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
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.
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
Charm a cost efficient multi cloud data hosting scheme with high availabilityKamal Spring
More and more enterprises and organizations are hosting their data into the cloud, in order to reduce the IT maintenance cost and enhance the data reliability. However, facing the numerous cloud vendors as well as their heterogenous pricing policies, customers may well be perplexed with which cloud(s) are suitable for storing their data and what hosting strategy is cheaper. The general status quo is that customers usually put their data into a single cloud (which is subject to the vendor lock-in risk) and then simply trust to luck. Based on comprehensive analysis of various state-of-the-art cloud vendors, this paper proposes a novel data hosting scheme (named CHARM) which integrates two key functions desired. The first is selecting several suitable clouds and an appropriate redundancy strategy to store data with minimized monetary cost and guaranteed availability. The second is triggering a transition process to re-distribute data according to the variations of data access pattern and pricing of clouds. We evaluate the performance of CHARM using both trace-driven simulations and prototype experiments. The results show that compared with the major existing schemes, CHARM not only saves around 20% of monetary cost but also exhibits sound adaptability to data and price adjustments.
An Optimal Cooperative Provable Data Possession Scheme for Distributed Cloud ...IJMER
International Journal of Modern Engineering Research (IJMER) is Peer reviewed, online Journal. It serves as an international archival forum of scholarly research related to engineering and science education.
DYNAMIC TASK SCHEDULING BASED ON BURST TIME REQUIREMENT FOR CLOUD ENVIRONMENTIJCNCJournal
Cloud computing has an indispensable role in the modern digital scenario. The fundamental challenge of cloud systems is to accommodate user requirements which keep on varying. This dynamic cloud environment demands the necessity of complex algorithms to resolve the trouble of task allotment. The overall performance of cloud systems is rooted in the efficiency of task scheduling algorithms. The dynamic property of cloud systems makes it challenging to find an optimal solution satisfying all the evaluation metrics. The new approach is formulated on the Round Robin and the Shortest Job First algorithms. The Round Robin method reduces starvation, and the Shortest Job First decreases the average waiting time. In this work, the advantages of both algorithms are incorporated to improve the makespan of user tasks.
NEURO-FUZZY SYSTEM BASED DYNAMIC RESOURCE ALLOCATION IN COLLABORATIVE CLOUD C...ijccsa
Cloud collaboration is an emerging technology which enables sharing of computer files using cloud
computing. Here the cloud resources are assembled and cloud services are provided using these resources.
Cloud collaboration technologies are allowing users to share documents. Resource allocation in the cloud
is challenging because resources offer different Quality of Service (QoS) and services running on these
resources are risky for user demands. We propose a solution for resource allocation based on multi
attribute QoS Scoring considering parameters such as distance to the resource from user site, reputation of
the resource, task completion time, task completion ratio, and load at the resource. The proposed algorithm
referred to as Multi Attribute QoS scoring (MAQS) uses Neuro Fuzzy system. We have also included a
speculative manager to handle fault tolerance. In this paper it is shown that the proposed algorithm
perform better than others including power trust reputation based algorithms and harmony method which
use single attribute to compute the reputation score of each resource allocated.
Neuro-Fuzzy System Based Dynamic Resource Allocation in Collaborative Cloud C...neirew J
This paper proposes a neuro-fuzzy system called Multi Attribute QoS scoring (MAQS) for dynamic resource allocation in collaborative cloud computing. MAQS uses a 3-layer neural network trained on 5 quality of service attributes - distance, reputation, task completion time, completion ratio, and load - to provide a QoS score for each resource. Resources are then allocated based on this score. The algorithm collects data periodically from nodes and calculates QoS scores for incoming tasks to select the highest scoring node for task allocation. The paper argues this approach considers multiple attributes and heterogeneity of resources better than previous single-attribute methods.
Cryptographic Cloud Storage with Hadoop ImplementationIOSR Journals
This document proposes a scheme for cryptographic cloud storage using Hadoop implementation. It introduces parallel homomorphic encryption schemes that allow computation over encrypted data through an evaluation algorithm that can run efficiently in parallel. This allows a client to outsource function evaluation on private inputs to a Hadoop cluster while maintaining data confidentiality. The scheme uses erasure coding to distribute encrypted data across servers and generate verification tokens to check integrity and locate errors. It analyzes how Hadoop security can be enhanced using Kerberos authentication and capabilities to control data access. The proposed approach aims to efficiently ensure cloud data storage security, correctness, and availability.
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.
