Context-aware multi-objective resource allocation in mobile cloud

Workload modeling for resource usage analysis and simulation in cloud computing

“…Thus, it can be used by researchers to build performance models and to produce tracelogs based on realistic scenarios and extrapolating the results with controlled modification of parameters such as number of users, software stack, and physical and virtual machine configuration. Furthermore, this implementation contributes to the development of performance models to support emerging cloud computing research domains, such as resource allocation in Mobile Cloud Computing (MCC) in which the trade-off between time and energy is a management challenge [32].…”

Resource management in cloud computing: Taxonomy, prospects, and challenges

“…In recent times, mobile cloud computing (MCC) is evolved by bringing mobile devices into the domain of cloud computing [48]. Traditionally, MCC is based on client-agent based architecture in which mobile devices can only use the resources that are available in cloud [49].…”

A Mobile Ad hoc Cloud Computing and Networking Infrastructure for Automated Video Surveillance System

“…Authors in (Hariharasudhan et al, 2015) have proposed a scheme that addresses network connectivity, node mobility and energy consumption problems. To deal with uncertainty, an idea of application waypoints has been introduced in (Ghasemi-Falavarjani et al, 2015). A service provider node executing application task reports to a broker node with an estimate of residual task completion time.…”

“…Due to recent advances in mobile computing and networking technologies, it has become feasible to integrate various mobile devices such as robots, aerial vehicles, sensors and smart phones with cloud computing systems. The approaches for integrating mobile devices with cloud computing systems are divided into two main categories: mobile cloud computing (Hariharasudhan et al, 2015;Shah, 2017) and mobile ad hoc cloud computing (Ghasemi-Falavarjani et al, 2015;Shah and Park, 2011;Shah, 2017).…”