Abstract: By the introduction of 5G (the fifth-generation wireless broadband), traditional network applications become more human-centric. Computer systems are increasingly capable of reading and responding to human emotions. These systems can be designed to provide response to human emotions promptly in receiving helpful feedback, dealing with negative emotions, and reinforcing positive feelings. These can be made available through mobile services in the form of instant text or video messaging. Cloud computing provides an illusion of infinite computing resources. Mobile cloud computing (MCC) is a new platform combining the mobile devices and cloud computing to create a new infrastructure, whereby cloud performs the heavy lifting of computing-intensive tasks and storing massive amounts of data. It provides many resource-intensive services to mobile users with the help of big mobile data delivery and cloud assisted computing. Both computational capabilities and the mobile broadband connections have improved, thus enabling the devices to constantly monitor the user, understanding his behavior and thus predicting his needs. Emotional mobile computing (EMC) framework is a system that is built on the development of an affordable and reliable system can perform an online analysis of the userís emotions. It is a design to provide emotion-aware mobile services by recognizing the changes in user emotions through cloud computing and big data analysis. The traditional MCC architecture is altered to achieve the required quality of experience in emotion-aware applications. The major tasks are processed in the mobile terminal and local cloudlet, while those tasks which require significant amount of resources, are offloaded to the remote cloud. The framework proposes to combine resource-intensive affective computing with mobile applications, while employing MCC to enhance the capability of mobile devices. Thus it proves its helpfulness in providing personalized human-centric emotion-aware services in 5G.
Keywords: Network applications, Human emotions, Computational capabilities, Mobile devices.