This paper proposes an initiative data prefetching scheme on storage servers in distributed file systems for cloud computing. Storage servers analyze I/O access history to predict future requests and prefetch data, then push it proactively to relevant client machines. Two prediction algorithms are proposed to forecast block access and direct prefetching. Evaluation experiments show the approach improves I/O performance for distributed file systems in cloud environments by reducing client involvement in prefetching.
Performing initiative data prefetchingKamal Spring
This paper presents an initiative data prefetching scheme on the storage servers in distributed file systems for cloud
computing. In this prefetching technique, the client machines are not substantially involved in the process of data prefetching, but the
storage servers can directly prefetch the data after analyzing the history of disk I/O access events, and then send the prefetched data
to the relevant client machines proactively. To put this technique to work, the information about client nodes is piggybacked onto the
real client I/O requests, and then forwarded to the relevant storage server. Next, two prediction algorithms have been proposed to
forecast future block access operations for directing what data should be fetched on storage servers in advance. Finally, the prefetched
data can be pushed to the relevant client machine from the storage server. Through a series of evaluation experiments with a
collection of application benchmarks, we have demonstrated that our presented initiative prefetching technique can benefit distributed
file systems for cloud environments to achieve better I/O performance. In particular, configuration-limited client machines in the cloud
are not responsible for predicting I/O access operations, which can definitely contribute to preferable system performance on them.
Performing initiative data prefetching in distributed file systems for cloud ...LeMeniz Infotech
Performing initiative data prefetching in distributed file systems for cloud computing
Do Your Projects With Technology Experts
To Get this projects Call : 9566355386 / 99625 88976
Visit : www.lemenizinfotech.com / www.ieeemaster.com
Mail : projects@lemenizinfotech.com
Performing initiative data prefetchingKamal Spring
This paper presents an initiative data prefetching scheme on the storage servers in distributed file systems for cloud
computing. In this prefetching technique, the client machines are not substantially involved in the process of data prefetching, but the
storage servers can directly prefetch the data after analyzing the history of disk I/O access events, and then send the prefetched data
to the relevant client machines proactively. To put this technique to work, the information about client nodes is piggybacked onto the
real client I/O requests, and then forwarded to the relevant storage server. Next, two prediction algorithms have been proposed to
forecast future block access operations for directing what data should be fetched on storage servers in advance. Finally, the prefetched
data can be pushed to the relevant client machine from the storage server. Through a series of evaluation experiments with a
collection of application benchmarks, we have demonstrated that our presented initiative prefetching technique can benefit distributed
file systems for cloud environments to achieve better I/O performance. In particular, configuration-limited client machines in the cloud
are not responsible for predicting I/O access operations, which can definitely contribute to preferable system performance on them.
Performing initiative data prefetching in distributed file systems for cloud ...LeMeniz Infotech
Performing initiative data prefetching in distributed file systems for cloud computing
Do Your Projects With Technology Experts
To Get this projects Call : 9566355386 / 99625 88976
Visit : www.lemenizinfotech.com / www.ieeemaster.com
Mail : projects@lemenizinfotech.com
NETWORK-AWARE DATA PREFETCHING OPTIMIZATION OF COMPUTATIONS IN A HETEROGENEOU...IJCNCJournal
Rapid development of diverse computer architectures and hardware accelerators caused that designing parallel systems faces new problems resulting from their heterogeneity. Our implementation of a parallel
system called KernelHive allows to efficiently run applications in a heterogeneous environment consisting
of multiple collections of nodes with different types of computing devices. The execution engine of the
system is open for optimizer implementations, focusing on various criteria. In this paper, we propose a new
optimizer for KernelHive, that utilizes distributed databases and performs data prefetching to optimize the
execution time of applications, which process large input data. Employing a versatile data management
scheme, which allows combining various distributed data providers, we propose using NoSQL databases
for our purposes. We support our solution with results of experiments with real executions of our OpenCL
implementation of a regular expression matching application in various hardware configurations.
Additionally, we propose a network-aware scheduling scheme for selecting hardware for the proposed
optimizer and present simulations that demonstrate its advantages.
