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Introduction
Multi-Cloud Scenario
Motivation
Available Data Hosting Schemes
The proposed Scheme CHARM
Conclusion and Future Scope
CHARM
(A Cost-Efficient Multi-Cloud Data Hosting
Scheme with High Availability)
Deeksha Arya
deekshasheokand@gmail.com
Computer Engineering Department
NIT Kurukshetra
May 5, 2016
Deeksha Arya CHARM: Multi-Cloud Data Hosting Scheme
Introduction
Multi-Cloud Scenario
Motivation
Available Data Hosting Schemes
The proposed Scheme CHARM
Conclusion and Future Scope
Outline
1 Introduction
Cloud Computing
2 Multi-Cloud Scenario
Single Cloud vs Multi-Cloud
Problems in Single Cloud Data Hosting
Problems in Multi-Cloud Data Hosting
3 Motivation
4 Available Data Hosting Schemes
Replication
Erasure Coding
5 The proposed Scheme CHARM
Architecture
Algorithms Used
6 Conclusion and Future Scope
Deeksha Arya CHARM: Multi-Cloud Data Hosting Scheme
Introduction
Multi-Cloud Scenario
Motivation
Available Data Hosting Schemes
The proposed Scheme CHARM
Conclusion and Future Scope
Cloud Computing
What is Cloud Computing?
Cloud Computing is the use of computing resources(hardware
and software) that are delivered as a service over a network.
Deeksha Arya CHARM: Multi-Cloud Data Hosting Scheme
Introduction
Multi-Cloud Scenario
Motivation
Available Data Hosting Schemes
The proposed Scheme CHARM
Conclusion and Future Scope
Cloud Computing
How does it work?
In cloud computing, users access the data, applications or any
other services with the help of a browser regardless of the device
used and the user’s location.
Deeksha Arya CHARM: Multi-Cloud Data Hosting Scheme
Introduction
Multi-Cloud Scenario
Motivation
Available Data Hosting Schemes
The proposed Scheme CHARM
Conclusion and Future Scope
Cloud Computing
Why Cloud Computing?
Deeksha Arya CHARM: Multi-Cloud Data Hosting Scheme
Introduction
Multi-Cloud Scenario
Motivation
Available Data Hosting Schemes
The proposed Scheme CHARM
Conclusion and Future Scope
Cloud Computing
History of Cloud Computing
Deeksha Arya CHARM: Multi-Cloud Data Hosting Scheme
Introduction
Multi-Cloud Scenario
Motivation
Available Data Hosting Schemes
The proposed Scheme CHARM
Conclusion and Future Scope
Cloud Computing
Different Cloud Vendors
Deeksha Arya CHARM: Multi-Cloud Data Hosting Scheme
Introduction
Multi-Cloud Scenario
Motivation
Available Data Hosting Schemes
The proposed Scheme CHARM
Conclusion and Future Scope
Single Cloud vs Multi-Cloud
Problems in Single Cloud Data Hosting
Basic Principle of Multi-cloud Data Hosting
Problems in Multi-Cloud Data Hosting
Single Cloud vs Multi Cloud
Which one is more beneficial?
How to decide?
Who will decide?
What if the situation changes?
Deeksha Arya CHARM: Multi-Cloud Data Hosting Scheme
Introduction
Multi-Cloud Scenario
Motivation
Available Data Hosting Schemes
The proposed Scheme CHARM
Conclusion and Future Scope
Single Cloud vs Multi-Cloud
Problems in Single Cloud Data Hosting
Basic Principle of Multi-cloud Data Hosting
Problems in Multi-Cloud Data Hosting
Heterogeneous Clouds
Existing clouds exhibit great heterogeneities in terms of both
working performances and pricing policies.
For instance,
Google Cloud Storage charges more for bandwidth
consumption,
Amazon S3 charges more for storage space
Deeksha Arya CHARM: Multi-Cloud Data Hosting Scheme
Introduction
Multi-Cloud Scenario
Motivation
Available Data Hosting Schemes
The proposed Scheme CHARM
Conclusion and Future Scope
Single Cloud vs Multi-Cloud
Problems in Single Cloud Data Hosting
Basic Principle of Multi-cloud Data Hosting
Problems in Multi-Cloud Data Hosting
Vendor Lock-in Risk
Customers usually put their data into a single cloud and then
simply trust to luck. This is subject to the so-called vendor
lock-in risk, because customers would be confronted with a
dilemma if they want to switch to other cloud vendors.
