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DotGrid: A.NET-based infrastructure for global Grid computing
, Article 6th IEEE International Symposium on Cluster Computing and the Grid, 2006. CCGRID 06, 16 May 2006 through 19 May 2006 ; 2006 ; 0769525857 (ISBN); 9780769525853 (ISBN) ; Abutalebi, A. H ; Ayough, L. M ; Hessabi, S ; Sharif University of Technology
IEEE Computer Society
2006
Abstract
Recently, Grid infrastructures have provided wide integrated use of resources. DotGrid intends to introduce required Grid services and toolkits that are implemented as a layer wrapped over the existing operating systems. Our DotGrid has been developed based on Microsoft .NET in Windows and MONO .NET in Linux and UNIX. Using DotGrid APIs, Grid middlewares and applications can be implemented easily. We evaluated our DotGrid capabilities by implementing some applications including a grid-based distributed cryptographic engine and also a typical computational problem. © 2006 IEEE
SkipTree: A Scalable range-queryable distributed data structure for multidimensional data
, Article 16th International Symposium on Algorithms and Computation, ISAAC 2005, Hainan, 19 December 2005 through 21 December 2005 ; Volume 3827 LNCS , 2005 , Pages 298-307 ; 03029743 (ISSN); 3540309357 (ISBN); 9783540309352 (ISBN) ; Toossi, M ; Ghodsi, M ; Sharif University of Technology
2005
Abstract
This paper presents the SkipTree, a new balanced, distributed data structure for storing data with multidimensional keys in a peer-to-peer network. The SkipTree supports range queries as well as single point queries which are routed in O(log n) hops. SkipTree is fully decentralized with each node being connected to O(logn) other nodes. The memory usage for maintaining the links at each node is O(log n log log n) on average and O(log2 n) in the worst case. Load balance is also guaranteed to be within a constant factor. © Springer-Verlag Berlin Heidelberg 2005
Formal process algebraic modeling, verification, and analysis of an abstract Fuzzy Inference Cloud Service
, Article Journal of Supercomputing ; Vol. 67, issue. 2 , February , 2014 , pp. 345-383 ; Online ISSN: 1573-0484 ; Rahmani, A. M ; Movaghar, A ; Teshnehlab, M
Abstract
In cloud computing, services play key roles. Services are well defined and autonomous components. Nowadays, the demand of using Fuzzy inference as a service is increasing in the domain of complex and critical systems. In such systems, along with the development of the software, the cost of detecting and fixing software defects increases. Therefore, using formal methods, which provide clear, concise, and mathematical interpretation of the system, is crucial for the design of these Fuzzy systems. To obtain this goal, we introduce the Fuzzy Inference Cloud Service (FICS) and propose a novel discipline for formal modeling of the FICS. The FICS provides the service of Fuzzy inference to the...
Learning of gaussian processes in distributed and communication limited systems
, Article IEEE Transactions on Pattern Analysis and Machine Intelligence ; Volume 42, Issue 8 , 2020 , Pages 1928-1941 ; Motahari, S. A ; Manzuri Shalmani, M. T ; Sharif University of Technology
IEEE Computer Society
2020
Abstract
It is of fundamental importance to find algorithms obtaining optimal performance for learning of statistical models in distributed and communication limited systems. Aiming at characterizing the optimal strategies, we consider learning of Gaussian Processes (GP) in distributed systems as a pivotal example. We first address a very basic problem: how many bits are required to estimate the inner-products of some Gaussian vectors across distributed machines? Using information theoretic bounds, we obtain an optimal solution for the problem which is based on vector quantization. Two suboptimal and more practical schemes are also presented as substitutes for the vector quantization scheme. In...
Network and application-aware cloud service selection in peer-assisted environments
, Article IEEE Transactions on Cloud Computing ; 2018 ; 21687161 (ISSN) ; Malekimajd, M ; Movaghar, A ; Sharif University of Technology
Abstract
There are a vast number of cloud service providers, which offer virtual machines (VMs) with different configurations. From the companies perspective, an appropriate selection of VMs is an important issue, as the proper service selection leads to improved productivity, higher efficiency, and lower cost. An effective service selection cannot be done without a systematic approach due to the modularity of requests, the conflicts between requirements, and the impact of network parameters. In this paper, we introduce an innovative framework, called PCA, to solve service selection problem in the hybrid environment of peer-assisted, public, and private clouds. PCA detects the conflicts between the...
Private Inner product retrieval for distributed machine learning
, Article 2019 IEEE International Symposium on Information Theory, ISIT 2019, 7 July 2019 through 12 July 2019 ; Volume 2019-July , 2019 , Pages 355-359 ; 21578095 (ISSN); 9781538692912 (ISBN) ; Maddah Ali, M. A ; Mirmohseni, M ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2019
Abstract
In this paper, we argue that in many basic algorithms for machine learning, including support vector machine (SVM) for classification, principal component analysis (PCA) for dimensionality reduction, and regression for dependency estimation, we need the inner products of the data samples, rather than the data samples themselves.Motivated by the above observation, we introduce the problem of private inner product retrieval for distributed machine learning, where we have a system including a database of some files, duplicated across some non-colluding servers. A user intends to retrieve a subset of specific size of the set of the inner product of every pair of data items in the database with...