Generic and automatic address configuration for data center networks

Chen, Kai; Guo, Chuanxiong; Wu, Haitao; Yuan, Jian; Zhang, Feng; Chen, Yan; Lu, Songwu; Wu, Wenfei

doi:10.1145/1851182.1851190

Cited by 46 publications

(16 citation statements)

References 28 publications

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“…Hosts in DCNs usually have IP addresses corresponding to their topological locations [7]. For example, in a fat tree based DCN, hosts in the same pod usually share the same subnet address [21].…”

Section: A Intra-cluster Processingmentioning

confidence: 99%

Joint Host-Network Optimization for Energy-Efficient Data Center Networking

Jiang

Cheocherngngarn

Levy

et al. 2013

2013 IEEE 27th International Symposium on Parallel and Distributed Processing

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Abstract-Data centers consume significant amounts of energy. As severs become more energy efficient with various energy saving techniques, the data center network (DCN) has been accounting for 20% or more of the energy consumed by the entire data center. While DCNs are typically provisioned with full bisection bandwidth, DCN traffic demonstrates fluctuating patterns. The objective of this work is to improve the energy efficiency of DCNs during off-peak traffic time by powering off idle devices. Although there exist a number of energy optimization solutions for DCNs, they consider only either the hosts or network, but not both. In this paper, we propose a joint optimization scheme that simultaneously optimizes virtual machine (VM) placement and network flow routing to maximize energy savings, and we also build an OpenFlow based prototype to experimentally demonstrate the effectiveness of our design. First, we formulate the joint optimization problem as an integer linear program, but it is not a practical solution due to high complexity. To practically and effectively combine host and network based optimization, we present a unified representation method that converts the VM placement problem to a routing problem. In addition, to accelerate processing the large number of servers and an even larger number of VMs, we describe a parallelization approach that divides the DCN into clusters for parallel processing. Further, to quickly find efficient paths for flows, we propose a fast topology oriented multipath routing algorithm that uses depth-first search to quickly traverse between hierarchical switch layers and uses the best-fit criterion to maximize flow consolidation. Finally, we have conducted extensive simulations and experiments to compare our design with existing ones. The simulation and experiment results fully demonstrate that our design outperforms existing host-or network-only optimization solutions, and well approximates the ideal linear program.

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Section: A Intra-cluster Processingmentioning

confidence: 99%

Joint Host-Network Optimization for Energy-Efficient Data Center Networking

Jiang

Cheocherngngarn

Levy

et al. 2013

2013 IEEE 27th International Symposium on Parallel and Distributed Processing

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“…Chen et al [23] proposed DAC: a generic and automatic Data center Address Configuration system. DAC automates the assignment of IDs to network devices.…”

Section: Middle-boxes/appliancesmentioning

confidence: 99%

Survey on Data Center Networking Technologies

Kiriha¹,

Nishihara²

2013

IEICE Trans. Commun.

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“…Recently, some methods have been proposed, such as DAC [5] and ETAC [6]. When there is no malfunction in physical graph, DAC maps the logical IDs to the device IDs quickly.…”

Section: Introductionmentioning

confidence: 99%

GA-MAP: An Error Tolerant Address Mapping Method in Data Center Networks Based on Improved Genetic Algorithm

Deng¹,

Wang²,

Zhang³

et al. 2015

IEICE Trans. Inf. & Syst.

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SUMMARY Address configuration is a key problem in data center networks. The core issue of automatic address configuration is assigning logical addresses to the physical network according to a blueprint, namely logical-to-device ID mapping, which can be formulated as a graph isomorphic problem and is hard. Recently years, some work has been proposed for this problem, such as DAC and ETAC. DAC adopts a sub-graph isomorphic algorithm. By leveraging the structure characteristic of data center network, DAC can finish the mapping process quickly when there is no malfunction. However, in the presence of any malfunctions, DAC need human effort to correct these malfunctions and thus is time-consuming. ETAC improves on DAC and can finish mapping even in the presence of malfunctions. However, ETAC also suffers from some robustness and efficiency problems. In this paper, we present GA-MAP, a data center networks address mapping algorithm based on genetic algorithm. By intelligently leveraging the structure characteristic of data center networks and the global search characteristic of genetic algorithm, GA-MAP can solve the address mapping problem quickly. Moreover, GA-MAP can even finish address mapping when physical network involved in malfunctions, making it more robust than ETAC. We evaluate GA-MAP via extensive simulation in several of aspects, including computation time, error-tolerance, convergence characteristic and the influence of population size. The simulation results demonstrate that GA-MAP is effective for data center addresses mapping.

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Generic and automatic address configuration for data center networks

Cited by 46 publications

References 28 publications

Joint Host-Network Optimization for Energy-Efficient Data Center Networking

Joint Host-Network Optimization for Energy-Efficient Data Center Networking

Survey on Data Center Networking Technologies

GA-MAP: An Error Tolerant Address Mapping Method in Data Center Networks Based on Improved Genetic Algorithm

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