Fundamentals of IRAS

Fundamentals of IRAS

Fundamental research into the principles, methodologies and efficient algorithms for Autonomous Learning Systems, different aspects of Computational Intelligence, including Artificial Neural Networks, Deep Learning, Dynamically Evolving Fuzzy rule-based Systems is the focus of interests of this Theme.

Theme Leader

Dr Peter Garraghan

Lecturer in Distributed Systems

DSI - Foundations, Lancaster Intelligent, Robotic and Autonomous Systems Centre, SCC (Distributed Systems)

+44 (0)1524 510306 B26, B - Floor, InfoLab21

Projects

  • EPSRC Project: "Deep Online Cognition in Modular Software" (EP/M029603/1)
  • Leverhulme project: "The Emergent Self-Aware Data Centre: Autonomous software landscaping at scale" (RPG-2017-166)
  • Royal Society Network Fund: "Emergent Systems for Smart Cities" (NMG\R2\170105)
  • GEM: translational software for outbreak analysis WelcomeTrust, PI, 2020 - 2021
  • Software Bug Detection and Fix Generation by Learning from Large Code Examples
  • The Royal Society International Collaboration Grant, PI, 03/2017 - 03/2019
  • Energy and Performance Optimisation for Mobile Systems EPSRC iCASE Studentship with ARM Ltd, PI, 02/2016 - 08/2019
  • Investigation of intelligent Controller for indirect Heaters on Gas Networks, £12,000.
  • Pin the Tail: Understanding Straggler Manifestation in Internet-based Distributed Systems. EPSRC. £119,000.

Media Coverage

CCS’18 paper on captcha security

UBICOMP ’18 paper on sleep monitoring:

