The Rate Control Index for Traffic Flow

The objective of Air Traffic Flow Management is to maintain safe and efficient use of airspace and airports by regulating theflow of traffic. In this paper, we introduce a single-valued metric for post-operatively rating the performance ofachieved traffic flow against targeted traffic flow. We provide variations on the metric, one of which factors out stochastic conditions upon which a plan is formulated, and show how those improve on current traffic control analysis techniques.The core of the metric is intuitive and simple, yet leads to an interesting optimization problem that can be efficiently solved via dynamic programming. Numerical results of the metric are given as well as a sample of the type of analysis that should follow a low rating by the metric. Although this metric was originally developed to rate the performance of GroundDelay Programs, it is equally applicable to any setting in which the flow of discrete objects such as vehicles is controlled and later evaluated

Active congestion control using ABCD (available bandwidth-based congestion detection).

With the growth of the Internet, the problem of congestion has attained the distinction of being a perennial problem. The Internet community has been trying several approaches for improved congestion control techniques. The end-to-end approach is considered to be the most robust one and it has served quite well until recently, when researchers started to explore the information available at the intermediate node level. This approach triggered a new field called Active Networks where intermediate nodes have a much larger role to play than that of the naive nodes. This thesis proposes an active congestion control (ACC) scheme based on Available Bandwidth-based Congestion Detection (ABCD), which regulates the traffic according to network conditions. Dynamic changes in the available bandwidth can trigger re-negotiation of flow rate. We have introduced packet size adjustment at the intermediate router in addition to rate control at sender node, scaled according to the available bandwidth, which is estimated using three packet probes. To verify the improved scheme, we have extended Ted Faber\u27s ACC work in NS-2 simulator. With this simulator we verify ACC-ABCD\u27s gains such as a marginal improvement in average TCP throughput at each endpoint, fewer packet drops and improved fairness index. Our tests on NS-2 prove that the ACC-ABCD technique yields better results as compared to TCP congestion control with or without the cross traffic. Source: Masters Abstracts International, Volume: 43-03, page: 0870. Adviser: A. K. Aggarwal. Thesis (M.Sc.)--University of Windsor (Canada), 2004

Hop-Based dynamic fair scheduler for wireless Ad-Hoc networks

In a typical multihop Ad-Hoc network, interference and contention increase when flows transit each node towards destination, particularly in the presence of cross-traffic. This paper observes the relationship between throughput and path length, self-contention and interference and it investigates the effect of multiple data rates over multiple data flows in the network. Drawing from the limitations of the 802.11 specification, the paper proposes a scheduler named Hop Based Multi Queue (HBMQ), which is designed to prioritise traffic based on the hop count of packets in order to provide fairness across different data flows. The simulation results demonstrate that HBMQ performs better than a Single Drop Tail Queue (SDTQ) scheduler in terms of providing fairness. Finally, the paper concludes with a number of possible directions for further research, focusing on cross-layer implementation to ensure the fairness is also provided at the MAC layer. © 2013 IEEE

Parameter estimation for stochastic hybrid model applied to urban traffic flow estimation

This study proposes a novel data-based approach for estimating the parameters of a stochastic hybrid model describing the traffic flow in an urban traffic network with signalized intersections. The model represents the evolution of the traffic flow rate, measuring the number of vehicles passing a given location per time unit. This traffic flow rate is described using a mode-dependent first-order autoregressive (AR) stochastic process. The parameters of the AR process take different values depending on the mode of traffic operation – free flowing, congested or faulty – making this a hybrid stochastic process. Mode switching occurs according to a first-order Markov chain. This study proposes an expectation-maximization (EM) technique for estimating the transition matrix of this Markovian mode process and the parameters of the AR models for each mode. The technique is applied to actual traffic flow data from the city of Jakarta, Indonesia. The model thus obtained is validated by using the smoothed inference algorithms and an online particle filter. The authors also develop an EM parameter estimation that, in combination with a time-window shift technique, can be useful and practical for periodically updating the parameters of hybrid model leading to an adaptive traffic flow state estimator

Joint Energy Efficient and QoS-aware Path Allocation and VNF Placement for Service Function Chaining

Service Function Chaining (SFC) allows the forwarding of a traffic flow along a chain of Virtual Network Functions (VNFs, e.g., IDS, firewall, and NAT). Software Defined Networking (SDN) solutions can be used to support SFC reducing the management complexity and the operational costs. One of the most critical issues for the service and network providers is the reduction of energy consumption, which should be achieved without impact to the quality of services. In this paper, we propose a novel resource (re)allocation architecture which enables energy-aware SFC for SDN-based networks. To this end, we model the problems of VNF placement, allocation of VNFs to flows, and flow routing as optimization problems. Thereafter, heuristic algorithms are proposed for the different optimization problems, in order find near-optimal solutions in acceptable times. The performance of the proposed algorithms are numerically evaluated over a real-world topology and various network traffic patterns. The results confirm that the proposed heuristic algorithms provide near optimal solutions while their execution time is applicable for real-life networks.Comment: Extended version of submitted paper - v7 - July 201

Evaluation of Coordinated Ramp Metering (CRM) Implemented By Caltrans

Coordinated ramp metering (CRM) is a critical component of smart freeway corridors that rely on real-time traffic data from ramps and freeway mainline to improve decision-making by the motorists and Traffic Management Center (TMC) personnel. CRM uses an algorithm that considers real-time traffic volumes on freeway mainline and ramps and then adjusts the metering rates on the ramps accordingly for optimal flow along the entire corridor. Improving capacity through smart corridors is less costly and easier to deploy than freeway widening due to high costs associated with right-of-way acquisition and construction. Nevertheless, conversion to smart corridors still represents a sizable investment for public agencies. However, in the U.S. there have been limited evaluations of smart corridors in general, and CRM in particular, based on real operational data. This project examined the recent Smart Corridor implementation on Interstate 80 (I-80) in the Bay Area and State Route 99 (SR-99, SR99) in Sacramento based on travel time reliability measures, efficiency measures, and before-and-after safety evaluation using the Empirical Bayes (EB) approach. As such, this evaluation represents the most complete before-and-after evaluation of such systems. The reliability measures include buffer index, planning time, and measures from the literature that account for both the skew and width of the travel time distribution. For efficiency, the study estimates the ratio of vehicle miles traveled vs. vehicle hour traveled. The research contextualizes before-and-after comparisons for efficiency and reliability measures through similar measures from another corridor (i.e., the control corridor of I-280 in District 4 and I-5 in District 3) from the same region, which did not have CRM implemented. The results show there has been an improvement in freeway operation based on efficiency data. Post-CRM implementation, travel time reliability measures do not show a similar improvement. The report also provides a counterfactual estimate of expected crashes in the post-implementation period, which can be compared with the actual number of crashes in the “after” period to evaluate effectiveness