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2020 – today
- 2024
[i16]Fatema Bannat Wala, Mariam Kiran:
5G Network Security Practices: An Overview and Survey. CoRR abs/2401.14350 (2024)- [i15]Krishnan Raghavan, George Papadimitriou, Hongwei Jin, Anirban Mandal, Mariam Kiran, Prasanna Balaprakash, Ewa Deelman:
Advancing Anomaly Detection in Computational Workflows with Active Learning. CoRR abs/2405.06133 (2024) - [i14]Oceane Bel, Mariam Kiran:
Simulators for Quantum Network Modelling: A Comprehensive Review. CoRR abs/2408.11993 (2024) - 2023
- [j20]Hongwei Jin
, Krishnan Raghavan, George Papadimitriou, Cong Wang, Anirban Mandal, Mariam Kiran, Ewa Deelman, Prasanna Balaprakash:
Graph neural networks for detecting anomalies in scientific workflows. Int. J. High Perform. Comput. Appl. 37(3-4): 394-411 (2023) - [j19]Mariam Kiran:
Engineering Autonomous Self-Driving Networks. SIGMETRICS Perform. Evaluation Rev. 51(2): 97-99 (2023) - [c42]Fatema Bannat Wala, Scott Campbell, Mariam Kiran:
Insights into DoH: Traffic Classification for DNS over HTTPS in an Encrypted Network. SNTA@HPDC 2023: 9-17 - [c41]Imtiaz Mahmud, George Papadimitriou, Cong Wang, Mariam Kiran, Anirban Mandal, Ewa Deelman:
Elephants Sharing the Highway: Studying TCP Fairness in Large Transfers over High Throughput Links. SC Workshops 2023: 806-818 - 2022
- [j18]Sugeerth Murugesan, Mariam Kiran, Bernd Hamann, Gunther H. Weber:
Netostat: analyzing dynamic flow patterns in high-speed networks. Clust. Comput. 25(4): 2915-2930 (2022) - [c40]Mariam Kiran, Scott Campbell, Nick Buraglio:
Hecate: AI-driven WAN Traffic Engineering for Science. INDIS@SC 2022: 41-49 - [c39]Mekena Metcalf, Huo Chen, Anastasiia Butko, Mariam Kiran:
Autonomous Pulse Control for Quantum Transducers with Deep Reinforcement Learning. OFC 2022: 1-3 - [c38]Hongwei Jin, Krishnan Raghavan, George Papadimitriou, Cong Wang, Anirban Mandal, Patrycja Krawczuk, Loïc Pottier, Mariam Kiran, Ewa Deelman, Prasanna Balaprakash:
Workflow Anomaly Detection with Graph Neural Networks. WORKS@SC 2022: 35-42 - [i13]Mariam Kiran, Buse Melis Özyildirim:
Hyperparameter Tuning for Deep Reinforcement Learning Applications. CoRR abs/2201.11182 (2022) - [i12]Deborah Bard, Cory Snavely, Lisa Gerhardt, Jason Lee, Becci Totzke, Katie Antypas, William Arndt, Johannes P. Blaschke, Suren Byna, Ravi Cheema, Shreyas Cholia, Mark R. Day, Bjoern Enders, Aditi Gaur, Annette Greiner, Taylor L. Groves, Mariam Kiran, Quincey Koziol, Tom Lehman, Kelly Rowland, Chris Samuel, Ashwin Selvarajan, Alex Sim, David Skinner, Laurie Stephey, Rollin C. Thomas, Gabor Torok:
The LBNL Superfacility Project Report. CoRR abs/2206.11992 (2022) - 2021
- [j17]Mariam Kiran, Scott Campbell, Fatema Bannat Wala, Nick Buraglio, Inder Monga:
Machine learning-based analysis of COVID-19 pandemic impact on US research networks. Comput. Commun. Rev. 51(4): 23-35 (2021) - [j16]George Papadimitriou, Cong Wang, Karan Vahi, Rafael Ferreira da Silva, Anirban Mandal, Zhengchun Liu, Rajiv Mayani, Mats Rynge, Mariam Kiran, Vickie E. Lynch, Rajkumar Kettimuthu, Ewa Deelman, Jeffrey S. Vetter, Ian T. Foster:
