The Experts below are selected from a list of 75228 Experts worldwide ranked by ideXlab platform
Timo Sukuvaara - One of the best experts on this subject based on the ideXlab platform.
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DIVANet@MSWiM - Wireless Traffic safety network for incident and weather information
Proceedings of the first ACM international symposium on Design and analysis of intelligent vehicular networks and applications - DIVANet '11, 2011Co-Authors: Timo Sukuvaara, Pertti Nurmi, Marjo Hippi, Riika Autio, Darya Stepanova, Pekka Eloranta, Laura Riihentupa, Kimmo KauvoAbstract:Vehicular Wireless communications with Vehicular Ad Hoc Networks (VANET) utilizing Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) communication tools are key technological approaches in efforts to improve Traffic safety and efficiency. The European project WiSafeCar (under the Celtic cluster of the EUREKA network) has as one of its key targets to develop an intelligent hybrid Wireless Traffic safety network between vehicles and infrastructure. Vehicle based sensors and observations are exploited to generate intelligent real-time services on a service platform for vehicles. WiSafeCar considers not only urban areas, but also the special case of operating in rural areas where no high-density base station (road side unit) network for V2I communication is available. Hybrid communication of cellular and IEEE 802.11p based Wireless vehicular networking has been employed, with the primary objective of the cellular communication to provide an alternative solution in areas outside of the range of the Wireless vehicular network.
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Wireless Traffic Safety Network Between Cars - Real Time Road Weather, Incident and Accident Data to Vehicles
2010Co-Authors: Pekka Eloranta, Juha Laakso, Timo SukuvaaraAbstract:The European Eureka/Celtic project WiSafeCar (2009 – 2011) aims to develop an effective service framework/platform and an advanced intelligent Wireless Traffic safety network between cars/other vehicles and infrastructure, with a possibility to exploit vehicle based sensor and observation data in order to generate secure and reliable intelligent real-time services for vehicles. The participants from various countries, full partners from Finland, Luxembourg & South Korea and contributing observers from Spain and Turkey, have planned and developed advanced services to be tested and offered within the project. This paper focuses on the Finnish pilot services dealing with incident/accident warnings and real time road condition and local road weather information.
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Wireless Traffic service platform for combined vehicle-to-vehicle and vehicle-to-infrastructure communications
IEEE Wireless Communications, 2009Co-Authors: Timo Sukuvaara, Pertti NurmiAbstract:Vehicular Wireless communications and vehicular ad hoc networks are nowadays widely identified enablers for improving Traffic safety and efficiency, and a large number of suggestions for vehicle-to-vehicle and vehicle-to-infrastructure communication have been presented. The focus is typically on bilateral communication between two vehicles or on broadcasting information from one vehicle or infrastructure to vehicles in the surrounding area. In the Carlink project [1, 2] of the European Celtic program call 3 we have developed an intelligent hybrid Wireless Traffic service platform between cars supported by roadside Wireless base stations. Communication between cars will be arranged in an ad hoc manner, supported by Wireless base station connection to the backbone network whenever possible. The platform consists of a specific set of services (e.g., local road weather service and incident warning service), but a variety of services can be integrated to this kind of a system. The ultimate goal was to enhance Traffic safety and smoothness, but also to generate a completely new communication entity, allowing new types of applications, services, and business opportunities. In this article we present the concept and example services of the Carlink platform. The platform simulations, field tests, and analysis show that the platform operability and efficiency are suitable for a large-scale Traffic system, to be verified in the pilot system deployment.
