Erasure Coding Scheduling Multiblock Updates


Erasure Coding Scheduling Multiblock Updates

Advancements in cloud computing are leading to a promising future for collaborative cloud computing (CCC), where globally-scattered distributed cloud resources belonging to different organizations or individuals (i.e., entities) are collectively used in a cooperative manner to provide services. Due to the autonomous features of entities in CCC, the issues of resource
management and Reputation management must be jointly addressed in order to ensure the successful deployment of CCC. However, these two issues have typically been addressed separately in previous research efforts, and simply combining the two systems generates double overhead. Also, previous resource and reputation management methods are not sufficiently efficient or effective. By providing a single reputation value for each node, the methods cannot reflect the reputation of a node in providing individual types of resources. By always selecting the highest-reputed nodes, the methods fail to exploit node reputation in resource selection to fully and fairly utilize resources in the system and to meet users? diverse QoS demands. We propose a CCC platform, called Harmony, which integrates resource management and reputation management in a harmonious manner. Harmony incorporates three key innovations: integrated multi-faceted source/reputation management, multi-QoS-oriented resource selection, and price-assisted resource/reputation control. The trace data we collected from an online trading platform implies the importance of multi-faceted reputation and the drawbacks of the highest-reputed node selection. Simulations and trace-driven experiments on the real-world Planet Lab testbed show that Harmony outperforms existing resource management and reputation management systems in terms of QoS, efficiency, and effectiveness Erasure Coding Scheduling Multiblock Updates


Cloud resource orchestration (i.e., resource provision, configuration, utilization, and decommissioning across a distributed set of physical resources in clouds) has been studied in recent years, these two issues have typically been addressed separately. Simply building and combining individual resMgt and repMgt systems in CCC will generate doubled, prohibitively high overhead. Moreover, most previous resMgt and repMgt approaches are not sufficiently efficient or effective in the large-scale and dynamic environment of CCC. Previous repMgt systems neglect resource heterogeneity by assigning each node one reputation value for providing all of its resources.

In existing system claims that node reputation is multi-faceted and should be differentiated across multiple resources (e.g., CPU, bandwidth, and memory). For example, a person trusts a doctor for giving advice on medical issues but not on financial issues. Similarly, a node that performs well for computing services does not necessarily perform well for storage services. Thus, previous repMgt systems are not effective enough to provide correct guidance for trustworthy individual resource selection. Erasure Coding Scheduling Multiblock Updates


  • Due to the issues of resMgt and repMgt, this is not efficient and trustworthy.
  • single-QoS-demand assumption


we propose a comprehensive solution for storing and maintaining log records in a server operating in a cloud-based environment. We address security and integrity issues not only just during the log generation phase, but also during other stages in the log management process, including log collection, transmission, storage, and retrieval. The major contributions of this paper are as follows. We propose an architecture for the various components of the system and develop cryptographic protocols to address integrity and confidentiality issues with storing, maintaining, and querying log records at the honest but curious cloud provider and in transit.


  • This provides very efficient, effective, and trustworthy resource sharing among clouds.
  • Choosing resources from the located option


Software Requirement:

Language – Java(JDK 1.7)

  1. OS – Windows 7 32bit
  2. MySql Server
  3. NetBeans IDE 7.1.2
  4. Apache Tomcat 7.0

Hardware Requirement :

  1. 1 GB RAM
  2. 80 GB Hard Disk
  3. Above 2GHz Processor
  4. Data Card
  5. Internet Connection

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