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`EXHIBIT 1-2
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`EXHIBIT A
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`JON B. WEISSMAN, Ph.D.
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`EDUCATION
`Ph.D., Computer Science, University of Virginia, 1995.
`M.S., Computer Science, University of Virginia, 1989.
`B.S., Applied Mathematics and Computer Science, Carnegie-Mellon University, 1984.
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`PROFESSIONAL EXPERIENCE
`Professor, Computer Science
`Associate Professor, Computer Science
`Visiting Researcher and Distinguished Visitor
`Assistant Professor, Computer Science
`Assistant Professor, Computer Science
`Member of Technical Staff
`Software Engineer
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` Univ. of Minnesota (Summer 2012 to date)
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`Univ. of Minnesota (Fall 2003 to Spring 2012)
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`National e-Science Center, University of Edinburgh (2007-2008)
`Univ. of Minnesota (1999-2003)
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`Univ. of Texas San Antonio (1995-1999)
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`Mitre Corporation, McLean Virginia (1989-1991)
` Software A&E, Arlington Virginia (1984-1987)
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`PROFESSIONAL ACTIVITIES
`Tau Beta Engineering Honor Society, Member ACM, IEEE Senior Member
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`ACADEMIC AWARDS AND HONORS
`• George W. Taylor Distinguished Teaching Award 2022.
`• Best paper nominee, IEEE International Conference on Cloud Engineering (IC2E) 2015.
`• Best paper, IEEE Grid conference, 2009.
`• Honorary Fellow, College of Science and Engineering, University of Edinburgh, 2007-2008.
`• IEEE Senior Member, promoted 2003.
`• Success Story, ARL HPC (HPCMO), Virtual Data Grid Project, 2002.
`• CAREER Award, National Science Foundation, 1996.
`• Supercomputing Award for “High-Performance Computing with Legion”, SC, 1995.
`• Teaching Award, University of Virginia Teaching Medal of Excellence, 1995.
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`CONSULTING HISTORY
`• Cisco, Edge Computing, 2022.
`• Instrumental Inc, Cloud computing, 2011.
`• Beckman Coulter Inc, scheduling automation software, 2009-10.
`• ApeniMED, health informatics software development, 2006.
`• Avaki Inc. (now part of Oracle), Grid computing, 1999.
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`Consulting Expert
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`• client: William G. Osborne, Esq., Superior Edge vs. Monsanto, area: distributed software, project: code analysis,
`report, represented: plaintiff, status: closed, 2015.
`• client: Arnold & Porter LLP, Rosebud v. Adobe, area: distributed software, project: patent analysis, repre-
`sented: defense, status: closed, 2015.
`• client: Jones Day, Summit 6 vs. Apple, area: web technologies, project: patent analysis, represented: defense,
`status: closed, 2014.
`• client: Ropes & Gray LLP, case: Parallel Iron vs. EMC, area: storage systems, project: patent analysis,
`represented: defense, status: closed, 2012-2013.
`• client: Bridges & Mavrakakis LLP, case: Nokia/HTC vs. Apple, area: operating systems, project: software,
`patent analysis, represented: defense, status: closed, 2011.
`Professional references
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`• Jim Day (Farella Braun + Martel): https://www.fbm.com/james-l-day
`• Andrew Mace (Cooley): www.cooley.com/people/andrew-mace
`• Larissa Bifano: (DLA Piper): www.dlapiper.com/en/us/people/b/bifano-larissa/
`• Timothy Sullivan: (Faegre Baker Daniels LLP): www.faegrebd.com/en/professionals/s/sullivan-timothy-m
`• Phil Haack: (Martin Ribera Schumann LLP): https://www.martonribera.com/haack
`• Diek Van Nort (Morrison & Foerster LLP): www.mofo.com/people/v/van-nort-diek-o
`• Joshua Goldberg (Finnegan LLP): http://www.finnegan.com/
`MAJOR RESEARCH AFFILIATIONS
`1. Distributed Computing Systems Group, University of Minnesota, Founder and Co-Director..
`The Distributed Computing Systems Group (DCSG) is collection of faculty and students working on topics in
`parallel and distributed computing, Internet/Web, mobile, cloud, edge, IoT, big data and machine learning.
`Cross-cutting topics include storage, networking, operating systems/middleware, security, and applications.
`Research centers on system building with a focus on resource management, efficiency, reliability, and enabling
`newly emerging applications.
