Distributed Algorithms

Our Group designs distributed algorithms for embedded systems that consider resource constraints, partial information at individual nodes, and overall system objectives. This body of work ranges from in-situ adaptation and learning, such as with generic programming, to distributed trust mechanisms such as in our optimised blockchain design for IoT security and privacy.

In-situ genetic programming

Embedded devices that sense the environment regularly observe new contexts and situations, yet their program logic for dealing with new contexts is typically static based on what programmers know at compile time. By allowing these devices to evolve their program logic in response to new contexts, we can ensure a high degree of versatility and adaptation in-situ without human involvement. We have demonstrated this concept for learning on mote devices and for personalisation of smart phones, where we implemented the first genetic programming framework on Android phones and allowed co-located smartphone to share their logic for quicker learning through the island model.

Optimised Blockchain for IoT Security and privacy

There has been increasing interest in adopting BlockChain (BC), that underpins the crypto-currency Bitcoin, in Internet of Things (IoT) for security and privacy. However, BCs are computationally expensive and involve high bandwidth overhead and delays, which are not suitable for most IoT devices. This project is designin a lightweight BC-based architecture for IoT that virtually eliminates the overheads of classic BC, while maintaining most of its security and privacy benefits. IoT devices benefit from a private immutable ledger, that acts similar to BC but is managed centrally, to optimize energy consumption. High resource devices create an overlay network to implement a publicly accessible distributed BC that ensures end-to-end security and privacy. The proposed architecture uses distributed trust to reduce the block validation processing time.

Related Publications

A. Dorri, S. Kanhere, and R. Jurdak, “Towards an Optimized BlockChain for IoT,” In proceedings of the 2nd IEEE International Conference on Internet-of-Things Design and Implementation (IoTDI 2017), as part of CPSWeek, Pittsburgh, USA, April, 2017.

A. Dorri, S. Kanhere, R. Jurdak., and P. Gauravaram, “Blockchain for IoT Security and Privacy: The Case Study of a Smart Home,” In proceedings of the 2nd IEEE Workshop on security, privacy, and trust in the Internet of things (PERCOM), Hawaii, USA, March, 2017.

J. Liu, K. Zhao, P. Sommer, S. Shang, B. Kusy, J-G. Lee, R. Jurdak, “A Novel Framework for Online Amnesic Trajectory Compression in Resource-constrained Environments,” Accepted at IEEE Transactions on Knowledge and Data Engineering(TKDE), March, 2016.

R. Rana, M. Hume, R. Jurdak, J. Soar, J. Reilly, “Transforming knowledge capture in healthcare: Opportunistic and Context-aware affect Sensing on Smartphones,” IEEE Pervasive Computing, 15 (2), 60-69, 2016.

V. Kumar, N. Bergmann, R. Jurdak, B. Kusy, “Cluster-based Position Tracking of Mobile Sensors,” To appear in proceedings of The IEEE Conference on Wireless Sensors (ICWiSe), Langkawi, Malaysia, October, 2016.

P. Sommer, J. Liu, K. Zhao, B. Kusy, R. Jurdak, “Information Bang for the Energy Buck: Energy- and Mobility-Aware Tracking,” In proceedings of The International Conference on Embedded Wireless Systems and Networks (EWSN), Graz, Austria, February, 2016.Winner of Best Paper Award

L. Salt, R. Jurdak, B. Kusy, “Hybrid Ensemble Learning for Triggering of GPS in Long-Term Tracking Applications,” Accepted at the International Journal of Hybrid Intelligent Systems, January 2016.

L. Salt, B. Kusy, R. Jurdak, “Adaptive Threshold Triggering of GPS for Long-term Tracking in WSN,” In proceedings of the 7th IEEE International Conference on Soft Computing and Pattern Recognition (SoCPaR), Fukuoka, Japan, November, 2015.

