Metropolitan network traffic demand study

Vaughn, M.D.; Wagner, Richard E.

doi:10.1109/leos.2000.890694

Cited by 38 publications

(15 citation statements)

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“…9. In order to dimension the network over a time period including the current situation, we use the traffic estimated by the traffic volume forecast model first proposed by Vaughn and Wagner [17,18] We use the node model and the associated equipment cost model of Fig. 6.…”

Section: Definitionmentioning

confidence: 99%

Techno-economic evaluation of the island based introduction of optical cross connects in an IP-over-WDM network

et al. 2006

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This article compares several traffic grooming approaches, based on expected capital expenditures (capex) to dimension and expand the network. For small traffic demands, the link-by-link grooming approach (efficiently filling SDH frames) is most interesting. We illustrate that, as traffic increases, there comes a point where the savings in IP layer expenses realized by endto-end grooming compensate the extra expenses of introducing the needed optical cross connects (OXCs). We study the network-wide migration from link-by-link towards end-to-end grooming at a single point in time, as well as a possible migration path, where OXCs are introduced gradually in so-called end-to-end grooming islands. This approach can lead to important savings in capex. We study total equipment costs as well as incremental and cumulative costs, indicating the total expenses to be paid by the operator over a certain time. The use of the Net Present Value (NPV) technique is clarified. Finally, also the sensitivity of the obtained results to changes in the component costs is studied.

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Section: Definitionmentioning

confidence: 99%

Techno-economic evaluation of the island based introduction of optical cross connects in an IP-over-WDM network

et al. 2006

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“…Forecasting future customer demand is a difficult problem [12][13][14] with an associated unavoidable forecast error, Forecast unreliability is problematic to operators, as they are-legitimately-concerned that the investments in network capacity will not match the actual requirements. Insufficient dimensioning may cause a loss of revenue because of displeased customers and penalty costs for unsatisfied Service Level Agreements (SLA).…”

Section: Strategic Planning Of Today's Optical Telecommunication Netwmentioning

confidence: 99%

“…[12][13][14], 3 distinguishes voice, transaction data, and IP traffic. It is based on the population, the number of non-production business employees, and the number of internet hosts in the considered cities, respectively.…”

Section: Forecasting Future Trafficmentioning

confidence: 99%

“…A-posteriori adjustment of uncertain variables indeed can- Fig. 10 Traffic prediction model proposed in [12][13][14] not handle the different safety margins used for the different traffic types in a straightforward way (see remark in Section Our model). Moreover, for equal safety margins a-priori and a-posteriori adjustments would give the same result, indicated by the square black points.…”

Section: Forecasting Future Trafficmentioning

confidence: 99%

“…Forecasting future customer demand is a difficult problem [12][13][14] with an associated unavoidable forecast error,…”

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confidence: 99%

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On Planning of Optical Networks and Representation of their Uncertain Input Parameters

et al. 2006

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This paper studies the use of uncertain inputs in the strategic network planning process. To model uncertain planning inputs three essential parameters are needed: the predicted value expressing for instance an expert's view, the uncertainty level indicating the doubt there is about the predicted value, and the confidence parameter denoting the probability that the output parameter was estimated big enough (compared to the actual output). Several planning approaches that handle uncertain variables are distinguished and their strengths and shortcomings are indicated. This allows to indicate the pitfalls in some common planning practices that use a fixed safety margin to handle uncertainty. It is shown that they can lead to incorrect planning decisions, such as underestimation of the impact of the input uncertainty and overdimensioning in case of inaccurately modelled dimensioning problems. Both a theoretic model and simulation results are shown. A real-life planning problem is studied, including forecasting future network traffic from uncertain inputs and dimensioning a network to accommodate an uncertain traffic demand.The network planning process and the changing environmentThe telecommunication landscape has undergone dramatic changes in recent years, especially due to the advances in optical networking. The number of customers grows, as well as the required bandwidth per user, causing the so-called market pull. This effect is very important for Internet traffic [1, 2] and is not expected to stop shortly [3]. Moreover, the operator's cost to be able to accommodate this demand (equipment cost, etc.) is subject to dynamic changes over time as a consequence of the technology push. The latter is apparent from major technological breakthroughs. We are witnessing an important evolution in optical networking technology, moving from point-to-point WDM transmission towards all-optical networks using Optical Path CrossConnects [4]. Finally, the liberalization in most countries has completely changed the telecommunication environment, confronting network operators with fierce competition [5,6]. In this dynamically changing environment, intelligent network planning has even become more important than it used to be [7,8]. Figure 1 gives a graphical overview of the strategic planning process. The overall goal of the process is to provide a network deployment plan optimising the profit of the network operator (trade-off between the expected revenues generated by the customers and the expected costs to realize the network), while taking into account the indirect customer requirements concerning survivability, etc [9][10][11].Especially when planning over a longer time horizon, the uncertainty of the considered planning data becomes important. Forecasting future customer demand is a difficult problem [12][13][14] with an associated unavoidable forecast error,

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Switching/merging node placement in survivable optical networks with SSP

Tapolcai

2010

Computer Communications

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Metropolitan network traffic demand study

Cited by 38 publications

References 1 publication

Techno-economic evaluation of the island based introduction of optical cross connects in an IP-over-WDM network

Techno-economic evaluation of the island based introduction of optical cross connects in an IP-over-WDM network

On Planning of Optical Networks and Representation of their Uncertain Input Parameters

Switching/merging node placement in survivable optical networks with SSP

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