Busfinder: A Personalized Multimodal Transportation Guide with Dynamic Routing

In our previous work, we elaborated the multistage virtual path (VP) control strategy and the VP topology optimization problem in which we assume a set of alternative routes exist between each source-destination (SD) pair. In the first part of this paper, a supplementary algorithm, which can yield all possible routes between two nodes and can be used for general routing problems, is provided. Based this algorithm, a dynamic VC routing policy is studied. The proposed policy distinguishes from other strategies in that it is considered in a generic networking environment. In the last part of this paper, we present a dynamic VP routing algorithm which is an important component of the dynamic VC routing policy. Detailed analyses and experimental results demonstrate these algorithms are correct, practical and useful.

The capsule network is a novel architecture to encode feature attributes and spatial relationships of an image. By using the dynamic routing (DR) algorithm, a capsule network (CapsNet) model can be trained. However, the original three-layer CapsNet with the DR algorithm performs poorly on complex data sets, such as FashionMNIST, CIFAR-10, and CIFAR-100. This deficiency limits the wider application of capsule networks. In this article, we propose a deep capsule network model combined with a U-Net preprocessing module (DCN-UN). Local connection and weight-sharing strategies are adopted from convolutional neural networks to design a convolutional capsule layer in the DCN-UN model. This allows considerably reducing the number of parameters in the network model. Moreover, a greedy strategy is incorporated into the design of a mask DR (MDR) algorithm to improve the performance of network models. DCN-UN requires up to five times fewer parameters compared with the original CapsNet and other CapsNet-based models. The performance improvement achieved by the DCN-UN model with the MDR algorithm over the original CapsNet model with the DR algorithm is approximately 12% and 17% on the CIFAR-10 and CIFAR-100 data sets, respectively. The experimental results confirm that the proposed DCN-UN model allows preserving advantages of image reconstruction and equivariance mechanism in capsule networks. Moreover, an efficient initialization method is explored to enhance training stability and avoid gradient explosion.

In this paper we devise an highly-efficient load balancing algorithm, called LB-HTA, for the dynamic provisioning of connections with known duration in WDM networks. We introduce a time-dependent link-weight assignment that captures future congestion of links, leveraging the knowledge of connection durations. By means of an extensive set of simulative experiments, we compare our approach to other traditional, yet holding-time agnostic, dynamic routing algorithms. For a typical US nationwide network, LB-HTA obtains significant saving in blocking probability for practical scenarios. Moreover, we address two key-questions regarding holding-time-aware dynamic routing. Three main traffic models are considered here, namely i) dynamic traffic, ii) dynamic traffic with known durations and iii) scheduled traffic: how much the knowledge of connection durations improves the performance with respect of a holding-time- agnostic solution? Is the obtained solution close to the most effective solution provided by scheduled traffic? In order to exhaustively evaluate the performance of LB-HTA, we consider as benchmark the solution obtained under the well-known Scheduled Traffic model (TI-ST) and also under an approximated, but more effective, approach for traffic scheduling, called Time-Variant Scheduled Traffic (TV-ST). For both TI-ST and TV-ST, Integer Linear Program (ILP) formulations are proposed and results compared with dynamic routing algorithms.

The current socio-economic conditions of some developed and developing countries are not favorable for the development of the public mass transport services. Most of the residents of large and medium-sized cities, but also smaller towns, use their own passenger car on mandatory trips. This phenomenon perfectly reflects the constantly growing of motorization index in such countries. The consequence of this is, of course, the decreasing number of passengers carried by means of public mass transport, in particular operating outside of large urbanized areas. This causes and unfortunately will cause not only further problems of automotive congestion on the transport networks of urban areas, reduction of the road safety level, but also adverse environmental effects in the form of pollution. The authors of the article analyzed the results of transport surveys, which were carried out in recent years among the public transport passengers. The surveys concerned the assessments and postulates and expectations of passengers. The research was carried out in one of the typical in terms of socio-economic conditions of Polish voivodships (a country dynamically developing in the passenger transport sector, in terms of both mobility, as well as the quantitative and qualitative status of transport means and transport infrastructure). The voivodship subjected to such analysis was the Kuyavian-Pomeranian Voivodship, located in the central part of Poland. The respondents were asked to speak on topics related to, among others, transport infrastructure, means of transport, access to services of public transport systems, comfort and safety of traveling. The analysis also included assessments and postulates related to tariff systems, travel information systems, and transport integration systems - functioning in the voivodship. The results of the research were analyzed by the rail passenger transport and bus passenger transport as part of the voivodship public transport system. In the majority of cases, passengers’ assessments were not satisfactory. The most frequently issued evaluations fluctuated only around the average (on a scale from 1 to 10). The authors have thoroughly analyzed the results of the transport survey, confronting the results obtained and trying to find out their causes depending on the characteristics of the area under analysis.