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
Charm a cost efficient multi cloud data hosting scheme with high availabilityKamal Spring
More and more enterprises and organizations are hosting their data into the cloud, in order to reduce the IT maintenance cost and enhance the data reliability. However, facing the numerous cloud vendors as well as their heterogenous pricing policies, customers may well be perplexed with which cloud(s) are suitable for storing their data and what hosting strategy is cheaper. The general status quo is that customers usually put their data into a single cloud (which is subject to the vendor lock-in risk) and then simply trust to luck. Based on comprehensive analysis of various state-of-the-art cloud vendors, this paper proposes a novel data hosting scheme (named CHARM) which integrates two key functions desired. The first is selecting several suitable clouds and an appropriate redundancy strategy to store data with minimized monetary cost and guaranteed availability. The second is triggering a transition process to re-distribute data according to the variations of data access pattern and pricing of clouds. We evaluate the performance of CHARM using both trace-driven simulations and prototype experiments. The results show that compared with the major existing schemes, CHARM not only saves around 20% of monetary cost but also exhibits sound adaptability to data and price adjustments.
An Optimal Cooperative Provable Data Possession Scheme for Distributed Cloud ...IJMER
International Journal of Modern Engineering Research (IJMER) is Peer reviewed, online Journal. It serves as an international archival forum of scholarly research related to engineering and science education.
DYNAMIC TASK SCHEDULING BASED ON BURST TIME REQUIREMENT FOR CLOUD ENVIRONMENTIJCNCJournal
Cloud computing has an indispensable role in the modern digital scenario. The fundamental challenge of cloud systems is to accommodate user requirements which keep on varying. This dynamic cloud environment demands the necessity of complex algorithms to resolve the trouble of task allotment. The overall performance of cloud systems is rooted in the efficiency of task scheduling algorithms. The dynamic property of cloud systems makes it challenging to find an optimal solution satisfying all the evaluation metrics. The new approach is formulated on the Round Robin and the Shortest Job First algorithms. The Round Robin method reduces starvation, and the Shortest Job First decreases the average waiting time. In this work, the advantages of both algorithms are incorporated to improve the makespan of user tasks.
NEURO-FUZZY SYSTEM BASED DYNAMIC RESOURCE ALLOCATION IN COLLABORATIVE CLOUD C...ijccsa
Cloud collaboration is an emerging technology which enables sharing of computer files using cloud
computing. Here the cloud resources are assembled and cloud services are provided using these resources.
Cloud collaboration technologies are allowing users to share documents. Resource allocation in the cloud
is challenging because resources offer different Quality of Service (QoS) and services running on these
resources are risky for user demands. We propose a solution for resource allocation based on multi
attribute QoS Scoring considering parameters such as distance to the resource from user site, reputation of
the resource, task completion time, task completion ratio, and load at the resource. The proposed algorithm
referred to as Multi Attribute QoS scoring (MAQS) uses Neuro Fuzzy system. We have also included a
speculative manager to handle fault tolerance. In this paper it is shown that the proposed algorithm
perform better than others including power trust reputation based algorithms and harmony method which
use single attribute to compute the reputation score of each resource allocated.
Neuro-Fuzzy System Based Dynamic Resource Allocation in Collaborative Cloud C...neirew J
This paper proposes a neuro-fuzzy system called Multi Attribute QoS scoring (MAQS) for dynamic resource allocation in collaborative cloud computing. MAQS uses a 3-layer neural network trained on 5 quality of service attributes - distance, reputation, task completion time, completion ratio, and load - to provide a QoS score for each resource. Resources are then allocated based on this score. The algorithm collects data periodically from nodes and calculates QoS scores for incoming tasks to select the highest scoring node for task allocation. The paper argues this approach considers multiple attributes and heterogeneity of resources better than previous single-attribute methods.
Cryptographic Cloud Storage with Hadoop ImplementationIOSR Journals
This document proposes a scheme for cryptographic cloud storage using Hadoop implementation. It introduces parallel homomorphic encryption schemes that allow computation over encrypted data through an evaluation algorithm that can run efficiently in parallel. This allows a client to outsource function evaluation on private inputs to a Hadoop cluster while maintaining data confidentiality. The scheme uses erasure coding to distribute encrypted data across servers and generate verification tokens to check integrity and locate errors. It analyzes how Hadoop security can be enhanced using Kerberos authentication and capabilities to control data access. The proposed approach aims to efficiently ensure cloud data storage security, correctness, and availability.
CHARM(A Cost-Efficient Multi-Cloud Data Hosting Scheme with High Availability)Deeksha Arya
The document proposes a multi-cloud data hosting scheme called CHARM that aims to store data across multiple clouds in a cost-efficient manner while maintaining high availability. CHARM uses both replication and erasure coding to redundantly store data blocks. It selects appropriate clouds and redundancy strategies to minimize monetary costs based on clouds' heterogeneous pricing policies and guarantee data availability. CHARM also rebalances data distribution in response to changes in data access patterns and cloud pricing.
secure data transfer and deletion from counting bloom filter in cloud computing.Venkat Projects
The document discusses a proposed system for secure data transfer and deletion from one cloud to another. It aims to achieve verifiable data transfer and reliable data deletion without a trusted third party. The system uses a counting Bloom filter scheme to allow a data owner, original cloud, and target cloud to verify that data was completely and accurately transferred or deleted. The scheme ensures data confidentiality, integrity, and public verifiability during the transfer and deletion processes.