For example, moving 100 TB of data from Amazon
S3(California data-center)to Aliyun OSS (Beijing data-center)
would consume as much as 12,300 (US) dollars.
Deeksha Arya CHARM: Multi-Cloud Data Hosting Scheme
Introduction
Multi-Cloud Scenario
Motivation
Available Data Hosting Schemes
The proposed Scheme CHARM
Conclusion and Future Scope
Single Cloud vs Multi-Cloud
Problems in Single Cloud Data Hosting
Basic Principle of Multi-cloud Data Hosting
Problems in Multi-Cloud Data Hosting
The vendor lock-in risk makes customers suffer from price
adjustments of cloud vendors.
Another issue is availability.
Clearly, it is unwise for an enterprise or an organization to
host all data in a single cloud— “your best bet is probably not
to put all your eggs in one basket ”.
Deeksha Arya CHARM: Multi-Cloud Data Hosting Scheme
Introduction
Multi-Cloud Scenario
Motivation
Available Data Hosting Schemes
The proposed Scheme CHARM
Conclusion and Future Scope
Single Cloud vs Multi-Cloud
Problems in Single Cloud Data Hosting
Basic Principle of Multi-cloud Data Hosting
Problems in Multi-Cloud Data Hosting
Multi-Cloud Scenario
Basic Principle of Multi-cloud Data Hosting
Deeksha Arya CHARM: Multi-Cloud Data Hosting Scheme
Introduction
Multi-Cloud Scenario
Motivation
Available Data Hosting Schemes
The proposed Scheme CHARM
Conclusion and Future Scope
Single Cloud vs Multi-Cloud
Problems in Single Cloud Data Hosting
Basic Principle of Multi-cloud Data Hosting
Problems in Multi-Cloud Data Hosting
Problems in Multi-Cloud Data Hosting
Two critical problems:
1 How to choose appropriate clouds to minimize monetary cost
in the presence of heterogeneous pricing policies?
2 How to meet the different availability requirements of different
services?
Deeksha Arya CHARM: Multi-Cloud Data Hosting Scheme
Introduction
Multi-Cloud Scenario
Motivation
Available Data Hosting Schemes
The proposed Scheme CHARM
Conclusion and Future Scope
Motivation
Major concern for customers: Which cloud(s) are suitable
for storing their data and what hosting strategy is
cheaper?
CHARM-the proposed Data Hosting scheme helps the
customers to select several suitable clouds and an appropriate
redundancy strategy to store the data with
1. Minimum monetary cost and
2. Guaranteed Availability
In addition, it also provides the function of re-distributing
the data according to the variations of data access patterns
and pricing of clouds.
Deeksha Arya CHARM: Multi-Cloud Data Hosting Scheme
Introduction
Multi-Cloud Scenario
Motivation
Available Data Hosting Schemes
The proposed Scheme CHARM
Conclusion and Future Scope
Replication
Erasure Coding
Available Data Hosting Schemes
Available Redundancy Mechanisms for Data Hosting:
1. Replication
2. Erasure Coding
Different schemes uses these redundancy mechanisms in
different ways( Random/Greedy).
Deeksha Arya CHARM: Multi-Cloud Data Hosting Scheme
Introduction
Multi-Cloud Scenario
Motivation
Available Data Hosting Schemes
The proposed Scheme CHARM
Conclusion and Future Scope
Replication
Erasure Coding
Replication
Traditional Storage Mode: Put the replicas into three
different storage nodes.
Advantages:
Provides High Availability
The data is lost only when the three nodes all crash.
Dis-advantage: Occupies 2x more storage space.
Deeksha Arya CHARM: Multi-Cloud Data Hosting Scheme
Introduction
Multi-Cloud Scenario
Motivation
Available Data Hosting Schemes
The proposed Scheme CHARM
Conclusion and Future Scope
Replication
Erasure Coding
Erasure Coding
Erasure coding is proposed to reduce storage consumption
greatly while guaranteeing the same or higher level of data
reliability as that of Replication.
Reed-Solomon code - A representative erasure-coding scheme:
Data of a segment is encoded into n blocks including
1. m data blocks and,
2. n-m coding blocks
These blocks are put into n different clouds.
