GENI: A federated testbed for innovative network experiments

Berman, Mark; Chase, Jeffrey S.; Landweber, Lawrence H.; Nakao, Akihiro; Ott, Maximilian; Raychaudhuri, Dipankar; Ricci, Robert; Seskar, Ivan

doi:10.1016/j.bjp.2013.12.037

Cited by 494 publications

(202 citation statements)

References 34 publications

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“…GENI [21] is a fast growing distributed large scale testbed providing virtualized networking environment in three aspects. First, computing and storage resources are virtualized using all three possible approaches (i.e., container-based, Xen and KVM).…”

Section: Virtualized Networking Testbedmentioning

confidence: 99%

Dynamic virtual network restoration with optimal standby virtual router selection

Medhi

2016

NOMS 2016 - 2016 IEEE/IFIP Network Operations and Management Symposium

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Network virtualization technologies allow service providers to request partitioned, QoS guaranteed and fault-tolerant virtual networks provisioned by the substrate network provider (i.e., physical infrastructure provider). A virtualized networking environment (VNE) has common features such as partition, flexibility, etc., but fault-tolerance requires additional efforts to provide survivability against failures on either virtual networks or the substrate network.Two common survivability paradigms are protection (proactive) and restoration (reactive). In the protection scheme, the substrate network provider (SNP) allocates redundant resources (e.g., nodes, paths, bandwidths, etc) to protect against potential failures in the VNE. In the restoration scheme, the SNP dynamically allocates resources to restore the networks, and it usually occurs after the failure is detected.iii In this dissertation, we design a restoration scheme that can be dynamically implemented in a centralized manner by an SNP to achieve survivability against node failures in the VNE. The proposed restoration scheme is designed to be integrated with a protection scheme, where the SNP allocates spare virtual routers (VRs) as standbys for the virtual networks (VN) and they are ready to serve in the restoration scheme after a node failure has been identified. These standby virtual routers (S-VR) are reserved as a sharedbackup for any single node failure, and during the restoration procedure, one of the S-VR will be selected to replace the failed VR. In this work, we present an optimal S-VR selection approach to simultaneously restore multiple VNs affected by failed VRs, where these VRs may be affected by failures within themselves or at their substrate host (i.e., power outage, hardware failures, maintenance, etc.). Furthermore, the restoration scheme is embedded into a dynamic reconfiguration scheme (DRS), so that the affected VNs can be dynamically restored by a centralized virtual network manager (VNM).We first introduce a dynamic reconfiguration scheme (DRS) against node failures in a VNE, and then present an experimental study by implementing this DRS over a realistic VNE using GpENI testbed. For this experimental study, we ran the DRS to restore one VN with a single-VR failure, and the results showed that with a proper S-VR selection, the performance of the affected VN could be well restored. Next, we proposed an Mixed-Integer Linear Programming (MILP) model with dual-goals to optimally select S-VRs to restore all VNs affected by VR failures while load balancing. We also present a iv heuristic algorithm based on the model. By considering a number of factors, we present numerical studies to show how the optimal selection is affected. The results show that the proposed heuristic's performance is close to the optimization model when there were sufficient standby virtual routers for each virtual network and the substrate nodes have the capability to support multiple standby virtual routers to be in service simultaneously.Finally, we presen...

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Section: Virtualized Networking Testbedmentioning

confidence: 99%

Dynamic virtual network restoration with optimal standby virtual router selection

Medhi

2016

NOMS 2016 - 2016 IEEE/IFIP Network Operations and Management Symposium

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“…For this reason, the Global Environment for Network Innovation (GENI) at the U.S. National Science Foundation provides researchers the network resources, scale, realism, and control necessary to deploy prototypes and evaluate new networking architectures [30]. To date, the OpenFlow specification 1.1.0 supports MPLS.…”

Section: Background and Related Workmentioning

confidence: 99%

Using GENI for experimental evaluation of Software Defined Networking in smart grids

et al. 2014

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The North American Electric Reliability Corporation (NERC) envisions a smart grid that aggressively explores advance communication network solutions to facilitate real-time monitoring and dynamic control of the bulk electric power system. At the distribution level, the smart grid integrates renewable generation and energy storage mechanisms to improve the reliability of the grid. Furthermore, dynamic pricing and demand management provide customers an avenue to interact with the power system to determine the electricity usage that best satisfies their lifestyle. At the transmission level, efficient communication and a highly automated architecture provide visibility in the power system and as a result, faults are mitigated faster than they can propagate. However, such higher levels of reliability and efficiency rest on the supporting communication infrastructure. To date, utility companies are moving towards Multiprotocol Label Switching (MPLS) because it supports traffic engineering and virtual private networks (VPNs). Furthermore, it provides Quality of Service (QoS) guarantees and fail-over mechanisms in addition to meeting the requirement of non-routability as stipulated by NERC. However, these benefits come at a cost for the infrastructure that supports the full MPLS specification. With this realization and given a two week implementation and deployment window in GENI, we explore the modularity and flexibility provided by the low cost OpenFlow Software Defined Networking (SDN) solution. In particular, we use OpenFlow to provide 1.) automatic fail-over mechanisms, 2.) a load balancing, and 3.) Quality of Service guarantees: all essential mechanisms for smart grid networks.

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“…To address such security threats, the United States, European Union, Japan, Korea, and other major advanced countries have undertaken research and development projects on the future Internet that can overcome the constraints of the existing Internet, guarantee transmission quality and mobility, and complete security so that it can be applied to new convergence services [4][5][6].…”

Section: Introductionmentioning

confidence: 99%

HB-DIPM: Human Behavior Analysis-Based Malware Detection and Intrusion Prevention Model in the Future Internet

2016

J Inf Process Syst

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As interest in the Internet increases, related technologies are also quickly progressing. As smart devices become more widely used, interest is growing in words are missing here like "improving the" or "figuring out how to use the" future Internet to resolve the fundamental issues of transmission quality and security. The future Internet is being studied to improve the limits of existing Internet structures and to reflect new requirements. In particular, research on words are missing here like "finding new forms of" or "applying new forms of" or "studying various types of" or "finding ways to provide more" reliable communication to connect the Internet to various services is in demand. In this paper, we analyze the security threats caused by malicious activities in the future Internet and propose a human behavior analysis-based security service model for malware detection and intrusion prevention to provide more reliable communication. Our proposed service model provides high reliability services by responding to security threats by detecting various malware intrusions and protocol authentications based on human behavior.

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GENI: A federated testbed for innovative network experiments

Cited by 494 publications

References 34 publications

Dynamic virtual network restoration with optimal standby virtual router selection

Dynamic virtual network restoration with optimal standby virtual router selection

Using GENI for experimental evaluation of Software Defined Networking in smart grids

HB-DIPM: Human Behavior Analysis-Based Malware Detection and Intrusion Prevention Model in the Future Internet

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