Equitable Vessel Traffic Scheduling in a Seaport

In the global maritime transportation network, the on-time performance of cargo transportation depends largely on the service capacity and accessibility of seaports. When opportunities for infrastructure expansions are not available, seaport congestion mitigation may require effective scheduling of the vessel traffic in the port waters. Although existing works on vessel traffic scheduling focus on minimizing vessel delays, this paper studies a novel vessel traffic scheduling problem that aims to address the inter-shipping line equity issue. We develop a lexicographic optimization model that accounts for two conflicting performance measures: efficiency, which favors minimizing total vessel delay; and equity, which favors balancing the impacts of delays fairly among shipping lines. Our model allows the port operator to quantify the efficiency-equity tradeoff and make the best vessel traffic scheduling decisions. For solving the model, we develop an effective two-stage solution method in which the first stage solves two single-objective models to obtain the maximum system efficiency and equity, whereas the second stage trades between efficiency and equity and seeks the best compromise between the two conflicting objectives. We apply our model and solution method on instances generated from the operational data of the Port of Shanghai. Our computational results show that an efficiency-oriented model can lead to highly inequitable traffic plans, whereas inter-shipping line equity can be achieved at only mild losses in efficiency, indicating that the consideration of inter-shipping line equity can lead to satisfactory service at both the vessel level and the shipping line level.

TDTS: Three-Dimensional Traffic Scheduling in Optical Fronthaul Networks with Conv-LSTM

Given the more intensive deployments of emerging Internet of Things applications with beyond-fifth-generation communication, the access network becomes bandwidth-hungry to support more kinds of services, requiring higher resource utilization of the optical fronthaul network. To enhance resource utilization, this study novelly proposed a three-dimensional traffic scheduling (TDTS) scheme in the optical fronthaul network. Specifically, large and mixed traffic data with multiple different requirements were firstly divided according to three-dimensions parameters of traffic requests, i.e., arriving time, transmission tolerance delay, and bandwidth requirements, forming eight types of traffic model. Then, historical traffic data with division results were put into convolutional-long short-term memory (Conv-LSTM) strategy for traffic prediction, obtaining a clear traffic pattern. Next, the traffic processing order was supported by a priority evaluation factor that was measured by traffic status of the link and network characteristics comprehensively. Finally, following the priority, the proposed TDTS scheme assigned the resource to traffic requests according to their results of traffic division, prediction, and processing order with the shortest path routing and first-fit spectrum allocation policies. Simulation results demonstrated that the proposed TDTS scheme, on the premise of accurate traffic prediction, could outperform conventional resource-allocation schemes in terms of blocking probability and resource utilization.

A QoS-aware Scheduling with Node Grouping for IEEE 802.11ah

The recent IEEE 802.11ah amendment has proven to be suitable for supporting large-scale devices in Internet of Things (IoT). It is essential to provide a minimum level of Quality of Service (QoS) for critical applications such as industrial automaton and healthcare. In this paper, we propose a QoSaware Medium Access Control (MAC) layer solution to enhance network reliability and reduce critical traffic latency by an adaptive station grouping and a priority traffic scheduling scheme. The proposed grouping scheme calculates the current traffic load and distributes among different RAW groups considering different requirements of the stations. The RAW scheduling scheme further provides priority slot access using a novel backoff scheme. Markov-chain model is developed to study the throughput and latency behaviours for the traffic generated from the critical application. The proposed protocol shows significant delay improvement for priority traffic. The overall throughput performance improves up to 12.7% over the existing RAW grouping scheme.