Data can be restored using any m chunks in the segment.
Deeksha Arya CHARM: Multi-Cloud Data Hosting Scheme
Introduction
Multi-Cloud Scenario
Motivation
Available Data Hosting Schemes
The proposed Scheme CHARM
Conclusion and Future Scope
Replication
Erasure Coding
Erasure Coding
Advantages:
Data availability can be guaranteed with lower storage space
(compared with replication).
Up to n − m simultaneous chunk failures can be tolerated.
Dis-advantages:
A read access has to be served by multiple clouds that store
the corresponding data blocks.
Consequently, erasure coding cannot make full use of the
cheapest cloud as what replication does.
Deeksha Arya CHARM: Multi-Cloud Data Hosting Scheme
Introduction
Multi-Cloud Scenario
Motivation
Available Data Hosting Schemes
The proposed Scheme CHARM
Conclusion and Future Scope
Replication
Erasure Coding
Replication in terms of Erasure Coding
Replication is a special case of Erasure Coding with m=1.
That is, in Replication we have
m = 1 data block
n − m = n − 1 coding blocks and
Up to n − m = n − 1 simultaneous failures can be tolerated.
Deeksha Arya CHARM: Multi-Cloud Data Hosting Scheme
Introduction
Multi-Cloud Scenario
Motivation
Available Data Hosting Schemes
The proposed Scheme CHARM
Conclusion and Future Scope
Architecture
Algorithms Used
CHARM
CHARM stands for a Cost-efficient data Hosting model with
high Availability in heteRogenous Multi-cloud system.
CHARM combines the two widely used redundancy
mechanisms, i.e., replication and erasure coding.
CHARM ≡ (Replication + Erasure Coding)
Deeksha Arya CHARM: Multi-Cloud Data Hosting Scheme
Introduction
Multi-Cloud Scenario
Motivation
Available Data Hosting Schemes
The proposed Scheme CHARM
Conclusion and Future Scope
Architecture
Algorithms Used
Architecture of CHARM
Deeksha Arya CHARM: Multi-Cloud Data Hosting Scheme
Introduction
Multi-Cloud Scenario
Motivation
Available Data Hosting Schemes
The proposed Scheme CHARM
Conclusion and Future Scope
Architecture
Algorithms Used
Multi-Cloud Scenario
Basic Principle of Multi-cloud Data Hosting
Deeksha Arya CHARM: Multi-Cloud Data Hosting Scheme
Introduction
Multi-Cloud Scenario
Motivation
Available Data Hosting Schemes
The proposed Scheme CHARM
Conclusion and Future Scope
Architecture
Algorithms Used
Components of CHARM
There are four main components in CHARM:
1. Data Hosting
2. Storage Mode Switching (SMS)
3. Workload Statistic
4. Predictor
Deeksha Arya CHARM: Multi-Cloud Data Hosting Scheme
Introduction
Multi-Cloud Scenario
Motivation
Available Data Hosting Schemes
The proposed Scheme CHARM
Conclusion and Future Scope
Architecture
Algorithms Used
Working of the Components
1. Data Hosting stores data using replication or erasure coding,
according to the size and access frequency of the data.
2. Storage Mode Switching (SMS) decides whether the
storage mode of certain data should be changed from
replication to erasure coding or in reverse, according to the
output of Predictor.
3. Workload Statistic keeps collecting and tackling access logs
to guide the placement of data. It also sends statistic
information to Predictor which guides the action of SMS.
4. Predictor is used to predict the future access frequency of
files.
