94 Hits in 8.4 sec

2020 Index IEEE Transactions on Parallel and Distributed Systems Vol. 31

2021 IEEE Transactions on Parallel and Distributed Systems  
., +, TPDS Jan. 2019 79-92 Resource-Aware Scheduling for Dependable Multicore Real-Time Systems: Utilization Bound and Partitioning Algorithm.  ...  Holistic Energy-Efficient Real-Time Scheduler for Mixed Stream and Batch Processing Workloads.  ... 
doi:10.1109/tpds.2020.3033655 fatcat:cpeatdjlpzhqdersvsk5nmzjkm

Special Issue on Artificial-Intelligence-Powered Edge Computing for Internet of Things

Lei Yang, Xu Chen, Samir M. Perlaza, Junshan Zhang
2020 IEEE Internet of Things Journal  
In the article "AWARE-CNN: Automated workflow for application-aware real-time edge acceleration of CNNs," Sanchez et al. presented AWARE-CNN accelerators for realtime execution of deep learning algorithms  ...  AWARE leverages the reconfigurability of FPGAs to create application-specific architectures customized to match the inherent dataflow of targeted deep neural networks and user-specified real-time requirements  ... 
doi:10.1109/jiot.2020.3019948 fatcat:mogalqnhnnaqpbxb7zivzdhvry

2020 Index IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems Vol. 39

2020 IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems  
., +, TCAD Oct. 2020 2925-2937 VisSched: An Auction-Based Scheduler for Vision Workloads on Heterogeneous Processors.  ...  ., +, TCAD Oct. 2020 3081-3092 Precedence-Aware Automated Competitive Analysis of Real-Time Scheduling.  ...  Entropy-Directed Scheduling for FPGA High-Level Synthesis. Shen, M., +, TCAD Oct. 2020 2588 -2601 FLASH: Fast, Parallel, and Accurate Simulator for HLS.  ... 
doi:10.1109/tcad.2021.3054536 fatcat:wsw3olpxzbeclenhex3f73qlw4

Table of contents

2020 2020 11th IEEE Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)  
An Efficient Accelerated Learning Algorithm for Tracking of Unknown, Spatially Correlated Signals in Ad-Hoc Wireless Sensor Networks Smart Real-Time Autonomous Navigation System Using Integration of MEMS-Based  ...  An FPGA-Based Implementation Method for Quadratic Spiking Neuron Model 0621 21.3 1570680454 A Machine Learning Approach to Temporal Traffic-Aware Energy- Efficient Cellular Networks 0628 21.4  ... 
doi:10.1109/uemcon51285.2020.9298057 fatcat:p4v3pn2m2zaaxdgobcaw5db76m

IEEE Access Special Section Editorial: Emerging Trends, Issues, and Challanges in Energy-Efficient Cloud Computing

Guangjie Han, Gangyong Jia, Jaime Lloret, Yuanguo Bi
2020 IEEE Access  
The cloud platform can predict the state of the dive line based on real-time data, limit the balance state parameters, reservoir water level and rainfall, etc., and then establish a numerical simulation  ...  In the article by Qureshi et al., ''Storage-tag-aware scheduler for Hadoop cluster,'' the authors present Storage-Tag-Aware Scheduler (STAS) that reduces processing latency by scheduling MapReduce jobs  ... 
doi:10.1109/access.2020.3001770 fatcat:agbvka652zhjfge47brz7vrwxm

IEEE Access Special Section Editorial: Security and Privacy in Emerging Decentralized Communication Environments

Xiaochun Cheng, Zheli Liu, Xiaojiang Du, Shui Yu, Leonardo Mostarda
2021 IEEE Access  
The article "A lightweight privacy-preserving protocol for VANETs based on secure outsourcing computing," by Wei et al., proposes an identity-based signature that achieves unforgeability against chosen-message  ...  Mobile-cloud architecture is emerging as 5G /6G mobile IoT devices are generating large volumes of data which need cloud infrastructure to process.  ...  The article ''Reliable access control for mobile cloud computing (MCC) with cache-aware scheduling,'' by Jamal et al., proposes an agent-based ABE access control method for the mobile cloud environment  ... 
doi:10.1109/access.2021.3075818 fatcat:7t3tgqarsndc5dq2gulr7hapzi

CloudLightning: a Self-Organized Self-Managed Heterogeneous Cloud

Huanhuan Xiong, Dapeng Dong, Christos Filelis-Papadopoulos, Gabriel G. Castañé, Theo Lynn, Dan C. Marinescu, John Morrison
2017 Proceedings of the 2017 Federated Conference on Computer Science and Information Systems  
A loosely-coupled, hierarchical, selfadapting management model, deployed across multiple layers, is used for heterogeneous resource management.  ...  The increasing heterogeneity of cloud resources, and the increasing diversity of services being deployed in cloud environments are leading to significant increases in the complexities of cloud resource  ...  The Hardware-and Network-Enhanced Software Systems for Cloud Computing (HARNESS) project [19] brings innovative and heterogeneous resources (such as FPGAs, GPUs) into cloud platforms by improving performance  ... 
doi:10.15439/2017f274 dblp:conf/fedcsis/XiongDFCLMM17 fatcat:6etgbwjpg5c6rc5f43pgvhlmvq

