Scalable Data Center Network Architecture With Distributed Placement of Optical Switches and Racks

Xiao, Jie; Wu, Bin; Jiang, Xiaohong; Pattavina, Achille; Hong, Wen; Zhang, Lei

doi:10.1364/jocn.6.000270

Cited by 21 publications

(6 citation statements)

References 27 publications

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“…e tradeoff between transport overhead, storage overhead, and user access performance [6][7][8] enables to gain maximum performance with minimal overhead. Based on this, the linear programming method is adopted to minimize the system cost [9][10][11][12] and reduce user response time and network load [13] by adding the consideration of network overhead. An overhead tradeoff layout solution can result in a good performance of load balance, but the transfer time is not optimal due to the damage of data dependency.…”

Section: Research Progress Of Data Layout In Storage Systemmentioning

confidence: 99%

Network-Aware Data Placement Strategy in Storage Cluster System

Shao

Song

Bian

et al. 2020

Mathematical Problems in Engineering

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The dramatic increase of storage devices in distributed storage cluster system and the inherent characteristics of distributed deployment mode make network resources become one of the bottlenecks of data storage process. By analyzing the functional characteristics of data flow transmission of the components of the storage system, the network topology structure of the storage system is constructed, and the evaluation index of node flow load is put forward based on the degree centrality and the betweenness centrality theory of the network to explore the network topology and real-time flow characteristics. According to the evaluation index of node flow load, a network-aware data layout scheme is proposed. By balancing the flow load of bottleneck link, congestion and transmission delay can be reduced to further shorten the total task execution time and improve the efficiency of data writing.

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Section: Research Progress Of Data Layout In Storage Systemmentioning

confidence: 99%

Network-Aware Data Placement Strategy in Storage Cluster System

Shao

Song

Bian

et al. 2020

Mathematical Problems in Engineering

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“…Efficient topologies and routing algorithms [9–14] are required to manage the increase in traffic within the optical interconnects of DC networks. A non‐blocking Spanke‐type scalable network with distributed control was proposed in [8].…”

Section: Introductionmentioning

confidence: 99%

Performance analysis of torus optical interconnect with data center traffic

Sharma

Gopalan

2020

ETRI Journal

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Two‐dimensional torus network nodes are typically interconnected using XY routing algorithm for transmitting a packet from a source node to a destination node. In XY routing, if all the paths are used efficiently, the throughput and latency can be improved. In this paper, to utilize all the paths efficiently, we propose a novel binary optical routing algorithm (BORA) to improve the throughput and latency. The throughput is calculated according to the injection rate and number of packets received at the destination. The XY routing algorithm and proposed BORA are implemented using objective modular network testbed in C++ simulation software and the results are analyzed and compared. In this paper, the simulation results show that the network latency reduces to 50% while using the proposed algorithm; moreover, the throughput is also improved.

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“…[1][2][3] Unlike traditional networks, SDN decouples control and data planes (see Figure 1) and provides a more structured software development environment. This is achieved by using a set of centralized controllers [5][6][7][8][9][10] and thus brings about many advantages such as high flexibility, programmability, vendor independence, and so on. 4 Concretely, SDN allows applications to use abstracted network resources in a programmable manner without concerning underlying network infrastructure.…”

Section: Introductionmentioning

confidence: 99%

“…Concretely, SDN allows applications to use abstracted network resources in a programmable manner without concerning underlying network infrastructure. This is achieved by using a set of centralized controllers and thus brings about many advantages such as high flexibility, programmability, vendor independence, and so on.…”

mentioning

confidence: 99%

Scalable SDN architecture with distributed placement of controllers for WAN

Zhao

2017

Concurrency and Computation

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By separating control plane from data plane, software-defined network (SDN) adopts centralized controllers to manage data flows in the network. Nevertheless, the rapid growth of network service traffic requires a large number of controllers, reducing network performance due to the scalability constraint. Therefore, we consider distributed placement of controllers in wide-area network to construct a scalable SDN architecture, by taking service traffics, traffic propagation delay, and load balancing into account. Specifically, we first partition the network into several small sections (named SDN domains) and then place the least amount of controllers to a proper node in each domain. The architecture provides a control channel to deliver requested messages for each SDN domain, so it reduces the link delay (which is assumed to be proportional to the physical length of the link) between switches and SDN controllers. Unfortunately, it also introduces extra latency among controller sets at different SDN domain. Accordingly, we formulate an integer linear program to optimize network cost and performance by considering all those conflicting factors and propose an efficient heuristic algorithm called distributed SDN placement to solve the problem. Simulation results confirm that our proposed heuristic distributed SDN placement can achieve suboptimal solutions as compared with the integer linear program results. KEYWORDScontroller sets (CSs), integer linear program (ILP), placement, scalability, software-defined network (SDN)

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Scalable Data Center Network Architecture With Distributed Placement of Optical Switches and Racks

Cited by 21 publications

References 27 publications

Network-Aware Data Placement Strategy in Storage Cluster System

Network-Aware Data Placement Strategy in Storage Cluster System

Performance analysis of torus optical interconnect with data center traffic

Scalable SDN architecture with distributed placement of controllers for WAN

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