`2. Digital Technology Center, University of Minnesota, Investigator. The Digital Technology Center
`(DTC)’s goal is to create, promote, and coordinate cooperative interdisciplinary advanced technology initiatives
`between University, government, industry, and to serve as a point of entry into research and development
`partnerships with various partners. The DTC is a hub of innovation and excellence at the University of Minnesota
`in the digital technologies serving the industrial, educational, and public needs of the state of Minnesota and the
`nation. The DTC integrates research, education, and outreach in digital design, computer graphics and visualization,
`telecommunications, intelligent data storage and retrieval systems, multimedia, datamining, scientific computation,
`and other digital technologies. See dcsg.cs.umn.edu for details.
`3. CRIS:Center for Research in Intelligent Storage, University of Minnesota, Investigator. The
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`Center for Research in Intelligent Storage (CRIS) is a partnership between universities and industry, featuring high-
`quality, industrially relevant fundamental research, strong industrial support of collaboration in research and
`education, and direct transfer of university developed ideas, research results, and technology to U.S. industry.
`Research areas include storage and memory technologies, big data, cloud computing, backup/restore, data
`deduplication, and file systems. See cris.cs.umn.edu.
`GRANT FUNDING
`1. Joint Principal Investigator, Edge Computing, Cisco, 2022-2023, $165K (with Chandra).
`2. Principal Investigator, CNS Core: Small: Scaling the IoT with Constellation, NSF, 2019-2022, $500K (PI
`Chandra).
`3. Co-Principal Investigator, I/UCRC Phase II: Center on Intelligent Storage, NSF, 2016-2019, $895,516 (PI
`Du, Co-PIs Chandra, Lilja, Mokbel).
`4. Co-Principal Investigator, CSR: Small: Location, location, location (L3): Support for Geo-Centric Appli-
`cations, NSF, 2016-2019, $528K (PI Chandra).
`5. Co-Principal Investigator, II-NEW: One Cloud Does Not Fit All: Minnesota Integrated cloud Systems
`research Testbed (MIST), NSF, 2013-2016, $350K, (PI DU, co-PIs Chandra, Zhang).
`6. Principal Investigator, An Integrated Middleware Framework to Enable Extreme Collaborative Science,
`DOE, 2012-2015, $342K UMn share, collaborative with Rutgers and University of Chicago.
`7. Principal Investigator, CSR: Medium: Enriching Mobile User Experience Through The Cloud, NSF, 2012-
`2015, $700K (co-PI Chandra, Karypis).
`8. Principal Investigator, DC: Small: One Thousand Points of Light: Accelerating Data-Intensive Applications
`By Proxy, NSF, 2009-2012, $482K, including REU supplement $36K (co-PI Chandra).
`9. Co-Investigator, Collaborative Research: A Multi-University I/UCRC Center on Intelligent Storage, NSF,
`2009-2014, $400K, (DU PI, many co-PIs).
`10. Principal Investigator, Grid Computing for E-Science, National E-Science Centre, University of Edinburgh,
`2007-2008, $52K.
`11. Co-Investigator, ePCRN: Electronic Primary Care Research Network, NIH Roadmap, 2006-2008, $50K (CSE
`share annual), (Peterson PI, Delaney PI, several co-investigators).
`12. Co-Principal Investigator, ITR: A Data Mining and Exploration Middleware for Grid and Distributed
`Computing, NSF ITR, 2003-2007, $1.5M, (Kumar PI, Weissman co-PI).
`13. Investigator, Intelligent Storage Consortium, DTC, 2003-2009, $250K (Du PI, Weissman, Lilja, Tewfik, Kim
`co-PIs).
`14. Investigator, MRI: Development of a System for Interactive Analysis and Visualization of Multi-Terabyte
`Datasets, NSF MRI, 2004-2006, $300K (Woodward PI).
`15. Contributor, NIH NCRR, Intelligent Data Storage Support for Microarray data, equipment, (Mayo Clinic
`PI, with Du), 2004, $222K.
`16. Co-Principal Investigator, Intelligent Storage Consortium - Engenio, Engenio Information Technologies,
`2004-2005, $45K, (Du PI, Weissman co-PI).
`17. Principal Investigator, Making Parallel Computing Easy, Department of Energy (Office of Advanced Scien-
`tific Computing Research), 2002-2007, $250K, sole PI.
`18. Principal Investigator, A Framework for Adaptive Grid Services, NSF ACR-CNS, 2003-2008, $240K, sole
`PI.
`19. Principal Investigator, Towards Community Services: Putting Parallel Network Services On-line, NSF EIA-
`NGS Program, 2002-2003, $30K, sole PI.
`20. Co-Principal Investigator, Collaborative Data Analysis and Visualization, NSF EIA Research Resources
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`(Collaborative Research), 2002-2005, $500K (incl. 2 RA’s shared with Du), (Woodward PI, Weissman, Du, Retzel,
`Wetherby co-PIs.)