Deeksha Arya CHARM: Multi-Cloud Data Hosting Scheme
Introduction
Multi-Cloud Scenario
Motivation
Available Data Hosting Schemes
The proposed Scheme CHARM
Conclusion and Future Scope
Architecture
Algorithms Used
Algorithm 1
Deeksha Arya CHARM: Multi-Cloud Data Hosting Scheme
Introduction
Multi-Cloud Scenario
Motivation
Available Data Hosting Schemes
The proposed Scheme CHARM
Conclusion and Future Scope
Architecture
Algorithms Used
Algorithm 1
Deeksha Arya CHARM: Multi-Cloud Data Hosting Scheme
Introduction
Multi-Cloud Scenario
Motivation
Available Data Hosting Schemes
The proposed Scheme CHARM
Conclusion and Future Scope
Architecture
Algorithms Used
Key Points
1. What should be the value of n? (n varies from 2 to nmax )
2. Which n clouds should be selected?
3. What should be the value of m? (m varies from 1 to n )
4. Goals:
Minimize the cost
Maximize the availability
5. Complexity of the Algorithm: O(NLogN)
Deeksha Arya CHARM: Multi-Cloud Data Hosting Scheme
Introduction
Multi-Cloud Scenario
Motivation
Available Data Hosting Schemes
The proposed Scheme CHARM
Conclusion and Future Scope
Architecture
Algorithms Used
Algorithm 2
Deeksha Arya CHARM: Multi-Cloud Data Hosting Scheme
Introduction
Multi-Cloud Scenario
Motivation
Available Data Hosting Schemes
The proposed Scheme CHARM
Conclusion and Future Scope
Conclusion and Future Scope
CHARM makes fine-grained decisions about which storage
mode to use and which clouds to place data in and hence
helps the user to distribute the data on different clouds in a
cost effective manner.
This system can be enhanced by developing an automatic
update methodology that updates only the required data
blocks.
The enhanced version will save the time for downloading and
uploading the file again.
Deeksha Arya CHARM: Multi-Cloud Data Hosting Scheme
Introduction
Multi-Cloud Scenario
Motivation
Available Data Hosting Schemes
The proposed Scheme CHARM
Conclusion and Future Scope
References
Quanlu Zhang, Shenglong Li, Zhenhua Li, Yuanjian Xing, Zhi Yang, and
Yafei Dai (2015)
CHARM: A Cost-Efficient Multi-Cloud Data Hosting Scheme with High
Availability
IEEE TRANSACTIONS ON CLOUD COMPUTING, VOL. 3, NO. 3,
372-386, JULY-SEPTEMBER 2015.
Gade Pooja V., Mate Shweta, A. Janjalkar Priti S. (2015)
Multi-Cloud Hosting for Performance Optimization and Security
International Journal for Scientific Research and Development, VOL. 3,
Issue 8 — ISSN (online), 2321-0613 2015.
Deeksha Arya CHARM: Multi-Cloud Data Hosting Scheme
Introduction
Multi-Cloud Scenario
Motivation
Available Data Hosting Schemes
The proposed Scheme CHARM
Conclusion and Future Scope
Thank You!
Deeksha Arya CHARM: Multi-Cloud Data Hosting Scheme

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CHARM(A Cost-Efficient Multi-Cloud Data Hosting Scheme with High Availability)

  • 1. Introduction Multi-Cloud Scenario Motivation Available Data Hosting Schemes The proposed Scheme CHARM Conclusion and Future Scope CHARM (A Cost-Efficient Multi-Cloud Data Hosting Scheme with High Availability) Deeksha Arya deekshasheokand@gmail.com Computer Engineering Department NIT Kurukshetra May 5, 2016 Deeksha Arya CHARM: Multi-Cloud Data Hosting Scheme
  • 2. Introduction Multi-Cloud Scenario Motivation Available Data Hosting Schemes The proposed Scheme CHARM Conclusion and Future Scope Outline 1 Introduction Cloud Computing 2 Multi-Cloud Scenario Single Cloud vs Multi-Cloud Problems in Single Cloud Data Hosting Problems in Multi-Cloud Data Hosting 3 Motivation 4 Available Data Hosting Schemes Replication Erasure Coding 5 The proposed Scheme CHARM Architecture Algorithms Used 6 Conclusion and Future Scope Deeksha Arya CHARM: Multi-Cloud Data Hosting Scheme
  • 3. Introduction Multi-Cloud Scenario Motivation Available Data Hosting Schemes The proposed Scheme CHARM Conclusion and Future Scope Cloud Computing What is Cloud Computing? Cloud Computing is the use of computing resources(hardware and software) that are delivered as a service over a network. Deeksha Arya CHARM: Multi-Cloud Data Hosting Scheme
