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Opportunistic Networks: Specialized Ad Hoc Networks for Emergency Response Applications

Opportunistic Networks: Specialized Ad Hoc Networks for Emergency Response Applications. Leszek Lilien WiSe Lab (Wi reless Sensornet Laboratory) http://www.cs.wmich.edu/wsn Department of Computer Science Western Michigan University Kalamazoo, MI 49008. Outline.

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Opportunistic Networks: Specialized Ad Hoc Networks for Emergency Response Applications

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  1. Opportunistic Networks:Specialized Ad Hoc Networksfor Emergency Response Applications Leszek Lilien WiSe Lab (Wireless Sensornet Laboratory) http://www.cs.wmich.edu/wsn Department of Computer Science Western Michigan University Kalamazoo, MI 49008

  2. Outline • Part 1. Motivation for Specialized Ad Hoc Networks • Part 2. Analogy to a Human Emergency Response Team • Part 3. Opportunistic Networks: A New Type of Specialized Ad Hoc Networks • Part 4. Related Research and Research Challenges • Part 5. Conclusions • Part 6. Current and Future Work 2

  3. Part 1. Motivation forSpecialized Ad Hoc Networks • Homeland Security • One of the crucial challenges facing the USA today • Among its 6 mission areas is Emergency Preparedness and Response(EPR) • EPR deals with: • Natural disasters • Man-made disasters (incl. accidents, terrorist attacks) [Natl. Strategy for Homeland Security, July 2002] • Mobile ad hoc networks (MANETs) proposed for EPR [Haas, 1999] 3

  4. Motivation forSpecialized Ad Hoc Networks (2) • MANETS are notquitea natural match for EPR • E.g., human rescue teams can find and mobilize as their helpers local firemen, police, National Guard or even regular citizens • No analogous capability of MANETs to find and “mobilize” devices/networks • Let’s find or define a specialization (a subclass) of ad hoc networks more suitablefor EPR applications • A new paradigm and a new technology to improve effectiveness & efficiency of EPR 4

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  6. Part 2. Analogy toa Human Emergency Response Team • Important characteristics of a human rescue team • Starts as a seed team(a small group of people) • The seed team growsopportunistically during its operations • Some people can always be ordered to join • Police, firemen, National Guard or Army Reserve personnel • Anybody can be ordered to join only in life-or-death situations • Legally required to help saving lives or critical resources • Anybody can be asked to join in other situations 6

  7. Analogy to a Human Emergency Response Team (2) • Who is ordered or invited to join? • In some situations any extra pair of hands can help • In others onlyhighly qualified people (e.g., doctors and nurses) are ordered/asked to join • Human helper types • Highly prepared • E.g., National Guard, Army Reserve or state militias • Signed up for service • Undergo training in preparation for duty (even unforeseen) • Somewhat prepared • E.g., people that volunteer for first aid courses • Become pretty valuable helpers in emergencies • Not prepared at all 7

  8. Analogy to a Human Emergency Response Team (3) • Benefits of the opportunistic growth of the rescue team • Opportunistic leveraging of all kinds of skills and resources that new helpers can bring • Obtaining a lot of help effectively and efficiently – even for free 8

  9. Analogy to a Human Emergency Response Team (4) • Analogous critical requirements for ad hoc network specialized for EPR in the priority order: • Minimal starting configuration – a pre-configured seed for EPR operations Analogy to the seed rescue team • High interoperability in terms of communication of diverse devices or networks(Wired/WiFi, Bluetooth, satellite, ham radios, WiMAX, ...) Analogy to a rescue team’s ability to contact different people, individually or via organizations • Highly heterogeneous software (& hardware) Analogy to heterogeneity of rescue teams in terms of members’ skills, communication and other equipment, and other resources • Harvesting of diverse resources as needed Analogy to finding people with different skills, equipment, and other resources • Persistent connectivity once it is established Analogy to being able to contact (maybe via a chain of others) members of the expanded team, including all helpers 9

  10. Analogy to a Human Emergency Response Team (5) • If there is no specialized ad hoc network (AHN) matching the requirements, then: • Define a new specialized AHN paradigm • Invent a new specialized AHNtechnology • No known specialized AHN matches the requirements Considered AHNs: • Mobile ad hoc networks (MANETs) • Mesh networks • P2P systems • Sensor networks • Spontaneous networks (in the narrow sense, cf. [Feeney et al. 2001]) => Need: - a new specialized AHNparadigm - a new specialized AHNtechnology 10

