Auditability-Aware Data Scheduling for Privacy Preserved Third-party
Cloud Computing is one of the top technology concepts. It has many names, including:grid computing, utility computing, and on-demand computing. The term "cloud computing" has at its core a single element:computing services are delivered over the Internet, on demand, from a remote location, rather that residing on one's own desktop, laptop, mobile device or even on an organization's servers. For organizations, this would mean that for a set or variable, usage-based fee or even possibly for free it would contract with a provider to deliver applications, computing power and storage via web.
Cloud storage plays an important role in the technology buzz?cloud computing, in which clients can store their data at cloud servers and can be accessed anywhere, any time and on any devices. This opens up the threat on the data which client is storing on the cloud as it has to stored and accessed via Internet. Data Security opens up lot of areas like authentication of client, integrity of the data, data privacy, etc. In this paper we are going to focus on data integrity area of the data security. In which, data auditing is concept of frequently auditing the integrity of the data to make sure that the data is not tampered. Clients offload the auditing process of their data to Third Party Auditors (TPA) who are able to check the validity of the data without actually accessing the data (adhering to data privacy). As with this there will be lot of requests to the big data cloud servers from clients, users and TPA. Each request has to be serviced within required amount of time by considering the priority of the request. In which, cloud scheduling has to play an important role. By making the TPA audit aware data scheduling, all the requests to the cloud server can be scheduled based on available resources along with the importance of the request. In this paper, we present the analysis done on the auditability aware data scheduling which enhances the data request handling efficiently at the cloud server.
Keywords: Cloud Computing, Big Data, Data Security, Cluster, Heuristics, Inter-Dependent Tasks, Job Scheduling, Heterogeneous Environment, Cloudsim
Conference Name: Third National Conference on Networking and Communication Systems
Conference Date: 13, February 2015
Paper ID: ncs01