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HetHetNets: Heterogeneous Traffic Distribution in Heterogeneous Wireless Cellular Networks [PDF]
IEEE Journal on Selected Areas in Communications, 2015 A recent approach in modeling and analysis of the supply and demand in heterogeneous wireless cellular networks has been the use of two independent Poisson point processes (PPPs) for the locations of base stations (BSs) and user equipments (UEs). This popular approach has two major shortcomings.
Meisam Mirahsan +2 more
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A Heterogenous System for Traffic Prediction
2020 19th RoEduNet Conference: Networking in Education and Research (RoEduNet), 2020Recent developments in the field of Machine Learning have resulted in great progress, both academically and commercially, in various applications. The success of these applications comes from being able to either predict or categorize series or elements that, before, could not be analyzed using classical statistical methods, thus solving complex, real ...
Razvan-Bogdan-Audrei Radoi +1 more
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Downlink Scheduling of Heterogeneous Traffic
2006 IEEE International Conference on Communications, 2006Next generation wireless cellular networks will support a variety of quality-of-service (QoS) sensitive applications like streaming multimedia and high-speed data for downlink users. Channel and QoS aware downlink packet scheduling policies are going to play a key role in efficiently utilizing system resources and enhancing QoS experienced by end users.
Aditya Dua, Nicholas Bambos
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A traffic stream model for heterogeneous traffic conditions
Proceedings of the Institution of Civil Engineers - Transport, 2014A comprehensive understanding of speed–flow–density relations is an essential requirement in planning, design and operation of transportation systems. Many researchers have investigated the nature of speed–flow–density relationships, commonly known as stream models, under homogeneous traffic conditions.
Ajitha Thankappan, Lelitha Vanajakshi
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Efficient Scheduling for Heterogeneous Traffic in Downlink
2007 IEEE 66th Vehicular Technology Conference, 2007This paper studies optimal allocation of resources to users in a fading broadcast channel (BC) to support heterogeneous traffic. Resource allocation is done in a cross-layer manner for both deadline-sensitive (DS) and best-effort (BE) data to provide users guaranteed Quality of Service (QoS).
Rajiv Agarwal +3 more
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GPS queues with heterogeneous traffic classes
Proceedings.Twenty-First Annual Joint Conference of the IEEE Computer and Communications Societies, 2003We consider a queue fed by a mixture of light-tailed and heavy-tailed traffic. The two traffic classes are served in accordance with the generalized processor sharing (GPS) discipline. GPS-based scheduling algorithms, such as weighted fair queueing (WFQ), have emerged as an important mechanism for achieving service differentiation in integrated ...
Sem C. Borst +2 more
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THE EFFECT OF THE HETEROGENEITY ON THE TRAFFIC FLOW BEHAVIOR
International Journal of Modern Physics C, 2010We propose a traffic flow model which takes into account the disorder in the length and the maximal speed of cars. Using cellular automaton model in parallel dynamics we have studied the behavior of traffic flow, especially the condition of formation (active phase) and the dissociation (absorbing phase) of platoons.
Jetto, K. +2 more
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Heterogeneous traffic estimation with particle filtering
2019 IEEE Intelligent Transportation Systems Conference (ITSC), 2019This article considers the state estimation problem for heterogeneous traffic characterized by various vehicle sizes. The interactions between vehicle classes display unique features that are distinct from homogeneous traffic flows. Modeling and estimation methods for heterogeneous traffic, however, still remain relatively unexplored.
Yanbing Wang, Daniel B. Work
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Traffic engineering for wireless mobile networks supporting heterogeneous traffic
IEEE Wireless Communications and Networking Conference, 2005, 2005In this paper, we present a practical framework that can be used as a basis for dimensioning 3G systems and beyond that support heterogeneous traffic (voice and multirate data). We start by performing multiplexing simulations as a means to capture the temporal randomness for different traffic profiles, prior to using static system simulation.
Leila Z. Ribeiro, Luiz A. DaSilva
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