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  12. Part 3. Opportunistic Networks: A New Type of Specialized Ad Hoc Networks • Paradigm of Opportunistic Networks (Oppnets) • Based on the analogy to operations of human rescue teams • Goals of oppnets: • Opportunistic growth • Opportunistic leveraging of resourcesaiming at (among others): • Bridging diversecommunication media • Offloading computations to additional platforms • Integrating independent sensing systems(enhancing their sensing capabilities) 12

  13. Link to the World Seed Nodes Controller (distributed) Startup: Seed Oppnet • Oppnet deployed as a seed oppnet • Seed oppnet localizes its nodes & self-configures 13

  14. Satellite Link to the World Appliance (refrigerator) Cellphone Tower Seed Nodes Controller (distributed) WiMAX Overturned Vehicle (with OnStar) Computer Network Growth: Expanded Oppnet • Seed oppnet grows into an expandedoppnet by: • Finding candidate helpers • Selecting candidates - they are ordered/asked to join • Add communication, computing, sensing, storage, other resources 14

  15. Summary of Oppnet Activities • Discovering & identifying candidate helpers • Contacting selected candidates • Invitingor orderingcandidates to join • Admitting & integrating helpers that join oppnet • Offloading tasks to helpers • Determining useful colaborative functionalities • Managing offloaded tasks • Cleaning up & releasing each helper when no longer needed 15

  16. Oppnet Reserve • A challenge in oppnet growth • Must discover candidate helpers, then contact selected ones • Difficult without facilities provided by candidates or infrastructure • A solution: oppnetreserve — facilitating discovery/contacting • Analogy to Army / Navy / Air Force Reserve, etc. • Volunteer helpers sign up for oppnet reserve • Maybe for some incentives(moral, financial, etc.) • Volunteers „trained” for active duty • Install facilities that make them easier to detect and contact by oppnets • E.g., install (future) standard oppnet protocols • Matched to their capabilities: heavy-, medium- and lightweight • Available for active oppnet duty whenever must/can help 16

  17. Oppnet Reserve (2) • Oppnet reserve is analogous to having highly prepared human helpers (Recall the classification of human helpers into: highly prepared, somewhat prepared, unprepared) • Oppnet reserve is not required but very helpful • Having highly prepared human helpers is not required either 17

  18. Basic Oppnet Categories • 2 major oppnet categories: • Benevolent oppnets • Malevolent oppnets • Corresponding oppnets scenarios: • Benevolent oppnet scenario: „Citizens Called to Arms” • Malevolent oppnet scenario: „Bad Guys Gang Up” 18

  19. 19 BenevolentOppnetScenario: „Citizens Called to Arms” (1) • Seed oppnet deployed after an earthquake(un- predictable emergency) • Seed is ad hoc wireless network with very powerful nodes • More energy, computing and communication resources • Seed tries to detect candidate helpers • For help in damage assessment and disaster recovery • Uses any available detection method — including: • Cellphone- or radio-based detection • Searching for nodes using the IP address range for the affected geographic area • AI-based visual detection(next) 19

  20. 20 BenevolentOppnetScenario: „Citizens Called to Arms” (2) • Example: • Helper 1 (supervisor of security cameras)monitoring a surveillance net views an overturned car • Helper 2(pattern recognition specialist)detects an overturned car • Helper 3(image analysis specialist)asked to recognize its license plate • Helper 4(DB manager)finds that the cars has OnStar link • Helper 5(OnStar agent)contactsBANs(Body Area Networks) on or within bodies of car occupants via OnStar infrastructure • Helper 6(vital sign evaluator)evaluates obtained info • Helper 7 (rescue dispatcher) decides if/when rescuers should be dispatched 20

  21. 21 BenevolentOppnetScenario: „Citizens Called to Arms” (3) • Oppnet selects optimalsubset of detected nodes • Inviting devices, clusters & entire networks • Helpers for communicating, sensing, computing • Using „hidden” capabilities, e.g. for sensing: • Desktop can „sense” presence of a potential victim at its keyboard • Cellphones can „sense” location • Even ones w/o GPS can be triangulated 21

  22. 22 Benevolent OppnetScenario: „Citizens Called to Arms” (4) • Using „hidden” emergency functionalities • Oppnet contacts 2 independent sensornets (SNs): water infrastructure control SN / public space surveillance SN • SNs ordered to abandon normal functions& help inrescue & recovery operations • Water infrastructure SN(with multisensor capabilities, under road surfaces) — ordered to sense vehicular movement and traffic jams • Public space surveillance SN — ordered to search for images of human victims 22