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Wireless Traffic service communication platform for cars
2009 Global Information Infrastructure Symposium, 2009Co-Authors: Djamel Khadraoui, Timo SukuvaaraAbstract:Rapidly changing weather conditions, especially in winter, have caused numerous disastrous Traffic accidents in Northern Europe and in the Alpine region during recent years. Information about hazardous weather and road conditions is often potentially available but difficult or sometimes even impossible to deliver to drivers. This paper presents the international CARLINK (Wireless Platform for Linking Cars) project [1,2] of the Celtic Cluster Programme Call 3 whose aim was to develop an intelligent Wireless Traffic service platform between cars supported with Wireless transceivers along the roads. The project was conducted between 2006 and 2008. The platform consisted of a specific set of services, however not only these but variety of other services can be integrated to this kind of a system. Two of the major services were real-time local road weather service and incident warning service. The real-time local road weather service is a solution where up-to-date local weather related information is being collected from cruising vehicles and then further delivered to other vehicles in the area. Incident warning service operates in the same manner, but concentrates to the parameters related to Traffic incidents or accidents, and (depending on seriousness of the incident) delivers a warning of such events to the vehicles in the Traffic network without delay. The ultimate goal was to develop an intelligent communication platform for vehicles so that they can deliver their own observations of Traffic and weather conditions to the platform core. Vehicular networking is nowadays a widely studied research field, and a large number of suggestions for vehicle-to-vehicle and vehicle-to-infrastructure communications have been presented. The focus is typically on bilateral communication between two vehicles or on broadcasting information from one vehicle or infrastructure to vehicles in the surrounding area. The CARLINK project developed an intelligent hybrid Wireless Traffic service platform between cars supported with Wireless base stations beside the road(s). Communication between the cars were arranged in an ad-hoc manner, supported with a Wireless base station connection to the backbone network, whenever possible. The ultimate goal was to enhance Traffic safety and smoothness, but also to generate completely new communication entity, allowing new types of applications, services and business opportunities. Not only the encountering cars and the infrastructure can broadcast data, but all the data can be delivered instantly over the communications network to all CARLINK-compliant vehicles. High impact and extreme weather generated challenges are increasing throughout the world, not least because of the climate change. CARLINK can truly contribute to meeting these challenges. The preliminary network simulations, communication tests and weather service prototypes have already shown that a new kind of Wireless communication environment can be created and it is indeed capable of enhancing Traffic safety.
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MCO - Wireless Traffic Service Communication Platform for Cars
Communications in Computer and Information Science, 2008Co-Authors: Timo Sukuvaara, Pertti Nurmi, D. Stepanova, E. Suutari, Marjo Hippi, Pekka Eloranta, Sami Suopajärvi, K. YlisiurunenAbstract:Rapidly changing weather conditions, especially in winter, have caused numerous disastrous Traffic accidents in Northern Europe and in the Alpine region during recent years. Information about hazardous weather and road conditions is often potentially available but difficult or sometimes even impossible to deliver to drivers. This paper presents the international CARLINK (Wireless Platform for Linking Cars) project [1] of the Celtic Cluster Programme Call 3 whose aim is to develop an intelligent Wireless Traffic service platform between cars supported with Wireless transceivers along the roads. The platform consists of a specific set of services, however not only these but variety of other services can be integrated to this kind of a system. Two of the major services are real-time local road weather service and incident warning service. The real-time local road weather service is a solution where up-to-date local weather related information is being collected from cruising vehicles and then further delivered to other vehicles in the area. Incident warning service operates in the same manner, but concentrates to the parameters related to Traffic incidents or accidents, and (depending on seriousness of the incident) delivers a warning of such events to the vehicles in the Traffic network without delay. The ultimate goal is to develop an intelligent communication platform for vehicles so that they can deliver their own observations of Traffic and weather conditions to the platform core.
Pertti Nurmi - One of the best experts on this subject based on the ideXlab platform.
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DIVANet@MSWiM - Wireless Traffic safety network for incident and weather information
Proceedings of the first ACM international symposium on Design and analysis of intelligent vehicular networks and applications - DIVANet '11, 2011Co-Authors: Timo Sukuvaara, Pertti Nurmi, Marjo Hippi, Riika Autio, Darya Stepanova, Pekka Eloranta, Laura Riihentupa, Kimmo KauvoAbstract:Vehicular Wireless communications with Vehicular Ad Hoc Networks (VANET) utilizing Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) communication tools are key technological approaches in efforts to improve Traffic safety and efficiency. The European project WiSafeCar (under the Celtic cluster of the EUREKA network) has as one of its key targets to develop an intelligent hybrid Wireless Traffic safety network between vehicles and infrastructure. Vehicle based sensors and observations are exploited to generate intelligent real-time services on a service platform for vehicles. WiSafeCar considers not only urban areas, but also the special case of operating in rural areas where no high-density base station (road side unit) network for V2I communication is available. Hybrid communication of cellular and IEEE 802.11p based Wireless vehicular networking has been employed, with the primary objective of the cellular communication to provide an alternative solution in areas outside of the range of the Wireless vehicular network.
