Matching Theory Research Articles

Broadband actively tunable metamaterial absorber based on vanadium dioxide and Fabry-Perot cavity

The dynamic tunable broadband perfect absorber based on vanadium dioxide (VO2) is proposed in this paper. And the VO2 conductivity can be changed by temperature, thus changing the absorption characteristics of the absorber. Under normal incident conditions, absorption is more than 90% of the absorber in the range of 5.8–17.2 THz (THz), with an average absorption rate of more than 96%. And impedance matching theory and magnetic resonance theory are used to illustrate the mechanism of operation. The effect of the incidence angle on the absorption performance was studied, and the results show that the absorbers still maintain excellent absorption when the incidence angle is less than 45∘. In addition, the absorption characteristics of the absorber working in water are also studied. We demonstrate that the absorber's absorption is more than 90% in the range of 5–18 THz with an absorption bandwidth of 13 THz at a water depth of 5.2 μm. And by adjusting the VO2 conductivity, the average absorption rate can be adjusted from 2.5% to 96.1% with a water depth of 5.2 μm. The proposed structure has potential significant applications in the design of heat emitters, optical switches, cloaking devices, and energy harvesting devices.

Service Routing in Multi-Tier Edge Computing: A Matching Game Approach

Although microservice envisioned as a promising approach for edge applications which can improves the development efficiency and the deployment productivity, it also leads to the operational complexity during service runtime. This leads to the emergence of service mesh, a decided infrastructure layer over microservices for reliable service-to-service communication. However, when migrating the service mesh to the multi-tier edge computing, the corresponding extensions on the top of service mesh is needed to overcome the challenges brought by the multi-tier edge servers, shared microservices and diverse QoS requirements. Therefore, in this paper, we investigate the problem of service routing to achieve the efficient microservice-based service provision in multi-tier edge computing. The objective is to route user requests to the optimal microservice instances with low service delay and resource cost. To this end, we first formulate the service routing problem as an integer non-linear optimization problem, which is NP-hard. Then we map it to a many-to-one matching problem by employing the matching game theory and propose a dependency-aware deferred acceptance algorithm with dynamic quota. The experimental results based on a real-world dataset demonstrate that our proposed algorithm can significantly outperform existing representative algorithms in terms of service delay and resource cost.

Blind matching algorithm based proxy distribution against internet censorship

AbstractProxy based censorship circumvention technique is treated as one of the most promising approaches to fighting against Internet censorship, and its practical applications like the onion router and Lantern have been widely utilized. However, the proxy distribution, as a basic and core issue, still remains unsolved due to (i) the finiteness and non‐renewable nature of proxy resources, (ii) the heterogeneity of clients and proxies requirements, and (iii) the existence of secondary censorship. In this paper, a win‐win driven proxy distribution mechanism for proxy based censorship circumvention systems is designed by leveraging the blind matching theory. Specifically, a combinational manner is developed to measure the quality of service (QoS) requirements of clients in terms of normalized bandwidth and reliability, and security requirements of proxies in terms of credits and suspicion. Then, by introducing the concept of virtual currency, the proxy distribution issue is formulated as two‐sided combinatorial problems from the perspective of clients and proxies, respectively. To solve the complex NP‐hard combinatorial problems in a win‐win manner without unilateral dominance, a two‐sided many‐to‐many context‐free matching game is constructed, in which the aspiration levels and agreement functions are defined to capture the security and QoS concerns of clients and proxies. Further, a modified notion of pairwise stability is exploited as the solution concept, and a client‐proxy blind matching algorithm with market and information decentralization is proposed to obtain the ε‐pairwise stable solution, where clients and proxies make encounters randomly and update their aspiration levels through a stochastic learning process. Finally, theoretical analysis and numerical results are carried out to validate the properties and performance of the proposed algorithm including stability, complexity, and convergence.

Nonreciprocal thermal emitter for near perpendicular incident light with cascade grating involving weyl semimetal

A nonreciprocal thermal emitter, consisting of a high refractive dielectric grating atop a Weyl semimetal (WS) grating and a metallic reflector, is proposed and studied. The emitter exhibits unequal directional absorption and emission, which breaks the traditional Kirchhoff's law and leads to the realization of strong nonreciprocal radiation. What's more, near-perfect nonreciprocity is realized at an angle of only 1o, which breaks the constraint of large operating angle confronted by existing nonreciprocal emitters and significantly enlarges the angular range. The physical origin of such phenomenon is disclosed by analyzing the magnetic field amplitude distribution and further confirmed by the impedance matching theory. To further confirm the range of angles that can be used, the strong nonreciprocity at several other angles is investigated. Last, the influence of the axial vector of the WS and the structure dimensions on the nonreciprocity is also investigated. We believed that the results should be useful for improving the efficiency of energy harvesting structures and developing novel thermal devices.

