Link Assignment Research Articles

Further investigation on the super classical mean labeling of graphs obtained from paths

Consider the graph G, with the injection Ω from node set to the first p + q natural numbers. Let us assume that the ceiling function of the classical average of the node labels of the end nodes of each link is the induced link assignment Ω *. If the union of range of Ω of node set and the range of Ω * of link set is all the first p + q natural numbers, then Ω is called a classical mean labeling. A super classical mean graph is a graph with super classical mean labeling. In this research effort, we attempted to address the super classical meanness of graphs generated by paths and those formed by the union of two graphs.

Numerical and Scientific Investigation of Some Molecular Structures Based on the Criterion of Super Classical Average Assignments

Numbering a graph is a very practical and effective technique in science and engineering. Numerous graph assignment techniques, including distance-based labeling, topological indices, and spectral graph theory, can be used to investigate molecule structures. Consider the graph G, with the injection Ω from the node set to 1,2,…,∆, where ∆ is the sum of the number of nodes and links. Assume that the induced link assignment Ω∗ is the ceiling function of the average of root square, harmonic, geometric, and arithmetic means of the vertex labels of the end vertices of each edge. If the union of range of Ω of the node set and the range of Ω of the link set is the set 1,2,…,∆, then Ω is called a super classical average assignment (SCAA). This is known as the SCAA criterion. In this study, the graphical structures corresponding to chemical structures based on the SCAA criterion are demonstrated. The graphical depiction of chemical substances was first defined and second, the union of any number of cycles Cn, the tadpole graph, the graph extracted by identifying a line of any two cycles Cm and Cn, and the graph extracted by joining any two cycles by a path are all examined in this work.

AALLA: Attack-Aware Logical Link Assignment Cost-Minimization Model for Protecting Software-Defined Networks against DDoS Attacks.

Software-Defined Networking (SDN), which is used in Industrial Internet of Things, uses a controller as its "network brain" located at the control plane. This uniquely distinguishes it from the traditional networking paradigms because it provides a global view of the entire network. In SDN, the controller can become a single point of failure, which may cause the whole network service to be compromised. Also, data packet transmission between controllers and switches could be impaired by natural disasters, causing hardware malfunctioning or Distributed Denial of Service (DDoS) attacks. Thus, SDN controllers are vulnerable to both hardware and software failures. To overcome this single point of failure in SDN, this paper proposes an attack-aware logical link assignment (AALLA) mathematical model with the ultimate aim of restoring the SDN network by using logical link assignment from switches to the cluster (backup) controllers. We formulate the AALLA model in integer linear programming (ILP), which restores the disrupted SDN network availability by assigning the logical links to the cluster (backup) controllers. More precisely, given a set of switches that are managed by the controller(s), this model simultaneously determines the optimal cost for controllers, links, and switches.

An Intersatellite Link Assignment Design for Megaconstellation Based on NSGA-II

The exploitation of intersatellite links (ISLs) makes the LEO satellite constellation based Internet service widely favored due to its advantages of low-latency and high-speed communications. However, considering the time-varying network topology, limited on-board resources, and high node failure probability, the design of link assignment has become one of the key challenges for the future megaconstellation. To solve this problem, we adopt the idea of modified finite state automaton (FSA) to model the LEO satellite network and use nondominated sorting genetic algorithm (NSGA-II) to optimize the minimum residual capacity and the maximum transmission delay. The simulation results show that our method is more invulnerable and flexible, which is fit for megaconstellations. This work can provide comprehensive guidance on intersatellite link assignment for future megaconstellations.

Secondary predation by omnivores: Cereal aphid consumption bears no risk of misinterpretation in DNA‐based diet analysis

