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Mobility-Aware IoT Applications Placement in the Cloud Edge Continuum
2021
IEEE Transactions on Services Computing
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To address this gap, we propose a novel mobility-aware multi-objective IoT application placement (mMAPO) method in the Cloud -Edge Continuum that optimizes completion time, energy consumption, and economic ...
The Edge computing extension of the Cloud services towards the network boundaries raises important placement challenges for IoT applications running in a heterogeneous environment with limited computing ...
3 Cloud -Edge infrastructure configuration. ...
doi:10.1109/tsc.2021.3094322
fatcat:elrfeep6ovfivbau7vuyemltzy
A Comprehensive Survey on Auction Mechanism Design for Cloud/Edge Resource Management and Pricing
2021
IEEE Access
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Driven by the vision of cloud and edge computing as the 5th utility, a major challenge is the efficient resources management and pricing taking into account incentives and preferences of cloud/edge providers ...
First, the problem statements and background are presented for cloud/edge computing and auction theory. ...
In this respect, the cloud/edge resource management and pricing problems need to be addressed jointly in order to improve system efficiency and incentivize price-driven self-interested users and providers ...
doi:10.1109/access.2021.3110914
fatcat:kxuk4olotfcqhkowkzkqv3ns54
Table of contents
2020
IEEE Journal on Selected Areas in Communications
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Wei, and F. Wu 1102 Energy-efficient Workload Allocation and Computation Resource Configuration in Distributed Cloud/Edge Computing Systems With Stochastic Workloads ........... W. Zhang, Z. ...
Leung 1118 Resource Allocation Based on Deep Reinforcement Learning in IoT Edge Computing ................................... ........................................................................... ...
doi:10.1109/jsac.2020.2992841
fatcat:a5dvop4cxfh3rf23ehbif2jjw4
An SDN-Enabled Resource Orchestration for Industrial IoT in Collaborative Edge-Cloud Networks
2021
IEEE Access
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ACKNOWLEDGMENT This research work was supported by Academy of Finland, under the projects: 6G Flagship and DigiHealth Projects (grants 318927, 326291) and by the AI Enhanced Mobile Edge Computing project ...
, funded by the Future Makers program of Jane and Aatos Erkko Foundation and Technology Industries of Finland Centennial Foundation. ...
various resource management strategies in cloud, edge, and mist computing environments [47] . ...
doi:10.1109/access.2021.3105944
fatcat:fvysjtp54rdr7mzffmutqkxpcq
Machine Learning Methods for Reliable Resource Provisioning in Edge-Cloud Computing
2019
ACM Computing Surveys
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In this way, cloud computing is cost-efficient in application deployment and maintenance, and flexible in resource provisioning and in decoupling services from underlying technologies at both the client ...
Large-scale software systems are currently designed as distributed entities and deployed in cloud data centers. ...
-88749-R) and the Comunidad de Madrid grant EdgeData-CM (P2018/TSC-4499). ...
doi:10.1145/3341145
fatcat:vkzofhgipfhqtm2z2w5swivksy
Orchestrating BigData Analysis Workflows
2017
IEEE Cloud Computing
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ACKNOWLEDGEMENT The authors would like thank Mazin Yousif (EIC, IEEE Cloud Computing) and Ivona Brandic (TU Wien, Austria) for their valuable feedback, which significantly contributed to improving quality ...
frameworks (e.g., Hadoop Distributed File system ); v) server utilization, throughput, and energy-efficiency for Cloud resources; and (vi) network stability, throughput optimality, routing delays, fairness ...
frameworks and heterogeneous computing environments (Cloud + Edge). ...
doi:10.1109/mcc.2017.55
fatcat:i7xqytpawnhbveohyc2kfwnx3q
Resource Scheduling in Edge Computing: A Survey
[article]
2021
arXiv
pre-print
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The resource scheduling in edge computing, which is the key to the success of edge computing systems, has attracted increasing research interests. ...
Particularly, we introduce a unified model before summarizing the current works on resource scheduling from three research issues, including computation offloading, resource allocation, and resource provisioning ...
Similarly, Xu et al. in [121] studied the computation offloading problem for IoT-enabled cloud-edge computing, and they focused on how to allocate the computing resource for tasks to minimize the execution ...
arXiv:2108.08059v1
fatcat:oo4lepcn3rhdfafefw5lkq2lia
Reinforcement Learning-Empowered Mobile Edge Computing for 6G Edge Intelligence
[article]
2022
arXiv
pre-print
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Mobile edge computing (MEC) is considered a novel paradigm for computation-intensive and delay-sensitive tasks in fifth generation (5G) networks and beyond. ...