On generalisations of the Aharoni–Pouzet base exchange theorem

AbstractThe Greene–Magnanti theorem states that if is a finite matroid, and are bases and is a partition, then there is a partition such that is a base for every . The special case where each is a singleton can be rephrased as the existence of a perfect matching in the base transition graph. Pouzet conjectured that this remains true in infinite‐dimensional vector spaces. Later, he and Aharoni answered this conjecture affirmatively not just for vector spaces but also for infinite matroids. We prove two generalisations of their result. On the one hand, we show that ‘being a singleton’ can be relaxed to ‘being finite’ and this is sharp in the sense that the exclusion of infinite sets is really necessary. In addition, we prove that if and are bases, then there is a bijection between their finite subsets such that is a base for every . In contrast to the approach of Aharoni and Pouzet, our proofs are completely elementary, they do not rely on infinite matching theory.

Resource Allocation in C-V2X Mode 3 Based on the Exchanged Preference Profiles

In this paper, we investigate the resource block (RB) allocation problem in cellular vehicle-to-everything (C-V2X) networks mode 3, where the cellular networks schedule the RBs for direct vehicular communications. First, we establish the communication model and introduce the effective capacity and queuing theory to describe the reliability of vehicle-to-vehicle (V2V) links. Then, we introduce the α-fair function and formulate the joint power control and RB allocation problem considering the allocation fairness and the different quality-of-service (QoS) requirements for vehicle-to-infrastructure (V2I) and V2V links. Our objective is to maximize the sum capacity of all V2I links with the α-fair function while guaranteeing the allocation fairness among V2I links and the transmission reliability for each V2V pair. To achieve this objective, we propose a novel matching game theory algorithm based on the exchanged preference profiles between the two participant sets, i.e., V2V and V2I links. Simulation results show that our proposed algorithm is adaptive to the dynamic vehicular network and achieves better efficiency and fairness trade-offs, outperforming the classic allocation method.

Spatial location constraint prototype loss for open set recognition

One of the challenges in pattern recognition is open set recognition. Compared with closed set recognition, open set recognition needs to reduce not only the empirical risk, but also the open space risk, and how to reduce the open space risk is the key of open set recognition. Compared with the previous work, this paper analyzes the distribution rules of the known and unknown features, which is highly related to the open space risk. Then, this paper proposes the matching theory to explain the origin of the open space risk. On this basis, the spatial location constraint prototype loss function is proposed to reduce both risks simultaneously. Extensive experiments on multiple benchmark datasets and many visualization results verify the validity of the proposed matching theory and the effectiveness of the proposed method.

Vibrational wave scattering in disordered ultra-thin film with integrated nanostructures

Abstract A theoretical model, the phase-field matching theory, has been used to investigate the localized states, their associated states, the local vibrational density of states, the coherent conductance, and the associated thermal conductivity of the perturbed ultra-thin film quasi-dimensional crystalline lattice. The defect disrupts the system’s translational symmetry in the perpendicular direction to it, which is axis Ox, and induces a localized state in its behavior that is not present in the bulk, scattering the incident elastic wave. The model was analyzed for three different cases of elastic parameters: softening, homogeneous, and hardening. The purpose is to investigate how the local dynamics can respond to changes in the microscopic environment in the perturbed domain. The analysis of the total phononic conductance spectra and the local vibrational densities states identifies distinguishing characteristics and demonstrates the sensor’s potential use in nondestroyed control.

