Quantification label for mobile apps

Nowadays every product we purchase has a tag informing its users how much an automobile or an appliance will cost to run and how much energy a food product will provide on consumption, for example. with the advent of internet, purchasing apps becomes habitual, as apps facilitate easy way of trading and generate money according to app online stores. currently, apps provide label that contains a combination of developer info, memory size, category, operating system compatibility, user ratings and reviews, and privacy policy. however, the product label information is asymmetrical and it varies with the developer. it is challenging to develop common standards explicit to users, as their needs are dynamic; moreover, the app undergoes a series of state changes during execution, according to the usage pattern. we propose a quantification label framework to assess the mobile/web app using a set of quantifiers, such as functionality, degree and domain of connectivity, battery consumption, and its vulnerability index for generating a set of standard labels. the corresponding labels in the label frame are : features, popularity, energy consumption and security. further, we utilized principal component analysis (PCA), a statistical technique to assist the customers in selecting the prominent features from the dataset and to compare related apps, which analyzes the quantifiers in the given datasets and distinguish them according to the variances. the experimental results in quantifying a real time traffic data of an internet based App validated the proposed label by revealing the key features to the users; moreover, PCA carried out on four sets of traffic data enabled the selection of prominent data, and the results also revealed the possible embedding of the framework within an App for dynamic monitoring.