International Journal of Engineering Research and Development (IJERD)IJERD Editor
journal publishing, how to publish research paper, Call For research paper, international journal, publishing a paper, IJERD, journal of science and technology, how to get a research paper published, publishing a paper, publishing of journal, publishing of research paper, reserach and review articles, IJERD Journal, How to publish your research paper, publish research paper, open access engineering journal, Engineering journal, Mathemetics journal, Physics journal, Chemistry journal, Computer Engineering, Computer Science journal, how to submit your paper, peer reviw journal, indexed journal, reserach and review articles, engineering journal, www.ijerd.com, research journals,
yahoo journals, bing journals, International Journal of Engineering Research and Development, google journals, hard copy of journal
Performance and Cost Evaluation of an Adaptive Encryption Architecture for Cl...Editor IJLRES
The cloud database as a service is a novel paradigm that can support several Internet-based applications, but its adoption requires the solution of information confidentiality problems. We propose a novel architecture for adaptive encryption of public cloud databases that offers an interesting alternative to the tradeoff between the required data confidentiality level and the flexibility of the cloud database structures at design time. We demonstrate the feasibility and performance of the proposed solution through a software prototype. Moreover, we propose an original cost model that is oriented to the evaluation of cloud database services in plain and encrypted instances and that takes into account the variability of cloud prices and tenant workloads during a medium-term period.
Data Partitioning in Mongo DB with CloudIJAAS Team
Cloud computing offers various and useful services like IAAS, PAAS SAAS for deploying the applications at low cost. Making it available anytime anywhere with the expectation to be it scalable and consistent. One of the technique to improve the scalability is Data partitioning. The alive techniques which are used are not that capable to track the data access pattern. This paper implements the scalable workload-driven technique for polishing the scalability of web applications. The experiments are carried out over cloud using NoSQL data store MongoDB to scale out. This approach offers low response time, high throughput and less number of distributed transaction. The result of partitioning technique is conducted and evaluated using TPC-C benchmark.
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09849539085, 09966235788 or mail us - ieeefinalsemprojects@gmail.co¬m-Visit Our Website: www.finalyearprojects.org
Data mining model for the data retrieval from central server configurationijcsit
A server, which is to keep track of heavy document traffic, is unable to filter the documents that are most
relevant and updated for continuous text search queries. This paper focuses on handling continuous text
extraction sustaining high document traffic. The main objective is to retrieve recent updated documents
that are most relevant to the query by applying sliding window technique. Our solution indexes the
streamed documents in the main memory with structure based on the principles of inverted file, and
processes document arrival and expiration events with incremental threshold-based method. It also ensures
elimination of duplicate document retrieval using unsupervised duplicate detection. The documents are
ranked based on user feedback and given higher priority for retrieval.
PUBLIC INTEGRITY AUDITING FOR SHARED DYNAMIC CLOUD DATA WITH GROUP USER REVO...Nexgen Technology
bulk ieee projects in pondicherry,ieee projects in pondicherry,final year ieee projects in pondicherry
Nexgen Technology Address:
Nexgen Technology
No :66,4th cross,Venkata nagar,
Near SBI ATM,
Puducherry.
Email Id: praveen@nexgenproject.com.
www.nexgenproject.com
Mobile: 9751442511,9791938249
Telephone: 0413-2211159.
NEXGEN TECHNOLOGY as an efficient Software Training Center located at Pondicherry with IT Training on IEEE Projects in Android,IEEE IT B.Tech Student Projects, Android Projects Training with Placements Pondicherry, IEEE projects in pondicherry, final IEEE Projects in Pondicherry , MCA, BTech, BCA Projects in Pondicherry, Bulk IEEE PROJECTS IN Pondicherry.So far we have reached almost all engineering colleges located in Pondicherry and around 90km
Ensuring Distributed Accountability for Data Sharing Using Reversible Data Hi...IOSR Journals
Recently, more and more attention is paid to reversible data hiding (RDH) in encrypted images,
since it maintains the excellent property that the original cover can be lossless recovered after embedded data is
extracted while protecting the image content’s confidentiality. All previous methods embed data by reversibly
vacating room from the encrypted images, which may be subject to some errors on data extraction and/or image
restoration. In this paper, we propose a novel method by reserving room before encryption with a traditional
RDH algorithm, and thus it is easy for the data hider to reversibly embed data in the encrypted image. The
proposed method can achieve real reversibility, that is, data extraction and image recovery are free of any
error. A major feature of the centralized database services is that users’ data are usually processed remotely in
unknown machines that users do not own or operate. While enjoying the convenience brought by this new
emerging technology, users’ fears of losing control of their own data (particularly, financial and health data)
can become a significant barrier to the wide adoption of centralized database services. To address this problem,
in this paper, we propose a novel highly decentralized information accountability framework to keep track of the
actual usage of the user’s data in the cloud Over-lay Network. We leverage the LOG file create a dynamic and
traveling object, and to ensure that any access to users’ data will trigger authentication and automated logging
local to the LOGs. To strengthen user’s control, we also provide distributed auditing mechanisms. We provide
extensive experimental studies that demonstrate the efficiency and effectiveness of the proposed approaches.
Index Terms : Reversible data hiding, image encryption, privacy protection, data sharing.
