SWAN: End-to-end orchestration for cloud network and WAN

Qian, Haiyang; Huang, Xin; Chen, Clark

doi:10.1109/cloudnet.2013.6710584

Cited by 5 publications

(2 citation statements)

References 13 publications

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“…In this case, we consider applying sampling techniques [26][27][28][29][30][31][32][33][34] to perform fast and accurate estimation for it. Last but not least, we are interested in applying our digraph spectral graph method to detect node and link failures in large-scale cloud computing environments [35][36][37][38].…”

Section: Resultsmentioning

confidence: 99%

Digraph Spectral Clustering with Applications in Distributed Sensor Validation

Zhai

2014

International Journal of Distributed Sensor Networks

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In various sensor networks, the performances of sensors vary significantly over time, due to the changes of surrounding environment, device hardware, and so forth. Hence, monitoring the status is essential in sensor network maintenance. Spectral clustering has been employed as an enabling technique to solve this problem. However, the traditional spectral clustering is developed for undirected graph, and the naive generalization for directed graph by symmetrization of the adjacency matrix will lead to loss of network information, and thus cannot efficiently detect bad sensor nodes while applying it for sensor validation. In this paper, we develop a generalized digraph spectral clustering method. Instead of simply symmetrizing the adjacency matrix, our method takes into consideration the network circulation while clustering the sensors. The extensive simulation results demonstrate that our method outperforms the traditional spectral clustering method by increasing the bad detection ratio from 19% to 41%.

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Section: Resultsmentioning

confidence: 99%

Digraph Spectral Clustering with Applications in Distributed Sensor Validation

Zhai

2014

International Journal of Distributed Sensor Networks

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“…Specifically, the OpenDaylight [214] SDN controller has added a LISP-based mapping service. SDN can preserve VM connectivity during intra and inter data center VM migration [182], [215]- [221] by inserting proper packet forwarding rules in switching devices to direct traffic to the new VM location.…”

Section: G Sdn For Cloud Computingmentioning

confidence: 99%

A Survey on Software-Defined Networking

Wei

Wen

Foh

et al. 2015

IEEE Commun. Surv. Tutorials

883

403

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Emerging mega-trends (e.g., mobile, social, cloud, and big data) in information and communication technologies (ICT) are commanding new challenges to future Internet, for which ubiquitous accessibility, high bandwidth, and dynamic management are crucial. However, traditional approaches based on manual configuration of proprietary devices are cumbersome and error-prone, and they cannot fully utilize the capability of physical network infrastructure. Recently, software-defined networking (SDN) has been touted as one of the most promising solutions for future Internet. SDN is characterized by its two distinguished features, including decoupling the control plane from the data plane and providing programmability for network application development. As a result, SDN is positioned to provide more efficient configuration, better performance, and higher flexibility to accommodate innovative network designs. This paper surveys latest developments in this active research area of SDN. We first present a generally accepted definition for SDN with the aforementioned two characteristic features and potential benefits of SDN. We then dwell on its three-layer architecture, including an infrastructure layer, a control layer, and an application layer, and substantiate each layer with existing research efforts and its related research areas. We follow that with an overview of the de facto SDN implementation (i.e., OpenFlow). Finally, we conclude this survey paper with some suggested open research challenges.

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Extending tenant networks across geographically distributed clouds

Park

Yoon

2014

2014 International Conference on Information and Communication Technology Convergence (ICTC)

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SWAN: End-to-end orchestration for cloud network and WAN

Cited by 5 publications

References 13 publications

Digraph Spectral Clustering with Applications in Distributed Sensor Validation

Digraph Spectral Clustering with Applications in Distributed Sensor Validation

A Survey on Software-Defined Networking

Extending tenant networks across geographically distributed clouds

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