Query: Network Traffic Aggregation

title: Load balancing in OpenFlow enabled switches for wireless access traffic aggregation
abstract: The immense development in mobile devices and the proliferation of ubiquitous cloud based services have led to a surge in the utilization of remote data centers. These dramatic advances in wireless based services induce a huge traffic flow within the network. However, consequent high load on the network devices may lead to faults and thus an adverse decrease in the user experience. On the other hand, balancing the aggregated multi flow traffic on ports of network switches is a challenging issue. This work presents a load balancing algorithm implemented in OpenDaylight controller for managing the load on the switch ports by utilizing Software Defined Networking (SDN) architecture. The switch acts a connector which aggregates traffic from wireless access nodes. An experiment design is constructed with hardware based OpenFlow enabled switch and connected wireless hosts. According to the load on the ports, the developed scheme dynamically load balances the incoming traffic towards the backhaul connection. It uses OpenFlow for gathering statistics and flow rule installation on the switch in an adaptive manner.

title: A distributed framework for network wide traffic monitoring and platoon information aggregation using V2V communications
abstract: This study explores an innovative framework for distributed traffic monitoring and information aggregation using vehicle to vehicle (V2V) communications alone. We envision the proposed framework as the foundation to an alternative or supplemental traffic operation and management system, which could be particularly helpful under abnormal traffic conditions caused by unforeseen disasters and special events. Each equipped vehicle, through the distributed protocols developed, keeps track of the average traffic density and speed within a certain range, flags itself as micro discontinuity in traffic if appropriate, and cross checks its flag status with its immediate up and down stream vehicles. The micro discontinuity flags define vehicle groups with similar traffic states, for initiating and terminating traffic information aggregation. The framework is validated using a microscopic traffic simulation platform VISSIM and its built in component object model. Vehicle groups are successfully identified and their average speed and density effectively estimated. The impact of market penetration rate (MPR) is also investigated with a new methodology for performance evaluation under multiple traffic scenarios. Our simulation results show that the proposed framework lends itself better to more congested traffic conditions for any given MPR. With 50% MPR, the framework is able to provide information coverage for at least 37.76% of the simulated roadway facility under various traffic scenarios. This indicates that proposed framework could be useful with an MPR as low as 50% Even with an MRP of 20% the coverage ratio, under relatively congested traffic, can still reach around 58.82% The framework is able to provide accurate speed estimation at high spatial resolution for the simulated roadway facility. The maximum relative error is under 10% for relatively congested traffic even with MPR as low as 20% When there is a wider range of speed distribution (less congested traffic) the worst case maximum relative error is still under 15% when MPR 20 The density estimation is more sensitive to MPR, and is more accurate under low demand and high MPR scenarios. As expected, the accuracy of both speed and density estimation increases with MPR for any given traffic scenario.

title: An LTE WiFi Spectrum Aggregation System for 5G Network: A Testbed
abstract: Nowadays, the continuous increase in the high data traffic demand and providing the different quality of services (QOS) to the customer is a very challenging task for all network operators. In the last few years, mobile data traffic is increased to a significant extent. To overcome the increasing traffic demand WiFi offloading is the best option to reduce the burden of cellular networks. So, by aggregating existing indoor WiFi technology to the cellular network is increased the network capacity and provides better QoS to customers. In this article, we proposed and implement the LTE WiFi aggregation system which is very similar to the 3GPP LWA system. Furthermore, the proposed system is integrated with the M CORD platform which is SDN, NFV, and cloud based open source solutions for providing a 5G environment. The implementation of the proposed system is based on the OpenAirInterface OAI software defined radio (SDR) platform where WLAN AP is directly connected to eNodeB. The aggregation of both technologies is done at the PDCP layer. Moreover, we test our proposed system with three kinds of policies for UDP and TCP traffic known as LTE only, WiFi only and LTE WiFi aggregated. The experimental result shows that our proposed LTE WiFi aggregated system gives better performance and provides high bandwidth as compared to single LTE.

title: Integration of a cell transmission model and macroscopic fundamental diagram: Network aggregation for dynamic traffic models
abstract: Network size can have a significant impact on the computational performance of traffic simulation models. Due to this, methods to reduce network size can be valuable when analyzing large networks. In this research, a novel model integrating a Cell Transmission Model (CTM) with the Macroscopic Fundamental Diagram (MFD) for urban networks is proposed and its effects analyzed. The concept that underlies this work is that a road network can be classified into two types of networks: the first includes roads that are modeled using CTM, and the second are components of the network that can be aggregated into large self contained cells that also maintain properties of the MFD. To test the proposed model and its computational efficiency, a case study involving an evacuation is introduced. The network and its demand, built from the Southeast Louisiana Hurricane Katrina evacuation event, were modeled using a combination of CTM and MFD. The spatio temporal profiles of volume and speeds on key routes and destinations from the proposed model were compared to observed data from the event. The results suggest that the model was able to realistically capture the observed shock wave phenomena, and reproduce the spatio temporal characteristics of the evacuation traffic. This simple methodology has considerable potential to improve computational efficiency in dynamic traffic assignment models, particularly for those large scale networks and processes, while ensuring that the traffic dynamics are realistically modeled.

