Radio Resource Allocation for Data Services in UMTS Networks

Kröner, Hans

doi:10.1078/1434-8411-00008

Cited by 5 publications

(1 citation statement)

References 5 publications

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“…The experimental result shows that the proposed method can archive an excellent overall performance than state-of-the-art works. Graph theory and algorithms have provided essential theory support for vehicular networks in resource allocation and communication modeling [28], and graph applications also help the network more informed and data-driven decisions. However, how to use graph theory and algorithms to support the distinctive characteristics of intelligent vehicular networks and provide high performance and real-time decision making policy remains challenging and represents a promising research direction.…”

Section: Introductionmentioning

confidence: 99%

Graph-Enabled Intelligent Vehicular Network Data Processing

Zheng

2022

IEEE Trans. Intell. Transport. Syst.

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Intelligent vehicular network (IVN) is the underlying support for the connected vehicles and smart city, but there are several challenges for IVN data processing due to the dynamic structure of the vehicular network. Graph processing, as one of the essential machine learning and big data processing paradigm, which provide a set of big data processing scheme, is well-designed to processing the connected data. In this paper, we discussed the research challenges of IVN data processing and motivated us to address these challenges by using graph processing technologies. We explored the characteristics of the widely used graph algorithms and graph processing frameworks on GPU. Furthermore, we proposed several graph-based optimization technologies for IVN data processing. The experimental results show the graph processing technologies on GPU can archive excellent performance on IVN data.

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Section: Introductionmentioning

confidence: 99%

Graph-Enabled Intelligent Vehicular Network Data Processing

Zheng

2022

IEEE Trans. Intell. Transport. Syst.

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Planning OBS networks with QoS constraints

Rodrigo

Remiche

2007

Photon Netw Commun

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The design of OBS networks that guarantee QoS provisioning for different classes of traffic is a major topic under current research. In this work we formulate a unified framework for studying QoS in OBS networks with a GMPLS-based control plane. We use this framework in order to investigate two problems. First, the configuration of the parameters of an aggregation strategy so that a given Forwarding Equivalency Class observes its corresponding QoS requirements. Second, we address the problem of planning a whole OBS network given a series of QoS constraints for each one of the Forwarding Equivalency Classes in the network. The presented QoS framework constitutes a valuable tool for studying QoS-related issues in OBS networks.

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Analytic approximation of the effective bandwidth for best-effort services in UMTS networks

Staehle

Leibnitz

Heck

et al.

The 57th IEEE Semiannual Vehicular Technology Conference, 2003. VTC 2003-Spring.

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The introduction of third generation mobile communication systems allows the service providers to oITer a large variety of services which are in the Universal Mobile Telecommunication System subsumed under the categories conversational, streaming, interactive, and background class. While the conversational and streaming classes have a guaranteed bandwidth and delay, the interactive and background class consume the remaining system capacity. On the downlink tbk system capacity is limited by the base station transmit power and on the uplink by the interference. In our analysis we approximate the capacity which the services with quality of service leave lor best-effort semces belonging to the interactive class. The background class is neglected. We focus our analysis on the downlink since for U M T S the expected tratlic is assumed to be asymmetric with the bulk of it lowards the mobile station and derive the distribution of the bandwidth available for best-effort users according to a spatial user distribution.

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Radio Resource Allocation for Data Services in UMTS Networks

Cited by 5 publications

References 5 publications

Graph-Enabled Intelligent Vehicular Network Data Processing

Graph-Enabled Intelligent Vehicular Network Data Processing

Planning OBS networks with QoS constraints

Analytic approximation of the effective bandwidth for best-effort services in UMTS networks

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