scholarly journals Design & Implementation of Enhanced Security Architecture to Improve Performance of Cloud Computing

2021 ◽  
Vol 23 (3) ◽  
Author(s):  
Anil Gupta ◽  
◽  
Dr. Meghna Dubey ◽  
Dr. Durgesh Kumar Mishra ◽  
◽  
...  
Keyword(s):  
Cloud Computing ◽  
Computation Time ◽  
Detailed Comparison ◽  
Public Access ◽  
Memory Consumption ◽  
Improve Performance ◽  
Solution Approach ◽  
Java Technology ◽  
Novel Model ◽  
Open Nature

Cloud computing offers various features such as creates, configure and customize application online. User can access applications over the Internet and they can also access database via Internet. Open nature and public access make their application vulnerable for several security attacks. This paper attempt to integrated different previously defined security approaches to propose a new and novel model of security. Here, proposed solution approach to improve performance of confidentiality, authentication, integrity and access control with better and strong way. Proposed solution is implemented using java technology and evaluated based on computation time and memory consumption. A detailed comparison with graph is also demonstrated in experimental analysis section.

scholarly journals Evaluasi Kepuasan Pelayanan Pengguna Aplikasi OPAC Perpustakaan STMIK AMIKOM Yogyakarta

2015 ◽  
Vol 1 (1) ◽  
pp. 46
Author(s):  
Fatimah Nur Arifah ◽  
Abidarin Rosidi ◽  
Hanif Al Fatta
Keyword(s):  
Performance Analysis ◽  
User Satisfaction ◽  
Ease Of Use ◽  
Public Access ◽  
End User ◽  
Improve Performance ◽  
Five Dimensions ◽  
Satisfaction Index ◽  
Level Of Satisfaction ◽  
End User Computing

Penelitian ini bertujuan untuk mengetahui dan mengukur tingkat kepuasan pengguna terhadap aplikasi Online Public Access Catalog (OPAC) pada Perpustakaan STMIK AMIKOM Yogyakarta. Subjek penelitian ini ialah mahasiswa yang terdaftar sebagai anggota perpustakaan dan objek penelitian ini adalah aplikasi OPAC Perpustakaan STMIK AMIKOM Yogyakarta. Analisis data dalam penelitian ini menggunakan diagram Importance Performance Analysis (IPA) dipadukan dengan Indeks Kepuasan Pengguna (IKP) didasarkan pada indikator-indikator dari lima dimensi End User Computing Satisfaction yaitu isi (content), keakuratan (accuracy), bentuk (format), kemudahan penggunaan (ease of use) dan ketepatan waktu (timeliness). Hasil penelitian menunjukkan pengguna OPAC Perpustakaan STMIK AMIKOM Yogyakarta cukup puas dengan hasil perhitungan IKP 78,01 %. Penelitian ini diharapkan dapat memberi masukan pada pengelola OPAC sebagai bahan acuan untuk meningkatkan kinerja OPAC.This study aims to identify and measure the level of satisfaction of users of the application Online Public Access Catalog (OPAC) in the library STMIK AMIKOM Yogyakarta. These subjects are students who are registered as members of the library and the object of this study is OPAC STMIK Library AMIKOM Yogyakarta. Analysis of the data in this study using a diagram of Importance Performance Analysis (IPA) which is combined with User Satisfaction Index (IKP) based on the five dimensions of End User Computing Satisfaction; content, accuracy, format, ease of use and timeliness. The results showed users of OPAC STMIK AMIKOM Yogyakarta quite satisfied with the results of the calculation IKP 78.01%. This research is expected to provide input to the manager of the OPAC as a reference to improve performance of the OPAC.

scholarly journals Optimization Models for Multiple Resource Planning

2021 ◽  
Author(s):  
Norah Mohammed Z. Al-Dossari ◽  
Mohamed Haouari ◽  
Mohamed Kharbeche
Keyword(s):  
Resource Planning ◽  
Solution Approach ◽  
Organizational Environments ◽  
Resource Loading ◽  
Administrative Development ◽  
Efficient Resource ◽  
Using Data ◽  
Multiple Resource ◽  
The Cost ◽  
Novel Model

Multiple resource planning is a very crucial undertaking for most organizations. Apart from reducing operational complexity, multiple resource planning facilitates efficient allocation of resources, which reduces costs by minimizing the cost of tardiness and the cost for additional capacity. The current research investigates multiple resource loading problems (MRLP). MRLPs are very prevalent in today’s organizational environments and are particularly critical for organizations that handle concurrent, time-intensive, and multiple-resource projects. Using data obtained from the Ministry of Administrative Development, Labor and Social Affairs (ADLSA), a MRLP is proposed. The problem utilizes data regarding staff, time, equipment, and finance to ensure efficient resource allocation among competing projects. In particular, the research proposes a novel model and solution approach for the MRLP. Computational experiments are then performed on the model. The results show that the model performs well, even for higher instances. The positive results attest to the effectiveness of the proposed MRLP problem.

