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Load balancing in data center networks: A survey
Data center networks usually employ the scale-out model to provide high bisection
bandwidth for applications. A large amount of data is required to be transferred frequently …
bandwidth for applications. A large amount of data is required to be transferred frequently …
Networking for big data: A survey
Complementary to the fancy big data applications, networking for big data is an
indispensable supporting platform for these applications in practice. This emerging research …
indispensable supporting platform for these applications in practice. This emerging research …
Efficient coflow scheduling without prior knowledge
Inter-coflow scheduling improves application-level communication performance in data-
parallel clusters. However, existing efficient schedulers require a priori coflow information …
parallel clusters. However, existing efficient schedulers require a priori coflow information …
CODA: Toward automatically identifying and scheduling coflows in the dark
Leveraging application-level requirements using coflows has recently been shown to
improve application-level communication performance in data-parallel clusters. However …
improve application-level communication performance in data-parallel clusters. However …
Sincronia: Near-optimal network design for coflows
We present Sincronia, a near-optimal network design for coflows that can be implemented
on top on any transport layer (for flows) that supports priority scheduling. Sincronia achieves …
on top on any transport layer (for flows) that supports priority scheduling. Sincronia achieves …
Loom: Flexible and efficient {NIC} packet scheduling
In multi-tenant cloud data centers, operators need to ensure that competing tenants and
applications are isolated from each other and fairly share limited network resources. With …
applications are isolated from each other and fairly share limited network resources. With …
Network-aware locality scheduling for distributed data operators in data centers
Large data centers are currently the mainstream infrastructures for big data processing. As
one of the most fundamental tasks in these environments, the efficient execution of …
one of the most fundamental tasks in these environments, the efficient execution of …
[PDF][PDF] Deepweave: Accelerating job completion time with deep reinforcement learning-based coflow scheduling
To improve the processing efficiency of jobs in distributed computing, the concept of coflow
is proposed. A coflow is a collection of flows that are semantically correlated in a multi-stage …
is proposed. A coflow is a collection of flows that are semantically correlated in a multi-stage …
Flexible cyclic queuing and forwarding for time-sensitive software-defined networks
Time-Sensitive Networking (TSN) is emerging to support critical real-time applications in
Industry 4.0. Recent proposals leverage Cyclic Queuing and Forwarding (CQF) to achieve …
Industry 4.0. Recent proposals leverage Cyclic Queuing and Forwarding (CQF) to achieve …
Cluster frameworks for efficient scheduling and resource allocation in data center networks: A survey
Data centers are widely used for big data analytics, which often involve data-parallel jobs,
including query and web service. Meanwhile, cluster frameworks are rapidly developed for …
including query and web service. Meanwhile, cluster frameworks are rapidly developed for …