  • 4. Introduction Multi-Cloud Scenario Motivation Available Data Hosting Schemes The proposed Scheme CHARM Conclusion and Future Scope Cloud Computing How does it work? In cloud computing, users access the data, applications or any other services with the help of a browser regardless of the device used and the user’s location. Deeksha Arya CHARM: Multi-Cloud Data Hosting Scheme
  • 5. Introduction Multi-Cloud Scenario Motivation Available Data Hosting Schemes The proposed Scheme CHARM Conclusion and Future Scope Cloud Computing Why Cloud Computing? Deeksha Arya CHARM: Multi-Cloud Data Hosting Scheme
  • 6. Introduction Multi-Cloud Scenario Motivation Available Data Hosting Schemes The proposed Scheme CHARM Conclusion and Future Scope Cloud Computing History of Cloud Computing Deeksha Arya CHARM: Multi-Cloud Data Hosting Scheme
  • 7. Introduction Multi-Cloud Scenario Motivation Available Data Hosting Schemes The proposed Scheme CHARM Conclusion and Future Scope Cloud Computing Different Cloud Vendors Deeksha Arya CHARM: Multi-Cloud Data Hosting Scheme
  • 8. Introduction Multi-Cloud Scenario Motivation Available Data Hosting Schemes The proposed Scheme CHARM Conclusion and Future Scope Single Cloud vs Multi-Cloud Problems in Single Cloud Data Hosting Basic Principle of Multi-cloud Data Hosting Problems in Multi-Cloud Data Hosting Single Cloud vs Multi Cloud Which one is more beneficial? How to decide? Who will decide? What if the situation changes? Deeksha Arya CHARM: Multi-Cloud Data Hosting Scheme
  • 9. Introduction Multi-Cloud Scenario Motivation Available Data Hosting Schemes The proposed Scheme CHARM Conclusion and Future Scope Single Cloud vs Multi-Cloud Problems in Single Cloud Data Hosting Basic Principle of Multi-cloud Data Hosting Problems in Multi-Cloud Data Hosting Heterogeneous Clouds Existing clouds exhibit great heterogeneities in terms of both working performances and pricing policies. For instance, Google Cloud Storage charges more for bandwidth consumption, Amazon S3 charges more for storage space Deeksha Arya CHARM: Multi-Cloud Data Hosting Scheme
  • 10. Introduction Multi-Cloud Scenario Motivation Available Data Hosting Schemes The proposed Scheme CHARM Conclusion and Future Scope Single Cloud vs Multi-Cloud Problems in Single Cloud Data Hosting Basic Principle of Multi-cloud Data Hosting Problems in Multi-Cloud Data Hosting Vendor Lock-in Risk Customers usually put their data into a single cloud and then simply trust to luck. This is subject to the so-called vendor lock-in risk, because customers would be confronted with a dilemma if they want to switch to other cloud vendors. For example, moving 100 TB of data from Amazon S3(California data-center)to Aliyun OSS (Beijing data-center) would consume as much as 12,300 (US) dollars. Deeksha Arya CHARM: Multi-Cloud Data Hosting Scheme
  • 11. Introduction Multi-Cloud Scenario Motivation Available Data Hosting Schemes The proposed Scheme CHARM Conclusion and Future Scope Single Cloud vs Multi-Cloud Problems in Single Cloud Data Hosting Basic Principle of Multi-cloud Data Hosting Problems in Multi-Cloud Data Hosting The vendor lock-in risk makes customers suffer from price adjustments of cloud vendors. Another issue is availability. Clearly, it is unwise for an enterprise or an organization to host all data in a single cloud— “your best bet is probably not to put all your eggs in one basket ”. Deeksha Arya CHARM: Multi-Cloud Data Hosting Scheme
  • 12. Introduction Multi-Cloud Scenario Motivation Available Data Hosting Schemes The proposed Scheme CHARM Conclusion and Future Scope Single Cloud vs Multi-Cloud Problems in Single Cloud Data Hosting Basic Principle of Multi-cloud Data Hosting Problems in Multi-Cloud Data Hosting Multi-Cloud Scenario Basic Principle of Multi-cloud Data Hosting Deeksha Arya CHARM: Multi-Cloud Data Hosting Scheme
  • 13. Introduction Multi-Cloud Scenario Motivation Available Data Hosting Schemes The proposed Scheme CHARM Conclusion and Future Scope Single Cloud vs Multi-Cloud Problems in Single Cloud Data Hosting Basic Principle of Multi-cloud Data Hosting Problems in Multi-Cloud Data Hosting Problems in Multi-Cloud Data Hosting Two critical problems: 1 How to choose appropriate clouds to minimize monetary cost in the presence of heterogeneous pricing policies? 2 How to meet the different availability requirements of different services? Deeksha Arya CHARM: Multi-Cloud Data Hosting Scheme
