Graph Routing Research Articles

Nanosatellite-5G Integration in the Millimeter Wave Domain: A Full Top-Down Approach

This paper presents a novel network architecture for an integrated nanosatellite (nSAT)-5G system operating in the millimeter-wave (mmWave) domain. The architecture is realized adopting a delay/disruption tolerant networking (DTN) approach allowing end users to adopt standard devices. A buffer aware contact graph routing algorithm is designed to account for the buffer occupancy of the nSATs and for the connection planning derived from their visibility periods. At the terrestrial uplink, a coded random access is employed to realize a high-capacity interface for the typically irregular traffic of 5G users, while, at the space uplink, the DTN architecture is combined with the contention resolution diversity slotted Aloha protocol to match the recent update of the DVB-RCS2 standard. To achieve a reliable testing of the introduced functionalities, an accurate analysis of the statistic of the signal to interference-plus-noise ratio and of the capture probability at each mmWave link is developed by including interference, shadowing, fading, and noise. The application of the designed architecture to data transfer services in conjunction with possible delay reduction strategies, and an extension to inter-satellite communication, are finally presented by estimating the resulting loss/delay performance through a discrete-time discrete-event platform based on the integration of Matlab with Network Simulator 3.

Assessment of Satellite Contacts Using Predictive Algorithms for Autonomous Satellite Networks

Upcoming Low Earth Orbit Satellite Networks will provide low-latency and high downlink capacity necessary for future broadband communications and Earth Observation missions. This architecture was proposed at the beginning of the 90's, although it has just recently re-gained popularity thanks to the so-called Mega-Constellations. This network is composed of satellites that have Inter-Satellite Links (ISL) to communicate between them. Due to the satellite motion, an ISL is a temporal contact between two satellites characterized by a lifetime in which the communication remains feasible. The determination of a route between distant satellites is a challenging problem in this context. However, the satellite follows a well-known deterministic orbit trajectory, being feasible the prediction of its position by propagating a trajectory model over time. The Contact Graph Routing protocol uses this feature to determine the evolution of the routes by pre-computing on-ground a planning of the satellite contacts. This centralized ground-dependent solution cannot be directly applied in the Internet of Satellites paradigm, which proposes the autonomous deployment of heterogeneous satellite networks without pre-assuming any specific satellite system architecture. Following this concept, the present work proposes a distributed algorithm by which a satellite predicts neighbor contacts, and generates a global contact plan without trajectory propagation. To achieve this solution, an ISL has been modeled as a “close approach” between two satellites, which is characterized by their relative motion. The present work details the predictive algorithm, and evaluates its performance in two scenarios with a hybrid satellite constellation and a mega-constellation.

МЕТОД АНАЛІЗУ РИЗИКІВ ДОСТУПУ ДО АКТИВІВ В СИСТЕМАХ ФІЗИЧНОГО ЗАХИСТУ

The subject of study in the article is asset access risk analysis methods inside a physical object. As an example, we consider the object of the physical security system of a scientific institution (as a block of a territorial element) with a hardware environment in the form of devices with low energy consumption and functioning in the Internet of things. The goal is to create a theoretical and mathematical model and method for analyzing the internal components of a security system and access to assets. The tasks set to cover the development of an approach to the analysis of the level of security, which is ensured by the established system of physical security and the formation of an approach to penetration to access assets. In solving the problems, methods were used such as spatial analysis of the physical distribution of system elements, the formation of route graphs, decomposition of blocks and physical protection algorithms, the study of a complete set of components and an individually oriented security element. The following results were obtained: an approach to the analysis of the security level of a physical object using basic parameters consisting of physical and information variables of existing multiple assets was developed, a mathematical model of the system components, block orientation of the perimeter of the object was built, a sequence of stages of penetration into a protected object using multiple routes was proposed. Conclusions: the scientific novelty of the results is as follows: the method of analyzing asset security through the use of environment variables and physical security controls of the facility, as well as the generation and evaluation of penetration routes to the facility to access critical assets, has been improved.

A Space–Time Graph Based Multipath Routing in Disruption-Tolerant Earth-Observing Satellite Networks

In this paper, we consider the problem of routing in disruption-tolerant-networking-based earth-observing satellite networks, which are characterized by a frequently changing topology and potentially sparse and intermittent connectivity. To handle the routing challenges posed by these properties, we propose a joined space-temporal routing algorithmic framework for those networks, where the time-varying topology is modeled as a space-time graph leveraging the predictability of satellites' relative motions. Based on this graph model, we devise a multipath routing algorithm [minimum-cost constrained multipath (MCMP)] to find a feasible set of available routing paths, through which a certain amount of mission data can be transferred back to ground stations within a tolerable delay with a minimum cost. To comparatively evaluate the performance of MCMP, moreover, we design an earliest arrival multipath routing policy (EAMP) algorithm based on the typical contact graph routing algorithm. The performance comparisons among MCMP, EAMP, and direct transfer strategy are simulated and analyzed.

