Efficient Secure Outsourcing Computation of Matrix Multiplication in Cloud Computing

2016 ◽  
Author(s):  
Shenmin Zhang ◽  
Hongwei Li ◽  
Kun Jia ◽  
Yuanshun Dai ◽  
Lian Zhao
Keyword(s):  
Cloud Computing ◽  
Matrix Multiplication ◽  
Secure Outsourcing

scholarly journals New Algorithms for Secure Outsourcing of Large-Scale Systems of Linear Equations

2020 ◽  
Vol 9 (5) ◽  
pp. 545-550
Keyword(s):  
Cloud Computing ◽  
Distributed Computing ◽  
Data Storage ◽  
Large Scale ◽  
Homomorphic Encryption ◽  
Linear Equations ◽  
Force Transmission ◽  
Large Scale Systems ◽  
Secure Outsourcing ◽  
Systems Of Linear Equations

Cloud computing is the on-request accessibility of computer system resources, specially data storage and computing power, without direct dynamic management by the client. In the simplest terms, cloud computing means storing and accessing data and programs over the Internet instead of your computer’s hard drive. Along the improvement of cloud computing, more and more applications are migrated into the cloud. A significant element of distributed computing is pay-more only as costs arise. Distributed computing gives strong computational capacity to the general public at diminished cost that empowers clients with least computational assets to redistribute their huge calculation outstanding burdens to the cloud, and monetarily appreciate the monstrous computational force, transmission capacity, stockpiling, and even reasonable programming that can be partaken in a compensation for each utilization way Tremendous bit of leeway is the essential objective that forestalls the wide scope of registering model for clients when their secret information are expended during the figuring procedure. Critical thinking is a system to arrive at the pragmatic objective of specific instruments that tackles the issues as well as shield from pernicious practices.. In this paper, we examine secure outsourcing for large-scale systems of linear equations, which are the most popular problems in various engineering disciplines. Linear programming is an operation research technique formulates private data by the customer for LP problem as a set of matrices and vectors, to develop a set of efficient privacypreserving problem transformation techniques, which allow customers to transform original LP problem into some arbitrary one while protecting sensitive input/output information. Identify that LP problem solving in Cloud component is efficient extra cost on cloud server. In this paper we are utilizing Homomorphic encryption system to increase the performance and time efficiency

A novel publicly delegable secure outsourcing algorithm for large-scale matrix multiplication

2020 ◽  
Vol 38 (5) ◽  
pp. 6445-6455
Author(s):  
Malay Kumar ◽  
Vaibhav Mishra ◽  
Anurag Shukla ◽  
Munendra Singh ◽  
Manu Vardhan
Keyword(s):  
Large Scale ◽  
Matrix Multiplication ◽  
Secure Outsourcing ◽  
Outsourcing Algorithm ◽  
Scale Matrix

scholarly journals Contextual Contracts for Component-Based Resource Abstraction in a Cloud of HPC Services

2019 ◽  
Author(s):  
Wagner Al Alam ◽  
Francisco Carvalho Junior
Keyword(s):  
Cloud Computing ◽  
Parallel Computing ◽  
Large Scale ◽  
Matrix Multiplication ◽  
Small Scale ◽  
Computing Systems ◽  
Computing Platform ◽  
Computing Platforms

The efforts to make cloud computing suitable for the requirements of HPC applications have motivated us to design HPC Shelf, a cloud computing platform of services for building and deploying parallel computing systems for large-scale parallel processing. We introduce Alite, the system of contextual contracts of HPC Shelf, aimed at selecting component implementations according to requirements of applications, features of targeting parallel computing platforms (e.g. clusters), QoS (Quality-of-Service) properties and cost restrictions. It is evaluated through a small-scale case study employing a componentbased framework for matrix-multiplication based on the BLAS library.

Modelling of Cloud Computing Enablers Using MICMAC Analysis and TISM

2019 ◽  
pp. 876-888 ◽  
Author(s):  
Nitin Chawla ◽  
Deepak Kumar
Keyword(s):  
Cloud Computing ◽  
Matrix Multiplication ◽  
Structural Modeling ◽  
Relationship Matrix ◽  
Interpretive Structural Modeling ◽  
Micmac Analysis ◽  
Business Efficiency ◽  
It Departments ◽  
Power And Dependence ◽  
The Relationship

This article describes how Cloud Computing is not just a buzzword but a shift from IT departments to the outsourcing vendors without impacting business efficiency. Some organizations are moving towards cloud computing but many have resistance to adopting cloud computing due to limitations in knowledge and awareness of the classifying elements, which effect decisions on the acceptance of cloud computing. Therefore, this article has focused on accumulating the elements, which can act as enablers, by reviewing existing literature and studies from both professional and academic viewpoints. All the identified enablers have been structurally modeled to develop the relationship matrix and establish the driving power and dependence power of every element. This is done by employing Total Interpretive Structural Modeling (TISM) and Cross Impact Matrix Multiplication Applied to Classification (MICMAC) analysis.

Modelling of Cloud Computing Enablers Using MICMAC Analysis and TISM

2018 ◽  
Vol 9 (3) ◽  
pp. 31-43
Author(s):  
Nitin Chawla ◽  
Deepak Kumar
Keyword(s):  
Cloud Computing ◽  
Matrix Multiplication ◽  
Structural Modeling ◽  
Relationship Matrix ◽  
Interpretive Structural Modeling ◽  
Micmac Analysis ◽  
Business Efficiency ◽  
It Departments ◽  
Power And Dependence ◽  
The Relationship

This article describes how Cloud Computing is not just a buzzword but a shift from IT departments to the outsourcing vendors without impacting business efficiency. Some organizations are moving towards cloud computing but many have resistance to adopting cloud computing due to limitations in knowledge and awareness of the classifying elements, which effect decisions on the acceptance of cloud computing. Therefore, this article has focused on accumulating the elements, which can act as enablers, by reviewing existing literature and studies from both professional and academic viewpoints. All the identified enablers have been structurally modeled to develop the relationship matrix and establish the driving power and dependence power of every element. This is done by employing Total Interpretive Structural Modeling (TISM) and Cross Impact Matrix Multiplication Applied to Classification (MICMAC) analysis.

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