Performing initiative data prefetchingKamal Spring
Abstract—This paper presents an initiative data prefetching scheme on the storage servers in distributed file systems for cloud
computing. In this prefetching technique, the client machines are not substantially involved in the process of data prefetching, but the
storage servers can directly prefetch the data after analyzing the history of disk I/O access events, and then send the prefetched data
to the relevant client machines proactively. To put this technique to work, the information about client nodes is piggybacked onto the
real client I/O requests, and then forwarded to the relevant storage server. Next, two prediction algorithms have been proposed to
forecast future block access operations for directing what data should be fetched on storage servers in advance. Finally, the prefetched
data can be pushed to the relevant client machine from the storage server. Through a series of evaluation experiments with a
collection of application benchmarks, we have demonstrated that our presented initiative prefetching technique can benefit distributed
file systems for cloud environments to achieve better I/O performance. In particular, configuration-limited client machines in the cloud
are not responsible for predicting I/O access operations, which can definitely contribute to preferable system performance on them.
NETWORK-AWARE DATA PREFETCHING OPTIMIZATION OF COMPUTATIONS IN A HETEROGENEOU...IJCNCJournal
Rapid development of diverse computer architectures and hardware accelerators caused that designing parallel systems faces new problems resulting from their heterogeneity. Our implementation of a parallel
system called KernelHive allows to efficiently run applications in a heterogeneous environment consisting
of multiple collections of nodes with different types of computing devices. The execution engine of the
system is open for optimizer implementations, focusing on various criteria. In this paper, we propose a new
optimizer for KernelHive, that utilizes distributed databases and performs data prefetching to optimize the
execution time of applications, which process large input data. Employing a versatile data management
scheme, which allows combining various distributed data providers, we propose using NoSQL databases
for our purposes. We support our solution with results of experiments with real executions of our OpenCL
implementation of a regular expression matching application in various hardware configurations.
Additionally, we propose a network-aware scheduling scheme for selecting hardware for the proposed
optimizer and present simulations that demonstrate its advantages.
International Journal of Engineering Research and Development (IJERD)IJERD Editor
journal publishing, how to publish research paper, Call For research paper, international journal, publishing a paper, IJERD, journal of science and technology, how to get a research paper published, publishing a paper, publishing of journal, publishing of research paper, reserach and review articles, IJERD Journal, How to publish your research paper, publish research paper, open access engineering journal, Engineering journal, Mathemetics journal, Physics journal, Chemistry journal, Computer Engineering, Computer Science journal, how to submit your paper, peer reviw journal, indexed journal, reserach and review articles, engineering journal, www.ijerd.com, research journals,
yahoo journals, bing journals, International Journal of Engineering Research and Development, google journals, hard copy of journal
Performance and Cost Evaluation of an Adaptive Encryption Architecture for Cl...Editor IJLRES
The cloud database as a service is a novel paradigm that can support several Internet-based applications, but its adoption requires the solution of information confidentiality problems. We propose a novel architecture for adaptive encryption of public cloud databases that offers an interesting alternative to the tradeoff between the required data confidentiality level and the flexibility of the cloud database structures at design time. We demonstrate the feasibility and performance of the proposed solution through a software prototype. Moreover, we propose an original cost model that is oriented to the evaluation of cloud database services in plain and encrypted instances and that takes into account the variability of cloud prices and tenant workloads during a medium-term period.
Data Partitioning in Mongo DB with CloudIJAAS Team
Cloud computing offers various and useful services like IAAS, PAAS SAAS for deploying the applications at low cost. Making it available anytime anywhere with the expectation to be it scalable and consistent. One of the technique to improve the scalability is Data partitioning. The alive techniques which are used are not that capable to track the data access pattern. This paper implements the scalable workload-driven technique for polishing the scalability of web applications. The experiments are carried out over cloud using NoSQL data store MongoDB to scale out. This approach offers low response time, high throughput and less number of distributed transaction. The result of partitioning technique is conducted and evaluated using TPC-C benchmark.
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09849539085, 09966235788 or mail us - ieeefinalsemprojects@gmail.co¬m-Visit Our Website: www.finalyearprojects.org
Data mining model for the data retrieval from central server configurationijcsit
A server, which is to keep track of heavy document traffic, is unable to filter the documents that are most
relevant and updated for continuous text search queries. This paper focuses on handling continuous text
extraction sustaining high document traffic. The main objective is to retrieve recent updated documents
that are most relevant to the query by applying sliding window technique. Our solution indexes the
streamed documents in the main memory with structure based on the principles of inverted file, and
processes document arrival and expiration events with incremental threshold-based method. It also ensures
elimination of duplicate document retrieval using unsupervised duplicate detection. The documents are
ranked based on user feedback and given higher priority for retrieval.