Dynamic routing algorithm based on the shortest path principle is criticized due to the oscillation induced by such routing scheme. In the present work, we propose the model of TCP/RED algorithm by a new frame of dynamic routing, based on the measurement of occupation ratio of router buffer for different links, which only requires the information of the queue size at the buffer of the router, to stabilize the system. We classify several types of equilibrium and employ the numerical method to study the stability of the steady state. Our numerical results show that the careful selection of the parameters characterizing the dynamic routing algorithm can stabilize the system in some cases.

With development of Internet of Things, wireless sensor networks (WSN) become larger and larger and if the present clustering and routing methods are widely used in large scale WSN, “energy hole” problem will deteriorate. To alleviate “energy hole” problem of WSN, a dynamic broadcast radius-based clustering and routing algorithm (DBRCR) is proposed. The algorithm calculates node broadcast radius every round, and based on the broadcast radius the neighbor table is established. Then according to the degrees of nodes, construct clusters iteratively. Finally, finding intra-cluster communication path based on data transmission success rate and routing for the inter-cluster communication based on nodes' residual energy and transmission energy consumption to minimize the data packet-loss rate and prolong the network lifetime.

For monitoring burst events in a kind of reactive wireless sensor networks (WSNs), a novel scheme of dynamic clustering routing algorithm (DCRA) based on support degree is proposed. The new approach lets sensors decide whether become a clusterhead (CH) according to the support degree coming from neighbors. Unlike traditional distributed clustering algorithms, DCRA combines energy, load balancing and topology information together by defining an objective function based on support degree. Furthermore, the clusterhead aggregates data and transmits the result to base station (sink node) along multiple paths. The new algorithm is completely distributed and location-unaware. Simulation results show that DCRA has great potential in efficiently distributing energy consumption and extending the network lifetime.

This study describes a non-dominated algorithm which we call the dynamic multi-objective routing algorithm (DyMORA) developed to improve the simple hybrid routing protocol (SHRP) in choosing the best route towards the Sink node. The multi-objective approach presented allows simultaneous analysis of the four metrics used in the protocol and generates a Pareto-optimal solution. The performance of SHRP concerned to time convergence and reliability with and without DyMORA was analysed via simulation tool NS-2. The performance of SHRP with DyMORA proved to have closed performance to the original SHRP protocol and in many cases superior performance, despite the use of a more complex election algorithm.

Today's networks are dominantly based on the Shortest Path First (SPF) routing algorithms. These algorithms assign weighting factors to links statically, such that the routing tables are recalculated only when a topology change occurs. As a result, the network traffic is often unevenly distributed, thus causing the congestion on some links even when the total traffic load is not particularly high. In this paper, we discuss how the above-mentioned problem could be alleviated by applying dynamic routing in Software-Defined Networks (SDNs). We propose three new dynamic routing algorithms and present their OpenFlow-based implementation. The efficiency of the proposed solutions has been verified on two OpenFlow network topologies in Mininet emulator. The obtained results show that the proposed solutions could significantly improve the network throughput in comparison to SPF routing model used in traditional networks.

