Name
Abstract | ||
|---|---|---|
Leveraging centralized and distributed load balancing algorithm to jointly schedule long and short flows attracts much attention since by classifying flows, they could reduce the completion times of flows without losing the scalability. However, existing centralized-distributed joint algorithms generally classify flows according to a static threshold and are unable to adapt to traffic dynamics. More importantly, through over investigation, the overheads of the controller caused by classifying flows and handling flows can be further reduced. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1016/j.comcom.2017.03.005 | Computer Communications |
Keywords | Field | DocType |
SDN,Datacenter,Load balancing | Control theory,Computer science,Load balancing (computing),Flow (psychology),Networking hardware,Computer network,Real-time computing,Functional testing (manufacturing),Traffic dynamics,Scalability,Overhead (business),Distributed computing | Journal |
Volume | ISSN | Citations |
106 | 0140-3664 | 4 |
PageRank | References | Authors |
0.44 | 18 | 6 |