scholarly journals Understanding Load Balancing Algorithms and Their Need in Cloud Computing

2021 ◽  
Vol 9 (VI) ◽  
pp. 5378-5385
Author(s):  
Mridul Sadhu
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Data Processing ◽  
Data Storage ◽  
Natural World ◽  
The Internet ◽  
Exponential Increase ◽  
The World ◽  
Share Data

With each passing day, the number of users on the internet increases and thus does the data associated with them. This implies an exponential increase in the data storage and data processing units of practically all the servers on the net. Considering that the underlying idea and original purpose of the internet was to share data and resources, it becomes an increasingly difficult task to manage gigantic amounts of data associated with the ever-increasing number of users. This is why Cloud Computing has been able to bring a revolution in the world of technology and become the indispensable part of the internet that it is today. In this paper, we review the topic of load balancing and the various load balancing algorithms upon different measures. We also try to understand the most challenging problems that the cloud faces and some new load balancing techniques inspired from the natural world.

Cloud Computing Security: An Investigation into the Security Issues and Challenges Associated with Cloud Computing, for both Data Storage and Virtual Applications

2015 ◽  
Vol 1 (2) ◽  
pp. 15
Author(s):  
Hamisu Alhaji Ali
Keyword(s):  
Information Technology ◽  
Cloud Computing ◽  
Data Storage ◽  
World Economy ◽  
The Internet ◽  
Cloud Environment ◽  
Cloud Computing Security ◽  
Security Issues ◽  
On Demand ◽  
The World

In recent years, cloud computing has developed from the promising business concept that it used to be, to one of Information Technology (IT) industry's most developing section. Now that the world economy was hit by recession, the victims of this tragedy continually understand that by just outsourcing or tapping the cloud  resources, a package of virtualise, elastic, instant on-demand provision, and scalable; infrastructure, platform, and software can be access fast and easy inform of services at a negligible amount via the internet. However, as individuals and organizations embarked on the course of deploying their information and data into the cloud, anxieties are beginning to develop on whether the cloud environment is safe. This research provides an overview of the cloud deployment model, the services they offer and discusses the security issues and challenges of cloud computing in both data storage and virtual applications/servers.

scholarly journals Analysis of Load Balancing Techniques in Cloud Computing

2005 ◽  
Vol 4 (2) ◽  
pp. 737-741 ◽  
Author(s):  
Amandeep Sidhu ◽  
Supriya Kinger
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Data Storage ◽  
Cloud Storage ◽  
Job Scheduling ◽  
Single Node ◽  
Computing Paradigm ◽  
System A ◽  
Share Data ◽  
Scalable Network

Cloud Computing is an emerging computing paradigm. It aims to share data, calculations, and service transparently over a scalable network of nodes. Since Cloud computing stores the data and disseminated resources in the open environment. So, the amount of data storage increases quickly. In the cloud storage, load balancing is a key issue. It would consume a lot of cost to maintain load information, since the system is too huge to timely disperse load. Load balancing is one of the main challenges in cloud computing which is required to distribute the dynamic workload across multiple nodes to ensure that no single node is overwhelmed. It helps in optimal utilization of resources and hence in enhancing the performance of the system. A few existing scheduling algorithms can maintain load balancing and provide better strategies through efficient job scheduling and resource allocation techniques as well. In order to gain maximum profits with optimized load balancing algorithms, it is necessary to utilize resources efficiently. This paper discusses some of the existing load balancing algorithms in cloud computing and also their challenges.

scholarly journals AN IMPLEMENTATION OF LOAD BALANCING ALGORITHM IN CLOUD ENVIRONMENT

2016 ◽  
Vol 15 (9) ◽  
pp. 7124-7129
Author(s):  
Sheenam Kamboj ◽  
Mr. Navtej Singh Ghumman
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Data Storage ◽  
Cloud Environment ◽  
Computing Paradigm ◽  
Share Data ◽  
Load Balancing Algorithm

Cloud Computing is an emerging computing paradigm. It aims to share data, calculations, and service transparently overascalable network of nodes. Since Cloud computing stores the data and disseminated resources in the openenvironment.So, the amount of data storage increases quickly. As we know that a cloud is the collection of many nodes,which can support various types of application that is used by the clients on a basis of pay per use. Therefore, the system,which is incurring a cost for the user should function smoothly and should have algorithms that can continue the propersystem functioning even at peak usage. In this paper, a load balancing algorithm has been discussed and implemented inCloudSim environment. Multiple number of experiments have been conducted to analyze the results.

scholarly journals OPTIMASI QUERY PADA LAPORAN TRANSAKSI PENJUALAN MENGGUNAKAN MATERIALIZED VIEW (Studi Kasus : Moonly café)

CCIT Journal ◽  
2018 ◽  
Vol 11 (1) ◽  
pp. 1-14
Author(s):  
Febrianta Surya Nugraha ◽  
Febryan Hari Purwanto ◽  
Fachruddin Edi Nugroho Saputro
Keyword(s):  
Cloud Computing ◽  
Information System ◽  
Data Processing ◽  
Data Storage ◽  
Query Optimization ◽  
The Internet ◽  
Materialized View ◽  
Android Platform ◽  
Speed Performance ◽  
Speed Up

The development of café business in Yogyakarta in 2017 is growing very rapidly. Moonly café currently uses sales information system using android platform and use data storage through cloud computing. The growing business café, transactions are done every day more and more. Sales information system runs slower when accessing larger data. These problems illustrate the lack of efficient time in data processing and the necessity of using query optimization in accessing data to speed up the process. The purpose of this study is to determine the speed performance in displaying monthly sales report by using query where clause, view table and materialized view table. The database is using MySql Server accessed via the internet, then recorded for the monthly sales report. In addition to comparing the performance of speed in displaying monthly sales reports, the authors also compare the speed of queries in displaying the report the amount of sales of each item each month on the table results of sales reports generated either from the query, view tables or materialized view tables. Use of materialized view to display monthly sales transaction reports faster than using query where clause or view. The use of materialized view to display reports the number of sales of each item each month faster than using the query where clause and view.