Resource Management in Fog/Edge Computing

Cheol-Ho Hong, Blesson Varghese
2019 ACM Computing Surveys  
[124] developed a unified edge and cloud platform for real-time data analytics.  ...  Heterogeneity-aware: Edge devices in a mobile cloud are heterogeneous at all levels.  ...  ACKNOWLEDGMENTS The authors are grateful to the anonymous reviewers for their valuable comments and suggestions.  ... 
doi:10.1145/3326066 fatcat:4hkvzb2djfaezipbhqwoncg5wu

2014 Index IEEE Transactions on Parallel and Distributed Systems Vol. 25

2015 IEEE Transactions on Parallel and Distributed Systems  
., +, TPDS May 2014 1166-1176 Job shop scheduling Parallel Real-Time Scheduling of DAGs.  ...  ., +, TPDS Dec. 2014 3295-3305 Cellular radio TAMES: A Truthful Double Auction for Multi-Demand Heterogeneous Spectrums.  ...  ., +, TPDS Aug. 2014 2840 -2850 Energy and Network Aware Workload Management for Sustainable Data Centers with Thermal Storage. 2030 -2042 Hyperbolic Utilization Bounds for Rate Monotonic Scheduling  ... 
doi:10.1109/tpds.2014.2371591 fatcat:qxyljogalrbfficryqjowgv3je

Simulating Resource Management across the Cloud-to-Thing Continuum: A Survey and Future Directions

Malika Bendechache, Sergej Svorobej, Patricia Takako Endo, Theo Lynn
2020 Future Internet  
This infrastructure is characterised by extreme heterogeneity, geographic distribution, and complexity, where the key performance indicators (KPIs) for the traditional model of cloud computing may no longer  ...  Simulation is a widely used technique in the development and evaluation of resource management mechanisms for cloud computing but is a relatively nascent research area for new C2T computing paradigms such  ...  They add a multi-resource scheduling and power consumption model which allows for a more accurate evaluation of power consumption in dynamic multi-resource scheduling for cloud computing.  ... 
doi:10.3390/fi12060095 fatcat:3fus7a5arncc3p4xgljm5lxium

Artificial Intelligence (AI)-Centric Management of Resources in Modern Distributed Computing Systems [article]

Shashikant Ilager, Rajeev Muralidhar, Rajkumar Buyya
2020 arXiv   pre-print
Finally, it provides a conceptual data-driven RMS model for DCS and presents the two real-time use cases (GPU frequency scaling and data centre resource management from Google Cloud and Microsoft Azure  ...  Contemporary Distributed Computing Systems (DCS) such as Cloud Data Centres are large scale, complex, heterogeneous, and distributed across multiple networks and geographical boundaries.  ...  Accordingly, we discuss two real-time AI-based RMS systems built by researchers at Google and Microsoft Azure Cloud.  ... 
arXiv:2006.05075v2 fatcat:tck54mz4yff3deesetflj34wke

Table of contents

2020 2020 Sixth International Conference on Parallel, Distributed and Grid Computing (PDGC)  
Scheduling Algorithm for Workflow Applications in Cloud Computing Environment 566-570 P111 1570675535 Synchronization in Parallel Programming Models for Heterogeneous Many-Cores 571-576 X001  ...  Wireless Sensor Networks 332-335 P066 1570674280 Novel Machine Learning Approach for Sentiment Analysis of Real Time Twitter Data with Apache Flume 336-340 P067 1570674490 An empirical study  ... 
doi:10.1109/pdgc50313.2020.9315770 fatcat:idng5upuj5fwfndjx76pk47tqa

Fog Computing Based on Machine Learning: A Review

Fady Esmat Fathel Samann, Adnan Mohsin Abdulazeez, Shavan Askar
2021 International Journal of Interactive Mobile Technologies  
This technology complements the cloud computing by providing processing power and storage to the edge of the network. However, it still suffers from performance and security issues.  ...  Thus, machine learning (ML) attracts attention for enabling FC to settle its issues.  ...  Different System-on-Chip Low-Power Devices (SoCs) platforms were tested for real-time data processing before the results were obtained on a cloud-based analysis platform.  ... 
doi:10.3991/ijim.v15i12.21313 fatcat:ztfuzrshq5eavduujcrhp3unhu

Resource Management in Fog/Edge Computing: A Survey [article]

Cheol-Ho Hong, Blesson Varghese
2018 arXiv   pre-print
Fog/edge resources are typically resource-constrained, heterogeneous, and dynamic compared to the cloud, thereby making resource management an important challenge that needs to be addressed.  ...  Contrary to using distant and centralized cloud data center resources, employing decentralized resources at the edge of a network for processing data closer to user devices, such as smartphones and tablets  ...  [140] developed a unified edge and cloud platform for real-time data analytics.  ... 
arXiv:1810.00305v1 fatcat:erskczbjtjh5jigiu2dy4jgmdu

A Survey of State-of-the-art on Edge Computing: Theoretical Models, Technologies, Directions, and Development Paths

Bin Liu, Zhongqiang Luo, Hongbo Chen, Chengjie Li
2022 IEEE Access  
We hope that this survey report will attract much more attention, stimulate fruitful discussions, and provide ideas and useful guidance for further research on the theoretical models, technologies, directions  ...  not meet the scenarios with high real-time requirements and QoE for users.  ...  to respond to real-time events.  ... 
doi:10.1109/access.2022.3176106 fatcat:7l3p2ug5dfb6pl6qvw7liuzayu
« Previous Showing results 1 — 15 out of 94 results