BEST FINAL YEAR PROJECT IEEE 2015 BY SPECTRUM SOLUTIONS PONDICHERRYRaushan Kumar Singh
SPECTRUM SOLUTIONS is a Pondicherry based R&D firm which always looks forward in the field of science and technology to provide best technical support for the final year students. SPECTRUM has a great team of technical experts for the design development of Electronic and software Systems using Embedded, MATLAB, Java, Dot Net Technology.
SPECTRUM SOLUTIONS always concentrate us to provide quality products for various institutions and students. We offer the projects in all domains for the students of Diploma, B.Tech/B.E,M.Tech/M.E,MS,BCA,MCA etc. Our major concern is in the field of technical education to bridge the gap between Industry and Academics. We are always in the good eyes of the Educational Institutions in India to provide training & projects in Embedded Systems MATLAB and software technologies. We also provide interview training for free of cost. We never stop in going that extra mile ahead in providing greater value to own ideas of students, may it be in terms of providing adequate workforce proficient in highly application cost oriented Embedded Systems or Software Systems.
WEBSITE : www.spectrumpondicherry.blogspot.in/
FACEBOOK : https://www.facebook.com/pages/Spectrum-Solutions/548721691855495?ref=hl
COST-MINIMIZING DYNAMIC MIGRATION OF CONTENT DISTRIBUTION SERVICES INTO HYBR...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
Modeling and Optimization of Resource Allocation in Cloud [PhD Thesis Progres...AtakanAral
The magnitude of data being stored and processed in the cloud is quickly increasing due to advancements in areas that rely on cloud computing, e.g. Big Data, Internet of Things and computation offloading. Efficient management of limited computing and network resources is necessary to handle such an increase in cloud workload. Some of the critical issues in resource management for cloud computing are \emph{modeling resources / requirements} and \emph{allocating resources to users}. Potential benefits of tackling these issues include increases in utilization, scalability, Quality of Service (QoS) and throughput as well as decreases in latency and costs.
A location based least-cost scheduling for data-intensive applicationsIAEME Publication
This document summarizes a research paper that proposes a location-based least-cost scheduling algorithm for transferring multiple data-intensive files simultaneously to multiple compute nodes in a grid environment. The proposed model includes an optimized meta-scheduler that receives multiple files, predicts the optimal number of parallel TCP streams to use for each file transfer based on sampling, and schedules the files to compute nodes using a greedy algorithm that considers location and cost. Experimental results showed the optimized model achieved better transfer times and throughput compared to non-optimized transfers.
NEW SECURE CONCURRECY MANEGMENT APPROACH FOR DISTRIBUTED AND CONCURRENT ACCES...ijiert bestjournal
Handover the critical data to the cloud provider sh ould have the guarantee of security and availabilit y for data at rest,in motion,and in use. Many alternatives sys tems exist for storage services,but the data confi dentiality in the database as a service paradigm are still immature. We propose a novel architecture that integrates clo ud database services paradigm with data confidentiality and exe cuting concurrent operations on encrypted data. Thi s is the method supporting geographically distributed client s to connect directly and access to an encrypted cl oud database,and to execute concurrent and independent operation s by using modifying the database structure. The proposed architecture has also the more advanta ge of removing intermediate proxies that limit the flexibility,availability,and expandability properties that are inbuilt in cloud-based systems. The efficacy of th e proposed architecture is evaluated by theoretical analyses a nd extensive experimental results with the help of prototype implementation related to the TPC-C standard benchm ark for various categories of clients and network l atencies. We propose a multi-keyword ranked search method for the encrypted cloud data databases,which simultan eously fulfill the needs of privacy requirements. The prop osed scheme could return not only the exact matchin g files,but also the files including the terms latent semantica lly associated to the query keyword.
This document proposes a scheme for public verifiability in cloud computing using signcryption based on elliptic curves. The key components of the proposed system include users, a cloud service provider, an authentication server, and a certificate authority. The scheme relies on erasure-correcting codes to distribute and redundantly store user data across multiple cloud servers. It uses signcryption/unsigncryption based on elliptic curves to generate verification tokens for the stored data and enable public verifiability, allowing an authentication server to verify the integrity and accuracy of user data on cloud servers without involving the user. The scheme aims to simultaneously detect any data errors and identify the misbehaving servers upon verification.
The magnitude of data being stored and processed in the Cloud is quickly increasing due to advancements in areas that rely on cloud computing, e.g. Big Data, Internet of Things and mobile code offloading. Concurrently, cloud services are getting more global and geographically distributed. To handle such changes in its usage scenario, the Cloud needs to transform into a completely decentralized, federated and ubiquitous environment similar to the historical transformation of the Internet. Indeed, research ideas for the transformation has already started to emerge including but not limited to Cloud Federations, Multi-Clouds, Fog Computing, Edge Computing, Cloudlets, Nano data centers, etc.
