Decentralized executions of privacy awareness data analytics workflows in the cloud

摘要

Nowadays,with the development of cloud computing technology, an increasing number of enterprisesor organizations have migrated applications to the cloud environment. Because of privacyconcerns, a companymay store sensitive data on a local server or a private cloud. As a result, thedata analytics tasks have to be performed only in the local environment even when the analysisresults will be shared to the outside. In this paper, we design a decentralized workflow system tospeed up the execution of a Privacy-Awareness Data Analytics application (PADA). Specifically, aworkflow system with actor layer and engine layer for distributed execution of PADA proposed.The actors are responsible for performing actual data analysis tasks on the data side while theengines are deployed into different regions of the public cloud and communicate with actors toexecute the whole workflow. Since engines in different regions have different communicationlatencieswhen invoking an actor, the optimization engine deployment scheme should be found tominimize the total execution time of a PADA. A path search-based heuristic algorithm is designedto select suitable cloud regions to place the engines in the public cloud. The experimental resultsindicate that the proposed algorithm is effective in reducing applicationmakespan.