`21. Investigator, Metacomputing: Enabling Technologies and the Virtual Data Grid, Army High Performance
`Computing and Research Center (AHPCRC), 2000-2004, $260K, original contributor to center proposal.
`22. Principal Investigator, Resource Management for Parallel and Distributed Systems, NSF CAREER award
`ACR, 1996-2001, $200K, REU supplement $5K (2000), sole PI.
`23. Principal Investigator, Smart File Objects: An Application-directed File Access Paradigm, Texas Advanced
`Research Program ARP-010115-226, 1997-2000, $106K, sole PI.
`24. Participant, Telecommunication Networks for Mobile and Distributed Computing and Communications,
`AFOSR-F49620-96-1-0472, 1996-2000, $2M, (PI Hiromoto).
`25. Co-Principal Investigator, Building a Pipeline for Minority Scholars, NSF CISE MI-I CDA-9633299, 1996
`- 1999, $1.3M. (Hiromoto PI, Weissman, Das, Boppana, Psarris, Jeffery, Rosen co-PIs).
`26. Fellowship, Applying Parallel Object-Oriented Computing to Scientific Applications, NASA Graduate Student
`Researchers Program Fellowship, Jet Propulsion Laboratory, 1991-1995, $66K.
`PUBLICATIONS
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`Journal Articles: for up-to-date-list, see www.cs.umn.edu/˜jon
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`1. Kwangsung Oh, Abhishek Chandra, and Jon Weissman, Network Cost-aware Geo-distributed Data Analytics System
`IEEE Transactions on Parallel and Distributed Systems, 2022.
`2. Kwangsung Oh, Nan Qin, Abhishek Chandra, and Jon Weissman, Wiera: Policy-Driven Multi-Tiered Geo-
`Distributed Cloud Storage System, IEEE Transactions on Parallel and Distributed Systems, Vol. 31, No. 11,
`Feb 2020.
`3. Albert Jonathan, Mathew Ryden, Kwangsung Oh, Abhishek Chandra, and Jon Weissman, Nebula: Dis- tributed
`Edge Cloud for Data Intensive Computing, IEEE Transactions on Parallel and Distributed Systems, Vol. 28,
`No. 11, Nov 2017.
`4. Benjamin Heintz, Abhishek Chandra, Ramesh Sitaraman, and Jon B. Weissman, End-to-end Optimization for
`Geo-Distributed MapReduce, IEEE Transactions on Cloud Computing, Vol. 4, No. 3, July 2016.
`5. Jinoh Kim, Seonho Kim, and Jon B. Weissman, A Security-enabled Grid System for MINDS Distributed Data
`Mining, Journal of Grid Computing, 2014.
`6. Murray Cole, Shantenu Jha, Daniel S. Katz, Manish Parashar, Omer Rana, and Jon B. Weissman, Dis- tributed
`Computing Practice for Large-Scale Science and Engineering Applications, Concurrency: Practice and
`Experience, Volume 25, Issue 11, September 2013.
`7. Adam Barker, Jon B. Weissman, Jano van Hemert, Accelerating Service-Oriented Workflows, IEEE Trans-
`actions on Services Computing, 5(3), 2012.
`8. Jinoh Kim, Abhishek Chandra and Jon B. Weissman, Passive Network Performance Estimation for Large- scale,
`Data-intensive Computing, IEEE Transactions on Parallel and Distributed Systems, 22(8), August 2011.
`9. Jia Jingxi, Bharadwaj Veeravalli, and Jon B. Weissman, Scheduling Multi-source Divisible Loads on Arbi- trary
`Networks, IEEE Transactions on Parallel and Distributed Systems, 21(4), April 2010.
`10. Jinoh Kim, Abhishek Chandra and Jon B. Weissman, Using Data Accessibility for Resource Selection in
`Large-scale Distributed Systems, IEEE Transactions on Parallel and Distributed Systems, 20(6), June 2009.
`11. Byoung-Dai Lee, Jon B. Weissman, Young-Kwang Nam, Adaptive middleware supporting scalable perfor- mance
`for high-end network services, Journal of Network and Computer Applications, 32(3), May 2009.
`12. Adam Barker, Jon B. Weissman and Jano van Hemert, The Circulate Architecture: Avoiding Workflow
`Bottlenecks Caused By Centralised Orchestration, Journal of Cluster Computing, 12(2), 2009.
`13. Jason D. Sonnek, Abhishek Chandra, and Jon B. Weissman, Adaptive Reputation-Based Scheduling on Un-
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`reliable Distributed Infrastructures, IEEE Transactions on Parallel and Distributed Systems, 18(11), November
`2007.
