TY - JOUR
T1 - Mobile cloud computing
T2 - A survey, state of art and future directions
AU - Rahimi, M. Reza
AU - Ren, Jian
AU - Liu, Chi Harold
AU - Vasilakos, Athanasios V.
AU - Venkatasubramanian, Nalini
PY - 2014/4
Y1 - 2014/4
N2 - In the recent years, cloud computing frameworks such as Amazon Web Services, Google AppEngine and Windows Azure have become increasingly popular among IT organizations and developers. Simultaneously, we have seen a phenomenal increase in the usage and deployment of smartphone platforms and applications worldwide. This paper discusses the current state of the art in the merger of these two popular technologies, that we refer to as Mobile Cloud Computing (MCC). We illustrate the applicability of MCC in various domains including mobile learning, commerce, health/wellness and social medias. We further identify research gaps covering critical aspects of how MCC can be realized and effectively utilized at scale. These include improved resource allocation in the MCC environment through efficient task distribution and offloading, security and privacy.
AB - In the recent years, cloud computing frameworks such as Amazon Web Services, Google AppEngine and Windows Azure have become increasingly popular among IT organizations and developers. Simultaneously, we have seen a phenomenal increase in the usage and deployment of smartphone platforms and applications worldwide. This paper discusses the current state of the art in the merger of these two popular technologies, that we refer to as Mobile Cloud Computing (MCC). We illustrate the applicability of MCC in various domains including mobile learning, commerce, health/wellness and social medias. We further identify research gaps covering critical aspects of how MCC can be realized and effectively utilized at scale. These include improved resource allocation in the MCC environment through efficient task distribution and offloading, security and privacy.
KW - MCC business model
KW - MCC security and privacy
KW - Mobile cloud computing
KW - Mobile computation offloading
KW - Survey
KW - Wireless bandwidth limitation
UR - https://www.scopus.com/pages/publications/84898825587
U2 - 10.1007/s11036-013-0477-4
DO - 10.1007/s11036-013-0477-4
M3 - Article
AN - SCOPUS:84898825587
SN - 1383-469X
VL - 19
SP - 133
EP - 143
JO - Mobile Networks and Applications
JF - Mobile Networks and Applications
IS - 2
ER -