The Experts below are selected from a list of 9597 Experts worldwide ranked by ideXlab platform
Yuji Oie - One of the best experts on this subject based on the ideXlab platform.
-
Flow allocation algorithms for traffic engineering
Lecture Notes in Computer Science, 2003Co-Authors: Manabu Kato, Hironobu Hida Hida, Kenji Kawahara, Yuji OieAbstract:The objective of traffic engineering (TE) is to optimize network resources, while satisfying traffic-oriented performance requirements. As a technology for TE, we focus on a method by which to Avoid Congestion on some links and balance the traffic load over the network. Given a traffic matrix representing traffic demands, we allocate their traffic flows over the network. In this paper, we propose a number of flow allocation algorithms for TE in ISP backbone networks. As an objective function, we employ the maximum link utilization. We then evaluate the effect of the proposed algorithms with respect to load balancing and compare the performance of these algorithms.
-
ICOIN - Flow allocation algorithms for traffic engineering
Information Networking, 2003Co-Authors: Manabu Kato, Hironobu Hida Hida, Kenji Kawahara, Yuji OieAbstract:The objective of traffic engineering (TE) is to optimize network resources, while satisfying traffic-oriented performance requirements. As a technology for TE, we focus on a method by which to Avoid Congestion on some links and balance the traffic load over the network. Given a traffic matrix representing traffic demands, we allocate their traffic flows over the network. In this paper, we propose a number of flow allocation algorithms for TE in ISP backbone networks. As an objective function, we employ the maximum link utilization. We then evaluate the effect of the proposed algorithms with respect to load balancing and compare the performance of these algorithms.
-
Performance analysis of backpressure Congestion control: preliminary case
Proceedings of GLOBECOM '95, 1Co-Authors: K. Kawahara, Yuji Oie, Masayuki Murata, Hideo MiyaharaAbstract:In ATM networks, preventive control is widely recognized as a way to Avoid Congestion efficiently, and it is implemented by a conjunction of call admission control (CAC) and usage parameter control (UPC). However, since Congestion may still happen because of unpredictable statistical fluctuations of traffic injected into networks, it would be effective to relieve Congestion using reactive control together with preventive control. In this paper, we investigate the performance of backpressure control which is a reactive control scheme with an analytical approach. Moreover, we propose backpressure control with cell pushout scheme to overcome some weaknesses of backpressure control. Numerical results show that the control with push-out scheme improves cell loss performance, without increasing delay too much.
Qiong Sun - One of the best experts on this subject based on the ideXlab platform.
-
A Practical Traffic Control Scheme With Load Balancing Based on PCE Architecture
IEEE Access, 2019Co-Authors: Pei Zhang, Kun Xie, Caixia Kou, Xiaohong Huang, Aijun Wang, Qiong SunAbstract:The path computation element (PCE) is used for the path computation for traffic engineering systems such as multi-protocol label switching (MPLS) and Generalized MPLS networks. It offers a good architecture for the centralized traffic routing and control. The classic routing policy aims to select one “best” path for the traffic, which may cause network Congestion in the best link. How to adjust traffic to alleviate or Avoid Congestion is an important issue for operating networks. In this paper, according to the topology and the traffic model of China Telecom’s network, we propose a practical traffic control scheme with load balancing based on the PCE architecture. The objective of the traffic control scheme is twofold. First, an adaptive end-to-end path selection algorithm is proposed to select high-quality main and backup paths with the consideration of cost and path utilization. Second, a global routing optimization algorithm is proposed to adjust the path for the traffic, which considers the Congestion feedback, the adjustment cost, and the expectation of load balance. The results show that our proposed scheme is able to efficiently alleviate or Avoid Congestion problem and achieve good performance in terms of the balance of link utilization and minimum computation time.
Zhongwei Zhang - One of the best experts on this subject based on the ideXlab platform.
-
QSHINE - Performance of STT-Vegas in heterogeneous wired and wireless networks
Proceedings of the 3rd international conference on Quality of service in heterogeneous wired wireless networks - QShine '06, 2006Co-Authors: Hong Zhou, Amoakoh Gyasi-agyei, Zhongwei ZhangAbstract:TCP Vegas is a proactive Congestion control mechanism proposed to improve TCP performance by using Round Trip Time (RTT) as a main parameter to monitor traffic condition and Avoid Congestion. However, TCP Vegas does not perform well on bidirectional links with unbalanced traffic, and on wireless links. A simple Single-Trip Time (STT) based modification to TCP Vegas, namely STT-Vegas, was introduced in [1] to improve the performance of TCP Vegas. It has been demonstrated that STT-Vegas outperforms Vegas in various network scenarios in wireline networks. This paper examines the performance of STT-Vegas in heterogeneous wired and wireless networks and investigates its possible enhancements in such networks
Manabu Kato - One of the best experts on this subject based on the ideXlab platform.
-
Flow allocation algorithms for traffic engineering
Lecture Notes in Computer Science, 2003Co-Authors: Manabu Kato, Hironobu Hida Hida, Kenji Kawahara, Yuji OieAbstract:The objective of traffic engineering (TE) is to optimize network resources, while satisfying traffic-oriented performance requirements. As a technology for TE, we focus on a method by which to Avoid Congestion on some links and balance the traffic load over the network. Given a traffic matrix representing traffic demands, we allocate their traffic flows over the network. In this paper, we propose a number of flow allocation algorithms for TE in ISP backbone networks. As an objective function, we employ the maximum link utilization. We then evaluate the effect of the proposed algorithms with respect to load balancing and compare the performance of these algorithms.
-
ICOIN - Flow allocation algorithms for traffic engineering
Information Networking, 2003Co-Authors: Manabu Kato, Hironobu Hida Hida, Kenji Kawahara, Yuji OieAbstract:The objective of traffic engineering (TE) is to optimize network resources, while satisfying traffic-oriented performance requirements. As a technology for TE, we focus on a method by which to Avoid Congestion on some links and balance the traffic load over the network. Given a traffic matrix representing traffic demands, we allocate their traffic flows over the network. In this paper, we propose a number of flow allocation algorithms for TE in ISP backbone networks. As an objective function, we employ the maximum link utilization. We then evaluate the effect of the proposed algorithms with respect to load balancing and compare the performance of these algorithms.
Alex Anas - One of the best experts on this subject based on the ideXlab platform.
-
the optimal pricing finance and supply of urban transportation in general equilibrium a theoretical exposition
Economics of Transportation, 2012Co-Authors: Alex AnasAbstract:We present a general equilibrium framework of optimal allocation treating the pricing, finance and supply of urban transportation. Uncongested public transportation technology with economies of scale supports the city's existence; and a congested road system subject to constant returns limits urban size. Optimal investment in public transit and in roads follow Samuelson's rule. With optimally determined urban population, roads are fully financed by Pigouvian Congestion tolls while aggregate differential land rents fully finance public transit and any other activity with internal or external economies of scale (Henry George Theorem). Marshallian agglomeration from production in the core and the suburbanization of jobs to Avoid Congestion are treated. We also see how the optimal rules and the Henry George Theorem are modified when the demand for location is determined by a random utility model.