  • 14. Introduction Multi-Cloud Scenario Motivation Available Data Hosting Schemes The proposed Scheme CHARM Conclusion and Future Scope Motivation Major concern for customers: Which cloud(s) are suitable for storing their data and what hosting strategy is cheaper? CHARM-the proposed Data Hosting scheme helps the customers to select several suitable clouds and an appropriate redundancy strategy to store the data with 1. Minimum monetary cost and 2. Guaranteed Availability In addition, it also provides the function of re-distributing the data according to the variations of data access patterns and pricing of clouds. Deeksha Arya CHARM: Multi-Cloud Data Hosting Scheme
  • 15. Introduction Multi-Cloud Scenario Motivation Available Data Hosting Schemes The proposed Scheme CHARM Conclusion and Future Scope Replication Erasure Coding Available Data Hosting Schemes Available Redundancy Mechanisms for Data Hosting: 1. Replication 2. Erasure Coding Different schemes uses these redundancy mechanisms in different ways( Random/Greedy). Deeksha Arya CHARM: Multi-Cloud Data Hosting Scheme
  • 16. Introduction Multi-Cloud Scenario Motivation Available Data Hosting Schemes The proposed Scheme CHARM Conclusion and Future Scope Replication Erasure Coding Replication Traditional Storage Mode: Put the replicas into three different storage nodes. Advantages: Provides High Availability The data is lost only when the three nodes all crash. Dis-advantage: Occupies 2x more storage space. Deeksha Arya CHARM: Multi-Cloud Data Hosting Scheme
  • 17. Introduction Multi-Cloud Scenario Motivation Available Data Hosting Schemes The proposed Scheme CHARM Conclusion and Future Scope Replication Erasure Coding Erasure Coding Erasure coding is proposed to reduce storage consumption greatly while guaranteeing the same or higher level of data reliability as that of Replication. Reed-Solomon code - A representative erasure-coding scheme: Data of a segment is encoded into n blocks including 1. m data blocks and, 2. n-m coding blocks These blocks are put into n different clouds. Data can be restored using any m chunks in the segment. Deeksha Arya CHARM: Multi-Cloud Data Hosting Scheme
  • 18. Introduction Multi-Cloud Scenario Motivation Available Data Hosting Schemes The proposed Scheme CHARM Conclusion and Future Scope Replication Erasure Coding Erasure Coding Advantages: Data availability can be guaranteed with lower storage space (compared with replication). Up to n − m simultaneous chunk failures can be tolerated. Dis-advantages: A read access has to be served by multiple clouds that store the corresponding data blocks. Consequently, erasure coding cannot make full use of the cheapest cloud as what replication does. Deeksha Arya CHARM: Multi-Cloud Data Hosting Scheme
  • 19. Introduction Multi-Cloud Scenario Motivation Available Data Hosting Schemes The proposed Scheme CHARM Conclusion and Future Scope Replication Erasure Coding Replication in terms of Erasure Coding Replication is a special case of Erasure Coding with m=1. That is, in Replication we have m = 1 data block n − m = n − 1 coding blocks and Up to n − m = n − 1 simultaneous failures can be tolerated. Deeksha Arya CHARM: Multi-Cloud Data Hosting Scheme
  • 20. Introduction Multi-Cloud Scenario Motivation Available Data Hosting Schemes The proposed Scheme CHARM Conclusion and Future Scope Architecture Algorithms Used CHARM CHARM stands for a Cost-efficient data Hosting model with high Availability in heteRogenous Multi-cloud system. CHARM combines the two widely used redundancy mechanisms, i.e., replication and erasure coding. CHARM ≡ (Replication + Erasure Coding) Deeksha Arya CHARM: Multi-Cloud Data Hosting Scheme
  • 21. Introduction Multi-Cloud Scenario Motivation Available Data Hosting Schemes The proposed Scheme CHARM Conclusion and Future Scope Architecture Algorithms Used Architecture of CHARM Deeksha Arya CHARM: Multi-Cloud Data Hosting Scheme