Standardization and resource management come up as the most significant issues for the realization of the distributed cloud paradigm. The focus in this thesis is the latter: efficient management of limited computing and network resources to adapt to the decentralization. Specifically, cloud services that consist of several virtual machines, dedicated network connections and databases are mapped to a multi-provider, geographically distributed and dynamic cloud infrastructure. The objective of the mapping is to improve quality of service in a cost-effective way. To that end; network latency and bandwidth as well as the cost of storage and computation are subjected to a multi-objective optimization.
The first phase of the resource mapping optimization is the topology mapping. In this phase, the virtual machines and network connections (i.e. the virtual cluster) of the cloud service are mapped to the physical cloud infrastructure. The hypothesis is that mapping the virtual cluster to a group of data centers with a similar topology would be the optimal solution.
Replication management is the second phase where the focus is on the data storage. Data objects that constitute the database are replicated and mapped to the storage as a service providers and end devices. The hypothesis for this phase is that an objective function adapted from the facility location problem optimizes the replica placement.
Detailed experiments under real-world as well as synthetic workloads prove that the hypotheses of the both phases are true.
International Journal of Engineering Research and Development (IJERD)IJERD Editor
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An optimized scientific workflow scheduling in cloud computingDIGVIJAY SHINDE
The document discusses optimizing scientific workflow scheduling in cloud computing. It begins with definitions of workflow and cloud computing. Workflow is a group of repeatable dependent tasks, while cloud computing provides applications and hardware resources over the Internet. There are three cloud service models: SaaS, PaaS, and IaaS. The document explores how to efficiently schedule workflows in the cloud to reduce makespan, cost, and energy consumption. It reviews different scheduling algorithms like FCFS, genetic algorithms, and discusses optimizing objectives like time and cost. The document provides a literature review comparing various workflow scheduling methods and algorithms. It concludes with discussing open issues and directions for future work in optimizing workflow scheduling for cloud computing.
This document summarizes a research paper that proposes a framework called Cooperative Provable Data Possession (CPDP) to verify the integrity of data stored across multiple cloud storage providers. The framework uses two techniques: 1) a Hash Index Hierarchy that allows responses from different cloud providers to a client's challenge to be combined into a single response, and 2) Homomorphic Verifiable Responses that enable efficient verification of data stored on multiple cloud providers. The document outlines the security properties and performance benefits of the CPDP framework for verifying data integrity in a multi-cloud storage environment.
Cost-Minimizing Dynamic Migration of Content Distribution Services into Hybri...1crore projects
IEEE PROJECTS 2015
1 crore projects is a leading Guide for ieee Projects and real time projects Works Provider.
It has been provided Lot of Guidance for Thousands of Students & made them more beneficial in all Technology Training.
Dot Net
DOTNET Project Domain list 2015
1. IEEE based on datamining and knowledge engineering
2. IEEE based on mobile computing
3. IEEE based on networking
4. IEEE based on Image processing
5. IEEE based on Multimedia
6. IEEE based on Network security
7. IEEE based on parallel and distributed systems
Java Project Domain list 2015
1. IEEE based on datamining and knowledge engineering
2. IEEE based on mobile computing
3. IEEE based on networking
4. IEEE based on Image processing
5. IEEE based on Multimedia
6. IEEE based on Network security
7. IEEE based on parallel and distributed systems
ECE IEEE Projects 2015
1. Matlab project
2. Ns2 project
3. Embedded project
4. Robotics project
Eligibility
Final Year students of
1. BSc (C.S)
2. BCA/B.E(C.S)
3. B.Tech IT
4. BE (C.S)
5. MSc (C.S)
6. MSc (IT)
7. MCA
8. MS (IT)
9. ME(ALL)
10. BE(ECE)(EEE)(E&I)
TECHNOLOGY USED AND FOR TRAINING IN
1. DOT NET
2. C sharp
3. ASP
4. VB
5. SQL SERVER
6. JAVA
7. J2EE
8. STRINGS
9. ORACLE
10. VB dotNET
11. EMBEDDED
12. MAT LAB
13. LAB VIEW
14. Multi Sim
CONTACT US
1 CRORE PROJECTS
Door No: 214/215,2nd Floor,
No. 172, Raahat Plaza, (Shopping Mall) ,Arcot Road, Vadapalani, Chennai,
Tamin Nadu, INDIA - 600 026
Email id: 1croreprojects@gmail.com
website:1croreprojects.com
Phone : +91 97518 00789 / +91 72999 51536
Survey on Division and Replication of Data in Cloud for Optimal Performance a...IJSRD
Outsourcing information to an outsider authoritative control, as is done in distributed computing, offers ascend to security concerns. The information trade off may happen because of assaults by different clients and hubs inside of the cloud. Hence, high efforts to establish safety are required to secure information inside of the cloud. On the other hand, the utilized security procedure should likewise consider the advancement of the information recovery time. In this paper, we propose Division and Replication of Data in the Cloud for Optimal Performance and Security (DROPS) that all in all methodologies the security and execution issues. In the DROPS procedure, we partition a record into sections, and reproduce the divided information over the cloud hubs. Each of the hubs stores just a itary part of a specific information record that guarantees that even in the event of a fruitful assault, no important data is uncovered to the assailant. Additionally, the hubs putting away the sections are isolated with certain separation by method for diagram T-shading to restrict an assailant of speculating the areas of the sections. Moreover, the DROPS procedure does not depend on the customary cryptographic procedures for the information security; in this way alleviating the arrangement of computationally costly approaches. We demonstrate that the likelihood to find and bargain the greater part of the hubs putting away the sections of a solitary record is to a great degree low. We likewise analyze the execution of the DROPS system with ten different plans. The more elevated amount of security with slight execution overhead was watched.
