Research overview

1. Research overview Murat Demirbas SUNY Buffalo CSE Dept.

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. 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, CMOS, CMOS radios • Real-world deployments have already started: • Environmental monitoring • Precision agriculture • Asset management • Military surveillance

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

6. Research statement Developing distributed, robust,resilientWSN services • Distributed: decentralized • Robust: strong, durable • Resilient: able to adapt and recover from hazards This requires work on several layers of the WSN protocol stack

7. Research overview • MAC layers for robust single-hop communication • Geometric infrastructures for resilient WSN services • Programming abstractions for robust computing • Real-world deployments of robust WSN • Theory of self-stabilization

8. 1. MAC layers for robust communication • Coordinated attack problem • Two armies are waiting to attack a city • They need to attack together to win • Each army coordinates with a messenger • Messenger may be captured by the city • Can generals reach agreement? • Agreement is impossible in the presence of unreliable channel • Wireless communication is unreliable due to collisions • Hidden node problem

9. Receiver-side collision detection (RCD) RCD circumvents the impossibility result • RCD enables coping with undetectable message loss • RCD is easily implementable in WSNs • Receiver side monitoring and notification of collisions • No info wrt # of lost messages or identities of senders • Classification of RCDs • Completeness: Ability to detect collisions • Accuracy: Ability to avoid false positives • Synchronized rounds to convey negative feedback • Collisions of negative feedback imply at least one negative feedback

10. Vote-Veto algorithm • Two phases: vote and veto • Vote phase: • Every active node sends out its vote • If a node hears no collision, the node updates its vote to min of received votes • If a node hears collision or different votes, it decides to veto • Veto phase: • If no veto messages are received or collisions detected, then a node can decide, else nodes continue to next round • Intuition: By having a dedicated veto phase, effects of collision is detectable • Robcast and BEMA MAC protocols for robust broadcast • They eliminate the hidden terminal problem and improve throughput

11. 2. Geometric infrastructures for resilient WSN services For scalability, local operations are needed over global structures By exploiting the geometry of WSNs, we can design efficient, minimal, and resilient infrastructures • Querying structures: Glance, DQT, PeeR-tree • O(d) time for querying, where d is the distance to the nearest answer • Graceful resilienceto the face node failures via simplicity of design • Tracking structures: Stalk, Trail • O(d) time for querying • O(m*logm) for update, where m is the distance the evader moved • Local self-healing via containment wave idea & stretch-factor idea

12. Geometric infrastructures for mobile WSN Mobility improves coverage and, hence, resilience • Mobile base-station for efficient data aggregation • Relocating the base-station in response to varying data rates • Deployment and relocation of mobile WSN • Sensor nodes relocate to provide dynamic coverage by following the interest gradient • Even though neighbors can change for each node, the network should stay connected • What are local rules to maintain such a mobile WSN ?

13. 3. Programming abstractions for robust computing 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 deployment of 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

14. 1 km Thick Entry Line 250 m A S S E T 4. Real-world deployments of robust WSN Line In The Sand • 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

15. 4. Real-world deployments of robust WSN… INSIGHT: INternet Sensor InteGration for HabitaT monitoring • Single-hop network • Basestation serves webpage • To circumvent firewall a replica is established via XML query • http://insight.podzone.net Elvis: In-building personnel localization

16. 5. Theory of self-stabilization • 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!

17. 5. Theory of self-stabilization… legitimate states from where safety and liveness are satisfied illegitimate states reached possibly due to faults • Closure: Set of legitimate states is closed under system execution • Convergence: Starting from any system state, every system • computation eventually reaches a legitimate state

18. 5. Theory of self-stabilization… • Graybox self-stabilization • Improves over the whitebox and blackbox approaches tried so far • Compositional reasoning for self-stabilization • Modular design and verification of self-stabilization • Syntax-based design of self-stabilization • Use programming patterns to achieve self-stabilization • Probabilistic & model-based verification of self-stabilization • Improves over strictly deterministic design and verification of self-stabilization

19. iComp Research group: • Current PhD students • Muzammil Hussain • Xuming Lu • Dola Saha • Onur Soysal • Several MS students are involved (via CSE 646) • Closely related research groups • Chunming Qiao : networking • Jan Chomicki, Michalis Petropoulos : database management

20. Questions ? • MAC layers for robust single-hop communication • Geometric infrastructures for resilient WSN services • Programming abstractions for robust computing • Real-world deployments of robust WSN • Theory of self-stabilization