Performance evaluation metrics for cloud, fog and edge computing: A review, taxonomy, benchmarks and standards for future research
Optimization is an inseparable part of Cloud computing, particularly with the emergence of
Fog and Edge paradigms. Not only these emerging paradigms demand reevaluating cloud …
Fog and Edge paradigms. Not only these emerging paradigms demand reevaluating cloud …
Rethinking data center networks: Machine learning enables network intelligence
To support the needs of ever-growing cloud-based services, the number of servers and
network devices in data centers is increasing exponentially, which in turn results in high …
network devices in data centers is increasing exponentially, which in turn results in high …
Machine learning empowered intelligent data center networking: A survey
To support the needs of ever-growing cloud-based services, the number of servers and
network devices in data centers is increasing exponentially, which in turn results in high …
network devices in data centers is increasing exponentially, which in turn results in high …
Fast and Efficient Scaling for Microservices with SurgeGuard
A Ghosh, NJ Yadwadkar, M Erez - … International Conference for …, 2024 - ieeexplore.ieee.org
The microservice architecture is increasingly popular for flexible, large-scale online
applications. However, existing resource management mechanisms incur high latency in …
applications. However, existing resource management mechanisms incur high latency in …
Optical Data Center Networking: A Comprehensive Review on Traffic, Switching, Bandwidth Allocation, and Challenges
PA Baziana - IEEE Access, 2024 - ieeexplore.ieee.org
The accelerated growth of data traffic in data centers (DCs) globally is driven by the
dominance of multiple emerging data-intensive applications hosted by edge/cloud DCs …
dominance of multiple emerging data-intensive applications hosted by edge/cloud DCs …
QoS Perception for Cloud Databases: Necessity, Trends, and Challenges
The advantages of resource elasticity and proactive data backup in cloud databases have
attracted a large number of users to consider deploying their IT systems in the cloud. Factors …
attracted a large number of users to consider deploying their IT systems in the cloud. Factors …
Machine learning empowered intelligent data center networking
Abstract Machine learning has been widely studied and practiced in data center networks,
and a large number of achievements have been made. In this chapter, we will review …
and a large number of achievements have been made. In this chapter, we will review …
Seec: semantic vector federation across edge computing environments
Semantic vector embedding techniques have proven useful in learning semantic
representations of data across multiple domains. A key application enabled by such …
representations of data across multiple domains. A key application enabled by such …
Deep Reinforcement Learning Scheduling of Container Cloud Workflow Considering Invalid Time-Consuming and Reliability
Y Wu, M Gao, Y Wang, L Duan - 2022 5th International …, 2022 - ieeexplore.ieee.org
Cloud computing workflow scheduling problem in now hundreds of thousands, millions of
sensors are distributed in the edge cloud, information is summarized to the proximal small …
sensors are distributed in the edge cloud, information is summarized to the proximal small …
Individualized precise scheduling strategy based on program's runtime characteristic for workload consolidation
L Wang, T Huang, S Geng - 2022 - researchsquare.com
In data centers, workload consolidation is the common method to improve resource
utilization. However, efficient workload consolidation faces challenges from two aspects: the …
utilization. However, efficient workload consolidation faces challenges from two aspects: the …