Exploration of Location based Services using AI for Mobile Cloud Services

Abstract

Mobile devices have several sensors, including GPS that can capture information about the location of a mobile user. The use of certain devices will, therefore, simplify services and make it simpler for operators to respond to the demands of mobile users. The main aim of this analysis is to incorporate middleware to pick suitable cloud services that leverage from mobile device position and cost preferences. If the number of small activities within a meta feature exceeds the number of major work, the Max min algorithm device operations are conducted in addition to big tasks, where the design of the process is dependent on how many functions it does. The model is wide since tasks cannot be conducted simultaneously. A new amendment to the computation system is used to overcome the drawbacks of the Max-Min algorithm. It encompasses the positives of Max-Min and eliminates drawbacks. This study focuses specifically on the number of resources and incidents. The work can be further expanded with the algorithm suggested for the cloud system and several other parameters such as scalability, performance, reliability, and others can be taken into account.