Resilient overlay networks

AndersenDavid,; BalakrishnanHari,; KaashoekFrans,; MorrisRobert,

doi:10.1145/502059.502048

Cited by 241 publications

(76 citation statements)

References 20 publications

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“…An overlay network is created by establishing a new virtual topology over one or more existing physical networks. The early Internet (ARPANet) began as an overlay on the existing telephone network [3].…”

Section: Virtual Networkmentioning

confidence: 99%

Mina

Jerkins

2012

Proceedings of the 50th Annual Southeast Regional Conference

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Connecting geographically dispersed sites by layer two virtual private networks is a widely deployed, cost effective, and reliable technology. The key feature of layer two virtual private networks is confidentiality. However, L2 VPNs are being rapidly replaced by layer three virtual networks as common carriers expand the roles of their shared IP networks. The recent increase of interest in L3 virtual networks has led to renewed interest and new questions concerning their privacy.We designate virtual network nodes that are undesirable as extrinsic. In this paper we propose a novel algorithm, Message Induced Network Appraisal (MINA), for detecting the presence of extrinsic nodes in virtual networks. MINA is inspired by Kleinberg's HITS algorithm for ranking web pages. The generalization of a HITS derived algorithm to detecting the presence of extrinsic nodes in virtual networks is novel.Our MINA algorithm constructs the communication graph induced by message exchange, scores the participating nodes to identify mutual nodes, and detects the presence of extrinsic nodes. Using the MINA algorithm, network users are presented with a useful indicator about the confidentiality of their L3 virtual network. In this paper we describe MINA and demonstrate that our method reliably detects the presence of extrinsic nodes in L3 virtual networks.

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Section: Virtual Networkmentioning

confidence: 99%

Mina

Jerkins

2012

Proceedings of the 50th Annual Southeast Regional Conference

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“…Our approach may help end-hosts (or intermediate systems) to identify pieces of networks, opening the way to a wide variety of research studies that aim to provide greater control over the entire end-to-end network paths. Some scenarios could be the following: adaptive and network-aware applications [41][42][43][44], reactive and intelligent routing [45,46], overlay networks [47][48][49][50], source-routing [51].…”

Section: Related Workmentioning

confidence: 99%

An approach to the identification of network elements composing heterogeneous end-to-end paths

2008

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a b s t r a c tToday's networks are becoming increasingly complex and the ability to effectively and efficiently operate and manage them is ever more challenging. Ways to provide end-to-end Quality of Service have to cope with the increasing heterogeneity of these networks, which is due to the several actors of current network scenarios, from access networks to end-user devices, from protocols to applications and operating systems. Exploiting such heterogeneity, in this paper we present an approach to the identification of each element composing an end-to-end path. Such identification is useful in several situations. For instance, it can improve the performance of adaptive and network-aware applications, it can help intelligent routing approaches, and it can be used in network and service overlay scenarios. Our approach, based on Bayesian classifiers, utilizes the measurements and off-line processing of three QoS parameters, that are delay, jitter, and packet loss. To illustrate the capabilities of our proposal, we present the results of a large set of experimentations performed with both different sets of features and different sets of QoS parameters. Using measures related to various time periods, in which the considered paths presented diverse characteristics, we show that a blind identification of network bricks is possible and that its results present a good degree of generalizability.

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“…Disruption tolerance in RONs has been a challenge for the research community in recent years [3]. Many overlay networks propose self-organization and self-healing techniques, so communications can continue after failures.…”

Section: Introductionmentioning

confidence: 99%

“…A RON is able to detect and recover from issues affecting its resilience within a short period of time [3]. RONs are mainly based on self-healing, self-organization and selfoptimization mechanisms detecting network disruptions, recovering from them and dynamically discovering optimal network paths among members [19].…”

Section: Introductionmentioning

confidence: 99%