@article{MAKHILLJEAS201914817660,
    title = {Task Scheduling for Mobile Cloud Computing Using Multi-Objective
EBCO-TS Algorithm},
    journal = {Journal of Engineering and Applied Sciences},
    volume = {14},
    number = {8},
    pages = {2716-2728},
    year = {2019},
    issn = {1816-949x},
    doi = {jeasci.2019.2716.2728},
    url = {https://makhillpublications.co/view-article.php?issn=1816-949x&doi=jeasci.2019.2716.2728},
    author = {C. and},
    keywords = {Energy-efficient,mobile applications,mobile cloud computing,task scheduling,enhanced bee
colony optimization based task scheduling algorithm,mobile devices},
    abstract = {Based on certain defects encountered in mobile devices, like insufficient storage space, limited battery
energy, mobile applications faces numerous confronts in energy management, mobility management, security
issues and so on. This leads to the emergence of the new computing paradigm known as Mobile Cloud
Computing (MCC). This kind of computation helps in off loading certain tasks to the nearby cloud/cloudlets
for execution this makes task scheduling more crucial mutually at both the mobile cloud and the mobile devices.
In this research, this crisis have been modelled as a problem of energy consumption optimization problem while
considering priority based scheduling, load balancing and reduced power consumption and further solve it by
means of Enhanced Bee Colony Optimization based Task Scheduling [EBCO-TS]. A series of iterations were
performed to evaluate the recital of the algorithm efficiency and the outcomes are extremely superior and
acceptable in contrast to existing methods.}
    }