STAG-Based QoS Support Routing Strategy for Multiple Missions Over the Satellite Networks

As the typical delay tolerant networks, the satellite networks possess the intermittent connections, the large-scale time delays and the time-varying topologies. Obviously, such features seriously affect the delivery of mission data with certain requirements on the traffic or latency. To decrease the delivery time, existing relay-based contact graph routing (CGR) method selects the earliest reachable path to forward mission data. However, this method cannot guarantee the transmission of a large amount data and wastes the rare contact opportunities. Therefore, in this paper, we focus on the transmission QoS problem of multiple missions over the satellite networks, and design a QoS support routing strategy to achieve multiple flow-maximizing paths with acceptable delivery delays. Especially, with the storage time aggregated graph (STAG), we construct an on-demand mission model to depict both the network dynamic characteristics and the different mission requirements, and then reduce the QoS support problem as a graph-based maximum flow problem. To solve this problem, one STAG-based multiple flow-maximizing routing scheme is proposed to ensure the mission QoS and match the rare network resources, which has low computation complexity. Finally, compared with CGR, simulation results demonstrate the proposed scheme can achieve a higher mission completion rate and resource utilization rate.

Latency and Lifetime Enhancements in Industrial Wireless Sensor Networks: A Q-Learning Approach for Graph Routing

Industrial wireless sensor networks usually have a centralized management approach, where a device known as network manager is responsible for the overall configuration, definition of routes, and allocation of communication resources. Graph routing is used to increase the reliability of communication through path redundancy. Some of the state-of-the-art graph-routing algorithms use weighted cost equations to define preferences on how the routes are constructed. The characteristics and requirements of these networks complicate to find a proper set of weight values to enhance network performance. Reinforcement learning can be useful to adjust these weights according to the current operating conditions of the network. In this article, we present the Q-learning reliable routing with a weighting agent approach, where an agent adjusts the weights of a state-of-the-art graph-routing algorithm. The states of the agent represent sets of weights, and the actions change the weights during network operation. Rewards are given to the agent when the average network latency decreases or the expected network lifetime increases. Simulations were conducted on a WirelessHART simulator considering industrial monitoring applications with random topologies. Results show, in most cases, a reduction of the average network latency while the expected network lifetime and the communication reliability are at least as good as what is obtained by the state-of-the-art graph-routing algorithms.

SEMANTIC ENRICHMENT OF ROUTING ENGINES USING LINKED DATA: A CASE STUDY USING GRAPHHOPPER

Abstract. Traveling is a basic part of our daily life, whenever a person wants to travel e.g. from home to workplace, the essential question that rises is which route to follow. The choice of a route also varies based on traveler’s interest e.g. visiting hospital on way back to home or traveling on a greener route. This varied route planning may be easy for any person in his local neighborhood, however in a new neighborhood and increasing number of options e.g. possible restaurant options to visit, a guiding system is required that suggests an optimal route according to traveler’s interests i.e. answering semantic queries. Most of the existing routing engines only answer geometric queries e.g. shortest route due to lack of data semantics and adding semantics to a routing graph requires a semantic data source. Geo-semantics can be added through combination of GIS and semantic web. Semantic web is an extension of World Wide Web (WWW) where the content is maintained and structured in a standard way that is understandable by machines; hence providing linked data as a way for semantic enrichment, in this study the semantic enrichment of routing dataset. To use this semantically enriched routing network a routing application needs to be developed that can answer the semantic queries. This research serves as a proof of concept for how linked data can be used for semantic enrichment of routing networks and proposes a prototype routing framework and application designed using open source technologies along with use cases where semantic routing queries are addressed. It also highlights the challenges of this approach and future research perspectives.