  23. MalevolentOppnetScenario: „Bad Guys Gang Up” (1) 23 • Scenario 1 — Terrorists createapparently harmless weather monito- ring sensornet (SN): • SN becomes a seed of a malevolent opportunistic SN • SN exploits other nodes from many other networks(w/o revealing its true goals) • “Critical mass” of the opportunistic SN is reached (in terms of geographical spread and sensing capabilities) • SN waits for wind patterns that can speed up spread of poisonous chemicals • Collected data used to decide when to start chemicalattack 23

  24. MalevolentOppnet Scenario:„Bad Guys Gang Up” (2) • Scenario 2 — network at home starts spying on you: • Becomes a seed oppnet • Exploits other devices/nets to collect all info on you: • From your fridge(& RFID-equipped food packaging): what/when you eat • From your computer: keylogs your passwords, sensitive data • From your cellphone: who you call & when • From your networked camera: what photos you take • From your home security surveillance system: your private images • Cyberfly with camera eyes and microphone ears • ... • Huge privacy problem! / Huge security problem! • Controls to counteract malevolent oppnets badly needed 24

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  26. Part 4. RelatedResearchand Research Challenges • Examples of Related Research • Interoperability • Among wireless networks - active research area • Among WANs, MANs, LANs, PANs(Personal Area Networks), etc. • Amongwired & wirelessnets - much less research • Ambient Networks(big European Union project, next-generation Internet—for 2015/2020, smaller networks able to compose themselves into bigger ones) • Localization andself-organization • MANETs / Sensornets • Network growth • P2P systems – search for peers in unstructured systems • Trojan Horses - agents spreading in search for helpers • Integrating and managing heterogeneous systems, incl. data integration & aggregation • Grid systems / MANETs / Sensornets • Other • … 26

  27. Research Challenges in Basic Operations • Challenges in seed oppnet deployment • E.g., localization, self-configuration, adaptability • Challenges in detecting helper systems • E.g., define primitivesto detect candidates, identify and categorize them, evaluate and classify them(e.g., based on dependability and usefulness) • Challenges in inviting & admitting candidate helpers • E.g., select candidates to invite, develop protocols for candidates to accept or reject invitation, devise primitives/methods to manage expanded oppnets • Etc., etc. for remaining oppnet primitives More: Leszek Lilien, Z. Huma Kamal, and Ajay Gupta, "Opportunistic Networks: Research Challenges in Specializing the P2P Paradigm,” Proc. 3rd International Workshop on P2P Data Management, Security and Trust (PDMST’06), Kraków, Poland, September 2006 (to appear) 27

  28. Research Challenges in Privacy & Security (1) • Privacy challenges in oppnets • Privacy is critical • Oppnets are pervasive systems • Must face all critical privacy challenges inherent to pervasive computing • Privacy is a „make it or break it” issue for pervasive computing => Privacy is a „make it or break it” issue for oppnets • Basic privacy protection goals in oppnets • Protecthelper resources from the host oppnet • Protectoppnet from its helpers • Protectenvironment from privacy violations by oppnet • Also from malevolent oppnets 28

  29. Research Challenges in Privacy & Security (2) 2) Securitychallenges in oppnets • Many have privacy aspects/components More: Leszek Lilien, Z. Huma Kamal, Vijay Bhuse and Ajay Gupta, "Opportunistic Networks: The Concept and Research Challenges in Privacy and Security,” Proc. International Workshop on Research Challenges in Security and Privacy for Mobile and Wireless Networks (WSPWN 2006), Miami, Florida, March 2006. 29

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  31. Part 5. Conclusions • High-payoff potential for the oppnet initiative • Social and economic benefits • Including reduction of human suffering & loss of life • Technological benefits • Research benefits • Educational benefits -- Details below -- 31

  32. 1) Social & Economic Impacts • Impacts onEmergency Preparedness and Response operationsin Homeland Security (HS) — current app focus • Tremendous leveraging potential in emergencies • A wealth of freely availableresources • Reduction of human suffering & loss of life • Increasing safety & efficiency of the first responders • Impacts on other applications both in HS and outside HS • Economic impacts • Technology transfer &commercialization • Benefits for the computer industry • Production of software / networking equipment • Benefits for other industries • Enhancing many products with standard oppnet interfaces • E.g., the auto industry: cars and trucksas oppnet platforms 32