`14. Darin England, Bharadwaj Veeravalli, and Jon B. Weissman, A Robust Spanning Tree Topology for Data Collection
`and Dissemination in Distributed Environments, IEEE Transactions for Parallel and Distributed Systems,
`18(5), May 2007.
`15. Rahul Trivedi, Abhishek Chandra, and Jon B. Weissman, Heterogeity-Aware Workload Distribution in Donation
`Based Grids, invited to the International Journal for High Performance Computing and Applications
`(IJHPCA), 20(4), 2006.
`16. Darin England and Jon B. Weissman, A Resource Leasing Policy for On-demand Computing, invited to the
`International Journal for High Performance Computing and Applications (IJHPCA), 20(1), 2006.
`17. Jon B. Weissman, Darin England, and Lakshman Abburi Rao, “Integrated Scheduling: The Best of Both Worlds,”
`Journal of Parallel and Distributed Computing, 63(6), 2003.
`18. Jon B. Weissman and Byoung-Dai Lee, “The Virtual Service Grid: An Architecture for Delivering High-End
`Network Services”, Concurrency: Practice and Experience, Vol. 14, No. 4, April 2002.
`19. Jon B. Weissman, “Predicting the Cost and Benefit of Adapting Parallel Applications in Clusters”, Journal
`of Parallel and Distributed Computing, Vol. 62, No. 8, August 2002.
`20. Jon B. Weissman, Mike Gingras, and Mahesh Marina, “Optimizing Remote File Access for Parallel and
`Distributed Network Applications” Journal of Parallel and Distributed Computing, Vol. 61, No. 11, November
`2001.
`21. Jon B. Weissman, “Prophet: Automated Scheduling of SPMD Programs in Workstation Networks”, Con-
`currency: Practice and Experience, Vol. 11, No. 6, August 1999.
`22. Jon B. Weissman “Gallop: The Benefits of Wide-Area Computing for Parallel Processing”, Journal of Parallel
`and Distributed Computing, Vol. 54, No. 2, November 1998.
`23. Jon B. Weissman and Xin Zhao, “Scheduling Parallel Applications in Distributed Networks,” Journal of Cluster
`Computing, Vol. 1, No. 1, May 1998, invited paper.
`24. Andrew S. Grimshaw, Jon B. Weissman, and W. Timothy Strayer, “Portable Run-time Support for Dynamic
`Object-Oriented Parallel Processing,” ACM Transactions on Computer Systems, Vol. 14, No. 2, May 1996.
`25. Jon B. Weissman and Andrew S. Grimshaw, “A Framework for Partitioning Parallel Computations in Heterogeneous
`Environments”, Concurrency: Practice and Experience, Vol. 7, No. 5, August 1995.
`26. Andrew Grimshaw, Jon B. Weissman, Emily West, and Edmond Loyot, Jr., “Metasystems: An Approach Combining
`Parallel Processing and Heterogeneous Distributed Computing Systems”, Journal of Parallel and Distributed
`Computing, Vol. 21, No. 3, June 1994.
`27. Jon B. Weissman, Andrew S. Grimshaw, and Robert R. Ferraro, “Parallel Object-Oriented Computation
`Applied to a Finite Element Problem,” Journal of Scientific Programming, Vol. 2, No. 4, 1993.
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`Books and Book Chapters
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`1. Benjamin Heintz, Abhishek Chandra and Jon Weissman, Cross-Phase Optimization in MapReduce, in Cloud
`Computing for Data-Intensive Applications, Springer, 2014.
`2. Jon B. Weissman and Jinoh Kim, Network Awareness in Volunteer Networks, in Desktop Grid Computing,
`CRC Press, 2013.
`3. Steve Chapin and Jon B. Weissman, Distributed and Multiprocessor Scheduling (Operating Systems Area),
`The Computer Science and Engineering Handbook, 2004.
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`Highly Selective Articles: : for up-to-date-list, see www.cs.umn.edu/˜jon
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`1. Yixuan Wang, Abhishek Chandra, and Jon Weissman, Jingle: IoT-Informed Autoscaling for Efficient Re-
`source Management in Edge Computing, to appear in IEEE/ACM CCGrid, 2024.
`2. Yixuan Wang, Abhishek Chandra, and Jon Weissman, SQuBA: Social Quorum Based Access Control for
`Open IoT Environments, IEEE Edge, 2023, best student paper awardee.