Distributed Graph Routing and Scheduling for Industrial Wireless Sensor-Actuator Networks

Wireless sensor-actuator networks (WSANs) technology is appealing for use in the industrial Internet of Things (IoT) applications because it does not require wired infrastructure. Battery-powered wireless modules easily and inexpensively retrofit existing sensors and actuators in the industrial facilities without running cabling for communication and power. The IEEE 802.15.4-based WSANs operate at low-power and can be manufactured inexpensively, which makes them ideal where battery lifetime and costs are important. Almost, a decade of real-world deployments of WirelessHART standard has demonstrated the feasibility of using its core techniques including reliable graph routing and time slotted channel hopping (TSCH) to achieve reliable low-power wireless communication in the industrial facilities. Today, we are facing the fourth Industrial Revolution as proclaimed by political statements related to the Industry 4.0 Initiative of the German Government. There exists an emerging demand for deploying a large number of field devices in an industrial facility and connecting them through the WSAN. However, a major limitation of current WSAN standards is their limited scalability due to their centralized routing and scheduling that enhance the predictability and visibility of network operations at the cost of scalability. This paper decentralizes the network management in WirelessHART and presents the first Di stributed ${G}$ raph routing and autonomous ${S}$ cheduling (DiGS) solution that allows the field devices to compute their own graph routes and transmission schedules. The experimental results from two physical testbeds and a simulation study shows our approaches can significantly improve the network reliability, latency, and energy efficiency under dynamics.

Generating a node in an AIS-based routing graph for improved Estimated Time of Arrival. (Big) Data challenge: using AIS for generating a routing graph

For the international exchange of goods, an exact estimated time of arrival (ETA), especially in case of delays, is of great importance. Using global data of the automatic identification system (AIS) a grid node is generated. The sum of such nodes and their connections form a routing graph. As an example, with one node of in total more than 100,000 nodes it is described how this point gets the maximum vessel length and draft assigned.

Analysis of Information Interaction Efficiency in Low-Orbit Satellite Constellations

The objects of the research are networks and information interactions in low-orbit satellite constellations performing tasks of remote sensing of the Earth. Research of network creation questions in this case is a necessary condition as opportunities and efficiency of information interaction directly depend on opportunities of a network. DTN (Delay-and-Disruption Tolerant Networking) technology is a basis of the network creation and CGR (Contact Graph Routing) approach is a basis of message routing. DTN technology and CGR approach are originally developed and used to provide communication with spacecraft located in a deep space. Therefore, the article discusses issues and problems arising in the context of their use in relation to low-orbit satellite constellations. The purpose of the information interaction study is development of effective interaction schemes (protocols). In the paper, the schemes of information interaction that can be used by a group of satellites in case of autonomous planning are considered. Along with autonomous planning, the paper also considers information interaction that can be used to implement network control of a satellite constellation in the case of ground planning. The effectiveness of the information interaction schemes are assessed by efficiency of orders’ execution. Measurement of efficiency is estimated via simulation of the communication network and the corresponding scheme of information interaction.

Spatio-Temporal Graph Routing for Skeleton-Based Action Recognition

With the representation effectiveness, skeleton-based human action recognition has received considerable research attention, and has a wide range of real applications. In this area, many existing methods typically rely on fixed physicalconnectivity skeleton structure for recognition, which is incapable of well capturing the intrinsic high-order correlations among skeleton joints. In this paper, we propose a novel spatio-temporal graph routing (STGR) scheme for skeletonbased action recognition, which adaptively learns the intrinsic high-order connectivity relationships for physicallyapart skeleton joints. Specifically, the scheme is composed of two components: spatial graph router (SGR) and temporal graph router (TGR). The SGR aims to discover the connectivity relationships among the joints based on sub-group clustering along the spatial dimension, while the TGR explores the structural information by measuring the correlation degrees between temporal joint node trajectories. The proposed scheme is naturally and seamlessly incorporated into the framework of graph convolutional networks (GCNs) to produce a set of skeleton-joint-connectivity graphs, which are further fed into the classification networks. Moreover, an insightful analysis on receptive field of graph node is provided to explain the necessity of our method. Experimental results on two benchmark datasets (NTU-RGB+D and Kinetics) demonstrate the effectiveness against the state-of-the-art.

A DTN Routing Scheme for LEO Satellites Topology

In delay/disruption-tolerant satellite networks, the existing routing algorithms have problems of long transmission delay, high packet loss rate, excessive network overhead and other issues. In the view of these shortcomings, an improved contact graph routing algorithm, ICGR, is proposed in this paper. Firstly, the impact of queuing delay is considered by defining a queue factor and proposing a queue scheduling mechanism in routing calculation; secondly, the effects of contact’s remaining capacity are taken into account to avoid the selected path being unable to forward the messages; thirdly, routing update mechanism is optimized by designing a message path update factor to strike a balance between real-time updates of transmission and resource consumption; finally, a LEO satellite network simulation platform is built with OPNET to verify the performance of this algorithm. Simulation results show that the ICGR, compared with the ED and CGR algorithm, has advantage in packet delivery rate, average transmission delay and network overhead.

