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Mobile Edge Computing and Artificial Intelligence: A Mutually-Beneficial Relationship
[article]
2020
arXiv
pre-print
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This article provides an overview of mobile edge computing (MEC) and artificial intelligence (AI) and discusses the mutually-beneficial relationship between them. ...
AI provides revolutionary solutions in nearly every important aspect of the MEC offloading process, such as resource management and scheduling. ...
access the computation resources; • Dependency among tasks: In many applications, the computation of a task depends on the computed results of other tasks. ...
arXiv:2005.03100v1
fatcat:zyu2ibxhn5fqhe2wpkfsuhwece
Secure and Energy-Efficient Computational Offloading Using LSTM in Mobile Edge Computing
2022
Security and Communication Networks
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The prediction of the computational tasks is done using the LSTM algorithm, the strategy for computation offloading of mobile devices is based on the prediction of tasks, and the migration of tasks for ...
In today's world, mobile edge computing is improving in various forms so as to provide better output and there is no room for simple computing architecture for MEC. ...
Fuzzy logic is an efficient approach for solving the edge computing workload scheduling problem described in recent years. ...
doi:10.1155/2022/4937588
fatcat:cm54h5tfcze43btke5hdxctbqi
Collaborative Computation for Offloading and Caching Strategy Using Intelligent Edge Computing
2022
Mobile Information Systems
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Computation offloading and caching strategy is a well-established concept for allowing mobile applications that are high in resources. ...
However, the problematic characteristics of offloading and caching strategy delay bandwidth transfer from mobile computing devices to cloud computing. ...
Intelligent edge processing gives users short-term and powerful computational services using computer terminals and servers on the edge of a network that satisfies delaysensitive task needs of users in ...
doi:10.1155/2022/4840801
fatcat:fv2auygttnb73g7chhlmdbuci4
Actions at the Edge: Jointly Optimizing the Resources in Multi-access Edge Computing
[article]
2022
arXiv
pre-print
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Multi-access edge computing (MEC) is an emerging paradigm that pushes resources for sensing, communications, computing, storage and intelligence (SCCSI) to the premises closer to the end users, i.e., the ...
edge intelligence and real-time processing and control. ...
Deng was supported in part by National Natural Science Foundation of China (No. 62172441, 61772553). ...
arXiv:2204.08169v1
fatcat:lryz46hip5byrnpa22v7ytfxua
Computational Offloading in FOG computing using Machine Learning Approaches
2020
International Journal of Scientific Research in Computer Science Engineering and Information Technology
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performance of offloading by reducing the delay in computing the tasks. ...
Computation offloading is a prominent exposition for the mobile devices that lack the computational power to execute applications that require a high computational cost. ...
In this context, the authors proposed a deep learning-based intelligent computation offloading based architecture which uses a multilevel LSTM algorithm for computation task prediction and depends on the ...
doi:10.32628/cseit206221
fatcat:ok7jmgd76vgdlbga4aggzklmti
Computing in the Sky: A Survey on Intelligent Ubiquitous Computing for UAV-Assisted 6G Networks and Industry 4.0/5.0
2022
Drones
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Intelligence (AI) techniques to extract discriminatory information from the massive amount of data for different tasks.Therefore, Mobile Edge Computing (MEC) has evolved as a promising computing paradigm ...
We highlight the utility of UAV computing and the critical role of Federated Learning (FL) in meeting the challenges related to energy, security, task offloading, and latency of IoT data in smart environments ...
The authors of [79] also proposed an intelligent task offloading algorithm for UAV-empowered MEC services in which the UAVs offload computing tasks to fixed MEC servers. ...
doi:10.3390/drones6070177
fatcat:533tggsjhbdjvbowfr3ku5mmci
Artificial Intelligence-Empowered Edge of Vehicles: Architecture, Enabling Technologies, and Applications
2020
IEEE Access
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With the proliferation of mobile devices and a wealth of rich application services, the Internet of vehicles (IoV) has struggled to handle computationally intensive and delay-sensitive computing tasks. ...
To substantially reduce the latency and the energy consumption, application work is offloaded from a mobile device to a remote cloud or a nearby mobile edge cloud for processing. ...
The task offloading scheme is analyzed in the scenario of an independent mobile edge computing device server and in the scenario of a collaborative mobile edge computing device server. ...
doi:10.1109/access.2020.2983609
fatcat:b45abdrxbracnbfpvtvtu5uxui
Special Issue on Artificial-Intelligence-Powered Edge Computing for Internet of Things
2020
IEEE Internet of Things Journal
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for AI-powered time-critical services in mobile-edge computing. ...
in edge computing for intelligent driving. ...
doi:10.1109/jiot.2020.3019948
fatcat:mogalqnhnnaqpbxb7zivzdhvry
Task partitioning and offloading in IoT cloud-edge collaborative computing framework: a survey
2022
Journal of Cloud Computing: Advances, Systems and Applications
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We also propose comprehensive taxonomy metrics for comparing task partitioning and offloading approaches in the IoT cloud-edge collaborative computing framework. ...