More importantly, associated with free mobility, dynamic channels, and distributed services, the MEC challenges that can be solved by different kinds of RL algorithms are identified, followed by how they ...
Considering the limited battery capacity and computational resources of UAVs, the cloud-edge computing framework was designed in the multi-UAV-enabled MEC system in [137] . ...
arXiv:2201.11410v4
fatcat:24igkq4kbrb2pjzwf3mf3n7qtq
CONFIGURATION MODELING AND DIAGNOSIS IN DATA CENTERS
2020
Figshare
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Task offloading, workload scheduling, application placement, and migration schemes used in Cloud/ Edge Computing largely pertain to network and computational resource allocation. ...
Chapter 2 studies the configuration problem with respect to resource allocation and performance-energy trade-off for energy efficient operation of data center networks. ...
doi:10.6084/m9.figshare.12616301
fatcat:hetr7siwh5bznm3s7z3m3o7rse
Resources Allocation for Distributed Systems: A Review
2021
Zenodo
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Resource allocation in a distributed system is the process of allocating the workload across multiple resources to optimize the required performance criteria. ...
Different techniques are used to manage resource allocation in such distributed systems. ...
A failure of a centralized reliable control point in many networked systems including cloud of cloud, edge clouds, and community networks among others. ...
doi:10.5281/zenodo.4462087
fatcat:co2led6hybgmjoeeagghdx3jjq
Two-Stage Robust Edge Service Placement and Sizing under Demand Uncertainty
[article]
2020
arXiv
pre-print
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Given the first-stage robust solution, the optimal resource and workload allocation decisions are computed in the second-stage after the uncertainty is revealed. ...
From the perspective of a service provider (SP), how to jointly optimize the service placement, sizing, and workload allocation decisions is an important and challenging problem, which becomes even more ...
The resource allocation and provisioning problem under uncertainty in cloud/edge computing has also been studied in recent literature. In [34] , T. ...
arXiv:2004.13218v2
fatcat:jv3prqg4cbbadlhkkqd4rhav4m
A Survey on Mobile Edge Computing: The Communication Perspective
2017
IEEE Communications Surveys and Tutorials
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This paper provides a comprehensive survey of the state-of-the-art MEC research with a focus on joint radio-and-computational resource management. ...
MEC promises dramatic reduction in latency and mobile energy consumption, tackling the key challenges for materializing 5G vision. ...
RESOURCE MANAGEMENT IN MEC SYSTEMS The joint radio-and-computational resource management plays a pivotal role in realizing energy-efficient and lowlatency MEC. ...
doi:10.1109/comst.2017.2745201
fatcat:rkgkslqx4bg6vp4ynidiuzqtga
A Survey on Mobile Edge Computing: The Communication Perspective
[article]
2017
arXiv
pre-print
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2017 pre-print arXiv:1701.01090v3 fatcat:fddwjvgj7zbfrdf4yuxin3l7xqOther Versions
This paper provides a comprehensive survey of the state-of-the-art MEC research with a focus on joint radio-and-computational resource management. ...
MEC promises dramatic reduction in latency and mobile energy consumption, tackling the key challenges for materializing 5G vision. ...
RESOURCE MANAGEMENT IN MEC SYSTEMS The joint radio-and-computational resource management plays a pivotal role in realizing energy-efficient and lowlatency MEC. ...
arXiv:1701.01090v4
fatcat:txpdpkp4irhibf6btbzvgth4n4
Sixth Edition of the IEEE JSAC Series on Network Softwarization and Enablers
2020
IEEE Journal on Selected Areas in Communications
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Edge and Fog Computing The tenth article focuses on the joint workload allocation and resource configuration problem in distributed cloud/edge computing. ...
The article firstly proposes a new energy consumption model for VMs with stochastic workloads, and both computation energy and reconfiguration energy are considered in the energy model. ...
doi:10.1109/jsac.2020.2986666
fatcat:qb663wjtefgszh4ydmogkri3ui
A Survey on Edge Performance Benchmarking
2021
ACM Computing Surveys
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Therefore, it is envisioned that a large-scale, geographically dispersed, and resource-rich distributed system will emerge and play a key role in the future Internet. ...
Edge computing is the next Internet frontier that will leverage computing resources located near users, sensors, and data stores to provide more responsive services. ...
time and energy efficiency (93) . ...
doi:10.1145/3444692
fatcat:75kmnweazzeppefekfyrxmemze
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