A Cloud Privacy-Preserving Model Using Gaussian Mutation-Based Bacterial Foraging Optimization and Genetic Crossover Operation

2021 ◽  
Author(s):  
K Anand ◽  
A. Vijayaraj ◽  
M. Vijay Anand
Keyword(s):  
Cloud Computing ◽  
Privacy Preservation ◽  
Cost Savings ◽  
Cloud Security ◽  
Public Access ◽  
Key Generation ◽  
Gaussian Mutation ◽  
Bacterial Foraging Optimization ◽  
Sensitive Data ◽  
Bacterial Foraging

Abstract The necessity of security in the cloud system increases day by day in which the data controllers harvest the rising personal and sensitive data volume.The cloud has some unprotected private data as well as data that has been outsourced for public access, which is crucial for cloud security statements. An advanced legal data protection constraint is required due to the resultant of repeated data violations. While dealing with sensitive data, most of the existing techniques failed to handle optimal privacy and different studies were performed to take on cloud privacy preservation. Hence, the novel model of privacy preservation in the cloud and artificial intelligence (AI) techniques were used to tackle these challenges. These AI methods are insight-driven, strategic, and more efficient organizations in cloud computing. However, the cost savings, agility, higher flexibility businesses are offered with cloud computing by data hosting. Data cleansing and restoration are the two major steps involved in the proposed privacy replica. In this study, we proposed Chaotic chemotaxis and Gaussian mutation-based Bacterial Foraging Optimization with genetic crossover operation (CGBFO- GC) algorithm for optimal key generation. Deriving the multi-objective function parameters namely data preservation ratio, hiding ratio, and modification degree that accomplishes optimal key generation using CGBFO- GC algorithm. Ultimately, the proposed CGBFO- GC algorithm provides more efficient performance results in terms of cloud security than an existing method such as SAS-DPSO, CDNNCS, J-SSO, and GC.

Green Cloud Computing

2014 ◽  
pp. 202-214 ◽  
Author(s):  
Haibo Wang ◽  
Da Huo
Keyword(s):  
Cloud Computing ◽  
Site Selection ◽  
Social Issues ◽  
Multiple Criteria Decision Making ◽  
Neighborhood Search ◽  
Solution Approach ◽  
Proposed Model ◽  
Selection Decision ◽  
Decision Making Model ◽  
Solution Methodology

This chapter considers the data center site selection problem in cloud computing with extensive reviews on site selection decision models. The factors considered in the site selection include economic, environmental, and social issues. After discussing the environmental impact of data centers and its social implications, the authors present a nonlinear multiple criteria decision-making model with green computing criteria and solve the problem by using a variable neighborhood search heuristic. The proposed model and solution methodology can be applied to other site selection problems to address the environmental awareness, and the results illustrate both the robustness and attractiveness of this solution approach.

Vehicular Cloud and Fog Computing Architecture, Applications, Services, and Challenges

2020 ◽  
pp. 268-296
Author(s):  
Priyanka Gaba ◽  
Ram Shringar Raw
Keyword(s):  
Cloud Computing ◽  
High Speed ◽  
Fog Computing ◽  
Detailed Comparison ◽  
Fast Response ◽  
Computing Technique ◽  
Vehicular Cloud ◽  
Network Bandwidth ◽  
Real Time Applications ◽  
Safety Features

VANET, a type of MANET, connects vehicles to provide safety and non-safety features to the drivers and passengers by exchanging valuable data. As vehicles on road are increasing to handle such data cloud computing, functionality is merged with vehicles known as Vehicular Cloud Computing(VCC) to serve VANET with computation, storage, and networking functionalities. But Cloud, a centralized server, does not fit well for vehicles needing high-speed processing, low latency, and more security. To overcome these limitations of Cloud, Fog computing was evolved, extending the functionality of cloud computing model to the edge of the network. This works well for real time applications that need fast response, saves network bandwidth, and is a reliable, secure solution. An application of Fog is with vehicles known as Vehicular Fog Computing (VFC). This chapter discusses cloud computing technique and its benefits and drawbacks, detailed comparison between VCC and VFC, applications of Fog Computing, its security, and forensic challenges.

