SECURE MAX-MIN FAIR RESOURCE ALLOCATION FOR A SELECTIVE FIELD OF STREAM BIG DATA ANALYTICS IN SHARED CLOUD

COMPUTER ENGINEERING

n a distributed environment, there is some complexity for resource allocation. The problem resource allocation faces are complication on time, space and data volumes. The dynamic incoming data are uploaded by multiple user login through internet. In stream big data analytics, the data processing workflow is abstracted as directed graph referred as a topology. Data are read from storage and processed tuple by tuple, because the content of data is in the format of meta store. The performance of topology is evaluated by its throughput. This paper proposes an efficient resource allocation scheme for a heterogeneous shared stream big data analytics cluster shared by multiple topologies by using Max-Min Resource Allocation (MFRAX) algorithm. To maintain the security in the cloud, the data will be converted into secure format by using K-anonymity algorithm. The combination of MFRAX and K-anonymity algorithm enrich the resource allocation and security

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