`3. Lei Huang, Zhiying Liang, Nikhil Sreekumar, Sumanth Kaushik Vishwanath, Cody Perakslis, Abhishek Chan- dra,
`and Jon Weissman, Armada: A Robust Latency-Sensitive Edge Cloud in Heterogeneous Edge-Dense Environments,
`42nd IEEE International Conference on Distributed Computing Systems (ICDCS), 2022.
`4. Kwangsung Oh, Abhishek Chandra, and Jon Weissman, A Network Cost-aware Geo-distributed Data Ana- lytics
`System 20th IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing (CCGrid, 2021.
`5. Albert Jonathan, Abhishek Chandra, and Jon Weissman, Wide-area Adaptive Stream Processing ACM
`Middleware, 2020.
`6. Nikhil Sreekumar, Abhishek Chandra, and Jon Weissman, Towards a Robust Edge-Native Storage System
`Fifth ACM/IEEE Symposium on Edge Computing (SEC), 2020.
`7. Zach Leidall, Abhishek Chandra, Jon Weissman, An Edge-based Framework for Cooperation in Internet of
`Things Applications, 2nd USENIX Workshop on Hot Topics in Edge Computing (HotEdge), Renton, Wash- ington,
`July 2019.
`8. Albert Jonathan, Abhishek Chandra, and Jon Weissman, Multi-Query Optimization in Wide-Area Streaming
`Analytics, ACM Symposium on Cloud Computing 2018 (SOCC), Carlsbad, California, October 2018.
`9. Feng Liu, Kate Keahey, Pierre Riteau, and Jon Weissman, Dynamically Negotiating Capacity between On- Demand
`and Batch Clusters, International Conference for High Performance Computing, Networking, Storage, and
`Analysis (SC’18), Nov 2018, Dallas, TX.
`10. Albert Jonathan, Abhsishek Chandra, and Jon B. Weissman, Rethinking Adaptability in Wide-Area Stream
`Processing Systems, Workshop on Hot Topics in Cloud Computing (HotCloud ’18), June 2018.
`11. Kwangsung Oh, Abhishek Chandra and Jon Weissman, TripS: Automated Multi-tiered Data Placement in a
`Geo-distributed Cloud Environment, 10th ACM International Systems and Storage Conference (SYSTOR),
`May 2017, Haifa Israel.
`12. Kwangsung Oh, Abhishek Chandra, and Jon Weissman, Wiera: Towards Flexible Multi-Tiered Geo-Distributed
`Cloud Storage Instances, 25th IEEE International Symposium on High Performance Distributed Computing
`(HPDC), June 2016, Kyoto, Japan.
`13. Matteo Turilli, Feng Liu, Zhao Zhang, Andre Merzky, Michael Wilde, Jon Weissman, Daniel S. Katz, and Shantenu
`Jha, Integrating Abstractions to Enhance the Execution of Distributed Applications, 30th IEEE International
`Parallel & Distributed Processing Symposium (IPDPS), May 2016, Chicago, Il.
`14. Albert Jonathan, Abhishek Chandra, and Jon Weissman, Awan: Locality-aware Resource Manager for Geo-
`distributed Data-intensive Applications, IEEE International Conference on Cloud Engineering, April 2016,
`Berlin, Germany.
`15. Francis Liu and Jon Weissman, Elastic Job Bundling: An Adaptive Resource Request Strategy for Large-Scale
`Parallel Applications, to appear in the International Conference for High Performance Computing, Networking,
`Storage, and Analysis (SC’15), Nov 2015, Austin, TX.
`16. John Kolb, Prashant Chaudhary, Alexander Schillinger, Abhishek Chandra and Jon Weissman, Cloud-Based, User-
`Centric Mobile Application, IEEE International Conference on Cloud Engineering, March 2015, Tempe, AZ.
`17. Ajaykrishna Raghavan, Abhishek Chandra, and Jon B. Weissman, Tiera: Towards Flexible Multi-Tiered
`Cloud Storage Instances, ACM Middleware, 2014.
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`18. John Kolb, Will Myott, Thao Nguyen, Abhishek Chandra and Jon B. Weissman, Exploiting User Interest in
`Data-Driven Cloud-based Mobile Optimization, IEEE Conference on Mobile Cloud Computing, April 2014,
`Oxford, UK
`19. Mathew Ryden, Kwangsung Oh, Abhishek Chandra and Jon B. Weissman, Nebula: Distributed Edge Cloud
`for Data Intensive Computing, IEEE International Conference on Cloud Engineering, March 2014, Boston,
`MA
`20. Abhishek Chandra, Jon Weissman, and Benjamin Heintz Decentralized Edge Clouds, IEEE Internet Com-
`puting, 2013.