Resource Management and Reflection Optimization for Intelligent Reflecting Surface Assisted Multi-Access Edge Computing Using Deep Reinforcement Learning

Multi-access edge computing (MEC) enables the computation-intensive and latency-critical application to be processed at the network edge, which reduces the transmission latency and energy consumption. The quality of the wireless channel seriously affects the performance of the edge network. Consequently, the performance of the edge network can be significantly improved from the perspective of communication. The recently advocated intelligent reflecting surface (IRS) intelligently controls the radio propagation environment to improve the quality of wireless communication links. This paper proposes an edge heterogeneous network with the assistance of intelligent reflecting surface. Specifically, the macro base station and small base stations are equipped with MEC servers, and IRS is adopted to provide an additional computation offloading link. The user association, computation offloading and resource allocation, as well as IRS phase shift design are optimized with the aim of minimizing the long-term energy consumption subject to the constraints imposed on quality of service (QoS) and available resources. The challenge of the optimization problem is rooted from the fact that update timescale of user association is different from others. Hence, a two-timescale mechanism is invoked by marrying tools from matching theory and deep reinforcement learning. More specifically, the user association decision takes place in the long timescale. In the short timescale, the computation offloading, resource allocation and IRS phase shift design strategy is performed. The effectiveness of the proposed two-timescale mechanism is verified by the simulation results.

Low-Latency Edge Video Analytics for On-Road Perception of Autonomous Ground Vehicles

To improve the transportation efficiency of advanced manufacturing, cameras have been extensively deployed to enhance the on-road perception of autonomous ground vehicles in smart industrial parks. Considering the informative yet substantial data volume of contents generated by those cameras, we employ vehicle-to-everything links to deliver the captured video frames to neighboring vehicles, road-side units, or base stations, in order to respond to vehicle-control-related video queries. To help vehicles obtain low-latency and high-accuracy on-road information for autonomous driving, an optimization problem is formulated, taking into account the impact of vehicle mobility and diverse resource demands of different video queries. Then, a two-stage algorithm is proposed to determine the frame rate of video cameras, as well as the destination of the associated video frames based on matching theory. Extensive simulation results show that this approach can improve the accuracy by up to 18% and reduce the response delay by 13.2%.

DISCO: Distributed computation offloading framework for fog computing networks

Fog computing networks have been widely integrated in IoT-based systems to improve the quality of services (QoS) such as low response service delay through efficient offloading algorithms. However, designing an efficient offloading solution is still facing many challenges including the complicated heterogeneity of fog computing devices and complex computation tasks. In addition, the need for a scalable and distributed algorithm with low computational complexity can be unachievable by global optimization approaches with centralized information management in the dense fog networks. In these regards, this paper proposes a distributed computation offloading framework (DISCO) for offloading the splittable tasks using matching theory. Through the extensive simulation analysis, the proposed approaches show potential advantages in reducing the average delay significantly in the systems compared to some related works.

On the Accuracy of Correlation Estimator Based Fault Location Methods in Transmission Lines via Polynomial Chaos and Regression Analysis

The electromagnetic time reversal (EMTR) method has recently shown a novel advantage in locating faults along transmission lines. Under the ideal condition for EMTR, the key parameters in the transmission line between the direct and reversed phases are assumed to be identical. Thus, the fault position can be pinpointed via the cross-correlation matching theory. However, due to natural and geographical causes, the parameters vary along the line; therefore, accurately obtaining the parameters is difficult. In this article, we first investigate the impact of uncertain parameters on the performance of EMTR-based fault location methods. It has been observed that the performance is insensitive to the variation of the parameters in the lossless case of transmission lines. But in the case of the overhead line above the lossy ground, a significant error in fault location is witnessed. So, under parameter uncertainty, a novel approach to finding the confidence fault interval is proposed, based on utilizing the polynomial chaos and regression analysis. A simulation case with uncertain parameters for different scenarios is presented to validate the performance of the proposed approach.

Machine learning assisted hepta band THz metamaterial absorber for biomedical applications

A hepta-band terahertz metamaterial absorber (MMA) with modified dual T-shaped resonators deposited on polyimide is presented for sensing applications. The proposed polarization sensitive MMA is ultra-thin (0.061 λ) and compact (0.21 λ) at its lowest operational frequency, with multiple absorption peaks at 1.89, 4.15, 5.32, 5.84, 7.04, 8.02, and 8.13 THz. The impedance matching theory and electric field distribution are investigated to understand the physical mechanism of hepta-band absorption. The sensing functionality is evaluated using a surrounding medium with a refractive index between 1 and 1.1, resulting in good Quality factor (Q) value of 117. The proposed sensor has the highest sensitivity of 4.72 THz/RIU for glucose detection. Extreme randomized tree (ERT) model is utilized to predict absorptivities for intermediate frequencies with unit cell dimensions, substrate thickness, angle variation, and refractive index values to reduce simulation time. The effectiveness of the ERT model in predicting absorption values is evaluated using the Adjusted R2 score, which is close to 1.0 for nmin = 2, demonstrating the prediction efficiency in various test cases. The experimental results show that 60% of simulation time and resources can be saved by simulating absorber design using the ERT model. The proposed MMA sensor with an ERT model has potential applications in biomedical fields such as bacterial infections, malaria, and other diseases.

