Book ChapterDOI
Task-Scheduling Algorithms in Cloud Environment
Preeta Sarkhel,Himansu Das,Lalit Kumar Vashishtha +2 more
- pp 553-562
TLDR
Three different task-scheduling algorithms such as Minimum-Level Priority Queue (MLPQ), MIN-Median, Mean-MIN-MAX which aims to minimize the makespan with maximum utilization of cloud are proposed.Abstract:
Cloud computing has increased its popularity due to which it is been used in various sectors Now it has come to light and is in demand because of amelioration in technology Many applications are submitted to the data centers, and services are given as pay-per-use basis As there is an increase in the client demands, the workload is increased, and as there are limited resources, workload is moved to different data centers in order to handle the client demands on as-you-pay basis Hence, scheduling the increasing demand of workload in the cloud environments is highly necessary In this paper, we propose three different task-scheduling algorithms such as Minimum-Level Priority Queue (MLPQ), MIN-Median, Mean-MIN-MAX which aims to minimize the makespan with maximum utilization of cloud The results of our proposed algorithms are also compared with some existing algorithms such as Cloud List Scheduling (CLS) and Minimum Completion Cloud (MCC) Schedulingread more
Citations
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Book ChapterDOI
Classification of Intrusion Detection Using Data Mining Techniques
Roma Sahani,Shatabdinalini,Chinmayee Rout,J. Chandrakanta Badajena,Ajay Kumar Jena,Himansu Das +5 more
TL;DR: This paper focuses to identify normal and attack data present in the network with the help of C4.5 algorithm which is one of the decisions tree techniques, and also it helps to improve the IDS system to identify the type of attacks present in a network.
Book ChapterDOI
Nature Inspired Optimizations in Cloud Computing: Applications and Challenges
TL;DR: This chapter aims at providing a detailed knowledge about nature inspired optimization algorithms and their use in the above mentioned problems of cloud computing.
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Intelligent Personality Analysis on Indicators in IoT-MMBD-Enabled Environment
Rohit Rastogi,Devendra K. Chaturvedi,Santosh Satya,Navneet Arora,Piyush Trivedi,Akshay Singh,Amit Kr. Sharma,Ambuj Singh +7 more
TL;DR: In this paper, the use of multimedia and IOT to detect the personality and to analyze the different human behaviors is discussed. And the authors have used one of the supervised learnings called regression.
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Intelligent Analysis for Personality Detection on Various Indicators by Clinical Reliable Psychological TTH and Stress Surveys
Rohit Rastogi,Devendra K. Chaturvedi,Santosh Satya,Navneet Arora,Piyush Trivedi,Akshay Singh,Amit Kr. Sharma,Ambuj Singh +7 more
TL;DR: In this paper, the authors used machine learning for personality detection that involves the development and initial validation of questionnaire, which assesses four dimensions relating to individual differences in uses of humor, which are Self-enhancing, Affiliative, Aggressive and Self-defeating.
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Big Data Scientific Workflows in the Cloud: Challenges and Future Prospects
TL;DR: This paper identifies open research problems associated with this domain, giving insights on specific issues like workflow scheduling and execution and deployment of big data scientific workflows in a multi-site cloud environment.
References
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Journal ArticleDOI
Cloud computing and emerging IT platforms: Vision, hype, and reality for delivering computing as the 5th utility
TL;DR: This paper defines Cloud computing and provides the architecture for creating Clouds with market-oriented resource allocation by leveraging technologies such as Virtual Machines (VMs), and provides insights on market-based resource management strategies that encompass both customer-driven service management and computational risk management to sustain Service Level Agreement (SLA) oriented resource allocation.
Journal ArticleDOI
Dynamic Resource Allocation Using Virtual Machines for Cloud Computing Environment
Zhen Xiao,Weijia Song,Qi Chen +2 more
TL;DR: This paper presents a system that uses virtualization technology to allocate data center resources dynamically based on application demands and support green computing by optimizing the number of servers in use and develops a set of heuristics that prevent overload in the system effectively while saving energy used.
Journal ArticleDOI
Online optimization for scheduling preemptable tasks on IaaS cloud systems
TL;DR: This paper proposes two online dynamic resource allocation algorithms that adjust the resource allocation dynamically based on the updated information of the actual task executions and shows that these algorithms can significantly improve the performance in the situation where resource contention is fierce.
Journal ArticleDOI
Efficient task scheduling algorithms for heterogeneous multi-cloud environment
TL;DR: Three task scheduling algorithms, called MCC, MEMAX and CMMN for heterogeneous multi-cloud environment, which aim to minimize the makespan and maximize the average cloud utilization are presented.
Journal ArticleDOI
Improved Max-Min Algorithm in Cloud Computing
TL;DR: Improved version of Max-min algorithm is proposed to outperform scheduling map at least similar to RASA map in total complete time for submitted jobs and demonstrates achieving schedules with comparable lower makespan rather than R ASA and original Max- Min.