Drops division and replication of data in cloud for optimal performance and s...Pvrtechnologies Nellore
This document proposes a method called DROPS (Division and Replication of Data in Cloud for Optimal Performance and Security) that divides files into fragments and replicates the fragments across cloud nodes for improved security and performance. The method stores each file fragment on a separate node to prevent attackers from accessing full files even if some nodes are compromised. It also separates nodes storing fragments using graph coloring to obscure fragment locations. The method aims to improve retrieval time by selecting central nodes and replicating fragments on high-traffic nodes. The document compares DROPS to 10 replication strategies and evaluates it using 3 data center network architectures.
This document discusses several cloud computing projects from IEEE in 2014. It provides descriptions of 8 projects, including their titles, programming languages, links, and abstract summaries. The projects focus on topics like network coding-based cloud storage systems, privacy-preserving search over encrypted cloud data, cloud service composition, cloud resource procurement, and competition/cooperation among cloud providers.
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
CHARM(A Cost-Efficient Multi-Cloud Data Hosting Scheme with High Availability)Deeksha Arya
The document proposes a multi-cloud data hosting scheme called CHARM that aims to store data across multiple clouds in a cost-efficient manner while maintaining high availability. CHARM uses both replication and erasure coding to redundantly store data blocks. It selects appropriate clouds and redundancy strategies to minimize monetary costs based on clouds' heterogeneous pricing policies and guarantee data availability. CHARM also rebalances data distribution in response to changes in data access patterns and cloud pricing.
secure data transfer and deletion from counting bloom filter in cloud computing.Venkat Projects
The document discusses a proposed system for secure data transfer and deletion from one cloud to another. It aims to achieve verifiable data transfer and reliable data deletion without a trusted third party. The system uses a counting Bloom filter scheme to allow a data owner, original cloud, and target cloud to verify that data was completely and accurately transferred or deleted. The scheme ensures data confidentiality, integrity, and public verifiability during the transfer and deletion processes.
BEST FINAL YEAR PROJECT IEEE 2015 BY SPECTRUM SOLUTIONS PONDICHERRYRaushan Kumar Singh
SPECTRUM SOLUTIONS is a Pondicherry based R&D firm which always looks forward in the field of science and technology to provide best technical support for the final year students. SPECTRUM has a great team of technical experts for the design development of Electronic and software Systems using Embedded, MATLAB, Java, Dot Net Technology.
SPECTRUM SOLUTIONS always concentrate us to provide quality products for various institutions and students. We offer the projects in all domains for the students of Diploma, B.Tech/B.E,M.Tech/M.E,MS,BCA,MCA etc. Our major concern is in the field of technical education to bridge the gap between Industry and Academics. We are always in the good eyes of the Educational Institutions in India to provide training & projects in Embedded Systems MATLAB and software technologies. We also provide interview training for free of cost. We never stop in going that extra mile ahead in providing greater value to own ideas of students, may it be in terms of providing adequate workforce proficient in highly application cost oriented Embedded Systems or Software Systems.
WEBSITE : www.spectrumpondicherry.blogspot.in/
FACEBOOK : https://www.facebook.com/pages/Spectrum-Solutions/548721691855495?ref=hl
COST-MINIMIZING DYNAMIC MIGRATION OF CONTENT DISTRIBUTION SERVICES INTO HYBR...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
Modeling and Optimization of Resource Allocation in Cloud [PhD Thesis Progres...AtakanAral
The magnitude of data being stored and processed in the cloud is quickly increasing due to advancements in areas that rely on cloud computing, e.g. Big Data, Internet of Things and computation offloading. Efficient management of limited computing and network resources is necessary to handle such an increase in cloud workload. Some of the critical issues in resource management for cloud computing are \emph{modeling resources / requirements} and \emph{allocating resources to users}. Potential benefits of tackling these issues include increases in utilization, scalability, Quality of Service (QoS) and throughput as well as decreases in latency and costs.
A location based least-cost scheduling for data-intensive applicationsIAEME Publication
This document summarizes a research paper that proposes a location-based least-cost scheduling algorithm for transferring multiple data-intensive files simultaneously to multiple compute nodes in a grid environment. The proposed model includes an optimized meta-scheduler that receives multiple files, predicts the optimal number of parallel TCP streams to use for each file transfer based on sampling, and schedules the files to compute nodes using a greedy algorithm that considers location and cost. Experimental results showed the optimized model achieved better transfer times and throughput compared to non-optimized transfers.
