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Congestion Identification in a Radio Access Transport NetworkMontojo Villasanta, Javier, Maqueda Viñas, Manuel January 2014 (has links)
The convergence of mobile services and Internet has brought a radical change in mobile networks. An all IP network architecture, an evolution of the radio access transport network, is required to support new high-bandwidth services. Unfortunately, existing control mechanisms are insufficient to guarantee end users a high quality of experience. However, coordinating radio and transport network resources is expected to yield a more efficient solution. This thesis project investigates the interactions between the congestion avoidance protocols, explicit congestion notification, and the traffic engineering metrics for latency and bandwidth, when using Open Shortest Path First with traffic engineering (OSPF-TE) as a routing protocol. Using knowledge of these interactions, it is possible to identify the appearance of bottlenecks and to control the congestion in the transport links within a radio access transport network. Augmenting a topology map with the network’s current characteristics and reacting to evidence of potential congestion, further actions, such as handovers can be taken to ensure the users experience their expected quality of experience. The proposed method has been validated in a test bed. The results obtained from experiments and measurements in this test bed provide a clear picture of how the traffic flows in the network. Furthermore, the behavior of the network observed in these experiments, in terms of real-time performance and statistical analysis of metrics over a period of time, shows the efficiency of this proposed solution. / Tjänstekonvergensen av Internet- och mobila tjänster har medfört en radikal förändring i mobilnäten. En ”All IP” nätverksarkitektur, en utveckling av radios transportnät. Utvecklingen krävs för att stödja de nya bredbandiga tjänsterna. Tyvärr är befintliga kontrollmekanismer otillräckliga för att garantera användarens kvalitetsupplevelse. Med att samordna radio- och transportnätverkets resurser förväntar man sig en effektivare lösning. Detta examensarbete undersöker samspelet mellan protokoll för att undvika överlast, direkt indikation av överlast och trafikal statistik för fördröjning och bandbredd med trafikstyrning baserat på fördröjning och bandbredd , vid användning av Open Shortest Path First ( OSPF - TE ) som routingprotokoll. Med hjälp av information om dessa interaktioner, är det möjligt att identifiera uppkomsten av flaskhalsar och för att styra trafikstockningar i transportförbindelser inom ett radioaccess transportnät. En utökad topologikarta med nätverkets aktuella egenskaper kommer att reagera på en potentiell överbelastning. Ytterligare åtgärder, till exempel överlämningar, vidtas i mobilnätet för att säkerställa användarens upplevda kvalitet. Den föreslagna metoden har validerats i en testmiljö. Resultaten från experiment och mätningar i denna testmiljö ger en tydlig bild av hur trafikflödena framskrider i nätverket. Beteendet hos nätverket som observeras i dessa experiment, i termer av realtidsprestanda och statistisk analys av mätvärden över en tidsperiod, visar effektiviteten av denna föreslagna lösning.
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Data-driven Methods for Identifying Travel Conditions Based on Traffic and Weather CharacteristicsAyfantopoulou, Georgia, Mintsis, Evangelos, Maleas, Zisis, Mitsakis, Evangelos, Grau, Josep Maria Salanova, Mizaras, Vassilis, Tzenos, Panagiotis 23 June 2023 (has links)
Accurate and reliable traffic state estimation is essential for the identification of congested areas and bottleneck locations. It enables the quantification of congestion characteristics, such as intensity, duration, reliability, and spreading which are indispensable for the deployment of appropriate traffic management plans that can efficiently ameliorate congestion problems. Similarly, it is important to categorize known congestion patterns throughout a long period of time, so that corresponding traffic simulation models can be built for the investigation of the performance of different traffic management plans. This study conducts cluster analysis to identify days with similar travel conditions and congestion patterns. To this end, travel, traffic and weather data from the Smart Mobility Living Lab of Thessaloniki, Greece is used. Representative days per cluster are determined to facilitate the development of traffic simulation models that typify average traffic conditions within each cluster.
Moreover, spatio-temporal matrices are developed to illustrate time-varying traffic conditions along different routes for the representative days. Results indicate that the proposed clustering technique can produce valid classification of days in groups with common characteristics, and that spatio-temporal matrices enable the development of traffic management plans which encompass routing information for competing routes in the city of Thessaloniki.
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