Delay-Constrained Routing via Heterogeneous Vehicular Communications in Software Defined BusNet

As a critical part of public transportation systems, buses driving routinely in urban areas naturally form a bus ad-hoc network (BusNet). Different from conventional vehicular ad-hoc networks, the sparse distribution of buses magnifies the problem of intermittent network connectivity, making it more challenging for real-time routing. In this paper, we first present a novel architecture called software-defined BusNet, where the distributed controllers (i.e., base stations) collect traffic information and real-time requests from buses via vehicle-to-cellular communication. The collected information enables the logically centralized controller to make routing decisions with global traffic information. Then, the routing decisions are returned to roadside units (RSUs) and buses, which will instruct the data broadcast from RSUs to buses via vehicle-to-roadside (V2R) communication, and data forwarding among the buses through vehicle-to-vehicle (V2V) communication. On this basis, we formulate the problem of delay-constrained routing for BusNet (DCRB) which aims to maximize both the delivery ratio and the bandwidth efficiency. We build a probabilistic model to analyze the encounter probability and encounter delay between the relay buses based on the predicable bus traces. Further, we derive the expected reachability and expected delivery delay of the multi-hop routing path. The routing graph is constructed for searching the feasible routing paths via the modified Dijkstra algorithm. Four routing selection strategies are proposed based on different metrics: HRF (highest reachability first), SDF (shortest delivery delay first), MHF (minimum number of hops first), and RDH (combination of reachability, delay, and hop). Finally, we build the simulation model and implement the proposed routing algorithms for performance evaluation. The comprehensive simulation results demonstrate that RDH achieves the best overall performance on improving system delivery ratio and enhancing bandwidth efficiency.

Markov decision process‐based routing algorithm in hybrid Satellites/UAVs disruption‐tolerant sensing networks

Recently, a hybrid remote sensing network constituted by satellites in constellation and Unmanned Aerial Vehicles (UAVs) in formation attracts a lot of interests, benefiting from the flexible architecture and excellent rapid responsiveness. Considering frequently intermittent connectivity and limited resource onboard, Disruption-Tolerant Networking (DTN) develops a feasible solution for the remote sensing scenarios. However, the intrinsic motion models of multifarious nodes lead to deterministic or semi-deterministic contacts, which makes finding a reliable end-to-end routing path for timely data delivery difficult, with typical routing strategies such as Contact Graph Routing (CGR). To cope with such routing challenge in the hybrid network, a Probabilistic Contact Graph (PCG) is designed, taking the diverse node properties into consideration. In particular, a probability prediction model for semi-deterministic contacts between the UAV nodes is proposed, with a semi-Markov motion model for the UAV nodes. Besides, a Markov Decision Process based Routing (MDPR) algorithm is designed to search for a feasible data transmission path with a series of hybrid deterministic and semi-deterministic contacts. Through the numerical and experimental simulations with Interplanetary Overlay Network (ION), the proposed MDPR algorithm shows excellent routing performance concerning delivery delay and delivery ratio, compared with the typical CGR strategy.

Aggregated multi-attribute query processing in edge computing for industrial IoT applications

The popularity of smart things constructs sensing networks for the Internet of Things (IoT), and promotes intelligent decision-makings to support industrial IoT applications, where multi-attribute query processing is an essential ingredient. Considering the huge number of smart things and large-scale of the network, traditional query processing mechanisms may not be applicable, since they mostly depend on a centralized index tree structure. To remedy this issue, this article proposes a multi-attribute aggregation query mechanism in the context of edge computing, where an energy-aware IR-tree is constructed to process query processing in single edge networks, while an edge node routing graph is established to facilitate query processing for marginal smart things contained in contiguous edge networks. This decentralized and localized strategy has shown its efficiency and applicability of query processing in IoT sensing networks. Experimental evaluation results demonstrate that this technique performs better than the rivals in reducing the traffic and energy consumption of the network.

Graph Routing Problem Using Euler’s Theorem and Its Applications

In this modern era, time and cases related to time is very important to us. For shortening time, Eulerian Circuit can open a new dimension. In computer science, social science and natural science, graph theory is a stimulating space for the study of proof techniques. Graphs are also effective in modeling a variety of optimization cases like routing protocols, network management, stochastic approaches, street mapping etc. Konigsberg Bridge Problem has seven bridges linked with four islands detached by a river in such a way that one can’t walk through each of the bridges exactly once and returning back to the starting point. Leonard Euler solved it in 1735 which is the foundation of modern graph theory. Euler’s solution for Konigsberg Bridge Problem is considered as the first theorem of Graph Theory which gives the idea of Eulerian circuit. It can be used in several cases for shortening any path. From the Konigsberg Bridge Problem to ongoing DNA fragmentation problem, it has its applications. Aiming to build such a dimension using Euler’s theorem and Konigsberg Bridge Problem, this paper presents about the history of remarkable Konigsberg Bridge Problem, Euler’s Explanation on it, an alternative explanation and some applications to Eulerian Circuit using graph routing and Fortran Coding of it.

