Toward decentralized probabilistic management

Prieto, Alberto; Gillblad, Daniel; Steinert, Rebecca; Miron, Avi

doi:10.1109/mcom.2011.5936159

Cited by 21 publications

(19 citation statements)

References 14 publications

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“…This protocol is a first step towards a complete framework for probabilistic management [14] and distributed event correlation in multi-layer networks. The method can be regarded as an alarm-filtering mechanism, that correlates relevant events both horizontally and vertically across the network.…”

Section: B Contributionmentioning

confidence: 99%

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A Distributed Spatio-Temporal Event Correlation Protocol for Multi-Layer Virtual Networks

Steinert

Gestrelius

Gillblad

2011

2011 IEEE Global Telecommunications Conference - GLOBECOM 2011

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We present a distributed spatio-temporal event correlation protocol for multi-layer networks. The problems that we address relate to scalability in stacked overlay networks and network equipment with asynchronous clocks, which complicates the problem of event correlation. We describe a cross-layer protocol designed to address these problems, operating in a fully distributed manner and taking into account asynchronous timestamps. It is assumed that events in one layer may arise from a series of events in lower layers. Detected events that are spatially related in one layer are aggregated using a gossiplike protocol, and constitute a root cause. The set of aggregated events is disseminated to lower layers and used for temporal correlation. We have tested the scalability and the performance of the distributed event protocol, using both synthetically generated and real-world topologies. The results indicate that the average overhead produced for collecting events down the stack of overlays increases with the number of layers. For a fixed number of layers, the protocol scales similarly with the graph-theoretic properties for a network of increasing size.

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Section: B Contributionmentioning

confidence: 99%

“…[14], [17]). When an event E (l) ij is reported in layer l, involved nodes n li and n lj defines the endpoints n s , n e of the affected topology T (l) ij , along with the time t w everything was known to be functional in node n li towards n lj and the time of the detected event t f , where t w < t f .…”

Section: Algorithm Descriptionmentioning

confidence: 99%

A Distributed Spatio-Temporal Event Correlation Protocol for Multi-Layer Virtual Networks

Steinert

Gestrelius

Gillblad

2011

2011 IEEE Global Telecommunications Conference - GLOBECOM 2011

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“…Decentralized probabilistic management becomes increasingly important for controlling large scale networks [4]. Compared to conventional deterministic management approaches, probabilistic methods can provide qualitative information about the network behaviour observed for a certain period of time.…”

Section: B Probabilistic Managementmentioning

confidence: 99%

“…. , π k,m that maximize (6) can then be used as objectives for configuring probabilistic management methods running in n k as described in Prieto et al [4].…”

Section: Probabilistic Managementmentioning

confidence: 99%

“…Similarly, nodes contributing to a service may be utilized in several simultaneous contexts, resulting in varying and highly unpredictable performance characteristics, such as in delay or bandwidth. One resource efficient way of dealing with this kind of uncertainty is to deploy probabilistic management locally in each node [4]. Probabilistic management allows each node to optimize its own performance with respect to a given performance objective, and is ideal for implementing a decentralized architecture for increased scalability and adaptability to varying conditions in local parts of the network.…”

Section: Introductionmentioning

confidence: 99%

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Translation of probabilistic QoS in hierarchical and decentralized settings

Bjurling

Steinert

Gillblad

2011

2011 13th Asia-Pacific Network Operations and Management Symposium

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In this paper we build on methods from probabilistic management for overcoming two issues in the translation of QoS into configurations of network nodes in dynamic, decentralized, and hierarchical networks. First, the inherent uncertainty about node performance in such networks (due to network dynamics) may impede adequate specification of QoS. We suggest how a probabilistic variant of QoS via optimization can be translated into objectives that can be handled with probabilistic management methods. Second, the dynamics of the network may make the interpretation of QoS dependent on the availability of network resources. We use methods from probabilistic management to suggest how the expression of QoS may be restricted in order to be able to ensure the existence of a translation of given QoS. The suggestions are applied to our own network architecture. The aim is to further develop our approach to a viable management solution for cloud computing and virtualized networks.

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Supporting Unified Distributed Management and Autonomic Decisions: Design, Implementation and Deployment

et al. 2016

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Nowadays, the prevailing use of networks based on traditional centralized management systems reflects on a fast increase of the management costs. The growth in the number of network equipments and services reinforces the need to distribute the management responsibilities throughout the network devices. In this approach, each device executes common network management functionalities, being part of the overall network management platform. In this paper, we present a Unified Distributed Network Management (UDNM) framework that provides a unified (wired and wireless) management network solution, where further different network services can take part of this infrastructure, e.g., flow monitoring, accurate routing decisions, distributed policies dissemination, etc. This framework is divided in two main components: (A) Situation awareness, which sets up initial information through bootstrapping, discovery, fault-management process and exchange of & Lucas Guardalben

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Toward decentralized probabilistic management

Cited by 21 publications

References 14 publications

A Distributed Spatio-Temporal Event Correlation Protocol for Multi-Layer Virtual Networks

A Distributed Spatio-Temporal Event Correlation Protocol for Multi-Layer Virtual Networks

Translation of probabilistic QoS in hierarchical and decentralized settings

Supporting Unified Distributed Management and Autonomic Decisions: Design, Implementation and Deployment

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