PUBLIC INTEGRITY AUDITING FOR SHARED DYNAMIC CLOUD DATA WITH GROUP USER REVO...Nexgen Technology
bulk ieee projects in pondicherry,ieee projects in pondicherry,final year ieee projects in pondicherry
Nexgen Technology Address:
Nexgen Technology
No :66,4th cross,Venkata nagar,
Near SBI ATM,
Puducherry.
Email Id: praveen@nexgenproject.com.
www.nexgenproject.com
Mobile: 9751442511,9791938249
Telephone: 0413-2211159.
NEXGEN TECHNOLOGY as an efficient Software Training Center located at Pondicherry with IT Training on IEEE Projects in Android,IEEE IT B.Tech Student Projects, Android Projects Training with Placements Pondicherry, IEEE projects in pondicherry, final IEEE Projects in Pondicherry , MCA, BTech, BCA Projects in Pondicherry, Bulk IEEE PROJECTS IN Pondicherry.So far we have reached almost all engineering colleges located in Pondicherry and around 90km
Ensuring Distributed Accountability for Data Sharing Using Reversible Data Hi...IOSR Journals
Recently, more and more attention is paid to reversible data hiding (RDH) in encrypted images,
since it maintains the excellent property that the original cover can be lossless recovered after embedded data is
extracted while protecting the image content’s confidentiality. All previous methods embed data by reversibly
vacating room from the encrypted images, which may be subject to some errors on data extraction and/or image
restoration. In this paper, we propose a novel method by reserving room before encryption with a traditional
RDH algorithm, and thus it is easy for the data hider to reversibly embed data in the encrypted image. The
proposed method can achieve real reversibility, that is, data extraction and image recovery are free of any
error. A major feature of the centralized database services is that users’ data are usually processed remotely in
unknown machines that users do not own or operate. While enjoying the convenience brought by this new
emerging technology, users’ fears of losing control of their own data (particularly, financial and health data)
can become a significant barrier to the wide adoption of centralized database services. To address this problem,
in this paper, we propose a novel highly decentralized information accountability framework to keep track of the
actual usage of the user’s data in the cloud Over-lay Network. We leverage the LOG file create a dynamic and
traveling object, and to ensure that any access to users’ data will trigger authentication and automated logging
local to the LOGs. To strengthen user’s control, we also provide distributed auditing mechanisms. We provide
extensive experimental studies that demonstrate the efficiency and effectiveness of the proposed approaches.
Index Terms : Reversible data hiding, image encryption, privacy protection, data sharing.
Performing initiative data prefetchingKamal Spring
Abstract—This paper presents an initiative data prefetching scheme on the storage servers in distributed file systems for cloud
computing. In this prefetching technique, the client machines are not substantially involved in the process of data prefetching, but the
storage servers can directly prefetch the data after analyzing the history of disk I/O access events, and then send the prefetched data
to the relevant client machines proactively. To put this technique to work, the information about client nodes is piggybacked onto the
real client I/O requests, and then forwarded to the relevant storage server. Next, two prediction algorithms have been proposed to
forecast future block access operations for directing what data should be fetched on storage servers in advance. Finally, the prefetched
data can be pushed to the relevant client machine from the storage server. Through a series of evaluation experiments with a
collection of application benchmarks, we have demonstrated that our presented initiative prefetching technique can benefit distributed
file systems for cloud environments to achieve better I/O performance. In particular, configuration-limited client machines in the cloud
are not responsible for predicting I/O access operations, which can definitely contribute to preferable system performance on them.
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
ieee projects is the most important projects for engineering students like BE Projects and ME Projects, MCA students Projects, BCA students Projects, MPhile Projects
Adaptive Offloading in Mobile Cloud Computing by automatic partitioning approach of tasks is the idea to augment execution through migrating heavy computation from mobile devices to resourceful cloud servers and then receive the results from them via wireless networks. Offloading is an effective way to
overcome the resources and functionalities constraints
of the mobile devices since it can release them from
intensive processing and increase performance of the
mobile applications, in terms of response time.
Offloading brings many potential benefits, such as
energy saving, performance improvement, reliability
improvement, ease for the software developers and
better exploitation of contextual information.
Parameters about method transitions, response times,
cost and energy consumptions are dynamically reestimated
at runtime during application executions.
Hybrid Scheduling Algorithm for Efficient Load Balancing In Cloud ComputingEswar Publications
In cloud computing environment, various users send requests for the transmission of data for different demands. The access to different number of users increase load on the cloud servers. Due to this, the cloud server does not provide best efficiency. To provide best efficiency, load has to be balanced. The highlight of this work is the division of different jobs into tasks. The job dependency checking is done on the basis of directed acyclic graph. The dependency checking the make span has to be created on the basis of first come first serve and priority based scheduling algorithms. In this paper, each scheduling algorithm has been implemented sequentially and the hybrid algorithm (round robin and priority based) has also been compared with other scheduling algorithms.