`21. Benjamin Heintz, Chenyu Wang, Abhishek Chandra, and Jon B. Weissman, Cross-Phase Optimization in
`MapReduce, IEEE International Conference on Cloud Engineering, March 2013, San Francisco, CA
`22. Chonglei Mei, Daniel Taylor, Chenyu Wang, Abhishek Chandra, and Jon B. Weissman, Sharing-aware Cloud-based
`Mobile Outsourcing IEEE 5th International Conference on Cloud Computing, 2012.
`23. Atul Katiyar and Jon B. Weissman, ViDeDup: An Application-Aware Framework for Video De-duplication,
`Third Usenix Workshop on Hot Topics in Storage and File Systems (HotStorage’11), Portland, OR 2011.
`24. Louis-Claude Canon, Emmanuel Jeannot, and Jon B. Weissman, A Scheduling and Certification Algorithm for
`Defeating Collusion in Desktop Grids, 31st IEEE International Conference on Distributed Computing Sys-
`tems (ICDCS), Minneapolis, MN, June 2011.
`25. Louis-Claude Canon, Emmanuel Jeannot, and Jon B. Weissman, A Dynamic Approach for Characterizing Collusion
`in Desktop Grids, 24th IEEE International Parallel and Distributed Processing Symposium (IPDPS), 2010.
`26. Abhishek Chandra and Jon B. Weissman, Nebulas: Using Distributed Voluntary Resources to Build Clouds,
`Workshop on Hot Topics in Cloud Computing (HotCloud ’09), June 2009.
`27. Jon B. Weissman and Siddharth Ramakrishnan, Using Proxies to Accelerate Cloud Applications, Workshop on
`Hot Topics in Cloud Computing (HotCloud ’09), June 2009.
`28. Adam Barker, Jon B. Weissman and Jano van Hemert, Eliminating the Middle-Man: Peer-to-Peer Dataflow, 17th
`IEEE International Symposium on High Performance Distributed Computing (HPDC), Boston, MA, June 2008.
`29. Jinoh Kim, Abhishek Chandra and Jon B. Weissman, Accessibility-based Resource Selection in Loosely- coupled
`Distributed Systems, 28th IEEE International Conference on Distributed Computing Systems (ICDCS), Beijing,
`China, June 2008.
`30. Krishnaveni Budati, Abhishek Chandra, and Jon B. Weissman, RIDGE: Combining Reliability and Per- formance
`in Open Grid Platforms, 16th IEEE International Symposium on High Performance Distributed Computing
`(HPDC), June 2007.
`31. Jason D. Sonnek, Mukesh Nathan, Abhishek Chandra, and Jon B. Weissman, Reputation Based Schedul- ing
`on Unreliable Distributed Infrastructures, The 26th International Conference on Distributed Computing
`Systems (ICDCS), July 2006.
`32. Darin England, Jayashree Sadagopan, and Jon B. Weissman, A New Metric for Robustness with Application to
`Job Scheduling, Fourteenth IEEE International Symposium on High Performance Distributed Computing
`(HPDC), 2005.
`33. Jon B. Weissman and Xin Zhao, “Run-time Support for Scheduling Parallel Applications in Heterogeneous NOWs,”
`Proceedings of the Sixth IEEE International Symposium on High Performance Distributed Computing (HPDC),
`August 1997.
`34. Jon B. Weissman and Andrew S. Grimshaw, “A Federated Model for Scheduling in Wide-Area Systems,”
`Proceedings of the Fifth IEEE International Symposium on High Performance Distributed Computing (HPDC),
`August 1996.
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`35. Jon B. Weissman and Andrew S. Grimshaw, “Network Partitioning of Data Parallel Computations,” Pro- ceedings
`of the Third IEEE International Symposium on High Performance Distributed Computing (HPDC), August
`1994.
`Selective Articles: : for up-to-date-list, see www.cs.umn.edu/˜jon
`36. Albert Jonathan, Abhishek Chandra, and Jon Weissman, Locality-Aware Load Sharing in Mobile Cloud Computing
`IEEE/ACM International Conference on Utility and Cloud Computing, 2017.
`37. Albert Jonathan, Abhishek Chandra, and Jon Weissman, Ensuring Reliability in Geo-Distributed Edge Cloud,
`IEEE RWS (Resilience Week), Wilmington, Delaware, 2017.
`38. Kwangsung Oh, Ajaykrishna Raghavan, Abhishek Chandra and Jon Weissman, Redefining Data Locality for Cross-
`Data Center Storage, International Workshop on Software-Defined Ecosystems (BigSystem 2015), June 2015,
`Portland, OR.
