Below the list of projects cofunded by the María de Maeztu program (selected via internal calls, in this link the first one launched at the beginning of the program, and in this link the second one, launched in September 2016).
In addition, the program supports:
- the joint calls for cooperation between DTIC and the UPF Department of Experimental and Health Sciences (CEXS), also recognised as a María de Maeztu Unit of Excellence. Here the link to the second call (November 2017). The first call took place in January 2017.
- its own Open Science and Innovation program
- a pilot program to promote educational research collaborations with industry
The detail of the internal procedures for the distribution of funds associated to the program can be found here
Data-driven distributed computation
Data-driven distributed computation
Data-driven distributed computation
Networking is becoming an intrinsic part of computation bringing with it a host of new theoretical and practical challenges. Services are hosted in virtual environments where the services outlive the computers where they are hosted: virtual computers where these services temporarily reside go up and down and migrate around different computers. This has increased the complexity of managing services and the physical networks and clusters of servers that host them. Researchers and industry have been looking for new management ideas and are playing with new models like Named Data Networking (NDN) where network addresses are replaced with data names instead of using device locations, or Software Defined Networking (SDN), where the control plane of the network (building routing tables) is removed from the network switches and routers and is implemented in software in regular computer servers
It has been recently shown that declarative database query languages, such as Datalog, could naturally be used to specify and implement network services and protocols. The approach, referred to as declarative networking, makes the specifications of complex network protocols concise and intuitive, and directly executable through distributed query processing algorithms. Applications for declarative networking go far beyond network protocols, and languages and techniques developed in this setting provide the basis for declarative distributed computing. This paradigm has been used for security and provenance in distributed query processing, in the analysis of asynchronous event systems.
There are several variants of concrete languages for specifying DDSs, but their common denominator is data centricity: computations in a single node are limited to evaluations of queries on a relational database (DB), and messages passed between nodes are snippets of DBs, providing a close correspondence between the programs and a formal specification in logic of their computation. Our aim in this project to provide a formal, systematic characterization of verification of DDSs.
This work complements a project in which one of the PI has been involved in collaboration with IBM T. J. Watson Research Center and the Department of Computing at Imperial College London that has been developing a system (depicted in the figure below) for the analysis and execution of declaratively specified distributed programs. Details of the system can be found here. The results of the project will help to guide the development of new verification tools.
To know more:
- Presentation by Jorge Lobo at the Data-driven Knowledge Extraction Workshop, June 2016, Barcelona
Slides and work referenced: J. Ma, F. Le, A. Russo and J. Lobo, "Declarative Framework for Specification, Simulation and Analysis of Distributed Applications," in IEEE Transactions on Knowledge and Data Engineering, vol. 28, no. 6, pp. 1489-1502.
Related Assets:
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Jorge Lobo receives Best Paper Award at SACMAT 2017
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Rankothge W, Le F, Russo A, Lobo J. Optimizing Resources Allocation for Virtualized Network Functions in a Cloud Center using Genetic Algorithms. IEEE Transactions on Network and Service Management ( Volume: PP, Issue: 99 )
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Rankothge W, Ma J, Le F, Russo A, Lobo J. Towards making network function virtualization a cloud computing service. Proceedings of the 2015 IFIP/IEEE International Symposium on Integrated Network Management (IM)
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Pasarella E, Lobo J. A Datalog Framework for Modeling Relationship-based Access Control Policies. 22nd ACM on Symposium on Access Control Models and Technologies
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[NETWORKS] Datasets for the Evaluation of Virtualized Network Functions Resource Allocation Algorithms
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[PhD thesis] Towards virtualized network functions as a service
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[NETWORKS] Data for NFVSDN experiments
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Calvanese D, Montali M, Lobo J. Verification of Fixed-Topology Declarative Distributed Systems with External Data. Proceedings of the 12th Alberto Mendelzon International Workshop on Foundations of Data Management
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Rullo A, Serra E, Bertino E, Lobo J. Shortfall-Based Optimal Placement of Security Resources for Mobile IoT Scenarios. Computer Security – ESORICS 2017. Lecture Notes in Computer Science, vol 10493
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Rankothge W, Le F, Russo A, Lobo J. Experimental results on the use of genetic algorithms for scaling virtualized network functions. 2015 IEEE Conference on Virtualization and Software Defined Network (NFV-SDN)
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Rullo A, Serra E, Lobo J. Redundancy as a Measure of Fault-Tolerance for the Internet of Things: A Review. Policy-Based Autonomic Data Governance. Lecture Notes in Computer Science.
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Ma J, Rankothge W, Makaya C, Morales M, Le F, Lobo J. An Overview of A Load Balancer Architecture for VNF chains Horizontal Scaling. 14th International Conference on Network and Service Management (CNSM)
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Briceno R, Bulatov A, Dalmau V, Larose B. Long range actions, connectedness, and dismantlability in relational structures. arXiv pre-print
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Rankothge W, Ramalhinho , Lobo J. On the Scaling of Virtualized Network Functions. 2019 IFIP/IEEE Symposium on Integrated Network and Service Management (IM)
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Dalmau V, Krokhin A, Manokaran R. Towards a Characterization of Constant-Factor Approximable Finite-Valued CSPs
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Law M, Russo A, Bertino A, Lobo J, Broda K. Representing and Learning Grammars in Answer Set Programming. The Thirty-Third AAAI Conference on Artificial Intelligence (AAAI 2019)
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Barceló P, Baumgartner A, Dalmau V, Kimelfeld B. Regularizing Conjunctive Features for Classification. 38th ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems
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Lobo J. Relationship‐based access control: More than a social network access control model. WIREs Data Mining Knowledge Discovery.