A Personal Privacy Data Protection Scheme for Encryption and Revocation of Hi...Shakas Technologies
A Personal Privacy Data Protection Scheme for Encryption and Revocation of High-Dimensional Attri
Shakas Technologies ( Galaxy of Knowledge)
#11/A 2nd East Main Road,
Gandhi Nagar,
Vellore - 632006.
Mobile : +91-9500218218 / 8220150373| land line- 0416- 3552723
Shakas Training & Development | Shakas Sales & Services | Shakas Educational Trust|IEEE projects | Research & Development | Journal Publication |
Email : info@shakastech.com | shakastech@gmail.com |
website: www.shakastech.com
Facebook: https://www.facebook.com/pages/Shakas-Technologies
Detecting Mental Disorders in social Media through Emotional patterns-The cas...Shakas Technologies
Detecting Mental Disorders in social Media through Emotional patterns-The case of Anorexia and depression
Shakas Technologies ( Galaxy of Knowledge)
#11/A 2nd East Main Road,
Gandhi Nagar,
Vellore - 632006.
Mobile : +91-9500218218 / 8220150373| land line- 0416- 3552723
Shakas Training & Development | Shakas Sales & Services | Shakas Educational Trust|IEEE projects | Research & Development | Journal Publication |
Email : info@shakastech.com | shakastech@gmail.com |
website: www.shakastech.com
Facebook: https://www.facebook.com/pages/Shakas-Technologies
CO2 EMISSION RATING BY VEHICLES USING DATA SCIENCE
Shakas Technologies ( Galaxy of Knowledge)
#11/A 2nd East Main Road,
Gandhi Nagar,
Vellore - 632006.
Mobile : +91-9500218218 / 8220150373| land line- 0416- 3552723
Shakas Training & Development | Shakas Sales & Services | Shakas Educational Trust|IEEE projects | Research & Development | Journal Publication |
Email : info@shakastech.com | shakastech@gmail.com |
website: www.shakastech.com
Facebook: https://www.facebook.com/pages/Shakas-Technologies
Identifying Hot Topic Trends in Streaming Text Data Using News Sequential Evo...Shakas Technologies
Identifying Hot Topic Trends in Streaming Text Data Using News Sequential Evolution Model Based on Distributed Representations.
Shakas Technologies ( Galaxy of Knowledge)
#11/A 2nd East Main Road,
Gandhi Nagar,
Vellore - 632006.
Mobile : +91-9500218218 / 8220150373| land line- 0416- 3552723
Shakas Training & Development | Shakas Sales & Services | Shakas Educational Trust|IEEE projects | Research & Development | Journal Publication |
Email : info@shakastech.com | shakastech@gmail.com |
website: www.shakastech.com
Facebook: https://www.facebook.com/pages/Shakas-Technologies
Synthetic Fiber Construction in lab .pptxPavel ( NSTU)
Synthetic fiber production is a fascinating and complex field that blends chemistry, engineering, and environmental science. By understanding these aspects, students can gain a comprehensive view of synthetic fiber production, its impact on society and the environment, and the potential for future innovations. Synthetic fibers play a crucial role in modern society, impacting various aspects of daily life, industry, and the environment. ynthetic fibers are integral to modern life, offering a range of benefits from cost-effectiveness and versatility to innovative applications and performance characteristics. While they pose environmental challenges, ongoing research and development aim to create more sustainable and eco-friendly alternatives. Understanding the importance of synthetic fibers helps in appreciating their role in the economy, industry, and daily life, while also emphasizing the need for sustainable practices and innovation.
Macroeconomics- Movie Location
This will be used as part of your Personal Professional Portfolio once graded.
Objective:
Prepare a presentation or a paper using research, basic comparative analysis, data organization and application of economic information. You will make an informed assessment of an economic climate outside of the United States to accomplish an entertainment industry objective.
Model Attribute Check Company Auto PropertyCeline George
In Odoo, the multi-company feature allows you to manage multiple companies within a single Odoo database instance. Each company can have its own configurations while still sharing common resources such as products, customers, and suppliers.
Embracing GenAI - A Strategic ImperativePeter Windle
Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
The Roman Empire A Historical Colossus.pdfkaushalkr1407
The Roman Empire, a vast and enduring power, stands as one of history's most remarkable civilizations, leaving an indelible imprint on the world. It emerged from the Roman Republic, transitioning into an imperial powerhouse under the leadership of Augustus Caesar in 27 BCE. This transformation marked the beginning of an era defined by unprecedented territorial expansion, architectural marvels, and profound cultural influence.