  33. 2) Impacts on Technology • Advancing the network and pervasive computing know-how • Development of the innovative oppnet technology • Enhancing network/pervasive applications by use of oppnet technologies • Enabling new network/pervasive application niches we can not even foresee • Advancing other areas of technology(not only computing) • Aside effect of oppnet developments • Technology impacts speeded up & enhanced by the planned technology transferpluscommercialization activities 33

  34. 3) Impacts on Research • Encouraging oppnet research • Building our oppnet research team at WMU • 4 professors, 2 Ph.D. students(incl. a Ph.D. dissertation), other students • 2 high-tech companies specializing in EPR products • From Ann Arbor - Michigan’s equivalent of the Sillicon Valley • Summer 2006: 1 more Ph.D. student, ≥1 M.S. students • Fall 2006: many student projects • Initiating research collaboration with researchers outside of the WMU • Encouraging independent oppnet research • Applying for state, NSF, and other funding for Ph.D. students and other students, post docs, and visiting faculty • Dissemination of research results and products: • Presentations: publications, seminars, poster sessions • A dedicated web site • Public availability of the oppnet prototype, tools & data 34

  35. 4) Impacts on Education • Impact on students • For project participants: hands-on training on the B.S./M.S./Ph.D levels • For others: course enhancements / course projects / seminars • Oppnet prototype used for lab experiments • Outreach activities • Including K-12 demos for underrepresented minorities • All activities will broadenthe America’s talent pool in critical technologies and applications • Training more minority & female students at all levels 35

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  37. Part 6. Current and Future Work • Building an oppnetprototype • Goal: Proof of concept • To demonstrate technical prowess & economic benefits • Designing oppnet architecture • With its associated components: • Methods, protocols, and algorithms • Oppnet prototype implementation • For stimulation and feedback • Necessary for fine-tuning oppnet design • Technology transfer&commercialization • Mentioned above 37

  38. More Details of Oppnet Prototyping • Building state-of-the-art lab facilities • Constructing an oppnetprototype in the lab • Developing performance analysis tools to support testing & fine-tuning activities • Extendingthe prototype toinclude living-laboratoryresources available in our sensor- & computer-rich building • Testingthe prototype within the living laboratory • For fine-tuning design & implementation • Obtainingexternal assessment of the prototype • From computer & homeland security labs in MI, IN, IL 38

  39. Search for Other Oppnet Applications • Search for oppnet utilization in all kinds of application areas • Search for applications that ... • ... can start with a seed • ... need high interoperability • ... need highly heterogeneous software • ... can benefit from leveraging diverse resources of helpers • ... can maintain persistent connectivity once it is established • ... • Welcome collaboration or independent contributions • Seeking funding that will allow to fund: • Ph.D. students (dissertations on oppnets) • Post docs (e.g., 3-12 months) • Visiting faculty (e.g., 1-6 months) 39

  40. Publications onOppnets(intensive work on oppnets started in our WiSe Lab in December 2005) • Leszek Lilien and Ajay Gupta, ” Opportunistic Networks for Emergency Preparedness and Response” (submitted for publication). • Leszek Lilien, Z. Huma Kamal, and Ajay Gupta, "Opportunistic Networks: Research Challenges in Specializing the P2P Paradigm,” Proc. 3rd International Workshop on P2P Data Management, Security and Trust (PDMST’06), Kraków, Poland, September 2006 (to appear) • Leszek Lilien, “Developing Specialized Ad Hoc Networks: The Case of Opportunistic Networks,” Proc. Workshop on Distributed Systems and Networks at the WWIC 2006 Conference,Bern, Switzerland, May 2006 (invited paper, proceedings to appear). • Leszek Lilien, Z. Huma Kamal, Vijay Bhuse and Ajay Gupta, "Opportunistic Networks: The Concept and Research Challenges in Privacy and Security,” Proc. International Workshop on Research Challenges in Security and Privacy for Mobile and Wireless Networks (WSPWN 2006), Miami, Florida, March 2006. • B. Bhargava, L. Lilien, A. Rosenthal, and M. Winslett, “Pervasive Trust,” IEEE Intelligent Systems, vol. 19(5), Sep./Oct.2004, pp. 74-77 (first brief mention of the oppnet idea, in the form of malevolent opportunistic sensor networks). 40

