To offload or not to offload? The bandwidth and energy costs of mobile cloud computing

By M. Barbera, Sokol Kosta, Alessandro Mei, Julinda Stefa. 2013 Proceedings IEEE INFOCOM, 2013

405 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/ef4261a7fb3f3017e6de97057ae4f651d9863b5e

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In Computer Networks and Communications

In Electrical and Electronic Engineering

Citations in the corpus

Task Offloading for Mobile Edge Computing in Software Defined Ultra-Dense Network (2018, background): “There are two major advantages of using the edge cloud [17], [18]: (i) In contrast to the local computing [19], the edge cloud computing can overcome the restrictions of limited computation capacity on mobile terminals; (ii) Compared with the computation offloading towards remote cloud [20], the edg”
Convergence of Edge Computing and Deep Learning: A Comprehensive Survey (2019, background): “sively distributed computing power and analyze their data: 1) a large number of computation tasks need to be delivered to the cloud for processing [3], which undoubtedly poses serious challenges on network capacity and the computing power of cloud computing infrastructures; 2) many new types of appl”
Efficient Multi-User Computation Offloading for Mobile-Edge Cloud Computing (2015, background): “2) if a user chooses the cloud computing, how can the user choose a proper channel in order to achieve high wireless access efﬁciency for computation ofﬂoading?”
Decentralized Computation Offloading Game for Mobile Cloud Computing (2014, background): “ing the performance of mobile cloud computing is the wireless access efficiency [7].”
5G roadmap: 10 key enabling technologies (2016, background): “With more advanced hacking technologies threatening the nternet around the world, more research focus has been put on etwork security [127,131] .”
Computation Offloading and Resource Allocation in Mixed Fog/Cloud Computing Systems With Min-Max Fairness Guarantee (2018, background): “The tradeoff between the EC for local computation and for remote communications was discussed in [20] and [21].”
Multiuser Joint Task Offloading and Resource Optimization in Proximate Clouds (2017, background): “latency, and consequently, the offloading decision becomes an issue [3].”
Joint Computation Offloading and Interference Management in Wireless Cellular Networks with Mobile Edge Computing (2017, neutral): “According to [13] and [26], the total overhead of MEC computing approach in terms of execution time and energy is computed as”
Communicating While Computing: Distributed mobile cloud computing over 5G heterogeneous networks (2014, background): “As pointed out in [7]–[9], humans are acutely sensitive to delay and jitter: as latency increases, interactive response suffers.”
Split Computing and Early Exiting for Deep Learning Applications: Survey and Research Challenges (2021, background): “bottlenecks in the model, straightforward splitting approaches would fail to improve performance in most settings [6, 35].”