NDSS’17 paper on Android pattern lock security

Publications

  • Zheng Wang and Michael O'Boyle, Machine Learning in Compiler Optimisation Proceedings of the IEEE (Proc. IEEE), 2018
  • Zheng Wang, Nikos Parasyris, Dimitrios S. Nikolopoulos, Bronis R. de Supinski, and Hugh Leather, ALEA: A Fine-grained Energy Profiling Tool Lev Mukhanov, Pavlos Petoumenos ACM Transaction on Architecture and Code Optimization (ACM TACO), April 2017
  • Zheng Wang, Dominik Grewe, and Michael O'Boyle, Automatic and Portable Mapping of Data Parallel Programs to OpenCL for GPU-based Heterogeneous Systems, ACM Transaction on Architecture and Code Optimization (ACM TACO), Volume 11 Issue 4, January 2015.
  • Zheng Wang, Georgios Tournavitis, Bjorn Franke and Michael O'Boyle, Integrating Profile-Driven Parallelism Detection and Machine-Learning Based Mapping ACM Transaction on Architecture and Code Optimization (ACM TACO), Volume 11 Issue 1, 2014.
  • Zheng Wang and Michael O’Boyle, Using Machine Learning to Partition Streaming Programs,
  • ACM Transactions on Architecture and Code Optimization (ACM TACO), 2013.
  • Guixin Ye, Zhanyong Tang, Dingyi Fang, Xiaojiang Chen, Willy Wolff, Adam Aviv, and Zheng Wang, A Video-based Attack for Android Pattern Lock, ACM Transactions on Privacy and Security (ACM TOPS), 2018
  • Kaiyuan Kuang, Zhanyong Tang, Xiaoqing Gong, Dingyi Fang, Xiaojiang Chen, Zheng Wang, Enhance virtual-machine-based code obfuscation security through dynamic bytecode scheduling Elsevier Computers and Security, 2018
  • Jie Zhang, Zhanyong Tang, Meng Li, Dingyi Fang, Xiaojiang Chen, Zheng Wang, Find Me A Safe Zone: A Countermeasure for Channel State Information Based Attacks, Elsevier Computers and Security, 2018
  • Christopher McGowan, Alexander Wild, Barry Porter, Experiments in Genetic Divergence for Emergent Systems, International Genetic Improvement Workshop, June 2018
  • Roberto Rodrigues Filho, Barry Porter, Defining Emergent Software using Continuous Self-Assembly, Perception, and Learning, Transactions on Autonomous and Adaptive Systems, September 2017
  • Barry Porter, Matthew Grieves, Roberto Rodrigues Filho, David Leslie, REx: A Development Platform and Online Learning Approach for Runtime Emergent Software Systems, Symposium on Operating Systems Design and Implementation, November 2016
  • Rodrigo C. O. Rocha, Pavlos Petoumenos, Zheng Wang, Murray Cole, Hugh Leather, Function Merging by Sequence Alignment International Symposium on Code Generation and Optimization (CGO), 2019.
  • B. Taylor, V.S. Marco, Y. Elkhatib, and Z. Wang, Adaptive Deep Learning Model Selection on Embedded Systems 19th Annual ACM SIGPLAN / SIGBED 2018 Conference on Languages, Compilers, and Tools for Embedded Systems (LCTES), 2018
  • Jie Zhang, Zhanyong Tang, Meng Li, Dingyi Fang, Petteri Nurmi, and Zheng Wang, CrossSense: Towards Cross-Site and Large-Scale WiFi Sensing The 24th ACM International Conference on Mobile Computing and Networking (MobiCom), 2018
  • Zhang, P., Fang, J., Tang, T., Yang, C. and Wang, Z, Auto-tuning Streamed Applications on Intel Xeon Phi 32nd IEEE International Parallel & Distributed Processing Symposium (IPDPS), 2018
  • J. Ren, X. Wang, J. Fang, Y. Feng, D. Zhu, Z. Luo, J. Zhang, Z. Wang, Proteus: Network-aware Web Browsing on Heterogeneous Mobile Systems The 14th ACM International Conference on emerging Networking EXperiments and Technologies (CoNEXT) (premier conference in parallel computing).
  • Chao Xue, Zhanyong Tang, Guixin Ye, Guanghui Li, Wei Wang, Dingyi Fang, Zheng Wang, Exploiting Code Diversity to Enhance Code Virtualization Protection The 24th International Conference on Parallel and Distributed Systems (ICPADS), 2018
  • Inference Qin Qing, Jie Ren, Yansong Feng, Jianbin Fang, Zheng Wang, To Compress, or Not to Compress: Characterizing Deep Learning Model Compression for Embedded The 16th IEEE International Symposium on Parallel and Distributed Processing with Applications (ISPA), 2018.
  • Guixin Ye, Zhanyong Tang, Dingyi Fang, Zhanxing Zhu, Yansong Feng, Zheng Wang, Yet Another Text Captcha Solver: A Generative Adversarial Network Based Approach The 25th ACM Conference on Computer and Communications Security (CCS), 2018
  • L. Chang, J. Lu, J. Wang, X. Chen, D. Fang, Z. Tang, P. Nurmi, Z. Wang, SleepGuard: Capturing Rich Sleep Information using Smartwatch Sensing Data ACM International Joint Conference on Pervasive and Ubiquitous Computing (Ubicomp), 2018 - ACM IMWUT, 2018
  • Adaptive Optimization of Sparse Matrix-Vector Multiplication on Emerging Many-Core Architectures S.Z. Chen, J. Fang, D.L.Chen, C.F. Xu, and Z. Wang The 20th IEEE International Conference on High-Performance Computing and Communications (HPCC), 2018.
