Oversubscription Bounded Multicast Scheduling in Fat-Tree Data Center Networks

2013 ◽  
Author(s):  
Zhiyang Guo ◽  
Jun Duan ◽  
Yuanyuan Yang
Keyword(s):  
Data Center ◽  
Data Center Networks ◽  
Tree Data ◽  
Multicast Scheduling

BEEP: Balancing Energy, Redundancy, and Performance in Fat-Tree Data Center Networks

2017 ◽  
Vol 21 (4) ◽  
pp. 44-53 ◽  
Author(s):  
Antonio Cleber de S. Araujo ◽  
Leobino N. Sampaio ◽  
Artur Ziviani
Keyword(s):  
Data Center ◽  
Data Center Networks ◽  
Balancing Energy ◽  
Tree Data ◽  
And Performance

Dynamic Big-Data Broadcast in Fat-Tree Data Center Networks With Mobile IoT Devices

2019 ◽  
Vol 13 (3) ◽  
pp. 2898-2905 ◽  
Author(s):  
Sudip Misra ◽  
Ayan Mondal ◽  
Swetha Khajjayam
Keyword(s):  
Big Data ◽  
Data Center ◽  
Data Center Networks ◽  
Data Broadcast ◽  
Tree Data ◽  
Iot Devices

scholarly journals Application and Analysis of Multicast Blocking Modelling in Fat-Tree Data Center Networks

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-12
Author(s):  
Guozhi Li ◽  
Songtao Guo ◽  
Guiyan Liu ◽  
Yuanyuan Yang
Keyword(s):  
Data Center ◽  
Network Performance ◽  
Blocking Probability ◽  
Scheduling Algorithm ◽  
Operation Time ◽  
Data Center Networks ◽  
Scheduling Strategy ◽  
Traffic Efficiency ◽  
Network Bandwidth ◽  
Multicast Scheduling

Multicast can improve network performance by eliminating unnecessary duplicated flows in the data center networks (DCNs). Thus it can significantly save network bandwidth. However, the network multicast blocking may cause the retransmission of a large number of data packets and seriously influence the traffic efficiency in data center networks, especially in the fat-tree DCNs with multirooted tree structure. In this paper, we build a multicast blocking model and apply it to solve the problem of network blocking in the fat-tree DCNs. Furthermore, we propose a novel multicast scheduling strategy. In the scheduling strategy, we select the uplink connecting to available core switch whose remaining bandwidth is close to and greater than the three times of bandwidth multicast requests so as to reduce the operation time of the proposed algorithm. Then the blocking probability of downlink in the next time-slot is calculated in multicast subnetwork by using Markov chains theory. With the obtained probability, we select the optimal downlink based on the available core switch. In addition, theoretical analysis shows that the multicast scheduling algorithm has close to zero network blocking probability as well as lower time complexity. Simulation results verify the effectiveness of our proposed multicast scheduling algorithm.

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