  41. Selected WiSe Lab Publications on Privacy, Trust, Security, Pervasive Computing & Sensornets • V. Bhuse, A. Gupta, and L. Lilien, "Research challenges in lightweight intrusion detection for sensornets" (submitted for publication). • L. Lilien and B. Bhargava, ”A Scheme for Privacy-preserving Data Dissemination,” IEEE Transactions on Systems, Man and Cybernetics (to appear). • T. Canli, M. Terwilliger, A. Gupta and A. Khokhar, "Power Efficient Algorithms for Computing Fast Fourier Transform over Wireless Sensor Networks," Proc. Fourth ACS/IEEE Conference on Computer Systems and Applications, Dubai, UAE, March 2006. • V. Bhuse, A. Gupta and L. Lilien, "DPDSN: Detection of packet-dropping attacks for wireless sensor networks," Proc. 4th   International Trusted Internet Workshop (TIW), International Conference on High Performance Computing, Goa, India, December 2005. • A. Gupta and V. Bhuse, “Anomaly Intrusion Detection in Wireless Sensor Networks," Journal of High Speed Networks,  vol. 15, issue 1, January-March 2006. • M. Terwilliger, A. Gupta, A. Khokhar and G. Greenwood,"Localization using Evolution Strategies in Sensornets," Proc. IEEE Congress on Evolutionary Computation, Edinburgh, UK, September 2005. • V. Bhuse, A. Gupta, M. Terwilliger, Z. Yang and Z. Kamal, "Using Routing Data for Information Authentication in Sensor Networks," Proc. 3rd   International Trusted Internet Workshop (TIW), International Conference on High Performance Computing, Bangalore, India, December 2004. • T. Canli, M. Terwilliger, A. Gupta and A. Khokhar, "Power-Time Efficient Algorithm for Computing FFT in Sensor Networks," (Extended Abstract). Proc. Second ACM Conference on Embedded Networked Sensor Systems (SenSys), Baltimore, Maryland, November 2004. • B. Bhargava, L. Lilien, A. Rosenthal, and M. Winslett, “Pervasive Trust,” IEEE Intelligent Systems, vol. 19(5), Sep./Oct.2004, pp. 74-77. • B. Bhargava and L. Lilien, “Private and Trusted Collaborations,” Proc. Secure Knowledge Management (SKM 2004): A Workshop, Amherst, NY, Sep. 2004. • M. Jenamani, L. Lilien, and B. Bhargava, “Anonymizing Web Services Through a Club Mechanism with Economic Incentives,” Proc. International Conference on Web Services (ICWS 2004), San Diego, California, July 2004, pp. 792-795. • Z. Kamal, M. Salahuddin, A. Gupta, M. Terwilliger, V. Bhuse and B. Beckmann, "Analytical Analysis of Data and Decision Fusion in Sensor Networks," Proc. 2004 International Conference on Embedded Systems and Applications. Las Vegas, June 2004. • M. Terwilliger, A. Gupta, V. Bhuse, Z. Kamal, and M. Salahuddin, "A Localization System Using Wireless Sensor Networks: A Comparison of Two Techniques," Proc. 2004 Workshop on Positioning, Navigation and Communication, Hanover, Germany, March 2004 , pp. 95-100. • V. Bhuse, A. Gupta and R. Pidva, "A Distributed Approach to Security in Sensornets," Proc. 58th IEEE Semiannual Vehicular Technology Conference, Orlando, Florida, USA, October 2003. • L. Lilien, “Developing Pervasive Trust Paradigm for Authentication and Authorization,” Proc. Third Cracow Grid Workshop (CGW’03), Kraków (Cracow), Poland, October 2003, pp. 42-49 (invited paper). 41

  42. WiSe Lab Experience in Sensornets – Selected Projects Since January 2003 NOTE: Results directly useful for oppnets are marked with an asterisk (*) • Designing of WiSe Security Protocols: DSPS • Location Tracker Using Motes (*) • RHS: Remote Home Surveillance (*) • Directed Diffusion: Attacks & Countermeasures • Improving the Accuracy of Mote Measurements by UsingNeural Networks • SOMS: Smart Occupancy Monitoring System Using Motes (*) • Comparative Study of Network Simulators • Collaborative Image Processing (*) • DENSe: a Development Environment for Networked Sensors • Incorporating Mobile-ware in Distributed Computations / Grids (*) • Extendingthe ns-2 Simulator to Satellite and WCN Simulations • Smart Antennas for WCNs • Energy Efficient MAC Protocols for IEEE 802.11x • A Wireless Security Testing System (*) • Mobile and Self-Calibrating Irrigation System • Collective Communications for Sensornets (*) 42

  43. Thank you very much for your time and attention!

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