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Wireless Traffic service platform for combined vehicle-to-vehicle and vehicle-to-infrastructure communications
IEEE Wireless Communications, 2009Co-Authors: Timo Sukuvaara, Pertti NurmiAbstract:Vehicular Wireless communications and vehicular ad hoc networks are nowadays widely identified enablers for improving Traffic safety and efficiency, and a large number of suggestions for vehicle-to-vehicle and vehicle-to-infrastructure communication have been presented. The focus is typically on bilateral communication between two vehicles or on broadcasting information from one vehicle or infrastructure to vehicles in the surrounding area. In the Carlink project [1, 2] of the European Celtic program call 3 we have developed an intelligent hybrid Wireless Traffic service platform between cars supported by roadside Wireless base stations. Communication between cars will be arranged in an ad hoc manner, supported by Wireless base station connection to the backbone network whenever possible. The platform consists of a specific set of services (e.g., local road weather service and incident warning service), but a variety of services can be integrated to this kind of a system. The ultimate goal was to enhance Traffic safety and smoothness, but also to generate a completely new communication entity, allowing new types of applications, services, and business opportunities. In this article we present the concept and example services of the Carlink platform. The platform simulations, field tests, and analysis show that the platform operability and efficiency are suitable for a large-scale Traffic system, to be verified in the pilot system deployment.
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MCO - Wireless Traffic Service Communication Platform for Cars
Communications in Computer and Information Science, 2008Co-Authors: Timo Sukuvaara, Pertti Nurmi, D. Stepanova, E. Suutari, Marjo Hippi, Pekka Eloranta, Sami Suopajärvi, K. YlisiurunenAbstract:Rapidly changing weather conditions, especially in winter, have caused numerous disastrous Traffic accidents in Northern Europe and in the Alpine region during recent years. Information about hazardous weather and road conditions is often potentially available but difficult or sometimes even impossible to deliver to drivers. This paper presents the international CARLINK (Wireless Platform for Linking Cars) project [1] of the Celtic Cluster Programme Call 3 whose aim is to develop an intelligent Wireless Traffic service platform between cars supported with Wireless transceivers along the roads. The platform consists of a specific set of services, however not only these but variety of other services can be integrated to this kind of a system. Two of the major services are real-time local road weather service and incident warning service. The real-time local road weather service is a solution where up-to-date local weather related information is being collected from cruising vehicles and then further delivered to other vehicles in the area. Incident warning service operates in the same manner, but concentrates to the parameters related to Traffic incidents or accidents, and (depending on seriousness of the incident) delivers a warning of such events to the vehicles in the Traffic network without delay. The ultimate goal is to develop an intelligent communication platform for vehicles so that they can deliver their own observations of Traffic and weather conditions to the platform core.
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Intelligent Road Weather Forecasting in the CARLINK Platform
2008Co-Authors: Pertti Nurmi, Timo Sukuvaara, Marjo HippiAbstract:The objective of the international R&D project CARLINK (Wireless Traffic Service Platform for Linking Cars) is to develop an intelligent Wireless Traffic service platform between cars, supported with Wireless transceivers along the roads. Over ten partner institutes and companies representing three countries, Finland, Luxembourg and Spain, participate in this three-year (2006-08) research undertaking. Each participating country has its own sitespecific application. The Finnish application relates to real-time observing and very shortrange forecasting of local road weather to address and ease wintertime road Traffic operations under adverse weather conditions, thus enhancing Traffic safety. The other partners develop services for public transportation (Luxembourg) and urban Traffic management (Spain). The road weather application is exclusively managed by Finnish Meteorological Institute (FMI).
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Wireless Traffic Service Communication Platform for Cars
2007 IEEE Globecom Workshops, 2007Co-Authors: Timo Sukuvaara, Pertti Nurmi, D. Stepanova, P. Eloranta, E. Suutari, K. YlisiurunenAbstract:Wireless communication between vehicles has been widely studied recently and a large number of suggestions for vehicle-to-vehicle communication have been presented. The main focus in these proposals has been on bilateral communication between two vehicles or on broadcasting information from one vehicle or infrastructure to vehicles in the surrounding area. The approach in the Carlink project of the Celtic program call 3 is to develop an intelligent hybrid Wireless Traffic service platform between cars supported with Wireless tranceivers acting as access points beside the road(s). Communication between cars will be arranged in an ad-hoc manner, supported with Wireless base station connection to the backbone network, whenever possible. The primary application is real-time local weather information, but also numerous other applications, such as accident warnings and Traffic intensity information for route planning can be integrated to this kind of a system. In this paper we present the concept and use cases of the Carlink platform. The platform operability and efficiency analysis are topics of future publications.