  • L. Chang, X. Li, J. Wang, H. Meng, X. Chen, D. Fang, Z. Tang, Z. Wang, Towards Large-Scale RFID Positioning: A Low-cost, High-precision Solution Based on Compressive Sensing IEEE International Conference on Pervasive Computing and Communications (PerCom), 2018.
  • Y. Zeng, Y. Feng, R. Ma, Z. Wang, C. Shi, Z. Yan, Scale Up Event Extraction Learning via Automatic Training Data Generation In the Thirty-Second AAAI Conference on Artificial Intelligence (AAAI), 2018.
  • Xu, P., Wang, L., Guan, Z., Zheng, X., Chen, X., Tang, Z., Fang, D., Gong, X. & Wang, Z, Evaluating Brush Movements for Chinese Calligraphy: A Computer Vision-Based Approach 27th International Joint Conference on Artificial Intelligence and the 23rd European Conference on Artificial Intelligence (IJCAI), 2018.
  • Vincent Sanz Marco, Ben Taylor, Barry Porter, Zheng Wang, Improving Spark Application Throughput Via Memory Aware Task Co-location: A Mixture of Experts Approach ACM/IFIP/USENIX Middleware Conference (Middleware), 2017.
  • Chris Cummins, Pavlos Petoumenos, Zheng Wang and Hugh Leather, End-to-end deep learning of optimization heuristics The 26th International Conference on. Parallel Architectures and Compilation Techniques (PACT), 2017. (premier conference in parallel computing, won the best paper award).
  • Systems Ben Taylor, Vicent Sanz Marco and Zheng Wang, Adaptive Optimization for OpenCL Programs on Embedded Heterogeneous ACM SIGPLAN/SIGBED Conference on Languages, Compilers and Tools for Embedded systems (LCTES), 2017. 
  • Jie Ren, Ling Gao, Hai Wang, and Zheng Wang, Optimise Web Browsing on Heterogeneous Mobile Platforms: A Machine Learning Based Approach, IEEE International Conference on Computer Communications (INFOCOM), 2017. (premier conference in networking).
  • William Ogilvie, Pavlos Petoumenos, Zheng Wang and Hugh Leather, Minimizing the cost of iterative compilation with active learning International Symposium on Code Generation and Optimization (CGO), 2017. (premier conference in code optimisation).
  • Chris Cummins, Pavlos Petoumenos, Zheng Wang and Hugh Leather, Synthesizing Benchmarks for Predictive Modeling, International Symposium on Code Generation and Optimization (CGO), 2017.
  • G.X Ye, Z.Y Tang, D.Y Fang, X.J Chen, K.I Kim, B. Taylor and Z Wang, Cracking Android Pattern Lock in Five Attempts The Network and Distributed System Security Symposium (NDSS), 2017.
  • Ce Zhang, Isabel Sargent, Xi Pan, Huapeng Li, Andy Gardiner, Jonathon Hare, Peter M. Atkinson, Joint Deep Learning for land cover and land use classification. Remote Sensing of Environment, 221: 173-187, 2019.
  • An object-based convolutional neural network (OCNN) for urban land use classification. Remote Sensing of Environment, 216: 57-70, 2018.
  • Ce Zhang, Isabel Sargent, Xin Pan, Andy Gardiner, Jonathon Hare, Peter M. Atkinson, VPRS-based regional decision fusion of CNN and MRF classifications for very fine resolution remotely sensed images IEEE Transactions on Geoscience and Remote Sensing, 56 (8): 4507-4521, 2018.
  • Ce Zhang, Xin Pan, Huapeng Li, Andy Gardiner, Isabel Sargent, Jonathon Hare, Peter M. Atkinson, A hybrid MLP-CNN classifier for very fine resolution remotely sensed image classificationISPRS Journal of Photogrammetry and Remote Sensing, 140: 133-144, 2018.
  • Ce Zhang, Xin Pan, Shuqing Zhang, Huapeng Li, Peter M. Atkinson, A rough set decision tree based MLP-CNN for very high resolution remotely sensed image classification. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLII-2/W7, 1451-1454, 2017. doi: 10.5194/isprs-archives-XLII-2-W7-1451-2017.
  • Ce Zhang, Peter M. Atkinson, Novel shape indices for vector landscape pattern analysis. International Journal of Geographical Information Science, 30(12): 2442-2461, 2016.
  • Huapeng Li, Ce Zhang, Shuqing Zhang, Peter M. Atkinson, Full year crop monitoring and separability assessment with fully-polarimetric L-band UAVSAR: a case study in the Sacramento Valley, California.  International Journal of Applied Earth Observation and Geoinformation. Vol. 74: 45-56, 2019.
  • Xiaowei Gu, Plamen P. Angelov, Ce Zhang, Peter M. Atkinson, A Massively Parallel Deep Rule-Based Ensemble Classifier for Remote Sensing Scenes.    IEEE Geoscience and Remote Sensing Letters, 15(3): 345-349, 2018.
  • Huapeng Li, Shuqing Zhang, Ce Zhang, Ping Li, Roger Cropp, A novel unsupervised Levy flight particle swarm optimization (ULPSO) method for multispectral remote sensing image classification. International Journal of Remote Sensing, 38(23): 6970-6992, 2017.
