ITM-CLD: Intelligent Traffic Management to Handling Cloudlets of the Large Data
The Cloud computing environment is the ultimate infrastructure for almost every kind of application missioned as a smart city or smart application concept, where heterogeneous network generating large data file of varied characteristics of increasing volume on time line which data at move as velocity etc. need to be stored, processed and analyzed. This paradigm shift from proprietary infrastructure to cloud infrastructures leads sudden and random loads as cloudlet to it. The conventional traffic management methods lack the robustness in terms of handling synchronization of heterogeneous network generated large data system. This paper proposes an intelligent traffic management namely ITM-CLD to provision a mechanism of varied traffic load in cloud environment for large data stream. The model ITM-CLD is simulated on numerical computation platform and computes performance metrics such as (1) Cloudlet handling time, (2) Unused resource, (3) Unused memory and finally, (4) Resource cost. Theses metrics are compared for different kinds of traffic load as job category with state of art work and it exhibits better performance.
KeywordsTraffic management Resource allocation Cloud computing
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