AbstractMany omnivorous arthropods act as important pest control agents in agroecosystems. Assessing their prey choices helps to better understand their biocontrol potential in different environmental settings. To this end, multi‐target approaches of molecular gut content analysis allow studying their prey choices. Yet, DNA‐based analysis of trophic interactions is challenged by the question of whether the detected food DNA was ingested primarily as direct prey, or secondarily via the gut content of a consumed animal. Experimental data are needed to understand the potential bias derived through secondary predation. Here we address this issue for a phloem‐feeding aphid consumed by omnivorous carabids. In feeding experiments, Pseudoophonus rufipes beetles were offered grain aphids Sitobion avenae as primary prey, which had fed on barley seedlings. Gut content samples of carabids collected after 0, 3, 9, 12, 24, 32 or 64 h of digestion time and whole‐body aphids were screened for the presence of aphid and plant DNA. Samples positive for plant DNA were subsequently tested with Poaceae‐specific primers. None of the 7.8% gut content samples that tested positive for general plant DNA amplified with the Poaceae primers. Moreover, none of the whole‐body extracted aphids tested positive for plant DNA, neither with general nor with family‐specific primers. We, therefore, conclude that the plant DNA detections in our experiment can be ascribed to remnants of plant material in the guts of the field‐collected carabids. Our findings demonstrate that these phloem‐feeding aphids are an unlikely cause of false trophic link assignment because no secondarily consumed plant DNA, derived either from aphid gut content or host‐plant environmental DNA on aphid bodies, could be detected in carabid gut content samples.

Link assignment of time-reference transfer from the space station to the BeiDou satellite constellation

With the successful in-orbit operation of the cold atomic optical clock in the Mengtian laboratory cabin, a highly precise space time-reference will be formed. The BeiDou navigation satellite constellation has the ability of global coverage. By establishing time-transfer links with BeiDou satellites, the space station can realize precise transfer of its time-reference to wide area users. Aiming at the problem of highly precise and robust time-transfer link assignment from the space station to the BeiDou constellation, a link assignment model was established with taking the maximum hop and the connectivity as the evaluation indexes respectively of the accuracy and robustness of the time-transfer network. A topology optimization algorithm based on the genetic algorithm (GA) was further designed. Taking the time-reference transfer from the space station to the BeiDou Walker constellation as an example, the link assignment simulation was implemented in a minimum common orbit period. The precise time-reference transfer was realized using about 30% of inter-satellite link (ISL) timeslots. The maximum hop of the time-transfer links reached the theoretical optimal value, and the network connectivity was not less than 3. It was demonstrated that with the complex constraints of the ISL system, the payload quantity and visibility, the proposed assignment method could realize highly precise and robust time-reference transfer from the space station to the BeiDou constellation in any operation period.

Design of survivable wireless backhaul networks with reliability considerations

The ever-increasing need for stable, seamless, high-speed connectivity places an enormous burden on the communications infrastructure, comprised of access, backhaul, and core networks. Furthermore, recent advances in access technologies shift the capacity bottleneck towards the newly popularized wireless backhaul network, which is also susceptible to different types of failures. In this paper, a wireless backhaul network design under reliability and survivability constraints is formulated as a mixed integer linear programming (MILP) model to determine the minimum cost bandwidth assignment of wireless links. We developed an accelerated Benders decomposition algorithm to solve this model. Extensive computational experiments show the accuracy of the model proposed to tackle the problem and the efficiency of the solving method, particularly in larger networks.

Link assignment based on vertex deleting using adjacency matrix for LEO optical satellite network

In the LEO optical satellite network (OSN), each satellite has more than a dozen potential links, but the number of onboard terminals is limited. The beam divergence angle of optical satellite communication is extremely small, so only one bidirectional communication link can be established between a pair of communication terminals, therefore how to use limited onboard communication terminals to establish inter-satellite links (ISLs) for each satellite to achieve high-efficiency communication is an urgent problem to be solved. However, previous studies on link assignment schemes cannot take into account the terminal utilization ratio and the small end-to-end delay of the network. To solve the above-mentioned link assignment problem, this paper proposes the link assignment scheme based on vertex deleting using adjacency matrix (VDAM-LAS) for the first time. This scheme can ensure that any number of communication terminals on each satellite can be used to establish ISLs and the smaller network delay and ISLs hops can be obtained. In addition, it solves the link assignment problem of the OSN with the limit of the maximum allowable link hops of a single satellite, which is a problem that cannot be optimized using the previous LASs. The simulation results show that when assigning incessant ISLs, compared with the Manhattan Street Network (MSN)-LAS, greedy-LAS and perfect match model (PMM)-LAS, the average hops are reduced by 8.87%, 3.13%, 0.49%, respectively, and the average propagation delay is reduced by 17.24%, 2.86%, 0.8%, respectively. When assigning intermittent ISLs, the average hops are reduced by 10.45% and 6.89%, respectively, compared with the greedy-LAS and PMM-LAS.

Effect of Doppler shift on preamplifier DPSK receivers using balanced detection for optical satellite networks.

