitoring Wireless Sensor Networks The Estimation Approach In network monitoring, the exact values of the network parameters are not required. Estimate the number of operating sensors using the statistical properties of the received samples. Question: Can we estimate accurately using less than N log N + O(N) samples? C. Budianu, S. Ben-David and L. Tong, Estimation of the Number of Operating Sensors in Large Scale Sensor Networks, ICASSP 2004, also submitted to IEEE Trans. Signal Proc., June, 2004.

20 c 2005 Cornell Sensor Network Workshop 20 Cooperative SENMA with Misinformed Sensors q(y x) q(y x) In cooperative sensor networks, sensors may not agree with each other. What is the maximum rate of information retrieval with the presence of misinformed sensors? Z. Yang and L. Tong, Cooprative Sensor Networks with Misinformed Sensors, Proc. of the 38th Annual Conference on Information Sciences and Systems (CISS 04), Princeton, NJ, March To be submitted to IEEE Trans. Information Theory, July, Z. Yang and L. Tong, The effect of fading on the achievable rate of cooperative sensor networks with misinfomred sensors, to appear in IEEE 2004 GLOBECOM,

21 c 2005 Cornell Sensor Network Workshop 21 Nonparametric Event Change Detection and Localization First data collection Second data collection Is there a change in the distributions of red and green? where? Can we guarantee detection precision? What is the computation complexity? S. Ben-David, T. He and L. Tong, Non-Parametric Approach to Change Detection and Estimation in Large Scale Sensor Networks, Proc. of the 38th Annual Conference on Information Sciences and Systems (CISS 04), Princeton, NJ, March 2004.

22 c 2005 Cornell Sensor Network Workshop 22 Stepping Stone Attack Detection of Stepping Stone Attack The attacker uses a chain of compromised hosts to construct a sequence of interactive attacks Quickest Attack Detection Detect possible stepping-stone attack pairs based on statistical properties of incoming and outgoing traffic. T. He and L. Tong, Detection of Encrypted Interactive Stepping Stone Attack: Algorithms and Performance, to be submitted to IEEE Trans. Signal Processing.

23 c 2005 Cornell Sensor Network Workshop 23 Target Detection and Tracking Mobile Access Points Control Center Sensor Networks Sensors perform low quality DoA estimation and target classification. The fusion center estimates the field parameters. Develop optimal detection, estimation, and fusion algorithms.

24 c 2005 Cornell Sensor Network Workshop 24 Related Projects National Science Foundation Signal Processing for Random Access: A Cross Layer Approach. SENSORS: The Reachback Channel in Wireless Sensor Networks. (Servetto (PI)) NET-NOSS: Ultra Low-Power Self-Configuring Wireless. (Wicker (PI)) TRUST: Team for Research in Ubiquitous Secure Technology (Wicker (PI)) Office of Naval Research Channel and QoS Adaptive Multimedia Wireless Ad-Hoc Networks (with Haas, Hemami, Manohar, Wicker, Proakis, Nahrstedt). DARPA Connectionless Networking. Army Research Laboratory Signal Processing for Sensor Networks. Cross Layer Design for Wireless Networks. Direction of Arrival Estimation with Networked Sensors.