Choosing the Objectives for Traffic Engineering in IP Backbone Networks Based on Quality-of-Service Requirements

Poppe, Fabrice; Bosch, Sven van den; Vallee-Poussin, P. de La; Hove, Hugo Van; Neve, H. De; Petit, Guido H.

doi:10.1007/3-540-39939-9_11

Cited by 9 publications

(5 citation statements)

References 3 publications

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“…What is the best segmentation number of data based on the networks usage level and data characteristics? Another issue is about the performance level transfer time of transfer protocols based on data type in this tool that needs to be addressed [25]. The main implication of this paper is applying adaptive Internet traffic measurement and analysis options based on the dynamic changes in network traffic environments.…”

Section: Resultsmentioning

confidence: 99%

Analysis of How Scalable Features in Hadoop / MapReduce by Internet Traffic Management

Jacob¹,

Tharwat²,

Fudzee³

et al. 2023

Int. J. Adv. Sci. Eng. Inf. Technol.

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Internet traffic monitoring is to measure and analyze the network bottlenecks to manage the online data are transferring processes efficiently. Various tools have been developed by using internet traffic measurement and internet traffic analysis tools, such as Hadoop. Activity measurement and adaptive examination represent the dynamics of information exchange. On the other hand, information exchange and dynamics measure movement in light of the system assets that can be accessed depending on the characteristics of the exchanged information. The main aim of this work is to apply scalable features of internet traffic measurement and analysis using Hadoop to understand the effects of these features on the speed of transferring data. This gives a new vision or opportunity to dynamically adapting the most suitable traffic measurement and analysis feature according to network capabilities and environment. This research employs Hadoop/Map Reduce as scalable internet traffic measurement and analysis tools. The simulation was conducted by using five personal computers; one as a server and four virtual computers as network nodes. Each computer has 2GB memory and 100GB storage. Five types of data segmentation are utilized 10 MB, 40MB, 64MB, 200MB, and500MB. The speed of the network is calculating in a megabit per second (Mbs) based upon the network speed on the number of allocated PCs (100 Mbs/4). The simulation is conducted to test the data transfer time based on various selections of network capabilities such as transferring extensive data through a network of medium and heavy usage.

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Section: Resultsmentioning

confidence: 99%

Analysis of How Scalable Features in Hadoop / MapReduce by Internet Traffic Management

Jacob¹,

Tharwat²,

Fudzee³

et al. 2023

Int. J. Adv. Sci. Eng. Inf. Technol.

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“…From there onward, we have witnessed significant increase in the total traffic volumes web traffic still occupies larger share of many networks (Yuan, 2001;Awduche et al, 1999;Bhattacharyya et al, 2001). However, the sharing of file often dominates the traffic application (Ahuja et al, 2015;Poppe et al, 2000). In addition, TV and video distribution over IP have become widely spread and produce increasing traffic volumes.…”

Section: Internet Trafficmentioning

confidence: 99%

Online Traffic Measurement and Analysis in Big Data: Comparative Research Review

Ibrahim¹,

Hassan

Ahmad

et al. 2016

American Journal of Applied Sciences

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Abstract:The Internet traffic measurement and analysis is important to avoid many problems of data transferring via online networks such as data losing and slow data transferring. The Internet traffic measuring and analysis could be effective to avoid the data transferring challenges. The Internet traffic measuring and analysis flexibility is important due to many reasons such as dynamicity of transferred data such as size and format, the data transferring protocols and the dynamicity of measure the traffic based on the networks available resources depend on the transferred data characteristics. The main objective of this paper is to review the most flexible Internet traffic measuring and analysis tools that could be adopted to handle the dynamicity of data transferring characteristics.

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“…In order to formulate it as a multi-commodity flow (MCF) problem we must decide how to model commodities. In the usual approach [1,8,11] commodities are modelled as sourcedestination pairs that are interpreted as "all traffic from source to destination". Thus, the set of commodities is a subset of the Cartesian product N × N ; consequently, the number of commodities is bounded by the square of the number of nodes.…”

Section: Optimisationmentioning

confidence: 99%

“…Poppe et al [11] have proposed using different linear objective functions in order to obtain traffic solutions that are desirable with respect to several criteria (including balance, in the form of minimising the maximum utilisation of edges). Fortz and Thorup [8,9], on the other hand, considers a fixed piece-wise linear objective function (consisting of six linear portions for each edge) which makes the cost of sending traffic along an edge depend on the utilisation of the edge.…”

Section: How To Obtain Desirable Solutionsmentioning

confidence: 99%

See 1 more Smart Citation

A Multi-path Routing Algorithm for IP Networks Based on Flow Optimisation

Abrahamsson¹,

Ahlgren²,

Alonso³

et al. 2002

From QoS Provisioning to QoS Charging

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Intra-domain routing in the Internet normally uses a single shortest path to forward packets towards a specific destination with no knowledge of traffic demand. We present an intra-domain routing algorithm based on multi-commodity flow optimisation which enable load sensitive forwarding over multiple paths. It is neither constrained by weight-tuning of legacy routing protocols, such as OSPF, nor requires a totally new forwarding mechanism, such as MPLS. These characteristics are accomplished by aggregating the traffic flows destined for the same egress into one commodity in the optimisation and using a hash based forwarding mechanism. The aggregation also results in a reduction of computational complexity which makes the algorithm feasible for on-line load balancing. Another contribution is the optimisation objective function which allows precise tuning of the tradeoff between load balancing and total network efficiency.

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Choosing the Objectives for Traffic Engineering in IP Backbone Networks Based on Quality-of-Service Requirements

Cited by 9 publications

References 3 publications

Analysis of How Scalable Features in Hadoop / MapReduce by Internet Traffic Management

Analysis of How Scalable Features in Hadoop / MapReduce by Internet Traffic Management

Online Traffic Measurement and Analysis in Big Data: Comparative Research Review

A Multi-path Routing Algorithm for IP Networks Based on Flow Optimisation

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