NEW SECURE CONCURRECY MANEGMENT APPROACH FOR DISTRIBUTED AND CONCURRENT ACCES...ijiert bestjournal
Handover the critical data to the cloud provider sh ould have the guarantee of security and availabilit y for data at rest,in motion,and in use. Many alternatives sys tems exist for storage services,but the data confi dentiality in the database as a service paradigm are still immature. We propose a novel architecture that integrates clo ud database services paradigm with data confidentiality and exe cuting concurrent operations on encrypted data. Thi s is the method supporting geographically distributed client s to connect directly and access to an encrypted cl oud database,and to execute concurrent and independent operation s by using modifying the database structure. The proposed architecture has also the more advanta ge of removing intermediate proxies that limit the flexibility,availability,and expandability properties that are inbuilt in cloud-based systems. The efficacy of th e proposed architecture is evaluated by theoretical analyses a nd extensive experimental results with the help of prototype implementation related to the TPC-C standard benchm ark for various categories of clients and network l atencies. We propose a multi-keyword ranked search method for the encrypted cloud data databases,which simultan eously fulfill the needs of privacy requirements. The prop osed scheme could return not only the exact matchin g files,but also the files including the terms latent semantica lly associated to the query keyword.
This document proposes a scheme for public verifiability in cloud computing using signcryption based on elliptic curves. The key components of the proposed system include users, a cloud service provider, an authentication server, and a certificate authority. The scheme relies on erasure-correcting codes to distribute and redundantly store user data across multiple cloud servers. It uses signcryption/unsigncryption based on elliptic curves to generate verification tokens for the stored data and enable public verifiability, allowing an authentication server to verify the integrity and accuracy of user data on cloud servers without involving the user. The scheme aims to simultaneously detect any data errors and identify the misbehaving servers upon verification.
The magnitude of data being stored and processed in the Cloud is quickly increasing due to advancements in areas that rely on cloud computing, e.g. Big Data, Internet of Things and mobile code offloading. Concurrently, cloud services are getting more global and geographically distributed. To handle such changes in its usage scenario, the Cloud needs to transform into a completely decentralized, federated and ubiquitous environment similar to the historical transformation of the Internet. Indeed, research ideas for the transformation has already started to emerge including but not limited to Cloud Federations, Multi-Clouds, Fog Computing, Edge Computing, Cloudlets, Nano data centers, etc.
Standardization and resource management come up as the most significant issues for the realization of the distributed cloud paradigm. The focus in this thesis is the latter: efficient management of limited computing and network resources to adapt to the decentralization. Specifically, cloud services that consist of several virtual machines, dedicated network connections and databases are mapped to a multi-provider, geographically distributed and dynamic cloud infrastructure. The objective of the mapping is to improve quality of service in a cost-effective way. To that end; network latency and bandwidth as well as the cost of storage and computation are subjected to a multi-objective optimization.
The first phase of the resource mapping optimization is the topology mapping. In this phase, the virtual machines and network connections (i.e. the virtual cluster) of the cloud service are mapped to the physical cloud infrastructure. The hypothesis is that mapping the virtual cluster to a group of data centers with a similar topology would be the optimal solution.
Replication management is the second phase where the focus is on the data storage. Data objects that constitute the database are replicated and mapped to the storage as a service providers and end devices. The hypothesis for this phase is that an objective function adapted from the facility location problem optimizes the replica placement.
Detailed experiments under real-world as well as synthetic workloads prove that the hypotheses of the both phases are true.
International Journal of Engineering Research and Development (IJERD)IJERD Editor
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An optimized scientific workflow scheduling in cloud computingDIGVIJAY SHINDE
The document discusses optimizing scientific workflow scheduling in cloud computing. It begins with definitions of workflow and cloud computing. Workflow is a group of repeatable dependent tasks, while cloud computing provides applications and hardware resources over the Internet. There are three cloud service models: SaaS, PaaS, and IaaS. The document explores how to efficiently schedule workflows in the cloud to reduce makespan, cost, and energy consumption. It reviews different scheduling algorithms like FCFS, genetic algorithms, and discusses optimizing objectives like time and cost. The document provides a literature review comparing various workflow scheduling methods and algorithms. It concludes with discussing open issues and directions for future work in optimizing workflow scheduling for cloud computing.
This document summarizes a research paper that proposes a framework called Cooperative Provable Data Possession (CPDP) to verify the integrity of data stored across multiple cloud storage providers. The framework uses two techniques: 1) a Hash Index Hierarchy that allows responses from different cloud providers to a client's challenge to be combined into a single response, and 2) Homomorphic Verifiable Responses that enable efficient verification of data stored on multiple cloud providers. The document outlines the security properties and performance benefits of the CPDP framework for verifying data integrity in a multi-cloud storage environment.