Construction and Local Routing for Angle-Monotone Graphs

A geometric graph in the plane is angle-monotone of width $\gamma$ if every pair of vertices is connected by an angle-monotone path of width $\gamma$, a path such that the angles of any two edges in the path differ by at most $\gamma$. Angle-monotone graphs have good spanning properties. We prove that every point set in the plane admits an angle-monotone graph of width $90^\circ$, hence with spanning ratio $\sqrt 2$, and a subquadratic number of edges. This answers an open question posed by Dehkordi, Frati and Gudmundsson. We show how to construct, for any point set of size $n$ and any angle $\alpha$, $0 < \alpha < 45^\circ$, an angle-monotone graph of width $(90^\circ+\alpha)$ with $O(\frac{n}{\alpha})$ edges. Furthermore, we give a local routing algorithm to find angle-monotone paths of width $(90^\circ+\alpha)$ in these graphs. The \emph{routing ratio}, which is the ratio of path length to Euclidean distance, is at most $1/\cos(45^\circ + \frac{\alpha}{2})$, i.e., ranging from $\sqrt 2 \approx 1.414$ to $2.613$. For the special case $\alpha = 30^\circ$, we obtain the full-$\Theta_6$-graph and our routing algorithm achieves the known routing ratio 2 while finding angle-monotone paths of width $120^\circ$.

Investigation of methods for solving a large dimensional routing problem

In this paper, we researched methods for solving a large-scale vehicle routing problem. First, we provided the description of the problem that modern logistic companies encounter during the planning of transportations. As a solution for this problem, we used meta-heuristics and clustering algorithms. Existing studies and publications in the field of large-scale routing were analyzed, giving us the opportunity to assess the quality of the presented meta-heuristics and select those that lead to the best results. The definition of the routing problem is presented, as well as the description of requirements and limitations for the final solution. Then, in the main part of the work, we offer a brief overview of the Clark-Wright heuristic, which we use to build initial solutions. Also we give a brief description of Guided Local Search and Tabu Search algorithms. Both meta-heuristics help to improve the initial solution obtained using the local search algorithms, while avoiding falling into local minima. The K-Means and Mean-Shift clustering algorithms are described and used to speed up the calculation of the solution and eliminate unnecessary costs during routes optimization. Finally, to check the quality of the proposed solution, we developed software that implements the described meta-heuristics and clustering algorithms, and provides the routing results in the form of a route graph and its total length. The program was tested on the set of benchmarks of the Belgian roads, which were provided in the work of F. Arnold, M. Gendreau, K. Sorensen K. The results of comparison with the best solutions are provided along with the conclusion on the optimality of the results obtained. That allows us to assert that in less than ten minutes of solving a problem on each of the clusters, the developed software gives results that differ from the best known only by 5-7%. Further work will be aimed at improving the results by exchanging points between neighboring clusters.

An Equilibrium Strategy-Based Routing Optimization Algorithm for Wireless Sensor Networks.

In energy-constrained wireless sensor networks (WSNs), the design of an energy-efficient smart strategy is a key to extend the network lifetime, but the unbalance of energy consumption and node load severely restrict the long-term operation of the network. To address these issues, a novel routing algorithm which considers both energy saving and load balancing is proposed in this paper. First of all, the transmission energy consumption, node residual energy and path hops are considered to create the link cost, and then a minimum routing graph is generated based on the link cost. Finally, in order to ensure the balance of traffic and residual energy of each node in the network, an “edge-cutting” strategy is proposed to optimize the minimum routing graph and turn it into a minimum routing tree. The simulation results show that, the proposed algorithm not only can balance the network load and prolong the lifetime of network, but meet the needs of delay and packet loss rate.

Vertex Labeling and Routing for Farey-Type Symmetrically-Structured Graphs

The generalization of Farey graphs and extended Farey graphs all originate from Farey graphs. They are simultaneously scale-free and small-world. A labeling of the vertices for them are proposed here. All of the shortest paths between any two vertices in these two graphs can be determined only on their labels. The number of shortest paths between any two vertices is the product of two Fibonacci numbers; it is increasing almost linearly with the order or size of the graphs. However, the label-based routing algorithm runs in logarithmic time O(logn). Our efficient routing protocol for Farey-type models should help contribute toward the understanding of several physical dynamic processes.