title: Short term traffic flow prediction in smart multimedia system for Internet of Vehicles based on deep belief network
abstract: In the multimedia system for Internet of Vehicles (IoVs) accurate traffic flow information processing and feedback can give drivers guidance. In traditional information processing for IoVs, few researches deal with traffic flow information processing by deep learning. Specially, most of the existing prediction technologies adopt shallow neural network, and their models for chaotic time series are prone to be restricted by multiple parameters. Over the last few years, the dawning of the big data era creates opportunities for the intelligent traffic control and management. In this paper, we take Restricted Boltzmann Machine (RBM) as the method for traffic flow prediction, which is a typical algorithm based on deep learning architecture. Considering traffic big data aggregation in IoVs, multimedia technologies provide enough real sample data for model training. RBM constructs the long term model of polymorphic for chaotic time series, using phase space reconstruction to recognize the data. To the best of our knowledge, it is the first time apply RBM model to short term traffic flow prediction, which can improve the performance of multimedia system in IoVs. Moreover, experimental results show that the proposed method has superior performance than traditional shallow neural network prediction methods.

title: Assessing the Demand Vulnerability of Equilibrium Traffic Networks via Network Aggregation
abstract: Studies of network vulnerability mostly focus on changes to the supply side; whether considering a degradation of link capacity or complete link failure. However, the level of service provided by a transport network is also vulnerable to increases in travel demand, with the consequent congestion causing additional delays. Traffic equilibrium models can be used to evaluate the influence of travel demand on level of service when interest is restricted to only a small number of pre specified demand scenarios. A demand vulnerability analysis requires understanding the impact of unknown future changes to any possible combination of OD demands. For anything but the smallest networks, this cannot be accomplished by re computing network equilibrium at all possible demand settings. We require a representation of the functional relationship between demands and levels of service, avoiding the need to re evaluate the equilibrium model. This process of collapsing the demand and network representations onto a single, coarse level network with explicit functional relationships is referred to here as 'network aggregation' We present an efficient method for network aggregation for networks operating under Stochastic User Equilibrium (SUE) In numerical experiments, we explore the nature and extent of the aggregation errors that may arise.

title: Research on Aggregation and Propagation of Self Similar Traffic in Satellite Network
abstract: It has already been confirmed that the traffic in high speed terrestrial network presents self similarity, but there is little research on self similarity of traffic in satellite network. Considering time varying network topology and link status, this paper analyzes the aggregation and propagation of self similar traffic between nodes in satellite network. Furthermore, a sort of special network node called ground gateway is modeled, based on which the characteristics of the output traffic that the input traffic from terrestrial network passes gateway into satellite network are analyzed. Theoretically analyses demonstrate that after aggregation and propagation between satellite nodes, traffic is still self similar, and the self similarity of the output traffic generated by gateway from terrestrial network to satellite network is more often than not weakened.

title: Traffic Aggregation Techniques for Environmental Monitoring in M2M Capillary Networks
abstract: In this paper, we address the problem of traffic aggregation in capillary M2M networks. In particular, we focus on monitoring application where sensor nodes gather information from the environment (e.g. temperature, humidity, concentration of pollutants, etc) and send it to the gateway (GW) The GW then processes and retransmits the data through a cellular network to a distant application server. In an attempt to reduce the traffic congestion in the cellular network, we propose a data compression strategy at the GW that effectively exploits the temporal and spatial correlation in the sensors observations. The data compression strategy is composed of two building blocks: an estimation block and a compression block. In the estimation block, the data streams are jointly processed by means of a multidimensional linear filter. Next, the output streams of the estimation block are compressed by resorting to a truncated version its Karhunen Loeve expansion.

title: QoS Aware Adaptive A MPDU Aggregation Scheduler for Voice Traffic in Aggregation Enabled High Throughput WLANs
abstract: Currently available IEEE 802.11n implementations do not apply aggregate MAC protocol data unit (A MPDU) aggregation to voice traffic because of its strict end to end delay requirements. When multiple nodes contend to send voice and other lower priority traffic, 802.11n network faces serious performance degradation problems for two major reasons: i) due to the medium access control (MAC) and physical (PHY) layer overheads of individual short voice packet transmissions, the available network throughput for lower priority traffic significantly decreases, and ii) increased contention results in high voice packet loss rate (PLR) This paper proposes a QoS aware adaptive A MPDU aggregation scheduler for voice traffic in 802.11n/ac WLANs that adaptively applies A MPDU aggregation to voice traffic based on QoS requirements and periodically obtained average medium access delay and end to end delay statistics. Performance evaluations on 20 nodes sending uplink 64Kbps voice and saturated best effort traffic at 150Mbps PHY rate showed that the proposed scheme achieved 160% throughput improvement compared to default implementations in driver. During the simulations with 50 nodes transmitting at 600Mbps PHY rate, the proposed scheme provided up to 275Mbps throughput against 0.13Mbps by default scheme; the proposed scheme delivered all voice packets (PLR 0 percent) and over 99.9 percent of them had less than 150ms end to end delay.

title: Performance quality evaluation with VoIP traffic aggregation in Mobile Ad Hoc Networks
abstract: VoIP traffic over Mobile Ad Hoc Networks (MANETs) faces many interacting challenges such as the mobility of the nodes that leads to continuous link breakages, the restricted bandwidth availability, the different characteristics of the existing routing protocols, the used voice codecs, the number of the mobile nodes and the background traffic. These factors introduce variability in the latency and the packet loss rate, which in turn severely affects the voice quality that is closely related to the voice codecs used by the VoIP network. This paper examines the effects of these factors to the quality of the VoIP traffic over a MANET via extensive simulations. It also presents ways to improve the performance, based either on the routing layer or on the application layer with the aggregation of multiple voice payloads to a single packet. This aggregation significantly improves the performance of the G.711 codec, while the impact to the other codecs is negligible.