  • Zhaofei Wen, Maohua Ma, Ce Zhang, Xuemei Yi, Jilong Chen, Shengjun Wu, Estimating seasonal aboveground biomass dynamics of a riparian pioneer plant species: an exploratory analysis by canopy structural data. Ecological Indicators, 83: 441-450, 2017.
  • Chunlei Jiang, Shuqing Zhang, Ce Zhang, Huapeng Li, Xiaohui Ding, Modelling and predicting of MODIS leaf area index time series based on a hybrid SARIMA and BP neural network method.  Spectroscopy and Spectral Analysis, 37 (1): 189-193, 2017.
  • Huapeng Li, Shuqing Zhang, Xiaohui Ding, Ce Zhang, Patricia Dale, Performance Evaluation of Some Cluster Validity Indices (CVIs) on Multi/Hyperspectral Remote Sensing Data Sets.  Remote Sensing, 8 (4): 295, 2016.
  • Huapeng Li, Shuqing Zhang, Xiaohui Ding, Ce Zhang, Roger Cropp, A novel unsupervised bee colony optimization (UBCO) method for remote sensing image classification: A case study in the heterogeneous marsh area. International Journal of Remote Sensing, 37(24): 5726-5748, 2016.
  • A Global Perspective on Drinking-water and Sanitation Classification: An Evaluation of Census Content.  PLOS ONE, 11(3): e0151645, 2016. 
  • Weiyu Yu, Nicola A Wardrop, Robert ES Bain, Yanzhao Lin, Ce Zhang, Jim A Wright, Every Team Deserves a Second Chance: An extended study on predicting team performance. L. S. Marcolino, A. Lakshminarayanan, V. Nagarajan, M. Tambe.  Journal of Autonomous Agents and Multi-Agent Systems, JAAMAS, 2016.
  • L. S. Marcolino, Y. T. dos Passos, Á. A. F. de Souza, A. S. Rodrigues, L. Chaimowicz, Avoiding target congestion on the navigation of robotic swarms. Journal Autonomous Robots, 2016, DOI 10.1007/s10514-016-9577-x.
  • R. Tavares, S. Anbalagan, L. S. Marcolino and L. Chaimowicz.  Algorithms or Actions? A Study in Large-Scale Reinforcement Learning. In Proceedings of the 27th International Joint Conference on Artificial Intelligence (IJCAI 2018), July 2018. 
  • A. Yadav, R. Noothigattu, E. Rice, L. Onasch-Vera, L. S. Marcolino, M. Tambe. Please be an Influencer? Contingency-Aware Influence Maximization. In Proceedings of the Seventeenth International Conference on Autonomous Agents & Multi-agent Systems (AAMAS 2018), July 2018.
  • M. Escarce Junior, G. R. Martins, L. S. Marcolino, Y. T. dos Passos. Emerging Sounds Through Implicit Cooperation: A Novel Model for Dynamic Music GenerationIn Proceedings of the 13th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment (AIIDE 2017), Utah, USA, October 2017.
  • Scale Garraghan, P., Yang, R., Wen, Z., Romanovsky, A., Xu, J., Buyya, R., Ranjan, R. Emergent Failures: Rethinking Cloud Reliability at In: IEEE Cloud Computing. 5, 5, p. 12-21. 2018.
  • Li, X., Garraghan, P., Jiang, X., Wu, Z., Xu, J. Holistic virtual machine scheduling in cloud datacenters towards minimizing total energy In: IEEE Transactions on Parallel and Distributed Systems. 29, 6, p. 1317-1331, 2018.
  • Ouyang, X., Garraghan, P., Primas, B., McKee, D., Townend, P., Xu, J.Adaptive Speculation for Ef´Čücient Internetware Application Execution in Clouds In: ACM Transactions on Internet Technology. 18, 2, 2018.
  • Li, X., Jiang, X., Garraghan, P., Wu, Z Holistic energy and failure aware workload scheduling in Cloud datacenters. In: Future Generation Computer Systems. 78, 3, p. 887-900. 2018.
  • Yang, R., Wen, Z., McKee, D., Lin, T., Xu, J., Garraghan, P. Fog Orchestration and Simulation for IoT Services In: Fog and Fogonomics. Wiley, 2018.
  • subscription Sun, X., Hu, C., Yang, R., Garraghan, P., Wo, T., Xu, J., Zhu, J., Li, C, ROSE: Cluster Resource Scheduling via Speculative Over- In: 38th IEEE International Conference on Distributed Systems Computing Systems. IEEE, 2018.
  • Zhang, Y., Garraghan, P., Feng, Y., Ouyang, J., Xu, J., Zhang, Z., Li, C. Reliable computing service in massive-scale systems through rapid low-cost failover Yang, R., In: IEEE Transactions on Services Computing. 10, 6, p. 969-983. 2017.
  • Services Wen, Z., Yang, R., Garraghan, P., Lin, T., Xu, J., Rovatsos, M. Fog Orchestration for the Internet of Things In: IEEE Internet Computing. 21, 2, p. 16-24. 2017.
  • Ouyang, X., Garraghan, P., McKee, D., Townend, P., Xu, J. Straggler detection in parallel computing systems through dynamic threshold calculation In: 2016 IEEE 30th International Conference on Advanced Information Networking and Applications (AINA). IEEE p. 414-421. 8 p. Electronic ISBN: 9781509018581, 2016.
  • Garraghan, P., Ouyang, X., Yang, R., McKee, D., Xu, J. Straggler root-cause and impact analysis for massive-scale virtualized cloud datacenters In: IEEE Transactions on Services Computing. 2016.