Oliver W. W. Yang - One of the best experts on this subject based on the ideXlab platform.
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Research on characterization of Wireless LANs Traffic
Communications in Nonlinear Science and Numerical Simulation, 2011Co-Authors: Huifang Feng, Yantai Shu, Oliver W. W. YangAbstract:Abstract In this paper, we employ actual Wireless data that draw from well known archives of network Traffic traces and investigate the characterization of the Wireless LANs Traffic. Firstly, useful preliminary information regarding the general Wireless Traffic dynamics is obtained using one standard statistical technique named Fourier power spectrum. Then the estimation of the parameters, such as the correlation dimension, the largest Lyapunov exponent and the principal components analysis indicate the existence of low-dimensional deterministic chaos in Wireless Traffic time series. Our results also show that the parameters selection of the phase space reconstruction influence the value of the correlation dimension and the largest Lyapunov exponent, but can not influence on diagnosis of chaotic nature of Wireless Traffic.
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Nonlinear analysis of Wireless LAN Traffic
Nonlinear Analysis: Real World Applications, 2009Co-Authors: Huifang Feng, Yantai Shu, Oliver W. W. YangAbstract:Abstract An understanding of Traffic characteristics and accurate Traffic models are necessary for the improvement of the capability of Wireless networks. In this paper we have analyzed the nonlinear dynamical behavior of several real Traffic traces collected from Wireless testbeds. We have found strong evidence that the Wireless Traffic is chaotic from our observations. That is, we found from the correlation dimension, the largest Lyapunov exponent and the principal components for analysis, which are typical indicators of chaotic Traffic. This gives us a good theoretical basis for the analysis and modeling of Wireless Traffic using chaos theory.
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Wireless Traffic Modeling and Prediction Using Seasonal ARIMA Models
IEICE Transactions on Communications, 2005Co-Authors: Yantai Shu, Oliver W. W. Yang, Jiakun Liu, Huifang FengAbstract:Seasonal ARIMA model is a good Traffic model capable of capturing the behavior of a network Traffic stream. In this paper, we give a general expression of seasonal ARIMA models with two periodicities and provide procedures to model and to predict Traffic using seasonal ARIMA models. The experiments conducted in our feasibility study showed that seasonal ARIMA models can be used to model and predict actual Wireless Traffic such as GSM Traffic in China.
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Study on the chaotic nature of Wireless Traffic
Performance Quality of Service and Control of Next-Generation Communication Networks II, 2004Co-Authors: Huifang Feng, Yantai Shu, Oliver W. W. YangAbstract:An understanding of the Traffic characteristics and accurate Traffic models are necessary for the improvement of the capability of Wireless networks. In this paper we have analyzed the non-linear dynamical behavour of several real Traffic traces collected from Wireless testbeds. We have found strong evidence that the Wireless Traffic is chaotic from our observations. That is we found from the Traffic correlation dimension, largest Lyapunov exponent and the principal components analysis, which are typical indicators of chaotic Traffic. This gives us the good theoretical basis for the analysis and modeling of Wireless Traffic using Chaos Theory.
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ICC - Wireless Traffic modeling and prediction using seasonal ARIMA models
IEEE International Conference on Communications 2003. ICC '03., 1Co-Authors: Yantai Shu, Jiakun Liu, Oliver W. W. YangAbstract:Seasonal ARIMA model is a good Traffic model capable of capturing the behavior of a network Traffic stream. In this paper, we give a general expression of seasonal ARIMA models with two periodicities and provide procedures to model and to predict Traffic using seasonal ARIMA models. Our feasibility study experiments showed that seasonal ARIMA models could be used to model and predict actual Wireless Traffic such as GSM Traffic in China.
Shuguang Cui - One of the best experts on this subject based on the ideXlab platform.
