Optimization of Cloud Resources for Air Pollution Monitoring Devices

Abstract

Cloud Computing has evolved out as one of the most advanced contrivance of the 21st century. It has integrated in almost every field and has now entered in such a stage where it is unfolding some new levels of usages that it can address. Air Pollution monitoring is one such application which is becoming prominent. Google, the face of the IT industry has integrated with Aclima to monitor air pollution with its street view application. But not everything meant to be perfect. The devices associated with monitoring part secretes out large and variable amount of data which makes it's handling a vicious constraint for cloud providers as allocated resources are not used up to their potential. Researchers areleaving no stone unturned by coming at the rock bottom level to figure out certain approaches to make this vogue affordable to the providers. The major contributing factor for this forfeiture is the elasticity factor which enables users to scale up or scale down resources at any instant of time. To counter this problem, this paperpresents a dynamic algorithmic approach foroptimization of resources. Analysis of results achieved shows that the algorithm helps to improve optimization by 20% to 30%.