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This document discusses several cloud computing projects from IEEE in 2014. It provides descriptions of 8 projects, including their titles, programming languages, links, and abstract summaries. The projects focus on topics like network coding-based cloud storage systems, privacy-preserving search over encrypted cloud data, cloud service composition, cloud resource procurement, and competition/cooperation among cloud providers.
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Jayant Ghorpade - Cloud Computing White PaperJayant Ghorpade
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IRJET- Cloud Cost Analyzer and OptimizerIRJET Journal
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dynamic resource allocation using virtual machines for cloud computing enviro...Kumar Goud
Abstract—Cloud computing allows business customers to scale up and down their resource usage based on needs., we present 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. We introduce the concept of “skewness” to measure the unevenness in the multidimensional resource utilization of a server. By minimizing imbalance, we will mix completely different of workloads nicely and improve the overall utilization of server resources. We develop a set of heuristics that prevent overload in the system effectively while saving energy used. Many of the touted gains in the cloud model come from resource multiplexing through virtualization technology. In this paper Trace driven simulation and experiment results demonstrate that our algorithm achieves good performance.
Index Terms—Cloud computing, resource management, virtualization, green computing.
International Journal of Engineering Research and DevelopmentIJERD Editor
This document summarizes a research paper on developing an efficient dynamic resource scheduling model called CRAM for cloud computing. The proposed model uses Stochastic Reward Nets to model cloud resources and client requests in an analytical way. It captures key concepts like virtualization, federation between clouds, and defines performance metrics from the perspective of both cloud providers and users. The model is scalable and can represent systems with thousands of resources to analyze the impact of different resource management strategies.
Psdot 15 performance analysis of cloud computingZTech Proje
The document discusses performance analysis of cloud computing centers using queuing systems. It aims to evaluate key performance indicators like response time distribution and mean number of tasks using a queuing model. The proposed system models cloud server farms as COCOMO II systems to obtain more accurate estimations of performance metrics while addressing issues with existing models like high traffic intensity and service time variation. It analyzes how changing server numbers and buffer sizes impacts the performance indicators.
Flaw less coding and authentication of user data using multiple cloudsIRJET Journal
This document discusses secure data storage in multiple cloud storage providers. It proposes a method for users to store encrypted data across multiple cloud storage providers using splitting and merging concepts. Private keys are generated during file access using a pseudo key generator and encrypted using 3DES for transmission. The method aims to increase data availability, confidentiality and reduce costs by distributing data across multiple cloud providers. It also discusses using image compression with reversible data hiding techniques to provide data confidentiality when storing images in the cloud.
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2014 IEEE JAVA CLOUD COMPUTING PROJECT Performance and cost evaluation of an adaptive encryption architecture for cloud databases
1. GLOBALSOFT TECHNOLOGIES
Performance and cost evaluation of an adaptive
encryption architecture for cloud databases
Abstract:
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 trade-off
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 workload during a medium-term period.
Existing System:
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2. The cloud computing paradigm is successfully converging as the fifth utility , but
this positive trend is partially limited by concerns about information confidentiality
and unclear costs over a medium-long term .We are interested in the Database as a
Service paradigm (DBaaS) that poses several research challenges in terms of
security and cost evaluation from a tenant’s point of view. Most results concerning
encryption for cloud-based services are in applicable to the database paradigm.
Other encryption schemes, which allow the execution of SQL operations over
encrypted data, either suffer from performance limits or they require the choice of
which encryption scheme must be adopted for each database column and
SQL operations .
Proposed System:
The proposed architecture guarantees in an adaptive way the best level of data
confidentiality for any database workload, even when the set of SQL queries
dynamically changes. The adaptive encryption scheme, which was initially
proposed for applications not referring to the cloud, encrypts each plain column
into multiple encrypted columns, and each value is encapsulated into different
layers of encryption, so that the outer layers guarantee higher confidentiality but
support fewer computation capabilities with respect to the inner layers. we propose
the first analytical cost estimation model for evaluating cloud database costs in
plain and encrypted instances from a tenant’s point of view in a medium-term
period. It takes also into account the variability of cloud prices and the possibility
that the database workload may change during the evaluation period. This model is
instanced with respect to several cloud provider offers and related real prices. As
expected, adaptive encryption influences the costs related to storage size and
3. network usage of a database service. However, it is important that a tenant can
anticipate the final costs in its period of interest, and can choose the best
compromise between data confidentiality and expenses.
Architecture :
Implementation Modules:
1. Adaptive encryption
2. Metadata structure
3. Encrypted database management
4. Cost Estimation of cloud database services
5. Cost model
4. 6. Cloud pricing models
7. Usage Estimation
Adaptive encryption:
The proposed system supports adaptive encryption methods for public cloud
database service, where distributed and concurrent clients can issue direct SQL
operations. By avoiding an architecture based on one [or] multiple intermediate
servers between the clients and the cloud database, the proposed solution
guarantees the same level of scalability and availability of the cloud service. Figure
1 shows a scheme of the proposed architecture where each client executes an
encryption engine that manages encryption operations. This software module is
accessed by external user applications through the encrypted database interface.