The empire's roots lie in the city of Rome, founded, according to legend, by Romulus in 753 BCE. Over centuries, Rome evolved from a small settlement to a formidable republic, characterized by a complex political system with elected officials and checks on power. However, internal strife, class conflicts, and military ambitions paved the way for the end of the Republic. Julius Caesar’s dictatorship and subsequent assassination in 44 BCE created a power vacuum, leading to a civil war. Octavian, later Augustus, emerged victorious, heralding the Roman Empire’s birth.
Under Augustus, the empire experienced the Pax Romana, a 200-year period of relative peace and stability. Augustus reformed the military, established efficient administrative systems, and initiated grand construction projects. The empire's borders expanded, encompassing territories from Britain to Egypt and from Spain to the Euphrates. Roman legions, renowned for their discipline and engineering prowess, secured and maintained these vast territories, building roads, fortifications, and cities that facilitated control and integration.
The Roman Empire’s society was hierarchical, with a rigid class system. At the top were the patricians, wealthy elites who held significant political power. Below them were the plebeians, free citizens with limited political influence, and the vast numbers of slaves who formed the backbone of the economy. The family unit was central, governed by the paterfamilias, the male head who held absolute authority.
Culturally, the Romans were eclectic, absorbing and adapting elements from the civilizations they encountered, particularly the Greeks. Roman art, literature, and philosophy reflected this synthesis, creating a rich cultural tapestry. Latin, the Roman language, became the lingua franca of the Western world, influencing numerous modern languages.
Roman architecture and engineering achievements were monumental. They perfected the arch, vault, and dome, constructing enduring structures like the Colosseum, Pantheon, and aqueducts. These engineering marvels not only showcased Roman ingenuity but also served practical purposes, from public entertainment to water supply.
The French Revolution, which began in 1789, was a period of radical social and political upheaval in France. It marked the decline of absolute monarchies, the rise of secular and democratic republics, and the eventual rise of Napoleon Bonaparte. This revolutionary period is crucial in understanding the transition from feudalism to modernity in Europe.
For more information, visit-www.vavaclasses.com
Introduction to AI for Nonprofits with Tapp NetworkTechSoup
Dive into the world of AI! Experts Jon Hill and Tareq Monaur will guide you through AI's role in enhancing nonprofit websites and basic marketing strategies, making it easy to understand and apply.
Welcome to TechSoup New Member Orientation and Q&A (May 2024).pdfTechSoup
In this webinar you will learn how your organization can access TechSoup's wide variety of product discount and donation programs. From hardware to software, we'll give you a tour of the tools available to help your nonprofit with productivity, collaboration, financial management, donor tracking, security, and more.
Francesca Gottschalk - How can education support child empowerment.pptxEduSkills OECD
Francesca Gottschalk from the OECD’s Centre for Educational Research and Innovation presents at the Ask an Expert Webinar: How can education support child empowerment?
Instructions for Submissions thorugh G- Classroom.pptxJheel Barad
This presentation provides a briefing on how to upload submissions and documents in Google Classroom. It was prepared as part of an orientation for new Sainik School in-service teacher trainees. As a training officer, my goal is to ensure that you are comfortable and proficient with this essential tool for managing assignments and fostering student engagement.
Instructions for Submissions thorugh G- Classroom.pptx
PERFORMING INITIATIVE DATA PERFECTING IN DISTRIBUTED FILE SYSTEMS FOR CLOUD COMPUTING
1. PERFORMING INITIATIVE DATA PERFECTING IN DISTRIBUTED FILE SYSTEMS
FOR CLOUD COMPUTING
ABSTRACT
This paper presents an initiative data prefetching scheme on the storage servers in
distributed file systems for cloud computing. In this prefetching technique, the client machines
are not substantially involved in the process of data prefetching, but the storage servers can
directly prefetch the data after analyzing the history of disk I/O access events, and then send the
prefetched data to the relevant client machines proactively. To put this technique to work, the
information about client nodes is piggybacked onto the real client I/O requests, and then
forwarded to the relevant storage server. Next, two prediction algorithms have been proposed to
forecast future block access operations for directing what data should be fetched on storage
servers in advance. Finally, the prefetched data can be pushed to the relevant client machine
from the storage server. Through a series of evaluation experiments with a collection of
application benchmarks, we have demonstrated that our presented initiative prefetching
technique can benefit distributed file systems for cloud environments to achieve better I/O
performance. In particular, configuration-limited client machines in the cloud are not
responsible for predicting I/O access operations, which can definitely contribute to preferable
system performance on them.