Optical satellite networks using laser intersatellite links are recognized as being capable of satisfying the increasing broadband communication demands. However, the Doppler shift due to relative movement between satellites must be taken into consideration. A convenient method that does not require complicated mathematical calculation is adopted to derive the relationship between the residual Doppler shift and the bit error rate (BER) for the balanced differential phase-shift keying (DPSK) detection system. It is shown that the DPSK receiver is sensitive to the residual Doppler shift; when the residual Doppler shift Δfres/Rb is 0.05, 0.10, and 0.15, the BER is reduced from a level of 10-17 to a level of 10-14, 10-11, and 10-6, respectively. The BER of a certain node pair under different link assignment schemes is calculated in a typical multi-hop LEO constellation. The results show that the communication BER of the same node pair is not only related to the step change of the Doppler but also related to the accumulation of the Doppler shift in the optical path. The results obtained here will be helpful in routing selection, link assignment, topology design, and system compensation.

Deep Learning-Based Scheduling Scheme for IEEE 802.15.4e TSCH Network

IEEE 802.15.4e time-slotted channel hopping (TSCH) is one of the most reliable resources of the Industrial Internet of Things (IIoT). TSCH operates on the slot-frame structure consisting of multiple channel-offsets and multiple slot-offsets. It is gaining acceptance due to its simple architecture and consume low power in industrial applications. The performance of TSCH is mainly dominated by the media access control (MAC) mechanism, which covers the refitment, enumeration, composition, and data transmission. However, in many cases, the data transmission schedules are not accurately prescribed. Therefore, most researchers are trying to define many pragmatic scenarios of scheduling. Their fundamental approach is to schedule TSCH network in a centralized way while framing scheduling based on network performance such as throughput and delay. In this work, a deep learning (DL)-based scheme has been proposed. TSCH network schedules for links to cell assignment of a slot-frame can be constructed as a maximum edge weighted bipartite matching approach. In this paper, we design bipartite edge weight to be composed of throughput and delay, and we use the Hungarian algorithm for proper cell assignment. With the Hungarian scheduling algorithm, we generate the training data and train a deep neural network (DNN) accordingly. In the simulation, we consider a simple TSCH network with 5 nodes where 12 links are formulated, and we consider 16 cells for the link assignment. The simulation results show that the proposed deep learning-based scheduling scheme can provide performance similar to the Hungarian algorithm-based scheduling scheme with above 90% accuracy and nearly 80% execution time reduction.

Inter-satellite time synchronization and ranging link assignment for autonomous navigation satellite constellations

The BeiDou Navigation Satellite System (BDS) has equipped its new-generation satellites with inter-satellite link (ISL) payloads for the autonomous operation. In the autonomous operation mode, the navigation constellation realizes the time unification and orbit determination through inter-satellite time synchronization and ranging, so as to self-maintain the time-space reference. For solving the problem of inter-satellite time synchronization and ranging link assignment for autonomous navigation constellations, assignment algorithms of time synchronization links based on satellite layers, as well as ranging links combining satellite selection and weighting, were proposed. The ISL assignment simulation of the BeiDou-3 global constellation was implemented using our algorithms, and the assignment was completed almost within 5 cycles. According to the statistical results, using 56.6% of ISL timeslots, the constellation had achieved the optimal mode of inter-satellite time synchronization with the least skips; the number of inter-satellite ranging links established per minute of each satellite was not less than 10, which met the constraint of the minimum links; the average PDOP of ranging links of the MEO, GEO and IGSO satellite was about 1, 1.6 and 1.5 respectively, close to the lower reference limit. It was demonstrated that the ISLs were reasonably assigned for the demand of inter-satellite time synchronization and ranging with constraints of the TDMA system, narrow beams, the quantity of payloads and inter-satellite visibility.

Dynamic optimization of intersatellite link assignment based on reinforcement learning

Intersatellite links can reduce the dependence of satellite communication systems on ground networks, reduce the number of ground gateways, and reduce the complexity and investment of ground networks, which are important future trends in satellite development. Intersatellite links are dynamic over time, and different intersatellite topologies have a great impact on satellite network performance. To improve the overall performance of satellite networks, a satellite link assignment optimization algorithm based on reinforcement learning is proposed in this article. Different from the swarm intelligence method in principle, this algorithm models the combinatorial optimization problem of links as the optimal sequence decision problem of a series of link selection actions. Realistic constraints such as intersatellite visibility, network connectivity, and number of antenna beams are regarded as fully observable environmental factors. The agent selects the link according to the decision, and the selection action utility affects the next selection decision. After a finite number of iterations, the optimal link assignment scheme with minimum link delay is achieved. The simulation results show that in 8 or 12 satellite network systems, compared with the original topology, the topology calculated by this method has better network delay and smaller delay variance.

