Cloud Computing for Mobile Users: Can Offloading Computation Save Energy?

By Karthik Kumar, Yung-Hsiang Lu. Computer, 2010

1,632 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Information Systems

View Paper: https://www.semanticscholar.org/paper/93a96e0f68038fbbe70f80952632e8f0770af56e

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In Computer Networks and Communications

In Information Systems

Citations in the corpus

Joint Optimization of Radio and Computational Resources for Multicell Mobile-Edge Computing (2014, background): “The trade-off between the energy spent for computation and communication was studied in [12]–[14], [22].”
Heterogeneity in Mobile Cloud Computing: Taxonomy and Open Challenges (2014, background): “However, cloudbased application offloading cannot always save energy with current developments and demands further efforts [6], [60], [61].”
A Survey on Mobile Edge Computing: The Communication Perspective (2017, background): “In [92] and [93], general guidelines were developed for determining the offloading decision for the purposes of minimizing the mobile-energy”
Energy-optimal mobile application execution: Taming resource-poor mobile devices with cloud clones (2012, background): “research on optimal policies for application offioading to cloud execution is limited in that they mostly consider a fixed computation scheduling in the mobile device and a fixed bandwidth model for the wireless channel [6], [10].”
A survey of mobile cloud computing: architecture, applications, and approaches (2013, background): “For example, clouds can be used for transcoding [26], playing chess [21], [27], or broadcasting multimedia services [28] to mobile devices.”
Cloud-Based Augmentation for Mobile Devices: Motivation, Taxonomies, and Open Challenges (2013, background): “to the cloud, network technologies and coverage, available bandwidth, traffic congestion, deployment cost, and even nature of augmentation tasks alter usefulness of the CMA approaches [40].”
DREAM: Dynamic Resource and Task Allocation for Energy Minimization in Mobile Cloud Systems (2015, background): “For instance, a chess game application [4] has much higher computations per bit than an image retrieval application [8].”
Communicating While Computing: Distributed mobile cloud computing over 5G heterogeneous networks (2014, background): “Examples of static offloading are Spectra [11], [17], [18] and Chroma [12].”
On Global Electricity Usage of Communication Technology: Trends to 2030 (2015, background): “The general problems and opportunities regarding electricity usage of WAN have been widely discussed [111–116].”
Performance and energy modeling for live migration of virtual machines (2011, background): “However, the primary constraints for mobile computing are limited energy and wireless bandwidth [23].”
Mobile Augmented Reality Survey: From Where We Are to Where We Go (2017, background): “Kumar and Lu [295] proposed a model to evaluate energy consumption by using computation offloading methods.”
Mobile Edge Computing: A Survey (2018, background): “To deal with these constraints, many researchers have managed computation offloading to computational power resources [33] [82] [49] , such as cloud.”
Edge Computing: Vision and Challenges (2016, neutral): “Numbers of researches have addressed the cloud ofﬂoading in terms of energy-performance tradeoff in a mobile-cloud environment [23], [24], [25], [26], [27].”