Journal Article10.1109/MCOM.2018.1700873
D2D Task Offloading: A Dataset-Based Q&A
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TL;DR: The main types of D2D applications, the characteristics of task offloading and the quality of experience in D1D ecosystems are presented, and five popular questions regarding the ability of other users to be helpful in terms of resources, connectivity, availability, incentives, and security are listed.
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Abstract: D2D interactions are promoted both in the context of traffic and computation offloading. Applications with functionalities that are executed in parallel in more than one mobile device have been proposed while the idea of using another mobile device as a relay is going to be part of 5G. In this work, we first present the main types of D2D applications, then we discuss the characteristics of task offloading and the quality of experience in D2D ecosystems. After that, we list five popular questions regarding the ability of other users to be helpful in terms of resources, connectivity, availability, incentives, and security. To answer the listed questions, we use two mobile big data datasets, one experimental study, and arguments from our experience and the literature.
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Citations
Latency Minimization for D2D-Enabled Partial Computation Offloading in Mobile Edge Computing
TL;DR: This work provides an integrated framework for partial offloading and interference management using orthogonal frequency-division multiple access (OFDMA) scheme and proposes a novel scheme named Joint Partial Offloading and Resource Allocation (JPORA), with aim to reduce the task execution latency.
222
Task Co-Offloading for D2D-Assisted Mobile Edge Computing in Industrial Internet of Things
TL;DR: In this paper , a learning-based task co-offloading algorithm was proposed to minimize the system cost (i.e., task delay and migration cost) in D2D-assisted MEC networks.
186
Incentive-Driven Deep Reinforcement Learning for Content Caching and D2D Offloading
TL;DR: A novel Incentive-driven and Deep Q Network (DQN) based Method, named IDQNM is proposed, in which the reverse auction is employed as the incentive mechanism, which greatly outperforms other baseline methods in terms of the CSP’s saving cost and the offloading rate in different scenarios.
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Task Co-Offloading for D2D-Assisted Mobile Edge Computing in Industrial Internet of Things
Xingxia Dai,Zhu Xiao,Hong Bin Jiang,Mamoun Alazab,John C. S. Lui,Schaharam Dustar,Jiangchuan Liu +6 more
TL;DR: A learning-based task co-offloading algorithm is investigated, with the goal of minimal system cost (i.e., task delay and migration cost).
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A smartphone perspective on computation offloading—A survey
Quang-Huy Nguyen,Falko Dressler +1 more
TL;DR: A categorization of fundamental aspects regarding computation offloading in heterogeneous cloud computing from the perspective of smartphone applications and state-of-the-art solutions for the identified categories is developed.
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