The proposed architecture manages five types of information.
• plain data is the tenant information;
• encrypted data is stored in the cloud database;
• plain metadata represent the additional information that is necessary to execute
SQL operations on encrypted data;
• encrypted metadata is the encrypted version of the metadata that are stored in the
cloud database;
• master key is the encryption key of the encrypted metadata that is distributed to
legitimate clients.
Metadata structure:
5. Metadata include all information that allows a legitimate client knowing the master
key to execute SQL operations over an encrypted database. They are organized and
stored at a table-level granularity to reduce communication overhead for retrieval,
and to improve management of concurrent SQL operations. We define all metadata
information associated to a table as table metadata. Let us describe the structure of
a table metadata .Table metadata includes the correspondence between the plain
table name and the encrypted table name because each encrypted table name is
randomly generated. Moreover, for each column of the original plain table
it also includes a column metadata parameter containing the name and the data
type of the corresponding plain column (e.g., integer, string, timestamp). Each
column metadata is associated to one or more onion metadata, as many as the
number of onions related to the column.
Encrypted database management:
The database administrator generates a master key, and uses it to initialize the
architecture metadata. The master key is then distributed to legitimate clients. Each
table creation requires the insertion of a new row in the metadata table. For each
table creation, the administrator adds a column by specifying the column name,
data type and confidentiality parameters. These last are the most important for this
paper because they include the set of onions to be associated with the column, the
starting layer (denoting the actual layer at creation time) and the field
confidentiality of each onion. If the administrator does not specify the
confidentiality parameters of a column, then they are automatically chosen by the
client with respect to a tenant’s policy. Typically, the default policy assumes that
the starting layer of each onion is set to its strongest encryption algorithm.
6. Cost Estimation of cloud database services:
A tenant that is interested in estimating the cost of porting its database to a cloud
platform. This porting is a strategic decision that must evaluate confidentiality
issues and the related costs over a medium-long term. For these reasons, we
propose a model that includes the overhead of encryption schemes and variability
of database workload and cloud prices. The proposed model is general enough to
be applied to the most popular cloud database services, such as Amazon Relational
Database Service.
Cost model:
The cost of a cloud database service can be estimated as a function of three main
parameters:
Cost = f(T ime, Pricing,Usage) where:
• Time: identifies the time interval T for which the tenant requires the service.
• Pricing: refers to the prices of the cloud provider for subscription and resource
usage; they typically tend to diminish during T .
• Usage: denotes the total amount of resources used by the tenant; it typically
increases during T .In order to detail the pricing attribute, it is important
to specify that cloud providers adopt two subscription
policies: the on-demand policy allows a tenant to payper-use and to withdraw its
subscription anytime; the reservation policy requires the tenant to commit in
advance for a reservation period. Hence, we distinguish between billing costs
depending on resource usage and reservation costs denoting additional fees for
commitment in exchange for lower pay-per-use prices. Billing costs are billed
periodically to the tenant every billing period.
7. Cloud pricing models:
Popular cloud database providers adopt two different billing functions, that we call
linear L and tiered T . Let us consider a generic resource x, we define as xb its
usage at the b-th billing period and px b its price. If the billing function is tiered,
the cloud provider uses different prices for different ranges of resource usage. Let
us define Z as the number of tiers, and [ˆx1, . . . , ˆxZ−1] as the set of thresholds
that define all the tiers. The uptime and the storage billing functions of Amazon
RDS are linear, while the network usage is a tiered billing function. On the other
hand, the uptime billing functions of Azure SQL is linear, while the
storage and network billing functions are tiered.
Usage Estimation:
The uptime is easily measurable, it is more difficult to estimate accurately the
usage of storage and network , since they depend on the database structure, the
workload and the use of encryption. We now propose a methodology for the
estimation of storage and network usage due to encryption. For clarity, we define
sp, se, sa as the storage usage in the plaintext, encrypted, and adaptively encrypted
databases for one billing period. Similarly, np, ne, na represent network usage of
the three configurations. We assume that the tenant knows the database structure
and the query workload and we assume that each column a A stores ra values. By
denoting as vp a the average storage size of each plaintext value stored in column
a, we estimate the storage of the plaintext database.
8. System Configuration:
HARDWARE REQUIREMENTS:
Hardware - Pentium
Speed - 1.1 GHz
RAM - 1GB
Hard Disk - 20 GB
Floppy Drive - 1.44 MB
Key Board - Standard Windows Keyboard
Mouse - Two or Three Button Mouse
Monitor - SVGA
SOFTWARE REQUIREMENTS:
Operating System : Windows
Technology : Java and J2EE
Web Technologies : Html, JavaScript, CSS
IDE : My Eclipse
Web Server : Tomcat
Tool kit : Android Phone
Database : My SQL
Java Version : J2SDK1.5