The research, development, and deployment of wavelength division multiplexing (WDM) technology are now evolving at a rapid pace to fulfill the increasing bandwidth requirement and deploy new network services. Routing and wavelength assignment algorithms play a key role in improving the performance of wavelength-routed all-optical networks. We study networks with dynamic wavelength routing and develop accurate analytical models for evaluating the blocking performance under dynamic input traffic in different topologies. Two dynamic routing algorithms are first developed and the performances of the algorithms in single-fiber WDM networks are studied using both analytical models and simulation. We also develop efficient algorithms to optimally place a given number of wavelength converters on a path of a network. Finally we consider the effect of multiple fibers on WDM networks without wavelength conversion. We develop analytical models for evaluating the blocking performance of multifiber networks with fixed-path routing, alternate-path routing, and fixed-path least-congestion routing algorithms. The number of fibers required to provide high performance in multifiber networks with different routing algorithms are also studied.

Dynamic routing algorithms have transformed contact center operations through AI-driven decision-making and real-time data analytics. These systems optimize customer-agent matching while enhancing operational efficiency through intelligent queue management and predictive analytics. The integration of machine learning, natural language processing, and sentiment analysis capabilities has revolutionized how contact centers handle customer interactions, leading to improved resolution rates and customer satisfaction. Cloud-native solutions and emerging technologies continue to advance routing capabilities, offering scalable and adaptable systems that respond to changing customer needs and business requirements. The sophisticated architecture of these systems incorporates multiple layers of data processing and decision intelligence, enabling real-time adaptation to changing interaction patterns and customer preferences. Advanced analytics components process vast amounts of historical and real-time data to create comprehensive customer profiles and interaction histories, facilitating more precise routing decisions. The implementation of dynamic routing algorithms has demonstrated significant improvements across key performance indicators, including reduced handling times, improved first-contact resolution rates, and enhanced customer experience metrics. Furthermore, the integration of artificial intelligence and machine learning continues to push the boundaries of routing sophistication, enabling more nuanced understanding of customer intent and emotional states, while cloud-based infrastructure ensures scalability and reliability across diverse operational environments.

In this paper we present a new dynamic routing algorithm specially implemented for a new electronic tissue called POEtic. This reconfigurable circuit is designed to ease the implementation of bio-inspired systems that bring cellular applications into play. Specifically designed for implementing cellular applications, such as neural networks, this circuit is composed of two main parts: a two-dimensional array of basic elements similar to those found in common commercial FPGAs, and a two-dimensional array of routing units that implement a dynamic routing algorithm which allows the creation of data paths between cells at runtime.KeywordsClock CycleEvolvable HardwareSpike Neural NetworkAdvance RISC MachineShift MemoryThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Multi-layer capsule network with joint dynamic routing for fire recognition

Wireless Sensor Networks (WSNs) is one of the most rapidly growing research domain.This is because of the development of sensor nodes with extremely low cost and the applications of such sensor nodes are ever growing.WSNs are group of sensor nodes with a set of processors and limited memory unit.Reliable routing of packets from sensor nodes to its base station is the most important task for these networks.Also mobility of the nodes is considered to be one major criterion for WSNs.In this paper, a dynamic routing algorithm called the Mobility Assisted Dynamic Routing (MADR) algorithm has been proposed for the mobile wireless sensor networking system, where both the base station and the sensor nodes are in moving condition.The cluster head selection is based on three parameters: the energy efficiency of the sensor nodes, the mobility of the sensor nodes and the accessibility to the neighboring sensor nodes.The concept of cluster head panel is applied additionally to minimize the re-clustering time.The proposed algorithm is compared with an existing algorithm Low Energy Adaptive Clustering Hierarchy (LEACH).The simulation results show an excellent prolongation in overall network lifetime.

The trend to implement the monitoring system with a wireless sensor network has been becoming urgent due to guaranteed flight safety and the passengers comfortability in travel. In this paper, a new dynamic routing algorithm is proposed to prolong the lifetime of the monitoring system with a distributed network based on the K‐coverage method, and filter algorithm to be used for data fusion. Finally, the simulation results validate the effectiveness of the proposed approach.