SYSTEM ANALYSIS
Existing System
We have proposed, implemented and evaluated an initiative data prefetching approach on
the storage servers for distributed file systems, which can be employed as a backend storage
system in a cloud environment that may have certain resource-limited client machines.To be
specific, the storage servers are capable of predicting future disk I/O access to guide fetching
data in advance after analyzing the existing logs, and then they proactively push the prefetched
data to relevant client file systems for satisfying future applications’ requests. For the purpose of
effectively modeling disk I/O access patterns and accurately forwarding the prefetched data.
#13/ 19, 1st Floor, Municipal Colony, Kangayanellore Road, Gandhi Nagar, Vellore – 6.
Off: 0416-2247353 / 6066663 Mo: +91 9500218218 /8870603602,
Project Titles: http://shakastech.weebly.com/2015-2016-titles
Website: www.shakastech.com, Email - id: shakastech@gmail.com, info@shakastech.com
2. .
PROPOSED SYSTEM
Two prediction algorithms have been proposed to forecast future block access
operations for directing what data should be fetched on storage servers in advance. Finally, the
prefetched data can be pushed to the relevant client machine from the storage server. We have
proposed, implemented and evaluated an initiative data prefetching approach on the storage
servers for distributed file systems, which can be employed as a backend storage system in a
cloud environment that may have certain resource-limited client machines. To be specific, the
storage servers are capable of predicting future disk I/O access to guide fetching data in advance
after analyzing the existing logs, and then they proactively push the prefetched data to relevant
client file systems for satisfying future applications’ requests. For the purpose of effectively
modeling disk I/O access patterns and accurately forwarding the prefetched data, the information
about client file systems is piggybacked onto relevant I/O requests, then transferred from client
nodes to corresponding storage server nodes. Therefore, the client file systems running on the
client nodes neither log I/O events nor conduct I/O access prediction; consequently, the thin
client nodes can focus on performing necessary tasks with limited computing capacity and
energy endurance. Besides, the prefetched data will be proactively forwarded to the relevant
client file system, and the latter does not need to issue a prefetching request. So that both
network traffics and network latency can be reduced to a certain extent, which have been
demonstrated in our evaluation experiments.
PROPOSED SYSTEM ALGORITHMS
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3. Two prediction algorithms have been proposed to forecast future block access operations
for directing what data should be fetched on storage servers in advance. Finally, the perfected
data can be pushed to the relevant client machine from the storage server.
Two prediction algorithms including the chaotic time series prediction algorithm and the
linear regression prediction algorithm have been proposed respectively.
MODULE DESCRIPTION
MODULE
Home ,
Rank Module,
Cryptography,
Encryption and Decryption Module,
Architecture And Implementation,
Assumptions in Application Contexts,
Piggybacking Client Information,
I/O Access Prediction,
Modeling Disk I/O Access Patterns,
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4. Chaotic Time Series Prediction,
MODULE DESCRIPTION
Home
Distributed file systems for mobile clouds. Moreover many studies about the storage
systems for cloud environments that enable mobile client devices have been published. A new
mobile distributed file system called mobile.
DFS has been proposed and implemented in which aims to reduce computing in mobile
devices by transferring computing requirements to servers. Hyrax, which is a infrastructure
derived from Hadoop support cloud computing on mobile devices. But Hadoopis designed for
general distributed computing, and the client machines are assumed to be traditional computers.
In short, neither of related work targets at the clouds that have certain resource-limited client
machines, for yielding attractive performance enhancements.
Rank Module
This paper intends to propose a novel prefetching scheme for distributed file systems in cloud
computing environments to yield better I/O performance. In this section, we first introduce
the assumed application contexts to use the proposed prefetching mechanism; then the
architecture and related prediction algorithms of the prefetching mechanism are discussed
specifically; finally, we briefly present the implementation details of the file system used in
evaluation experiments, which enables the proposed prefetching scheme.
Cryptography Module
Initiative data prefetching on storage servers:. Without any intervention from client file
systems except for piggybacking their information onto relevant I/O requests to the storage
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5. servers. The storage servers are supposed to log disk I/O access, and classify access patterns
after modeling disk I/O events. Next, by properly using two proposed prediction algorithms,
the storage servers can predict the future disk I/O access to guide prefetching data. Finally,
the storage servers proactively forward the prefetched data to the relevant client file system
for satisfying future application’s requests.
Encryption and Decryption Module
Filebench which allows generating.A large variety of workloads to assess the
performance of storage systems. Besides, Filebench is quite flexible and enables to minutely
specify a collection of applications, such as mail, web, file, and database servers [12].We chose
Filebench as one of benchmarks, as it has been widely used to evaluate file systems by emulating
a variety of several server-like applications. I Ozone, which is a micro-benchmark that evaluates
the performance of a file system by employing a collection of access workloads with regular
patterns, such as sequential, random, reverse order, and strided [11]. That is why we utilized it to
measure read data throughput of the file systems with various prefetching schemes, when the
workload have different access patterns.