`39. William Myott, Thao Nguyen, Abhishek Chandra, George Karypis, and Jon B. Weissman, Opportunities for
`Data-Driven Cloud-based Mobile Optimization, invited to 2014 International Conference on Collaboration
`Technologies and Systems, Minneapolis, MN, May 2014.
`40. Siddharth Ramakrishna, Robert Reutiman, Abhishek Chandra, and Jon B. Weissman, Accelerating Dis- tributed
`Workflows With Edge Resources, Second International Workshop on Workflow Models, Systems, Ser- vices
`and Applications in the Cloud (CloudFlow), Boston MA, May 2013.
`41. Mike Cardosa, Anshuman Nangia, Chenyu Wang, Abhishek Chandra and Jon B. Weissman, Exploring MapReduce
`Efficiency with Highly-Distributed Data, The Second International Workshop on MapReduce and its
`Applications (MapReduce ’11), June 2011.
`42. Pradeep Sundarrajan, Abhishek Gupta, Matthew Ryden, Rohit Nair, Abhishek Chandra, and Jon B. Weiss- man,
`Early Experience with the Distributed Nebula Cloud, The Fourth International Workshop on Data Intensive
`Distributed Computing (DIDC ’11), June 2011.
`43. Shantenu Jha, Daniel S. Katz, Manish Parashar, Omer Rana, and Jon B. Weissman, Critical Perspectives on
`Large-Scale Distributed Applications and Production Grids, 10th IEEE/ACM Conference on Grid Computing
`(Grid 2009), Banff, Canada, 2009, winner best paper award.
`44. Adam Barker, Paolo Besanay, David Robertson, and Jon B. Weissman, The Benefits Of Service Choreography For
`Data-Intensive Computing, Proceedings of the 2009 Workshop in Challenges of Large Applications in
`Distributed Environments (CLADE), 2009.
`45. Adam Barker, Jon B. Weissman and Jano van Hemert, Orchestrating Data-centric Workflows, IEEE/ACM CCGrid
`International Symposium on Cluster Computing and the Grid (CCGrid), Lyon, France, May 2008.
`46. Vasumathi Sundaram, Abhishek Chandra and Jon B. Weissman, Exploring the Throughput-Fairness Tradeoff of
`Deadline Scheduling in Heterogeneous Computing Environments, Proceedings of the ACM International
`Conference on Measurement and Modeling of Computer Systems (SIGMETRICS), short paper, Annapolis,
`MD, June 2008.
`47. Krishnaveni Budati, Jinoh Kim, Abhishek Chandra and Jon Weissman, NGS: Service Adaptation in Open Grid
`Platforms, Proceedings of the IPDPS NSF Next Generation Software Workshop, March 2007.
`48. Jon B. Weissman, Vipin Kumar, Varun Chandola, Eric Eilertson, Levent Ertoz, Gyorgy Simon, Seonho Kim,
`and Jinoh Kim, DDDAS/ITR: A Data Mining and Exploration Middleware for Grid and Distributed Computing,
`Workshop on Dynamic Data Driven Application Systems - DDDAS 2007, Beijing, China, May 2007.
`49. Jinoh Kim, Abhishek Chandra, and Jon B. Weissman, Exploiting Heterogeneity for Collective Data Down- loading
`in Volunteer-based Networks, IEEE/ACM CCGrid International Symposium on Cluster Computing and the
`Grid (CCGrid), 2007.
`50. Jon B. Weissman, Seonho Kim, and Darin England, A Framework for Dynamic Service Adaptation in the Grid,
`Proceedings of the IPDPS NSF Next Generation Software Workshop Denver, Colorado, April 2005.
`51. Jason D. Sonnek and Jon B. Weissman, A Quantitative Comparison of Reputation Systems in the Grid, 6th
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`IEEE/ACM International Workshop on Grid Computing (GRID).
`52. Jon B. Weissman, Seonho Kim, and Darin England, Supporting the Dynamic Grid Service Lifecycle,
`IEEE/ACM CCGrid International Symposium on Cluster Computing and the Grid (CCGrid), 2005.
`53. Darin England and Jon B. Weissman, “A Stochastic Control Model for the Deployment of Dynamic Grid Services”,
`5th IEEE/ACM International Workshop on Grid Computing (GRID), 2004.
`54. Darin England and Jon B. Weissman, “A Load Sharing Model for the Computational Grid,” Workshop on Job
`Scheduling Strategies for Parallel Processing (JSSPP) with Sigmetrics 2004.
`55. Seonho Kim and Jon B. Weissman, “A GA-based approach for scheduling decomposable data grid applica- tions,”
`International Conference on Parallel Processing (ICPP) 2004.