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Wireless Traffic prediction with scalable gaussian process framework algorithms and verification
IEEE Journal on Selected Areas in Communications, 2019Co-Authors: Feng Yin, Jiaru Lin, Shuguang CuiAbstract:The cloud radio access network (C-RAN) is a promising paradigm to meet the stringent requirements of the fifth generation (5G) Wireless systems. Meanwhile, the Wireless Traffic prediction is a key enabler for C-RANs to improve both the spectrum efficiency and energy efficiency through load-aware network managements. This paper proposes a scalable Gaussian process (GP) framework as a promising solution to achieve large-scale Wireless Traffic prediction in a cost-efficient manner. Our contribution is three-fold. First, to the best of our knowledge, this paper is the first to empower GP regression with the alternating direction method of multipliers (ADMM) for parallel hyper-parameter optimization in the training phase, where such a scalable training framework well balances the local estimation in baseband units (BBUs) and information consensus among BBUs in a principled way for large-scale executions. Second, in the prediction phase, we fuse local predictions obtained from the BBUs via a cross-validation-based optimal strategy, which demonstrates itself to be reliable and robust for general regression tasks. Moreover, such a cross-validation-based optimal fusion strategy is built upon a well acknowledged probabilistic model to retain the valuable closed-form GP inference properties. Third, we propose a C-RAN-based scalable Wireless prediction architecture, where the prediction accuracy and the time consumption can be balanced by tuning the number of the BBUs according to the real-time system demands. The experimental results show that our proposed scalable GP model can outperform the state-of-the-art approaches considerably, in terms of Wireless Traffic prediction performance.
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Wireless Traffic Prediction with Scalable Gaussian Process: Framework, Algorithms, and Verification
IEEE Journal on Selected Areas in Communications, 2019Co-Authors: Feng Yin, Jiaru Lin, Shuguang CuiAbstract:The cloud radio access network (C-RAN) is a promising paradigm to meet the stringent requirements of the fifth generation (5G) Wireless systems. Meanwhile, Wireless Traffic prediction is a key enabler for C-RANs to improve both the spectrum efficiency and energy efficiency through load-aware network managements. This paper proposes a scalable Gaussian process (GP) framework as a promising solution to achieve large-scale Wireless Traffic prediction in a cost-efficient manner. Our contribution is three-fold. First, to the best of our knowledge, this paper is the first to empower GP regression with the alternating direction method of multipliers (ADMM) for parallel hyper-parameter optimization in the training phase, where such a scalable training framework well balances the local estimation in baseband units (BBUs) and information consensus among BBUs in a principled way for large-scale executions. Second, in the prediction phase, we fuse local predictions obtained from the BBUs via a cross-validation based optimal strategy, which demonstrates itself to be reliable and robust for general regression tasks. Moreover, such a cross-validation based optimal fusion strategy is built upon a well acknowledged probabilistic model to retain the valuable closed-form GP inference properties. Third, we propose a C-RAN based scalable Wireless prediction architecture, where the prediction accuracy and the time consumption can be balanced by tuning the number of the BBUs according to the real-time system demands. Experimental results show that our proposed scalable GP model can outperform the state-of-the-art approaches considerably, in terms of Wireless Traffic prediction performance.
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ICC - Distributed Gaussian Process: New Paradigm and Application to Wireless Traffic Prediction
ICC 2019 - 2019 IEEE International Conference on Communications (ICC), 2019Co-Authors: Feng Yin, Jiaru Lin, Shuguang CuiAbstract:Distributed Gaussian Process (GP) is a scalable Bayesian method that is promising for handling big data. Our contribution in applying GP for Traffic prediction is two-fold. First, to the best of our knowledge, this paper is the first to empower GP regression with the alternating direction method of multipliers (ADMM) for distributed hyper-parameter optimization in the training phase, where the ADMM training framework well balances local estimation and information consensus in a principled way. Second, in the prediction phase, we fuse local predictions obtained from distributed computing units via a cross-validation based optimal strategy, which demonstrates itself to be reliable and robust for general regression tasks. Moreover, the cross-validation based optimal fusion strategy is built upon a well acknowledged probabilistic model to retain the valuable closed-form GP prediction properties. Experimental results show that our proposed distributed GP model can outperform the state-of-the-art distributed GP models considerably, in terms of Wireless Traffic prediction performance.
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Spatio-Temporal Wireless Traffic Prediction With Recurrent Neural Network
IEEE Wireless Communications Letters, 2018Co-Authors: Chen Qiu, Zhiyong Feng, Yanyan Zhang, Ping Zhang, Shuguang CuiAbstract:Accurate prediction of user Traffic in cellular networks is crucial to improve the system performance in terms of energy efficiency and resource utilization. However, existing work mainly considers the temporal Traffic correlation within each cell while neglecting the spatial correlation across neighboring cells. In this letter, machine learning models that jointly explore the spatio-temporal correlations are proposed. Specifically, several recurrent neural network structures are utilized. Furthermore, a multi-task learning approach is adopted to explore the commonalities and differences across cells in improving the prediction performance. Base on real data, we demonstrate the benefits of joint learning over spatial and temporal dimensions.