Plant-based food is unhealthy—that’s not true! How can corrective messages help promote plant-based menus in quick-service restaurants?

Purpose This study aims to identify effective ways to promote plant-based foods in quick-service restaurants by considering customers’ food-related health involvement. Design/methodology/approach This study conducted a 2 (message format: myth/fact or fact-only) × 2 (message focus: benefit- or attribute-focused) × 2 (health involvement: high or low) quasi-experimental design via a scenario-based online survey. A multivariate analysis of covariance and a bootstrapping approach were used to test the hypotheses (N = 365). Findings The results indicated that message format and focus jointly influenced customers’ perceived health consequences of plant-based foods and purchase intentions; customers’ health involvement altered the two-way interaction between message format and focus; and perceived health consequences mediated the effects of message format and focus as and customers’ health involvement on purchase intentions. Research limitations/implications This study identifies the effectiveness of message format and focus in promoting plant-based foods and extends the sustainable product promotion literature by using resource matching theory and the elaboration likelihood model. Future studies should use field studies to examine how can message framing influence customers’ actual behaviors when purchasing plant-based foods. Practical implications This study can help quick-service restaurants better promote plant-based foods considering message format and focus and customers’ food-related health involvement. Originality/value This is one of only a few studies that have tested how messages containing both negative and positive information about a product could help promote plant-based foods.

Backhaul-Aware User Association and Throughput Maximization in UAV-Aided Hybrid FSO/RF Network

Free-space optical (FSO) communication is expected to play an indispensable role with high data rates and low system complexity in beyond fifth-generation (B5G) networks. However, infrequent adverse weather conditions can incapacitate its performance. The combination of FSO and radio frequency (RF) has emerged as an effective alternative for meeting the growing need for high data rates in wireless communication networks. Unmanned aerial vehicles (UAVs) are also anticipated to play an instrumental role in B5G networks due to their flexible movement and deployment. In this paper, a UAV-aided hybrid FSO/RF backhauling system using a matching game theory (GT) and reinforcement learning (RL) framework is investigated. We deploy a UAV to provide a user offloading service to an already existing ground base station (GBS), which is facing a reduced backhaul capacity due to weather attenuation (e.g., fog). It is considered that the GBS has a pre-installed FSO backhaul connection to a macro-base station (MBS). However, during adverse weather conditions, the FSO backhaul is severely affected, compromising the reliability of the FSO link. With the reduced FSO backhaul capacity, the GBS needs an additional backhaul link to support its backhaul data transmission to the destination MBS. As a result, instead of building an expensive permanent parallel RF link for the rare foggy situation, a UAV can be hired to serve a portion of the users, thereby reducing the GBS load. The users perform a matching game-based procedure to select the base station (BS) of their choice to maximize their utility. The UAV is deployed at an optimal altitude, and the bandwidth partition between the GBS and the UAV is optimized to maximize the system throughput using RL. Real weather data from the cities of Edinburgh and London in the U.K. are used to evaluate the performance of the system. The numerical results show the superiority and effectiveness of the proposed scheme compared to conventional methods.

Miniaturized frequency selective rasorber with absorption in S–C band and transmission in X band

A miniaturized frequency selective rasorber (FSR) that has a wide absorption band in the S–C band and a wide transmission band based on X-band is presented in this paper. The FSR consists of a lossy layer loaded with lumped resistors and a bandpass layer with a three-screen cascade structure, which has the advantages of low insertion loss, wide passband bandwidth, and stable structural performance in the operating band. The rectangular spiral resonant (RSR) is loaded in the middle of the four arms of the cross to form a lossy layer. The aggregate resistance is loaded between the units to form a closed loop, which will absorb the detection signal and thus greatly reduce the radar cross section (RCS). The bandpass layer is divided into three layers, with two identical square patches coupled with a layer of complementary cross grids to form a multi-order bandpass filter. Furthermore, the operating mechanism of low absorption and high transmission is analyzed and verified based on equivalent circuit theory and impedance matching theory. The simulation results show that the 1 dB transmission band of the FSR is 8.0–12.5 GHz and the 10 dB absorption band is 2.8–6.6 GHz. The highest transmittance reaches over 97% at 10.0–11.5 GHz and the lowest insertion loss is 0.012 dB. It has important theoretical reference value and great application in the field of the new stealthy radome.