Rolling weight-matching methods for the inter-satellite link assignment in global navigation satellite systems

Inter-satellite links (ISLs) have become an important technology for developing global navigation satellite systems (GNSSs). Due to satellite platform restrictions, the number of ISLs is limited, how to optimize ISL assignment is a crucial challenge. A mathematical optimization model is formulated that accommodates both ranging and communication requirements. We prove that the ISL assignment problem for ranging performance optimization is non-deterministic polynomial-time complete (NP-complete), and propose a rolling weight-matching method to solve the problem, where Edmonds’ blossom algorithm is used to find a maximum weight matching. Then, a weight enhancement strategy is designed to improve communication performance, classifying links into four types and adjusting the corresponding weights. A simulation experiment consisting of 10,080 epochs is run to evaluate the effectiveness of the proposed methods. The results demonstrate that the solution found is close to the optimal solution of the ranging performance, and the method with weight enhancement obtains better solutions than the other studied algorithms on both objectives.

An Adaptive Topology Optimization Strategy for Inter-Satellite Links in GNSS

Inter-satellite links (ISLs) are an effective way for the Global Navigation Satellite System (GNSS) to reduce its dependence on ground infrastructures, which guarantees constellation orbit determination and satellite communication. When the number of onboard Ka-band antennas is less than that of visible satellites, ISL assignment of GNSS cause a problem. For the problem of ISL scheduling, considering that the result of the allocated link has a feedback effect on the subsequent link assignment as a priori knowledge, an adaptive topology optimization Algorithm Based on Signed Variance (ABSV) is proposed. In order to meet the requirements of communication and ranging performance, the time slots are divided into communication time slots and ranging time slots. Taking the communication time delay (TD) form overseas satellites to anchor satellites and Position Dilution of Precision (PDOP) as measurement indexes, the proposed strategy is simulated for 10080 min. The results show that the ranging performance of this strategy is better than other recently published methods, which verifies the effectiveness of signed variance for adaptive link planning and is also beneficial to the survivability of constellation.

Link Assignment Based on Vertex Deleting Using Adjacency Matrix for Leo Optical Satellite Network

Link Assignment Based on Vertex Deleting Using Adjacency Matrix for Leo Optical Satellite Network

Artificial Intelligence for Smart Resource Management in Multi-User Mobile Heterogeneous RF-Light Networks

Recent trends in 5G and beyond wireless networks have encouraged the migration from the already congested radio frequency (RF) spectrum to higher frequency bands. In this context, the ubiquitous presence of lighting systems supports wide scale deployment of wireless communication links via light. However, the susceptibility of light to user mobility hinders its wide adoption. Hence, the coexistence of RF and light-based wireless communications has the potential to offer seamless heterogeneous network (HetNet) coverage through intelligent vertical handover policies in the presence of users' mobility. In this article, we first present new insights on the implementation of realistic indoor mobile optical channels and the impact of crowd mobility on relevant channel statistics. Then, an artificial intelligence (AI)-based framework for efficient resource management in mobile multi-user RF-light HetNets is proposed using a deep learning-empowered optical link predictor and a multiagent reinforcement learning-based link assignment strategy. The proposed AI-based framework helps to lay down the foundations of smart resource management in mobile multi-user HetNets.

BeiDou satellites cross-regional communication path assignment model and resource management

Time division inter-satellite communication and ranging link assignment of BeiDou satellites have made important progress; however, there is still the unsolved issue of integrated communication between ground gateway, aircraft, or even ship, and the BeiDou satellites. Therefore, in this study, we develop a path assignment model based on the idea of clustering and Markov chain. The optimal path is determined by the objective function based on the maximum transition probability. The transition probability takes into account the communication environment, congestion status, aircraft mobility, and reduces the complexity of path assignment by hiding the topology in the region. At the same time, due to the limited resources of onboard computing, storage and bandwidth, we also design a resource management strategy based on task urgency, aimed at minimizing the unreasonable allocation index, to enable the readjustment of link application resources. Finally, the performance of the model and the strategy in average link handover times, link reliability, resource allocation fairness, and network quality of service is determined by simulation.