Architecture And Implementation
This paper intends to propose a novel prefetching scheme for distributed file systems in cloud
computing environments to yield better I/O performance. In this section, we first introduce the
assumed application contexts to use the proposed prefetching mechanism.
Then the architecture and related prediction algorithms of the prefetching mechanism are
discussed specifically; finally, we briefly present the implementation details of the file system
used in evaluation experiments, which enables the proposed prefetching scheme.
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6. Assumptions in Application Contexts
This newly presented prefetching mechanism cannot work well for all workloads in the real
world, and its target application contexts must meet two assumptions
Assumption 1: resource-limited client machines. This newly proposed prefetching
mechanism can be used primarily for the clouds that have many resourcelimited client machines,
not for generic cloud environments. This is a reasonable assumption given that mobile cloud
computing, which employs powerful cloud infrastructures to offer computing and storage
services on demand, for alleviating resource utilization in mobile devices.
Assumption 2: On-Line Transaction Processing (OLTP) applications. It is true that all
prefetching schemes in distributed file systems make sense for a limited number of read-
intensive applications such as database-related OLTP and server-like applications. That is
because these long-time running applications may have a limited number of access patterns, and
the patterns may occur repetitively during the lifetime of execution, which can definitely
contribute to boosting the effectiveness of perfecting.
Piggybacking Client Information,
Most of the I/O tracing approaches proposed by other researchers focus on the logical I/O
access events occurred on the client file systems, which might be useful for affirming
application’s I/O access patterns [16], [30]. Nevertheless, without relevant information about
physical I/O access, it is difficult to build the connection between the applications and the
distributed file system for improving the I/O performance to a great extend.
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7. In this newly presented initiative prefetching approach, the data is prefetched by storage
servers after analyzing disk I/O traces, and the data is then proactively pushed to the relevant
client file system for satisfying potential application’s requests. Thus, for the storage servers, it is
necessary to understand the information about client file systems and applications. To this end,
we leverage a piggybacking mechanism, which is illustrated in Figure 1, to transfer related
information from the client node to storage servers for contributing to modeling disk I/O access
patterns and forwarding the prefetched data As clearly described in Figure 1, when sending a
logical I/O request to the storage server, the client file system piggybacks information about the
client file systems and the application. In this way, the storage servers are able to record disk I/O
events with associated client information, which plays a critical role for classifying access
patterns and determining the destination client file system for the prefetched data. On the other
side, the client information is piggybacked to the storage servers, so that the storage servers are
possible to record the disk I/O operations accompanying with the information about relevant
logical I/O events.
I/O Access Prediction
Many heuristic algorithms have been proposed to shepherd distributing file data on disk
storage, as a result, data stripes that are expected to be used together will be located close to one
another [17], [18]. Moreover, J. Oly and D. Reed discovered that the spatial patterns of I/O
requests in scientific codes could be represented with Markov models, so that future access can
be also predicted by Markov models with proper state definitions [36]. N. Tran and D. Reed have
presented an automatic time series modeling and prediction framework to direct 1. Work flow
among client who runs the application, client file system, storage server and low level file
system: the client file system is responsible for generating extra information about the
application, client file system (CFS) and the logical access attributes; after that, it piggybacks the
extra information onto relevant I/O request, and sends them to the corresponding storage server.
On the other hand, the storage server is supposed to parse the request to separate piggybacked
information and the real I/O request. Apart from forwarding the I/O request to the low level file
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8. system, the storage server records the disk I/O access with the information about the
corresponding logical I/O access.
Modeling Disk I/O Access Patterns
Modeling and classifying logical I/O access patterns are beneficial to perform I/O
optimization strategies including data prefetching on the client nodes [29], [36]. But, it is
different from logical I/O access patterns, disk I/O access patterns may change without any
regularities, because the disk I/O access does not have information about applications.
As mentioned before, Z. Li et al. have confirmed that block correlations are common
semantic patterns in storage systems, and the information about these correlations can be
employed for enhancing the effectiveness of storage caching, prefetching and disk scheduling
[39]. This finding inspired us to explore the regularities in the disk I/O access history for hinting
data prefetching; currently, we can simply model disk I/O access patterns as two types, i.e. the
sequential access pattern and the random access pattern .
The disk access patterns of an OLTP application benchmark, i.e. Sysbench can be classified
into either a sequential access tendency or a random access tendency by using our presented
working set-like algorithm. After modeling I/O access patterns. we can understand that block
I/Os may have certain regularities, i.e. a linear tendency and a chaotic tendency. Therefore, we
have proposed two prediction algorithms to forecast the future I/Os when the I/O history follows
either of two tendencies after pattern classification by using the working set-like approach.
System Architecture
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