Enhanced Trust Path between Two Entities in Cloud Computing Environment

2016 ◽  
Vol 6 (3) ◽  
pp. 15-31 ◽  
Author(s):  
Usha Divakarla ◽  
K. Chandrasekaran
Keyword(s):  
Cloud Computing ◽  
Network Security ◽  
Service Provider ◽  
Common Factor ◽  
Computation Time ◽  
Trust Model ◽  
Computing Environment ◽  
Cloud Computing Environment ◽  
The Common

Trust is the common factor of any network security. In cloud, trust is the major factor as this trust develops a relation between the user and resource of the service provider. To develop a strong trust there has to be a strong trust path between two entities. The model proposed builds a strong trust path between two important entities in cloud namely user and resources of the service provider. The trust path thus built strengthens the security of the resources as well as the authentication of the user. The implementation proved that trust model developed is more efficient in terms of computation time.

scholarly journals Exploiting Coarse-Grained Parallelism Using Cloud Computing in Massive Power Flow Computation

Energies ◽  
2018 ◽  
Vol 11 (9) ◽  
pp. 2268 ◽  
Author(s):  
Dong-Hee Yoon ◽  
Sang-Kyun Kang ◽  
Minseong Kim ◽  
Youngsun Han
Keyword(s):  
Cloud Computing ◽  
Power Systems ◽  
Power System ◽  
Power Flow ◽  
Computation Time ◽  
Coarse Grained ◽  
Contingency Analysis ◽  
Flow Computation ◽  
Cloud Computing System ◽  
The Impact

We present a novel architecture of parallel contingency analysis that accelerates massive power flow computation using cloud computing. It leverages cloud computing to investigate huge power systems of various and potential contingencies. Contingency analysis is undertaken to assess the impact of failure of power system components; thus, extensive contingency analysis is required to ensure that power systems operate safely and reliably. Since many calculations are required to analyze possible contingencies under various conditions, the computation time of contingency analysis increases tremendously if either the power system is large or cascading outage analysis is needed. We also introduce a task management optimization to minimize load imbalances between computing resources while reducing communication and synchronization overheads. Our experiment shows that the proposed architecture exhibits a performance improvement of up to 35.32× on 256 cores in the contingency analysis of a real power system, i.e., KEPCO2015 (the Korean power system), by using a cloud computing system. According to our analysis of the task execution behaviors, we confirmed that the performance can be enhanced further by employing additional computing resources.

scholarly journals Model checking software for phylogenetic trees using distribution and database methods

2013 ◽  
Vol 10 (3) ◽  
pp. 16-30 ◽  
Author(s):  
José Ignacio Requeno ◽  
José Manuel Colom
Keyword(s):  
Model Checking ◽  
Phylogenetic Tree ◽  
Dna Sequence ◽  
Phylogenetic Trees ◽  
Computation Time ◽  
Biological Properties ◽  
Traditional Model ◽  
Temporal Logics ◽  
Memory Consumption ◽  
Speed Up

Summary Model checking, a generic and formal paradigm stemming from computer science based on temporal logics, has been proposed for the study of biological properties that emerge from the labeling of the states defined over the phylogenetic tree. This strategy allows us to use generic software tools already present in the industry. However, the performance of traditional model checking is penalized when scaling the system for large phylogenies. To this end, two strategies are presented here. The first one consists of partitioning the phylogenetic tree into a set of subgraphs each one representing a subproblem to be verified so as to speed up the computation time and distribute the memory consumption. The second strategy is based on uncoupling the information associated to each state of the phylogenetic tree (mainly, the DNA sequence) and exporting it to an external tool for the management of large information systems. The integration of all these approaches outperforms the results of monolithic model checking and helps us to execute the verification of properties in a real phylogenetic tree.

scholarly journals A Novel Approach for Discovering Condition-Specific Correlations of Gene Expressions within Biological Pathways by Using Cloud Computing Technology

2014 ◽  
Vol 2014 ◽  
pp. 1-8
Author(s):  
Tzu-Hao Chang ◽  
Shih-Lin Wu ◽  
Wei-Jen Wang ◽  
Jorng-Tzong Horng ◽  
Cheng-Wei Chang
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Cloud Computing ◽  
Cancer Recurrence ◽  
Computation Time ◽  
Gene Expression Omnibus ◽  
Biological Pathways ◽  
Data Sets ◽  
Gene Expressions ◽  
Differential Gene

Microarrays are widely used to assess gene expressions. Most microarray studies focus primarily on identifying differential gene expressions between conditions (e.g., cancer versus normal cells), for discovering the major factors that cause diseases. Because previous studies have not identified the correlations of differential gene expression between conditions, crucial but abnormal regulations that cause diseases might have been disregarded. This paper proposes an approach for discovering the condition-specific correlations of gene expressions within biological pathways. Because analyzing gene expression correlations is time consuming, an Apache Hadoop cloud computing platform was implemented. Three microarray data sets of breast cancer were collected from the Gene Expression Omnibus, and pathway information from the Kyoto Encyclopedia of Genes and Genomes was applied for discovering meaningful biological correlations. The results showed that adopting the Hadoop platform considerably decreased the computation time. Several correlations of differential gene expressions were discovered between the relapse and nonrelapse breast cancer samples, and most of them were involved in cancer regulation and cancer-related pathways. The results showed that breast cancer recurrence might be highly associated with the abnormal regulations of these gene pairs, rather than with their individual expression levels. The proposed method was computationally efficient and reliable, and stable results were obtained when different data sets were used. The proposed method is effective in identifying meaningful biological regulation patterns between conditions.

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