  • 22. Introduction Multi-Cloud Scenario Motivation Available Data Hosting Schemes The proposed Scheme CHARM Conclusion and Future Scope Architecture Algorithms Used Multi-Cloud Scenario Basic Principle of Multi-cloud Data Hosting Deeksha Arya CHARM: Multi-Cloud Data Hosting Scheme
  • 23. Introduction Multi-Cloud Scenario Motivation Available Data Hosting Schemes The proposed Scheme CHARM Conclusion and Future Scope Architecture Algorithms Used Components of CHARM There are four main components in CHARM: 1. Data Hosting 2. Storage Mode Switching (SMS) 3. Workload Statistic 4. Predictor Deeksha Arya CHARM: Multi-Cloud Data Hosting Scheme
  • 24. Introduction Multi-Cloud Scenario Motivation Available Data Hosting Schemes The proposed Scheme CHARM Conclusion and Future Scope Architecture Algorithms Used Working of the Components 1. Data Hosting stores data using replication or erasure coding, according to the size and access frequency of the data. 2. Storage Mode Switching (SMS) decides whether the storage mode of certain data should be changed from replication to erasure coding or in reverse, according to the output of Predictor. 3. Workload Statistic keeps collecting and tackling access logs to guide the placement of data. It also sends statistic information to Predictor which guides the action of SMS. 4. Predictor is used to predict the future access frequency of files. Deeksha Arya CHARM: Multi-Cloud Data Hosting Scheme
  • 25. Introduction Multi-Cloud Scenario Motivation Available Data Hosting Schemes The proposed Scheme CHARM Conclusion and Future Scope Architecture Algorithms Used Algorithm 1 Deeksha Arya CHARM: Multi-Cloud Data Hosting Scheme
  • 26. Introduction Multi-Cloud Scenario Motivation Available Data Hosting Schemes The proposed Scheme CHARM Conclusion and Future Scope Architecture Algorithms Used Algorithm 1 Deeksha Arya CHARM: Multi-Cloud Data Hosting Scheme
  • 27. Introduction Multi-Cloud Scenario Motivation Available Data Hosting Schemes The proposed Scheme CHARM Conclusion and Future Scope Architecture Algorithms Used Key Points 1. What should be the value of n? (n varies from 2 to nmax ) 2. Which n clouds should be selected? 3. What should be the value of m? (m varies from 1 to n ) 4. Goals: Minimize the cost Maximize the availability 5. Complexity of the Algorithm: O(NLogN) Deeksha Arya CHARM: Multi-Cloud Data Hosting Scheme
  • 28. Introduction Multi-Cloud Scenario Motivation Available Data Hosting Schemes The proposed Scheme CHARM Conclusion and Future Scope Architecture Algorithms Used Algorithm 2 Deeksha Arya CHARM: Multi-Cloud Data Hosting Scheme
  • 29. Introduction Multi-Cloud Scenario Motivation Available Data Hosting Schemes The proposed Scheme CHARM Conclusion and Future Scope Conclusion and Future Scope CHARM makes fine-grained decisions about which storage mode to use and which clouds to place data in and hence helps the user to distribute the data on different clouds in a cost effective manner. This system can be enhanced by developing an automatic update methodology that updates only the required data blocks. The enhanced version will save the time for downloading and uploading the file again. Deeksha Arya CHARM: Multi-Cloud Data Hosting Scheme
  • 30. Introduction Multi-Cloud Scenario Motivation Available Data Hosting Schemes The proposed Scheme CHARM Conclusion and Future Scope References Quanlu Zhang, Shenglong Li, Zhenhua Li, Yuanjian Xing, Zhi Yang, and Yafei Dai (2015) CHARM: A Cost-Efficient Multi-Cloud Data Hosting Scheme with High Availability IEEE TRANSACTIONS ON CLOUD COMPUTING, VOL. 3, NO. 3, 372-386, JULY-SEPTEMBER 2015. Gade Pooja V., Mate Shweta, A. Janjalkar Priti S. (2015) Multi-Cloud Hosting for Performance Optimization and Security International Journal for Scientific Research and Development, VOL. 3, Issue 8 — ISSN (online), 2321-0613 2015. Deeksha Arya CHARM: Multi-Cloud Data Hosting Scheme
  • 31. Introduction Multi-Cloud Scenario Motivation Available Data Hosting Schemes The proposed Scheme CHARM Conclusion and Future Scope Thank You! Deeksha Arya CHARM: Multi-Cloud Data Hosting Scheme