Virtual landmarks for the internet

Tang, Liying; Crovella, Mark

doi:10.1145/948221.948223

Cited by 40 publications

(39 citation statements)

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“…We can use the upper and lower bounds of the triangle inequality of the distances to these landmarks [19], [20], [21] to predict the distance intervals for two nodes. Unfortunately, the intervals have approximation errors, since the Internet delay space contains TIVs.…”

Section: A Background and Related Workmentioning

confidence: 99%

A relative coordinate based distributed sparse-preserving matrix factorization approach towards self-stabilizing network location service - Withdrawn

Wang²,

Peng³

et al. 2024

IEEE Trans. Parallel Distrib. Syst.

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The network location service that efficiently obtains the network latency among large-scale nodes has been a hot topic during the last decade. With increasing numbers of participating nodes, the network location service has to balance the accuracy and the scalability. The network-coordinate methods scale well by embedding the pairwise latency into a low-dimensional coordinate system. The prediction errors are iteratively optimized by adjusting the coordinates with respect to neighbors. Unfortunately, the optimization process is vulnerable to the inaccurate coordinates, leading to destabilized positions. In this paper, we propose RMF, a relative coordinate based distributed sparsepreserving matrix-factorization method to provide guaranteed stability for the coordinate system. In RMF, each node maintains a low-rank squared matrix that is incrementally adjusted with respect to its neighbors' relative coordinates. The optimization is self-stabilizing, guaranteeing to converge and not interfered by inaccurate coordinates, since the relative coordinates do not have computational errors. By exploiting the sparse structure of the squared matrix, the optimization enforces the L1-norm regularization to preserve the sparseness of the squared matrix. Simulation results and a PlanetLab-based experiment confirm that, RMF converges to stable positions within 10 to 15 rounds, and decreases the prediction errors by 10% to 20%. 2 centralized and distributed methods. (i) Centralized methods, GNP [4] and IDES [5] require a set of centralized landmark nodes to serve as reference nodes for calculating the coordinates, which could cause performance bottlenecks as the system increases. (ii) Distributed methods, Vivaldi [6], DMF [7] and DMFSGD [9] directly let each node adjust its coordinate with respect to the coordinates of a number of sampled neighbors, which avoids the single points of failures.The network coordinate methods have to be consistently accurate under varying system conditions. For example, end hosts may join or leave the system at any time, yielding churns. A well-studied stabilization model is the self stabilization that guarantees to converge to a "legitimate" state in a bounded amount of time, regardless of the initial state [13]. We introduce a self-stabilized network coordinate model in section II. We propose to map the "legitimate" state to the local-minimum position of each network coordinate that is not interfered by system churns.Distributed network-coordinate methods face the destabilization issue: some neighbors' coordinates can be arbitrarily inaccurate due to the churns of the distributed systems, accordingly, the coordinate optimization process is easily tampered by these neighbors' positions, as shown in section VI-B. Researchers [6], [2], [8], [9] propose to use weights to estimate the accuracy of neighbors' coordinates, and to adjust the coordinate movements scaled by weights. The weights are correlated with the accuracy of neighbors' coordinates. However, calculating exact weights is challenging, since ...

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Section: A Background and Related Workmentioning

confidence: 99%

A relative coordinate based distributed sparse-preserving matrix factorization approach towards self-stabilizing network location service - Withdrawn

Wang²,

Peng³

et al. 2024

IEEE Trans. Parallel Distrib. Syst.

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“…Green clouds is a recent research topic where VM migration has another optimization constraint-the energy efficiency [33]. For lack of a better term, "dormant VMs" might substantially decrease the management cost of VM populations.…”

Section: Optimization Of Vm Populationsmentioning

confidence: 99%

Multisource Stream Aggregation in the Cloud

Zhanikeev

2014

Advanced Content Delivery, Streaming, and Cloud Services

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“…[8]- [10]) have been proposed for predicting Internet latencies. These typically use metric, or more specifically Euclidean coordinates.…”

Section: Introductionmentioning

confidence: 99%

“…Thus these coordinates are obtained in one shot, from d measurements per node. In contrast the metric coordinates used in [8]- [10] are continuously updated on the basis of new measurements, and thus potentially more finely tuned than in a one-shot approach.…”

Section: Introductionmentioning

confidence: 99%

Non-Metric Coordinates for Predicting Network Proximity

Key

Massoulié

Tomozei

2008

2008 Proceedings IEEE INFOCOM - The 27th Conference on Computer Communications

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Abstract-We consider the problem of determining the "closest", or best Internet host to connect to, from a list of candidate servers. Most existing approaches rely on the use of metric, or more specifically Euclidean coordinates to infer network proximity. This is problematic, given that network distances such as latency are known to violate the triangle inequality. This leads us to consider non-metric coordinate systems. We perform an empirical comparison between the "min-plus" non-metric coordinates and two metric coordinates, namely L-infinity and Euclidean. We observe that, when sufficiently many dimensions are used, min-plus outperforms metric coordinates for predicting Internet latencies.We also consider the prediction of "widest path capacity" between nodes. In this framework, we propose a generalization of min-plus coordinates. These results apply when node coordinates consist in measured network proximity to a random subset of landmark nodes. We perform empirical validation of these results on widest path bandwidth between PlanetLab nodes.We conclude that appropriate non-metric coordinates such as generalized min-plus systems are better suited than metric systems for representing the underlying structure of Internet distances, measured either via latencies or bandwidth.

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Virtual landmarks for the internet

Cited by 40 publications

References 0 publications

A relative coordinate based distributed sparse-preserving matrix factorization approach towards self-stabilizing network location service - Withdrawn

A relative coordinate based distributed sparse-preserving matrix factorization approach towards self-stabilizing network location service - Withdrawn

Multisource Stream Aggregation in the Cloud

Non-Metric Coordinates for Predicting Network Proximity

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