Universal and flexible design for high-sensitivity and wide-ranging surface plasmon resonance sensors based on a three-dimensional tuning hypersurface

Surface plasmon resonance (SPR), generally including propagating SPR (PSPR) and localized SPR (LSPR), has attracted wide attention due to the uniqueness of the strong evanescent field. The PSPR has the merit of high sensitivity over the LSPR, but lacks flexibility to tune resonant wavelength and serves limited application. Here we revisit the fundamental PSPR wavevector matching theory and construct a three-dimensional (3D) tuning hypersurface for the parameters of resonant wavelength, incident angle, and surrounding refractive index, which provides the performance tuning guide map. With assistance of the hypersurface, a hypersurface-tuning PSPR (HT-PSPR) sensor is designed with high sensitivity and ultra-wide detection range. Experiments demonstrate that the sensor can selectively tune the resonance and render the sensitivity to a theoretical upper limit of ∼105 nm/RIU, or an ultra-wide detection range of 0.518 RIU, which satisfies the requirement for most gas and liquid sensing applications. Using D-biotin as the detection sample of small molecule (MW=244 Da), the HT-PSPR sensor achieves an ultra-low detection limit down to 27.5 fM. The hypersurface-tuning has created an intrinsic, universal and flexible method for tuning PSPR at the desired resonant wavelength, sensitivity and detection range, which is expected to find great significance in SPR design and applications.

Wide-angle and broadband nonreciprocal thermal emitter with cascaded dielectric and Weyl semimetal grating structure

The recent review [Phys. Rev. Appl. 18, 027001 (2022)] has considered that the existing schemes of nonreciprocal radiation are greatly limited by the narrow-operated bandwidth and small angular range. To address these key challenges, here, the wide-angle and broadband nonreciprocal radiation based on cascaded dielectric and Weyl semimetal (WS) grating atop a thick continuous metal film is investigated. It is shown that strong nonreciprocal radiation with nonreciprocity larger than 0.9 is achieved in the spectral range of 14.77–16.175 μm for the angle of 59°. The physical origin behind this broadband nonreciprocal radiation is revealed through investigating the magnetic field distributions at several selected wavelengths and is also confirmed by the impedance matching theory. In addition, the broadband nonreciprocal radiation performance remains stably in a wide parameter space. Furthermore, it is found that the broadband spectral nonreciprocity can be maintained well in a wide angular range, in particular, above 0.7 nonreciprocity can be realized in the wavelength range of 14.5–16.5 μm for the angle between 36° and 64.5°. Both features make the proposed scheme very attractive for real production. Finally, the broadband spectral nonreciprocity can be flexibly controlled through change in the axial vector of the WS. We believe that the conclusions will pave the way for designing energy harvesting and conversion devices with improved efficiency.

A Two-Stage Matching Game and Repeated Auctions for Users Admission and Channels Allocation in 5G HetNets

The fifth-generation (5G) wireless cellular networks aim to increase the users’ capacities and quality of experience as well as to integrate different wireless bands and modes of access. The introduction of cognitive radio technology and heterogeneous networks (HetNets) as part of the architecture of the 5G aims to efficiently reuse the available spectrum. This paper presents a two-stage framework based on matching theory and auction games with the objective of efficiently admitting secondary users to the wireless scene. In the first stage, a fast convergence matching game for the users admission problem in 5G HetNets is considered, where secondary users are associated to appropriate secondary base stations. These base stations access the available primary spectrum on behalf of its associated users in the next stage, namely a repeated modified English auction. Results show the existence of a stable matching point for the users admission game and a Walrasian equilibrium point for the repeated auctions. In addition, extensive simulations are performed to compare the proposed repeated auction against the single auction and the matching theory. It is proven that the repeated auction game outperforms the single auction game and matching game in terms of the occupancy of primary channels and the satisfaction of the secondary users.

Decentralized optimal parking lot allocation by static and dynamic two-stage matching

In this paper, we propose an optimal parking lot allocation method based on matching theory that takes into account the desires of both drivers searching for parking lots and parking lot managers. In the conventional method, the allocation calculation is performed centrally, making it difficult to expand the area. We propose a decentralized allocation method that combines static and dynamic matching. In this method, individual drivers and parking lots perform calculations, and the allocation is determined in a decentralized manner through information communication, making it possible to expand the area. Finally, we confirm the effectiveness of the proposed method through numerical simulations.