A-GAP: An Adaptive Protocol for Continuous Network Monitoring with Accuracy Objectives

Prieto, Alberto; Stadler, Rolf

doi:10.1109/tnsm.2007.030101

Cited by 47 publications

(33 citation statements)

References 11 publications

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“…We substantiate this claim by the fact that the trusted modules construct a secure distributed execution environment for the essential sub-protocols. Given that the aggregation protocol in question is decomposed into its secure and generic components, we can claim that it retains its original scalability properties (modulo authentication) as well as completeness guarantees and accuracy objectives [31]. Note that although we focus on tree-based aggregation protocols in this work, the trusted devices approach is generally applicable to distributed aggregation protocols, e.g.…”

Section: A Brief Analysis Of System Propertiesmentioning

confidence: 99%

Secure distributed top-k aggregation

Jónsson

Palmskog

Vigfússon

2012

2012 IEEE International Conference on Communications (ICC)

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Abstract-In-network aggregation is an efficient and scalable distributed approach to global state approximation. However, security remains an open problem in such systems, especially when we consider dynamic network effects, such as mobility, packet loss and churn. In this paper, we consider the resilience of the top-k aggregate to manipulation by active insider adversaries. Unfortunately, this versatile aggregation function is inherently insecure. We propose a simple, low-overhead solution which leverages the principles of trusted systems. The solution we propose is generally applicable, even to the challenging problem of securing distributed aggregation in a dynamic network.

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Section: A Brief Analysis Of System Propertiesmentioning

confidence: 99%

Secure distributed top-k aggregation

Jónsson

Palmskog

Vigfússon

2012

2012 IEEE International Conference on Communications (ICC)

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“…A-GAP [2] is a protocol for continuous monitoring of global metrics, which aims at achieving a given monitoring accuracy with minimal overhead.…”

Section: Overview Of the A-gap Protocolmentioning

confidence: 99%

“…1). In our previous work [2][3], we focused on the trade-off between overhead and accuracy. This trade-off is controlled by the filter widths.…”

Section: E Controlling Performance Trade-offsmentioning

confidence: 99%

Controlling performance trade-offs in adaptive network monitoring

Prieto

Stadler

2009

2009 IFIP/IEEE International Symposium on Integrated Network Management

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Abstract-A key requirement for autonomic (i.e., self-*) management systems is a short adaptation time to changes in the networking conditions. In this paper, we show that the adaptation time of a distributed monitoring protocol can be controlled. We show this for A-GAP, a protocol for continuous monitoring of global metrics with controllable accuracy. We demonstrate through simulations that, for the case of A-GAP, the choice of the topology of the aggregation tree controls the tradeoff between adaptation time and protocol overhead in steadystate. Generally, allowing a larger adaptation time permits reducing the protocol overhead. Our results suggest that the adaptation time primarily depends on the height of the aggregation tree and that the protocol overhead is strongly influenced by the number of internal nodes. We outline how A-GAP can be extended to dynamically self-configure and to continuously adapt its configuration to changing conditions, in order to meet a set of performance objectives, including adaptation time, protocol overhead, and estimation accuracy.

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“…Because jointly optimizing these metrics generally is not possible, the right operating point in the parameter space created by these metrics must be selected. For instance, recent results suggest that allowing for some modest errors, the protocol overhead to estimate an aggregate can be reduced by an order of magnitude in a realistic setting [3]. Taking into account that different management applications have different requirements regarding the quality of the estimates (delay, accuracy, etc.…”

Section: Distributed Monitoringmentioning

confidence: 99%

“…Sampling techniques have proven useful for IP packet-level monitoring. More recently, they also were successfully applied directly to distributed monitoring functions to measure, for example, a near real-time estimate of VoIP flows in a large network [3].…”

Section: Uncertainty and Probabilistic Approachesmentioning

confidence: 99%

Key research challenges in network management

Pras¹,

Schönwälder²,

Burgess³

et al. 2007

IEEE Commun. Mag.

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Although network management has always played a key role for industry, it only recently received a similar level of attention from many research communities, accelerated by funding opportunities from new initiatives, including the FP7 Program in Europe and GENI/FIND in the United States. Work is ongoing to assess the state of the art and identify the challenges for future research in the field, and this article contributes to this discussion. It presents major findings from a two-day workshop organized jointly by the IRTF/NMRG and the EMANICS Network of Excellence, at which researchers, operators, vendors, and technology developers discussed the research directions to be pursued over the next five years. The workshop identified several topic areas, including management architectures, distributed real-time monitoring, data analysis and visualization, ontologies, economic aspects of management, uncertainty and probabilistic approaches, as well as understanding the behavior of managed systems.

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A-GAP: An Adaptive Protocol for Continuous Network Monitoring with Accuracy Objectives

Cited by 47 publications

References 11 publications

Secure distributed top-k aggregation

Secure distributed top-k aggregation

Controlling performance trade-offs in adaptive network monitoring

Key research challenges in network management

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