A REVIEW ON OVERVIEW OF ETHICAL HACKING

2021 ◽  
Vol 6 (4) ◽  
Author(s):  
Vaishnavi Bhagwat Savant ◽  
Rupali D. Kasar ◽  
Priti B. Savant
Keyword(s):  
Cloud Computing ◽  
Credit Card ◽  
Dark Side ◽  
The Internet ◽  
The People ◽  
The World ◽  
Private Citizens ◽  
E Mail

The explosive growth of the Internet has brought many good things such as E-commercebanking, E-mail, cloud computing, but there is also a dark side such as Hacking, Backdoors, Trapdoors etc. Hacking is the first big problem faced by Governments, companies, and private citizens around the world. Hacking means reading email’s of someone, stealing passwords, stealing credit card numbers etc. An ethical hacker is one who can help the people who are suffered by this hackings. This paper describes about Ethical hackers, it’s types and phases of hacking

NoSQL Databases

2014 ◽  
pp. 186-215 ◽  
Author(s):  
Ganesh Chandra Deka
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Data Processing ◽  
Open Source ◽  
Data Storage ◽  
Big Data Processing ◽  
Nosql Databases ◽  
Data Intensive ◽  
Huge Data ◽  
Data Intensive Applications

NoSQL databases are designed to meet the huge data storage requirements of cloud computing and big data processing. NoSQL databases have lots of advanced features in addition to the conventional RDBMS features. Hence, the “NoSQL” databases are popularly known as “Not only SQL” databases. A variety of NoSQL databases having different features to deal with exponentially growing data-intensive applications are available with open source and proprietary option. This chapter discusses some of the popular NoSQL databases and their features on the light of CAP theorem.

The Internet

2016 ◽  
Keyword(s):  
Cloud Computing ◽  
World Wide ◽  
Criminal Liability ◽  
The Internet ◽  
Freedom Of Information ◽  
Freedom Of Information Act ◽  
Technical Description ◽  
Legal Perspective ◽  
The World ◽  
Use Of The Internet

The internet is now the main way in which information is obtained. Chapter 13 considers the internet from a legal perspective, focusing on information and its disclosure. It seeks to provide a non-technical description of the operation of the internet as exemplified by the world wide web. It discusses the use of the internet by bodies subject to the Freedom of Information Act 2000 and other statutes and outlines some of the pitfalls of such use. For instance, a publication of information on a website operated from England may expose the publisher to civil or criminal liability in any country of the world on the basis of the law of those countries. The chapter explains the meaning of cookies, cloud computing, hackers, crackers and viruses. and discusses the problems of determining jurisdiction and seeking enforcement.

Emerging Trends of Big Data in Cloud Computing

2021 ◽  
pp. 38-55
Author(s):  
Poonam Nandal ◽  
Deepa Bura ◽  
Meeta Singh
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Data Processing ◽  
Open Source ◽  
Software Framework ◽  
Effective Solution ◽  
Apache Hadoop ◽  
Large Sets ◽  
Exponential Increase ◽  
Emerging Trends

In today's world where data is accumulating at an ever-increasing rate, processing of this big data was a necessity rather than a need. This required some tools for processing as well as analysis of the data that could be achieved to obtain some meaningful result or outcome out of it. There are many tools available in market which could be used for processing of big data. But the main focus on this chapter is on Apache Hadoop which could be regarded as an open source software based framework which could be efficiently deployed for processing, storing, analyzing, and to produce meaningful insights from large sets of data. It is always said that if exponential increase of data is processing challenge then Hadoop could be considered as one of the effective solution for processing, managing, analyzing, and storing this big data. Hadoop versions and components are also illustrated in the later section of the paper. This chapter majorly focuses on the technique, methodology, components, and methodologies adopted by Apache Hadoop software framework for big data processing.

Auto-Scaling in the Cloud Environment

2020 ◽  
pp. 84-98
Author(s):  
Ravindra Kumar Singh Rajput ◽  
Dinesh Goyal
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
The Internet ◽  
Data Traffic ◽  
Cloud Environment ◽  
Software Application ◽  
Workload Balancing ◽  
Specific Configuration ◽  
Using Data ◽  
Auto Scaling

Every software application has its own minimum set of requirements like CPU, storage, memory, networking, and power. These have to be integrated into a specific configuration to allow the smooth functioning of the software application. When data traffic becomes higher than expected, higher resources are required. There may not be enough time to provision new resources manually; in such cases, an auto-scaling system is required for managing these situations. Cloud computing means using data, programs, and other resources pooled in the data center and accessed through the internet instead of the user's computer. In the chapter, the authors discussed some aspects related to cloud computing like cloud workload, load balancing, load balancing algorithms, scaling techniques, and auto-scaling to fulfill cloud workload balancing requirements.

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