1. Research overview Murat Demirbas University at Buffalo, SUNY CSE Dept. iComp

2. 2 Personal computing ? PC processors are only 2% of all processors Where do the rest of the processors go?  Automotive industry, e.g., new car has dozens of microprocessors  Communications, e.g., cell-phones  Consumer electronics, e.g., microwaves, washing machines  Industrial equipment, e.g., factory floor robots

3. 3 Ubiquitous computing Instead of us interacting with the computers in the virtual world, the computers should interact with us in our physical world Technology is now available via MEMS and CMOS radios Real-world deployments have already started:  Environmental monitoring  Asset management  Military surveillance iComp

4. 4 Wireless sensor networks (WSNs) ‏ A sensor node (mote)  8K RAM, 4Mhz processor  magnetism, heat, sound, vibration, infrared  wireless (radio broadcast) communication up to 100 feet  costs ~$10 (right now costs ~$100) ‏

5. 5 Challenges in WSN Scalability  Thousands of nodes collaborate; for achieving scalability distributed & local algorithms are needed  Distributed algorithms are notoriously difficult to design Reliability  Wireless communication is unreliable due to collisions  Consensus is hard to achieve  Nodes fail due to adverse environmental conditions and software bugs  Maintenance of infrastructures are costly and difficult

6. 6 Research overview 1. WSNs in-network querying and tracking services 2. Wireless Sensor Actor Networks (WSANs)‏ 3. Internet-integrated large-scale WSN deployments 4. Self-stabilizing systems theory

7. 7 1. In-network querying & tracking The objective is to answer contextual & spatial queries in WSNs What is the location of the nearest enemy tank?  a soldier may query the WSN (via a palm device) in a battlefield scenario What is a safe path to the nearest available exit?  a firefighter may ask in a rescue-evacuation scenario

8. 8 “Line In The Sand” military surveillance WSN In OSU, we developed a surveillance service for DARPA-NEST  Detect, track, and classify trespassers as car, soldier, civilian  LiteS: 100 nodes in 2003, ExScal: 1000 nodes in Dec 2004 Thick Entry Line A S S E T: pipeline or border to be secured 1 km 250 m

9. 9 Our results... For scalability, local operations are needed over global structures By exploiting the geometry of WSNs, we design efficient, minimal, and resilient infrastructures GlanceDQTPeeR-treeQuerying structures: Glance, DQT, PeeR-tree  O(d) time for querying, where d is the distance to the nearest answer  Graceful resilience to the face node failures via simplicity of design StalkTrail, DQT-mobileTracking structures: Stalk, Trail, DQT-mobile  O(d) time for querying  O(m*logm) for update, where m is the distance the evader moved containment wave stretch-factor  Local self-healing via containment wave idea & stretch-factor idea

10. 10 2. Wireless Sensor Actor Networks The objective is to achieve collaboration and coordination in swarm robotic/vehicular/sensor networks Distributed control applications for in-network actuation  Active vibration and noise cancellation in factory floors  Task and resource allocation in multimedia (video) WSNs  Leader election, consensus, in-network information fusion Deployment and relocation of mobile WSANs for environmental pollution surveillance and removal −Sensors relocate to provide dynamic coverage by following the gradient –Although neighbors can change for nodes, the network should stay connected –What are local rules and suitable primitives to maintain such mobile WSANs?

11. 11 Our results... (NSF Career award) Transact Transact : A transactional framework for programming WSANs Effectively managing concurrent execution is a big challenge  concurrency needs to be tamed to prevent unintentional nondeterministic executions  concurrency needs to be boosted for achieving timeliness Transactional, optimistic concurrency control framework  enables understanding of a system execution as a single thread of control, while permitting the actual execution over multiple threads distributed on several nodes  by exploiting the properties of wireless broadcast communication, we provide a distributed and local conflict detection and serializability Pollcast, Countcast, Coordcast Pollcast, Countcast, Coordcast : Lightweight singlehop collaboration and coordination primitives for WSANs Omnitaxis Omnitaxis : A decentralized mobile topology control protocol for robotic surveillance and rescue networks

12. 12 3. Internet-integrated large-scale WSN deployments INSIGHT INSIGHT : INternet Sensor InteGration for HabitaT monitoring –Single-hop network –Basestation serves webpage –Deployed for monitoring the greenhouse at UB Elvis Elvis : In-building personnel localization and tracking Gate monitoring WSNs HPC monitoring WSNs Cellphone as a healthcare platform Cellphone as a healthcare platform : Indirect sensing applications

13. Insight Deployment

14. 14 Plant & play parking lot monitoring 14

15. 15 Plant & play parking lot monitoring

16. 16 Plant & play parking lot monitoring

17. 17 Anybody interested in iphone/ipod programming class? 17

18. 18 4. Self-stabilizing systems theory Self-stabilization is the ability of a system to recover within bounded steps from arbitrary states to states from where the system exhibits desired behavior Arbitrary state corruption provides a clean abstraction of how many systems are perturbed by their diverse environments  Self-stabilization provides a viable method to deal with state corruption  Case-by-case analysis of faults and recovery is shunned in favor of a uniform mechanism Self-stabilizing systems do not need any initialization  Self-configuring! 18