`56. Byoung-Dai Lee and Jon B. Weissman, “Adaptive Resource Selection for Grid-enabled Network Services,”
`IEEE 2nd International Symposium on Network Computing and Applications (NCA), 2003.
`57. Byoung-Dai Lee and Jon B. Weissman, “Adaptive Resource Scheduling for Network Services,” IEEE 3rd
`International Workshop on Grid Computing, 2002.
`58. Byoung-Dai Lee and Jon B. Weissman, “Community Service Toolkit for Rapid Deployment of Network Services,”
`IEEE 2002 Workshop on Cluster Computing, 2002.
`59. Jon B. Weissman and Pramod Srinivasan, “Ensemble Schedulng: Resource Co-Allocation on the Computa- tional
`Grid”, IEEE 2nd International Workshop on Grid Computing (GRID), November 2001.
`60. Byoung-Dai Lee and Jon B. Weissman, “An Adaptive Service Grid Architecture for Dynamic Replication,”
`IEEE 2nd International Workshop on Grid Computing (GRID), November 2001.
`61. Jon B. Weissman and Byoung-Dai Lee, “The Service Grid: Supporting Scalable Heterogenous Services in Wide-
`Area Networks,” The IEEE 2001 Symposium on Applications and the Internet (SAINT), January 2001.
`62. Jon B. Weissman, “Scheduling Multi-Component Applications in Heterogeneous Wide-area Networks,” Het-
`erogeneous Computing Workshop, International Parallel and Distributed Processing Symposium, May 2000.
`63. Jon B. Weissman, “Fault Tolerant Wide-Area Parallel Computing,” IEEE Workshop on Fault-Tolerant Parallel
`and Distributed Systems, International Parallel and Distributed Processing Symposium, May 2000.
`64. Mike Gingras and Jon B. Weissman, “Smart Multimedia File Objects,” IEEE Workshop on Internet Appli-
`cations (WIA), July 1999.
`65. Jon B. Weissman, “Smart File Objects: A Remote File Access Paradigm,” Sixth ACM Workshop on I/O in
`Parallel and Distributed Systems (IOPADS), May 1999.
`66. Jon B. Weissman, “The Interference Paradigm for Network Job Scheduling,” Heterogeneous Computing
`Workshop, Tenth International Parallel and Distributed Processing Symposium, April 1996.
`67. Jon B. Weissman, Andrew S. Grimshaw, and Robert R. Ferraro, “Parallel Object-Oriented Computation
`Applied to a Finite Element Problem,” Object-Oriented Numerics, 1993.
`68. Lisa Sokol, Jon B. Weissman, and Paula Mutchler, “The Role of Event Granularity in Parallel Simulation Design,”
`Proceedings of the Parallel and Distributed Simulation Conference (PADS), 1992.
`69. Richard Weatherly, David Seidel, and Jon B. Weissman, “Aggregate Level Simulation Protocol,” Proceedings of
`the 1991 Summer Computer Simulation Conference, July 1991.
`70. Lisa Sokol, Jon B. Weissman, and Paula Mutchler, “An Empirical Comparison of MTW and Time Warp in
`a Shared Memory Environment,” Proceedings of the SCS Multiconference on Work in Progress (WSMC),
`January 1991.
`71. Lisa Sokol, Jon B. Weissman, and Paula Mutchler, “MTW: An Empirical Performance Study,” Proceedings of
`the Winter Simulation Conference (WSC), December 1991.
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`Short Papers
`
`1. Zach Leidall, Abhishek Chandra, Jon Weissman Creating an Abstraction to Exploit IoT Synergies, 2nd ACM/IEEE
`International Conference on Internet-of-Things Design and Implementation (IoTDI 2017), Ex- tended
`Abstract/Poster, April 2017.
`2. Arvanitis TN, Taweel A, Zhao L, Delaney BC, Peterson KA , Speedie SM, Sim I, Weissman J, Fontaine P,
`Lange C, Janowiec M, and Stone J, Supporting e-trials over distributed networks: a tool for capturing randomised
`control, MEDNET 2007.
`3. Seonho Kim, Jon B. Weissman, Kevin A. Peterson, A Secure Federated Health Data Query System for Primary
`Care Clinical Trials on the Grid, 2007 Annual Meeting NIH Cancer Grid (CABig), February 2007.
`4. Speedie SM, Peterson K, Fontaine P, Weissman J, Delaney B, Arvanitis T, Taweel A, Sim I, Lange C, Janowiec
`M, Stone J, Wolff, A., An Infrastructure for Conducting Clinical Trials in Primary Care. “Current Issues in
`Clinical Re