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GLOBECOM - High-Accuracy Wireless Traffic Prediction: A GP-Based Machine Learning Approach
GLOBECOM 2017 - 2017 IEEE Global Communications Conference, 2017Co-Authors: Feng Yin, Jiaru Lin, Shuguang CuiAbstract:Wireless Traffic prediction can effectively reduce the uncertainty in network demand and supply, and thus is a key enabler of smart management in next-generation Wireless networks. To the best of our knowledge, this paper is the first to establish a Wireless Traffic prediction model by applying the Gaussian Process (GP) method based on real 4G Traffic data. Our work is two-fold: First, based on the observed Wireless Traffic patterns, the kernel in our proposed GP model is designed accordingly to capture both the periodic trend and dynamic deviations; second, by leveraging the Toeplitz structure in the covariance matrix, the computational complexity of hyperparameter learning is significantly reduced from Ο(n^3) to Ο(n^2) and that of inference is reduced from Ο(n^3) to Ο(n \log n), without any loss of prediction accuracy. Experimental results show that the proposed GP model can attain up to 97% prediction accuracy, and outperform the state-of-the-art algorithms considerably.
Huifang Feng - One of the best experts on this subject based on the ideXlab platform.
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Research on characterization of Wireless LANs Traffic
Communications in Nonlinear Science and Numerical Simulation, 2011Co-Authors: Huifang Feng, Yantai Shu, Oliver W. W. YangAbstract:Abstract In this paper, we employ actual Wireless data that draw from well known archives of network Traffic traces and investigate the characterization of the Wireless LANs Traffic. Firstly, useful preliminary information regarding the general Wireless Traffic dynamics is obtained using one standard statistical technique named Fourier power spectrum. Then the estimation of the parameters, such as the correlation dimension, the largest Lyapunov exponent and the principal components analysis indicate the existence of low-dimensional deterministic chaos in Wireless Traffic time series. Our results also show that the parameters selection of the phase space reconstruction influence the value of the correlation dimension and the largest Lyapunov exponent, but can not influence on diagnosis of chaotic nature of Wireless Traffic.
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Nonlinear analysis of Wireless LAN Traffic
Nonlinear Analysis: Real World Applications, 2009Co-Authors: Huifang Feng, Yantai Shu, Oliver W. W. YangAbstract:Abstract An understanding of Traffic characteristics and accurate Traffic models are necessary for the improvement of the capability of Wireless networks. In this paper we have analyzed the nonlinear dynamical behavior of several real Traffic traces collected from Wireless testbeds. We have found strong evidence that the Wireless Traffic is chaotic from our observations. That is, we found from the correlation dimension, the largest Lyapunov exponent and the principal components for analysis, which are typical indicators of chaotic Traffic. This gives us a good theoretical basis for the analysis and modeling of Wireless Traffic using chaos theory.
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Wireless Traffic Modeling and Prediction Using Seasonal ARIMA Models
IEICE Transactions on Communications, 2005Co-Authors: Yantai Shu, Oliver W. W. Yang, Jiakun Liu, Huifang FengAbstract:Seasonal ARIMA model is a good Traffic model capable of capturing the behavior of a network Traffic stream. In this paper, we give a general expression of seasonal ARIMA models with two periodicities and provide procedures to model and to predict Traffic using seasonal ARIMA models. The experiments conducted in our feasibility study showed that seasonal ARIMA models can be used to model and predict actual Wireless Traffic such as GSM Traffic in China.
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Study on the chaotic nature of Wireless Traffic
Performance Quality of Service and Control of Next-Generation Communication Networks II, 2004Co-Authors: Huifang Feng, Yantai Shu, Oliver W. W. YangAbstract:An understanding of the Traffic characteristics and accurate Traffic models are necessary for the improvement of the capability of Wireless networks. In this paper we have analyzed the non-linear dynamical behavour of several real Traffic traces collected from Wireless testbeds. We have found strong evidence that the Wireless Traffic is chaotic from our observations. That is we found from the Traffic correlation dimension, largest Lyapunov exponent and the principal components analysis, which are typical indicators of chaotic Traffic. This gives us the good theoretical basis for the analysis and modeling of Wireless Traffic using Chaos Theory.