End-to-end online performance data capture and analysis for scientific workflows. Future Gener. Comput. Syst. 117: 387-400 (2021) - [j15]Bashir Mohammed, Nandini Krishnaswamy, Mariam Kiran, Keshang Wu:
Predicting WAN traffic volumes using Fourier and multivariate SARIMA approach. Int. J. Big Data Intell. 8(1): 1-12 (2021) - [j14]Buse Melis Özyildirim, Mariam Kiran:
Levenberg-Marquardt multi-classification using hinge loss function. Neural Networks 143: 564-571 (2021) - [c37]Bashir Mohammed, Mariam Kiran, Bjoern Enders:
NetGraf: An End-to-End Learning Network Monitoring Service. INDIS@SC 2021: 12-22 - [c36]Meriam Gay Bautista, Zhi Jackie Yao, Anastasiia Butko, Mariam Kiran, Mekena Metcalf:
Towards Automated Superconducting Circuit Calibration using Deep Reinforcement Learning. ISVLSI 2021: 462-467 - [c35]Vincent Dumont, Casey Garner, Anuradha Trivedi, Chelsea Jones, Vidya Ganapati, Juliane Mueller, Talita Perciano, Mariam Kiran, Marc Day:
HYPPO: A Surrogate-Based Multi-Level Parallelism Tool for Hyperparameter Optimization. MLHPC@SC 2021: 81-93 - [c34]Sheng Shen, Mariam Kiran, Bashir Mohammed:
DynamicDeepFlow: An Approach for Identifying Changes in Network Traffic Flow Using Unsupervised Clustering. MLN 2021: 98-116 - [c33]Huy Tu, George Papadimitriou, Mariam Kiran, Cong Wang, Anirban Mandal, Ewa Deelman, Tim Menzies:
Mining Workflows for Anomalous Data Transfers. MSR 2021: 1-12 - [c32]Patrycja Krawczuk, George Papadimitriou, Shubham Nagarkar, Mariam Kiran, Anirban Mandal, Ewa Deelman:
Anomaly Detection in Scientific Workflows using End-to-End Execution Gantt Charts and Convolutional Neural Networks. PEARC 2021: 26:1-26:5 - [i11]Huy Tu, George Papadimitriou, Mariam Kiran, Cong Wang, Anirban Mandal, Ewa Deelman, Tim Menzies:
Mining Scientific Workflows for Anomalous Data Transfers. CoRR abs/2103.12221 (2021) - [i10]Divneet Kaur, Bashir Mohammed, Mariam Kiran:
NetGraf: A Collaborative Network Monitoring Stack for Network Experimental Testbeds. CoRR abs/2105.10326 (2021) - [i9]Vincent Dumont, Casey Garner, Anuradha Trivedi, Chelsea Jones, Vidya Ganapati, Juliane Mueller, Talita Perciano, Mariam Kiran, Marc Day:
HYPPO: A Surrogate-Based Multi-Level Parallelism Tool for Hyperparameter Optimization. CoRR abs/2110.01698 (2021) - [i8]Shan Sun, Mariam Kiran, Wei Ren:
MAMRL: Exploiting Multi-agent Meta Reinforcement Learning in WAN Traffic Engineering. CoRR abs/2111.15087 (2021) - 2020
- [j13]Sugeerth Murugesan, Kristofer E. Bouchard, Jesse A. Brown, Mariam Kiran, Dan Lurie, Bernd Hamann, Gunther H. Weber:
State-based network similarity visualization. Inf. Vis. 19(2) (2020) - [j12]Mariam Kiran, Samir Khan:
Editorial: Machine learning for safety-critical applications in engineering. Mach. Learn. 109(5): 1101-1102 (2020) - [j11]Mariam Kiran, Cong Wang, George Papadimitriou, Anirban Mandal, Ewa Deelman:
Detecting anomalous packets in network transfers: investigations using PCA, autoencoder and isolation forest in TCP. Mach. Learn. 109(5): 1127-1143 (2020) - [c31]Nandini Krishnaswamy, Mariam Kiran, Kunal Singh, Bashir Mohammed:
Data-driven Learning to Predict WAN Network Traffic. SNTA@HPDC 2020: 11-18 - [c30]Hocine Mahtout, Mariam Kiran, Anu Mercian, Bashir Mohammed:
Using Machine Learning for Intent-based provisioning in High-Speed Science Networks. SNTA@HPDC 2020: 27-30 - [c29]Cong Wang, George Papadimitriou, Mariam Kiran, Anirban Mandal, Ewa Deelman:
Identifying Execution Anomalies for Data Intensive Workflows Using Lightweight ML Techniques. HPEC 2020: 1-7 - [c28]Bjoern Enders, Debbie Bard, Cory Snavely, Lisa Gerhardt, Jason Lee, Becci Totzke, Katie Antypas, Suren Byna, Ravi Cheema, Shreyas Cholia, Mark R. Day, Aditi Gaur, Annette Greiner, Taylor L. Groves, Mariam Kiran, Quincey Koziol, Kelly Rowland, Chris Samuel, Ashwin Selvarajan, Alex Sim, David Skinner, Rollin C. Thomas, Gabor Torok:
Cross-facility science with the Superfacility Project at LBNL. XLOOP@SC 2020: 1-7 - [c27]Scott Campbell, Mariam Kiran, Fatema Bannat Wala:
Unsupervised Anomaly Detection in Daily WAN Traffic Patterns. SMC 2020: 240-256 - [i7]Buse Melis Özyildirim, Mariam Kiran:
Do optimization methods in deep learning applications matter? CoRR abs/2002.12642 (2020) - [i6]Tanwi Mallick, Mariam Kiran, Bashir Mohammed, Prasanna Balaprakash:
Dynamic Graph Neural Network for Traffic Forecasting in Wide Area Networks. CoRR abs/2008.12767 (2020)
2010 – 2019
- 2019
- [j10]Mariam Kiran, Anshuman Chhabra:
Understanding flows in high-speed scientific networks: A Netflow data study. Future Gener. Comput. Syst. 94: 72-79 (2019) - [c26]Bashir Mohammed, Nandini Krishnaswamy, Mariam Kiran:
Multivariate Time-Series Prediction for Traffic in Large WAN Topology. ANCS 2019: 1-4 - [c25]Bashir Mohammed, Mariam Kiran, Nandini Krishnaswamy:
DeepRoute on Chameleon: Experimenting with Large-scale Reinforcement Learning and SDN on Chameleon Testbed. ICNP 2019: 1-2 - [c24]Mariam Kiran, Bashir Mohammed, Nandini Krishnaswamy:
DeepRoute: Herding Elephant and Mice Flows with Reinforcement Learning. MLN 2019: 296-314 - [c23]George Papadimitriou, Mariam Kiran, Cong Wang, Anirban Mandal, Ewa Deelman:
Training Classifiers to Identify TCP Signatures in Scientific Workflows. INDIS@SC 2019: 61-68 - 2018
- [j9]Mariam Kiran, Eric Pouyoul, Anu Mercian, Brian Tierney, Chin Guok, Inder Monga:
Enabling intent to configure scientific networks for high performance demands. Future Gener. Comput. Syst. 79: 205-214 (2018) - [j8]Marco Gribaudo, Mauro Iacono, Mariam Kiran:
A performance modeling framework for lambda architecture based applications. Future Gener. Comput. Syst. 86: 1032-1041 (2018) - [j7]Fatma Alali, Nathan Hanford, Eric Pouyoul, Rajkumar Kettimuthu, Mariam Kiran, Ben Mack-Crane, Brian Tierney, Yatish Kumar, Dipak Ghosal:
Calibers: A bandwidth calendaring paradigm for science workflows. Future Gener. Comput. Syst. 89: 736-745 (2018) - [c22]Amel Bennaceur, Ampaeli Cano, Lilia Georgieva, Mariam Kiran, Maria Salama, Poonam Yadav:
Issues in Gender Diversity and Equality in the UK. GE@ICSE 2018: 5-9 - 2017
- [j6]Tatyana Eftonova, Mariam Kiran, Mike Stannett:
Long-term Macroeconomic Dynamics of Competition in the Russian Economy using Agent- based Modelling. Int. J. Syst. Dyn. Appl. 6(1): 1-20 (2017) - [j5]Bashir Mohammed, Mariam Kiran, Kabiru M. Maiyama, Mumtaz M. Kamala, Irfan-Ullah Awan:
Failover strategy for fault tolerance in cloud computing environment. Softw. Pract. Exp. 47(9): 1243-1274 (2017) - [c21]Kabiru Muhammad Maiyama, Demetres D. Kouvatsos, Bashir Mohammed, Mariam Kiran, Mumtaz Ahmed Kamala:
Performance Modelling and Analysis of an OpenStack IaaS Cloud Computing Platform. FiCloud 2017: 198-205 - [c20]Muhammad Usman, Adnan Iqbal, Mariam Kiran:
A bandwidth friendly architecture for Cloud Gaming. ICOIN 2017: 179-184 - [c19]Anu Mercian, Mariam Kiran, Eric Pouyoul, Brian Tierney, Inder Monga:
INDIRA: 'Application Intent' network assistant to configure SDN-based high performance scientific networks. OFC 2017: 1-3 - [c18]Bashir Mohammed, Babagana Modu, Kabiru M. Maiyama, Hassan Ugail, Irfan Awan, Mariam Kiran:
Failure Analysis Modelling in an Infrastructure as a Service (Iaas) Environment. UKPEW 2017: 41-54 - [i5]Bashir Mohammed, Sibusiso Moyo, Kabiru M. Maiyama, Sulayman Kinteh, Al Noaman M. K. Al-Shaidy, Mumtaz Ahmed Kamala, Mariam Kiran:
Technical Report on Deploying a highly secured OpenStack Cloud Infrastructure using BradStack as a Case Study. CoRR abs/1712.09152 (2017) - 2016
- [j4]Mariam Kiran, Anthony J. H. Simons:
Testing Software Services in Cloud Ecosystems. Int. J. Cloud Appl. Comput. 6(1): 42-58 (2016) - [c17]Bashir Mohammed, Mariam Kiran, Irfan-Ullah Awan, Kabiru M. Maiyama:
Optimising Fault Tolerance in Real-Time Cloud Computing IaaS Environment. FiCloud 2016: 363-370 - [c16]Bashir Mohammed, Mariam Kiran, Irfan-Ullah Awan, Kabiru M. Maiyama:
An Integrated Virtualized Strategy for Fault Tolerance in Cloud Computing Environment. UIC/ATC/ScalCom/CBDCom/IoP/SmartWorld 2016: 542-549 - 2015
- [c15]Mariam Kiran:
Modelling Cities as a Collection of TeraSystems - Computational Challenges in Multi-Agent Approach. ANT/SEIT 2015: 974-979 - [c14]Mariam Kiran, Peter Murphy, Inder Monga, Jon Dugan, Sartaj Singh Baveja:
Lambda architecture for cost-effective batch and speed big data processing. IEEE BigData 2015: 2785-2792 - [c13]Bashir Mohammed, Mariam Kiran:
Analysis of Cloud Test Beds Using OpenSource Solutions. FiCloud 2015: 195-203 - [c12]Ashraf Al-Ou'n, Mariam Kiran, Demetres D. Kouvatsos:
Using Agent-Based VM Placement Policy. FiCloud 2015: 272-281 - [c11]Savas Konur, Mariam Kiran, Marian Gheorghe, Mark Burkitt, Florentin Ipate:
Agent-Based High-Performance Simulation of Biological Systems on the GPU. HPCC/CSS/ICESS 2015: 84-89 - [c10]Mariam Kiran, Kabiru Maiyama, Haroon Mir, Bashir Mohammed, Ashraf Al-Ou'n:
Agent-Based Modelling as a Service on Amazon EC2: Opportunities and Challenges. UCC 2015: 251-255 - 2014
- [j3]Mariam Kiran, Gregory Katsaros, Jordi Guitart, Juan Luis Prieto:
Methodology for Information Management and Data Assessment in Cloud Environments. Int. J. Grid High Perform. Comput. 6(4): 46-71 (2014) - [c9]Mariam Kiran, Anthony J. H. Simons:
Model-Based Testing for Composite Web Services in Cloud Brokerage Scenarios. ESOCC Workshops 2014: 190-205 - [i4]Mariam Kiran:
Using FLAME Toolkit for Agent-Based Simulation: Case Study Sugarscape Model. CoRR abs/1408.3441 (2014) - [i3]Bashir Mohammed, Mariam Kiran:
Experimental Report on Setting up a Cloud Computing Environment at the University of Bradford. CoRR abs/1412.4582 (2014) - [i2]Mariam Kiran, Wei Liu:
Converting a Systems Dynamic Model to an Agent-based model for studying the Bicoid morphogen gradient in Drosophila embryo. CoRR abs/1412.5459 (2014) - 2013
- [j2]Mike Holcombe, Simon Coakley, Mariam Kiran, Lee Shawn Chin, Chris Greenough, David Worth, Silvano Cincotti, Marco Raberto, Andrea Teglio, Christophe Deissenberg, Sander van der Hoog, Herbert Dawid, Simon Gemkow, Philipp Harting, Michael Neugart:
Large-Scale Modeling of Economic Systems. Complex Syst. 22(2) (2013) - [c8]Afnan Ullah Khan, Manuel Oriol, Mariam Kiran:
Threat methodology for securing scalable video in the Cloud. ICITST 2013: 428-436 - [c7]Mariam Kiran, Andreas Friesen, Anthony J. H. Simons, Wolfgang K. R. Schwach:
Model-Based Testing in Cloud Brokerage Scenarios. ICSOC Workshops 2013: 192-208 - 2012
- [c6]Afnan Ullah Khan, Manuel Oriol, Mariam Kiran, Ming Jiang, Karim Djemame:
Security risks and their management in cloud computing. CloudCom 2012: 121-128 - [c5]Tom Kirkham, Karim Djemame, Mariam Kiran, Ming Jiang, Django Armstrong, George Kousiouris, George Vafiadis, Athanasia Evangelinou:
Risk based SLA management in clouds: A legal perspective. ICITST 2012: 156-160 - [c4]Tom Kirkham, Django Armstrong, Karim Djemame, Marcelo Corrales, Mariam Kiran, Iheanyi Nwankwo, Ming Jiang, Nikolaus Forgó:
Assuring Data Privacy in Cloud Transformations. TrustCom 2012: 1063-1069 - 2011
- [c3]Salem Fawaz Adra, Mariam Kiran, Phil McMinn, Neil Walkinshaw:
A multiobjective optimisation approach for the dynamic inference and refinement of agent-based model specifications. IEEE Congress on Evolutionary Computation 2011: 2237-2244 - [c2]Mariam Kiran, Ming Jiang, Django Armstrong, Karim Djemame:
Towards a Service Lifecycle Based Methodology for Risk Assessment in Cloud Computing. DASC 2011: 449-456 - 2010
- [b1]Mariam Kiran:
Investigating coevolutionary algorithms in agent-based economic systems. University of Sheffield, UK, 2010 - [c1]Mariam Kiran, Paul Richmond, Mike Holcombe, Lee Shawn Chin, David Worth, Chris Greenough:
FLAME: simulating large populations of agents on parallel hardware architectures. AAMAS 2010: 1633-1636 - [i1]Chris Greenough, Lee Shawn Chin, David Worth, Simon Coakley, Mike Holcombe, Mariam Kiran:
An Approach to the Parallelisation of Agent-Based Applications. ERCIM News 2010(81) (2010)
2000 – 2009
- 2008
- [j1]Mariam Kiran, Simon Coakley, Neil Walkinshaw, Phil McMinn, Mike Holcombe:
Validation and discovery from computational biology models. Biosyst. 93(1-2): 141-150 (2008)
Coauthor Index
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last updated on 2024-10-07 22:10 CEST by the dblp team
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