Internet Service Selection Using Service Association Factor (SAF)

Abstract

Today, business IT organizations equip themselves with modern regime of online application infrastructure through cloud, fog and edge computing. In the presence of several opportunities, selection criterion for such internet based services becomes vital when there is no supporting information available. Recommender systems provide best services using customer's feedback, applying quality of service parameters, k-mean clustering as well as some other approaches. However, existing schemes typically relay on customer’s feedback and do not provide any information of interrelationship between the services. Feedback may be self-generated or biased and may lead to improper recommendation to service seekers. To address this, we propose an innovative service association factor approach that calculates value of interrelationship among online services appearing together in provider’s package. It enables the users to select best services on their preferences. The proposed agent works on fog environment to recommend user’s desires in all types of service models.