Microbursts are traffic events that can cause severe performance degradation in a network. With the advent of modern big data applications, microburst events are not uncommon in a data center. Rather than attempting superficial ad-hoc solutions, such as providing large buffer switches/routers, under provisioning bandwidth, etc., this proposal provides a technique to identify an offending application causing a microburst based on queue-level thresholds. Once identified, appropriate remedial action(s) (e.g., Quality of Service (QoS) actions, security actions, etc.) can be performed by a network administrator
Traffic anomalies can create network congestion, so its prompt and accurate detection would allow ne...
DRILL is a micro load balancing algorithm designed to efficiently utilize the path redundancy in mod...
This study proposes a capable, scalable, and reliable edge-to-edge model for filtering malicious tra...
It may be difficult to identify root causes of protocol failures or degradations in application traf...
The data center has become the infrastructure of most Internet services, and its network carries dif...
The proliferation of distributed internet services has reaffirmed the need for reliable and high-per...
While numerous studies have examined the macro-level behav-ior of traffic in data center networks—ov...
Debugging faults in complex networks often requires cap-turing and analyzing traffic at the packet l...
Buffer sizing is a tricky task --- it depends on a large number of variables, ranging from congestio...
AbstractCongestion scenarios in Data Center Network (DCN) arise due to burst traffic and cause packe...
Today, data centers deal with fast growing data volumes. To deliver services, they deploy growing am...
This paper discusses the performance of traffic flow over Local Area Networks (LAN) utilizing buffer...
Modern datacenter network applications continue to demand ultra low latencies and very high throughp...
Active queue management (AQM) techniques are used to maintain congestion at network routers. Random ...
There is an increased demand for higher levels of network availability and reliability. Effective mo...
Traffic anomalies can create network congestion, so its prompt and accurate detection would allow ne...
DRILL is a micro load balancing algorithm designed to efficiently utilize the path redundancy in mod...
This study proposes a capable, scalable, and reliable edge-to-edge model for filtering malicious tra...
It may be difficult to identify root causes of protocol failures or degradations in application traf...
The data center has become the infrastructure of most Internet services, and its network carries dif...
The proliferation of distributed internet services has reaffirmed the need for reliable and high-per...
While numerous studies have examined the macro-level behav-ior of traffic in data center networks—ov...
Debugging faults in complex networks often requires cap-turing and analyzing traffic at the packet l...
Buffer sizing is a tricky task --- it depends on a large number of variables, ranging from congestio...
AbstractCongestion scenarios in Data Center Network (DCN) arise due to burst traffic and cause packe...
Today, data centers deal with fast growing data volumes. To deliver services, they deploy growing am...
This paper discusses the performance of traffic flow over Local Area Networks (LAN) utilizing buffer...
Modern datacenter network applications continue to demand ultra low latencies and very high throughp...
Active queue management (AQM) techniques are used to maintain congestion at network routers. Random ...
There is an increased demand for higher levels of network availability and reliability. Effective mo...
Traffic anomalies can create network congestion, so its prompt and accurate detection would allow ne...
DRILL is a micro load balancing algorithm designed to efficiently utilize the path redundancy in mod...
This study proposes a capable, scalable, and reliable edge-to-edge model for filtering malicious tra...
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