RETRACTED: Improving mobile cloud computing service efficiency using energy competent and federated learning process

Abstract

Mobile cloud computing (MCC) helps to make effective communication that is used to transmit various information like voice, data, and video. The MCC environments support different real‐time applications, including gaming and virtual reality implications. During the data transmission, energy conservation is one of the major issues for retaining the application span incorporating distributed and personalized computing and resource sharing. Ability‐sustained energy competent method (ASECM) is introduced to overcome these issues and manage energy efficiency. The ASECM approach analyzes the session span and energy requirements for managing the applications' energy factor. In addition, the federated learning and computation offloading process is incorporated to retain the energy factor for ensuring reliable services. The effective utilization of the offloading process is used to meet the application deadline and energy‐sufficient operations, preventing failures. In the recommendation process, cloud service availability with energy management constraints is considered for reducing energy expenditures. This process is nonrecurrent as the user/application requirements rely on diverse resources over different energy management techniques. The performance is measured using energy efficacy, utilization, application span, and failures.

Challenges in human centric intelligent systems for wireless sensor networks: A state of art

“…The propagation model for body area networks standardized by IEEE 802.15.6 is not connected with any specific human body part 24 . In this context, a survey on smart body area networks was carried out, which enunciated the control layers for the designed networks with low power and various parameters relevant to the transmission environment 25,26 . In the above survey, more focus was thrown on the devices placed on the human body externally compared to respective implanted devices 27 …”