In this paper, we make a comprehensive overview on the existing task partitioning and offloading frameworks, focusing on the input and core of decision engine of the framework for task partitioning and ...
[11] The authors focused on architecture, computation migration, edge caching, and service orchestration in task offloading. ...
doi:10.1186/s13677-022-00365-8
fatcat:3ogennvxojhzlbhm4lwvcgxlxu
A Survey on Offloading in Federated Cloud-Edge-Fog Systems with Traditional Optimization and Machine Learning
[article]
2022
arXiv
pre-print
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Edge and fog computing provide similar services with lower latency but with limited capacity, capability, and coverage. ...
We then provide a comprehensive survey on offloading in federated systems with machine learning approaches and the lessons learned as a result of these surveys. ...
for edge computing [12] ML Machine learning-based approaches in mobile edge computing Our Multiple T/ML Offloading in federated cloud-edge-fog systems The authors of [13] - [17] discussed traffic ...
arXiv:2202.10628v1
fatcat:72oyy5unmbcwdn4rrnjy3t7dgu
Artificial intelligence for edge service optimization in Internet of Vehicles: A survey
2022
Tsinghua Science and Technology
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Secondly, we review the edge service frameworks for IoV and explore the use of AI in edge server placement and service offloading. ...
Edge Computing (EC) that deploys physical resources near road-side units is involved in IoV to support real-time services for vehicular users. ...
AI for service offloading across edge servers in IoV As shown in the Fig. 2 , we present an architecture of service offloading across edge servers with the help of AI in IoV. ...
doi:10.26599/tst.2020.9010025
fatcat:zgakvppxojawjb7cto4tu6237u
Beyond 5G Networks: Integration of Communication, Computing, Caching, and Control
[article]
2022
arXiv
pre-print
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We also highlight the need for intelligence in resources integration. Then, we discuss integration of sensing and communication (ISAC) and classify the integration approaches into various classes. ...
Next, we describe different models of communication, computing, caching, and control (4C) to lay the foundation of the integration approach. ...
Both intelligent edge and edge intelligence require each other. In fact, the DL services in intelligent edge are likewise a piece of edge intelligence. ...
arXiv:2212.13141v1
fatcat:5ftcjml6k5cjvhbsv3a46zxvni
When Deep Reinforcement Learning Meets Federated Learning: Intelligent Multi-Timescale Resource Management for Multi-access Edge Computing in 5G Ultra Dense Network
[article]
2020
arXiv
pre-print
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Thus, we first propose an intelligent ultra-dense edge computing (I-UDEC) framework, which integrates blockchain and Artificial Intelligence (AI) into 5G ultra-dense edge computing networks. ...
Ultra-dense edge computing (UDEC) has great potential, especially in the 5G era, but it still faces challenges in its current solutions, such as the lack of: i) efficient utilization of multiple 5G resources ...
CONCLUSIONS In this article, a joint computation offloading, resource allocation and service caching placement problem is studied for ultra-dense edge computing networks First, we introduced an intelligent ...
arXiv:2009.10601v1
fatcat:wxika4igsjg65pwu64ted23aqa
A Survey on Intelligent Computation Offloading and Pricing Strategy in UAV-Enabled MEC Network: Challenges and Research Directions
[article]
2022
arXiv
pre-print
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for computation offloading in the UAV-MEC network and the high computing demands of upcoming applications. ...
This study looks at some of the research on the benefits of computation offloading process in the UAV-MEC network, as well as the intelligent models that are utilized for computation offloading. ...
Intelligent Price Decision for Computation Offloading in UAV-MEC The offloading producers of the Space-Air-Ground Integrated Network depend on the MDs' positions in the network and the execution time of ...
arXiv:2208.10072v1
fatcat:hhqj3dmuuneo5exy6xcbmupngu
UAV-Enabled Mobile Edge-Computing for IoT Based on AI: A Comprehensive Review
2021
Drones
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In this context, mobile edge computing (MEC) has emerged as a way to bring cloud computing (CC) processes within reach of users, to address computation-intensive offloading and latency issues. ...
, task offloading, energy demand, and security. ...
This approach allows terrestrial mobile users to offload their computing duties intelligently. ...
doi:10.3390/drones5040148
fatcat:ypovd7expfbypfv7juuq5nropq
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