J. Liu, K. Zhao, P. Sommer, S. Shang, B. Kusy, & R. Jurdak, “Bounded Quadrant System: Error-bounded Trajectory Compression on the Go,” In proceedings of the 31st IEEE International Conference on Data Engineering (ICDE), Seoul, Korea, April, 2015.

E. Basha, R. Jurdak, and D. Rus, ”In-Network Distributed Solar Current Prediction”, ACM Transactions on Sensor Networks 11(2), May 2015.

P. Valencia, A. Haak, A. Cotillon, R. Jurdak, “Genetic Programming for Smart Phone Personalisation,” Applied Soft Computing,, 25 (2014) 86–96, DOI: 10.1016/j.asoc.2014.08.058, September, 2014.

G. Murtaza, S. Kanhere, A. Ignjatovic, R. Jurdak, and S. Jha, “Trajectory Approximation for Resource Constrained Mobile Sensor Networks,” In proceedings of the 9th IEEE Conference on Distributed Computing in Sensor Systems (DCOSS), Marina Del Rey, CA, USA, May, 2014.

B. Kusy, D. Abbott, C. Richter, C. Huynh, M. Afanasyev, W. Hu, M. Bruenig, D. Ostry, and R. Jurdak, “Radio Diversity of Reliable Communication in Sensor Networks,” ACM Transactions on Sensor Networks, Vol. 10, Iss. 2, May 2014.

K. Li, B. Kusy, R. Jurdak, A. Ignjatovic, S. Kanhere, S. Jha, “κ-FSOM: Fair Link Scheduling Optimization for Energy-Aware Data Collection in Mobile Sensor Networks,” In Proceedings of the 11th European Conference on Wireless Sensor Networks (EWSN), Oxford, UK, February 2014.

R. Jurdak, B. Kusy, P. Sommer, N. Kottege, C. Crossman, A. McKeown, D. Westcott, “Camazotz: Multimodal Activity-based GPS Sampling,” In proceedings of the 12th International Conference on Information Processing in Sensor Networks (IPSN), Philadelphia, USA, April, 2013.

M. Hansen, B. Kusy, R. Jurdak, K. Langendoen. “AutoSync: Automatic Duty-Cycle Control for Synchronous Low-Power Listening,” In proceedings of 9th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks (SECON), Seoul Korea, June, 2012.

A. Barreira, P. Sommer, B. Kusy, and R. Jurdak, “Towards Collaborative Localization of Mobile Users with Bluetooth,” In proceedings of 3rd workshop on Networks of Cooperating Objects (CONET), co-located with CPS-week 2012, Bejing China, April 2012.

A. Cotillon, P. Valencia, and R. Jurdak, “Android Genetic Programming Framework,” In proceedings of the 15th European Genetic Programming Conference (EuroGP), pages 13-24, Malaga Spain, April, 2012.

B. Kusy, C. Richter, W. Hu, M. Afanasyev, R. Jurdak, M. Bruenig, D. Abbott, C. Huynh, and D. Ostry. “Radio Diversity for Reliable Communication in WSNs,” In Proceedings of the 10th International Conference on Information Processing in Sensor Networks (IPSN), Chicago, USA, April, 2011.

R. Jurdak, P. Corke, D. Dharman, and G. Salagnac. “Adaptive GPS Duty Cycling and Radio Ranging for Energy-Efficient Localization,” In proceedings of the 8th ACM Conference on Embedded Networked Sensor Systems (Sensys), pages 57-70. Zurich, Switzerland, November 2010.

P. Valencia, R. Jurdak, and P. Lindsay. “Fitness Importance for Online Evolution,” In proceedings of the Late Breaking Workshop of the ACM Genetic and Evolutionary Computation Conference (GECCO), Portland Oregon, July 2010.

P. Valencia, P. Lindsay, and R. Jurdak. “Distributed Genetic Evolution in WSN,” In Proceedings of the 9th International Conference on Information Processing in Sensor Networks (IPSN), Stockholm Sweden, April, 2010.