Customized bus is a typical demand‐responsive transit (DRT) service that allows passengers to customize their bus route on demand and be picked up and dropped off at their desired location. A set of ride requests sent at various times by geographically dispersed passengers are operated in real time by the controller and then assigned to the shared bus with the assurance of maintaining the minimum vehicle and driver costs, which introduces a new challenge to scheduling. In this paper, a mixed integer linear programming (MILP) model is presented to solve the customized bus scheduling problem. To quickly generate satisfactory scheduling solutions in the case of single‐ and multi‐depots, a heuristic multi‐objective optimization algorithm based on preemptive scheduling is proposed, which can converge to the optimal solution among a set of vehicle blocks (consecutive trips by one bus). A real‐world customized bus scheduling problem from the public transport company of Chengdu, China that contains 2,000‐trip instances operated on a day is used to demonstrate that the proposed approach reduces total operating costs by 30.51% and 30.71%, compared with the simulated annealing algorithm and genetic algorithm, respectively.

Energy conserving design is the research focus to prolong the lifetime of wireless sensor networks. A simple and effective way to save energy is to place sensor nodes in sleep mode periodically. However, sleep mode corresponds to low power consumption as well as to reduced network capacity and increased latency. This paper develops an analytical framework to study the interaction between random sleep scheme and network performance. Our framework consists of the queueing model for sensor node and performance model for the whole network. We derived the network throughput, power consumption and packet delivery delay. Our analytical models shed light on the guidelines to design random sleep scheme and enable us to explore the trade-offs existing between sensor sleep/active dynamics and those performance measures.

This letter presents the recursive formulas of the moments of queue length for the M/M/1 queue and M/M/1/B queue, respectively. The higher moments of queue length are important for optimization problem. Our method provides an alternative approach to derive the moments of queue length, instead of taking the derivatives of the moment generating function.

The trade-off between resource efficiency and Quality of Service (QoS) is always a vital issue for communication networks, and link overbooking is a common technique used to improve resource efficiency. How to properly overbook a link and analytically determine its overbooking factor under QoS constraints are still problems, especially when achieving advanced QoS by per-flow queueing, as urged by the emerging mobilized applications in the access networks. This paper first proposes an Opportunistic Link Overbooking (OLO) scheme for an edge gateway to improve its link efficiency, and then develops an integrated analytical framework for determining the suitable link overbooking factor with service guarantee on flow level. In our scheme, once the idle time of a high priority flow's quasi-dedicated link is larger than a specified threshold, the link is temporarily overbooked to a low priority flow; and then when the high priority flow's subsequent packets start arriving, the link can be recovered at the expense of a setup delay. To explore the balance between link efficiency and the flow's QoS in the proposed scheme, we develop the corresponding queueing model under either bounded packet delay (relevant to delaysensitive flow) or finite buffer size (relevant to loss-sensitive flow). Our queueing analysis reveals the inherent trade-offs among the link overbooking factor, packet loss rate and delay/jitter under different traffic patterns.

Sustainable development has become a scientific and decision-making consensus in countries and regions around the world. The current research on sustainable development mainly focuses on urban areas with a high level of economic development and intensive land use. Small-scale research, especially for underdeveloped areas, is required to reveal the spatial patterns and differences within administrative units. This study focuses on 1241 towns in Guangxi to assess the sustainable development process and variations at the township scale from 2014 to 2020 by using the entropy method, the coupled coordination degree method, and cluster analysis. The results show that the average sustainable development goal composite index (SDGCI) of towns in Guangxi is around 0.12, and their overall sustainable development level is low. The SDGCI of towns in the central region shows an increasing trend, while that in the northern and southern regions shows a decreasing trend. Then, the SDGs are divided into three systems, namely people, planet, and prosperity. The prosperity system contributes the most to the overall SDGCI, and the low values of the people and planet systems are the reason for the low level of sustainable development in Guangxi. The coupling degree of the SDGCI among the three systems is at a high level, and the level of coupling coordination degree is good, which indicates high consistency and close linkage of the towns in Guangxi when pursuing the SDGs. The results of hierarchical cluster analysis show that towns in Guangxi can be divided into three categories to adapt to different features based on SDGCI values. The assessment of SDG process in towns in Guangxi could guide local governments to refine their development policy, formulate and adjust development strategies in a targeted manner, and promote balanced and sustainable development under townships.

The high node density, large scale node number and limitation of resource in wireless sensor networks introduce significant challenges when preventing active denial of services (DoS) attacks. This paper established an attacking-defending gaming model, where the strategy space and payoff matrix are given to both the intrusion detection system (IDS) and the malicious nodes. The Nash equilibrium of mixed strategy is then achieved. Simulation results show that our gaming model can detect active DoS attacks effectively.