A credibility-based fuzzy programming model for the hierarchical multimodal hub location problem with time uncertainty in cargo delivery systems

This paper studies the fuzzy hierarchical multimodal hub location problem for cargo delivery systems. It differs from traditional hub location problem in two ways. First, this paper constructs a hierarchical multimodal hub-and-spoke distribution network for the cargo delivery systems, which involves two transportation modes (road and air), two types of hubs (ground and airport) and three corresponding layers. Second, this paper develops a credibility-based fuzzy programming model capturing the uncertainty in travel time and handling time of the cargo delivery systems. This new model aims to minimize the latest arrival time (travel time plus handling time) for delivering cargoes from each pair of origin and destination nodes under diverse credibility of chance constraints. Under mild assumptions, the original model can be turned into an equivalent deterministic integer linear programming model. However, even for small instances of the problem, the equivalent model becomes too hard to be tackled by a general solver, e.g., CPLEX. This fact motivates the development of a two-stage heuristic procedure, wherein the first stage for the hub location subproblem is solved by a variable neighborhood search algorithm. These location solutions are then embedded into the second-stage process for the link assignment subproblem based on a shortest path method. To verify the proposed model and method, extensive numerical experiments are conducted on the well-known Turkish network data set.

Hybrid PMC (HPMC) fault model and diagnosability of interconnection networks

System level diagnosis, an area pioneered by Preparata, Metze and Chien, has been a dominant area of research in the broader area of fault-tolerant computing since the proposition of the PMC model. In this paper, we study the fault diagnosis problem for systems in hybrid fault circumstances where both node and link faults may occur. Under our diagnosis model, a test involves two adjacent processors and the link between them. We propose the definition of consistent faulty pairs and distinguishable faulty pairs. Given an assignment of testing links, we establish necessary and sufficient conditions for distinguishable faulty pairs. Finally, we introduce parameters to measure the fault diagnosis capability of multiprocessor systems under this model and as an application the fault diagnosis capability of hypercubes under this model has been evaluated.

Air quality and fossil fuel driven transportation in the Metropolitan Area of São Paulo

In this paper, we use origin and destination mobility surveys and high-resolution assignment and emission models to study air quality and short-lived climate pollutant impacts related to on-road transportation in the Metropolitan Area of São Paulo (MASP). To begin with, we calculate transport carbon dioxide (CO2) emissions from fossil fuel-driven vehicles (light and heavy-duty) at spatial and temporal resolutions of 500 m and one hour, by means of traffic demand forecasting. These estimates, carry out for 2007 and 2012, are based on passenger and freight trips and the height of the atmospheric boundary layer, among other variables. These proxies depend also on ancillary parameters as particulate matter concentrations and dilution rates. In the second place, we evaluate the changes in CO2 emissions from the MASP (3%/year). Transport emission inventories combine mobility surveys and road network assignments with air quality data. In spite of using different methodologies, bottom-up road link assignments versus top-down vehicle activity-based and fuel consumption approaches, the estimated CO2 emissions are consistent with the Official São Paulo State's Inventory. This work found that the CO2 emissions in MASP were 10,044 and 11,503 t Ceq./day in 2007 and 2012 (73% light and 27% heavy vehicles), respectively. On-road emission patterns agree with the spatial-temporal variation of transportation journeys and corresponding passenger and freight network assignments. Temporal patterns, diurnal, weekly and monthly, were determined using traffic counts and congestion surrogates. The patterns were also crosschecked with average CO2 measurements, available for 2014 at the road (western area of MASP) and background sites (Jaraguá Peak). Kerbside road measurements showed two prominent peaks associated to the morning (437 ± 45 ppm) and night rush hours (435 ± 49 ppm), coupled to low values of boundary layer height (313 m) and dilution rate (329 m2/h). Background values (414 ± 2 ppm) were subtracted from on-road measurements to estimate excess CO2 (12 ± 8 ppm) directly attributed to vehicles. The inventory reflects the relationships between traffic patterns and emissions, and the developed methodology could be used to evaluate the impacts of forthcoming urban transport and emission control policies. In the future, our estimates will be verified with ground measurements of CO2 concentrations over a bigger monitoring network in the MASP.