Single Source Node Research Articles

Ergodic rate analysis and power allocation schemes for a novel active simultaneous transmission and reflection reconfigurable intelligent surface‐aided wireless network

SummaryIn this work, we propose the ergodic rate analysis and power allocation schemes for a novel active simultaneous transmits and reflects reconfigurable intelligent surface (STAR‐RIS) aided downlink wireless network. Here, the system model comprises of a single antenna source node (S) that uses the ES protocol to broadcast information to two users (T user and R user) via active STAR‐RIS. Each active STAR‐RIS element can function simultaneously in transmission and reflection modes owing to this ES protocol. We first derive the closed‐form analytical expressions for the system's ergodic rate. An optimization problem is formulated with a total power constraint to enhance the ergodic rate of the proposed system. A computationally inexpensive particle swarm optimization‐based power allocation (PSO‐PA) scheme and the Lagrange multiplier method (LMM) are adopted to solve the described optimization problem and to find the optimized power allocation factors for the source node and the active STAR‐RIS that can enhance the ergodic rate. Additionally, a comparison of the suggested PSO‐PA scheme, the LMM approach, and the equal power allocation (EPA) scheme is shown in terms of ergodic rate. Our results unveil that the proposed active STAR‐RIS system outperforms the passive STAR‐RIS and conventional RIS (transmitting/reflecting) aided systems. Further, the ergodic rate can be significantly improved with the proposed PSO‐PA and LMM schemes over the EPA scheme.

The routing algorithms for maximum probability paths under degree constraints in networks

ABSTRACT Driven by the rapid development of information technology, the network has been researched extensively and the efficient routing design has become particularly important and valuable. Since the data transmission in networks is mainly based on the establishment of communication, the instability of links and the capacity of nodes should be considered. Motivated by this, considering the routing optimization under the degree constraints, we formulate the problem of designing paths with maximum probability in the network from a single source node to all other nodes. Then we propose five polynomial-time algorithms for this problem by using the technical methods of bidirectional optimization, probability first strategy, the selection of the node with the maximum number of degrees and the restriction of the depth. In addition, the simulations and comparative analysis show that the algorithms have obvious advantages in practice.

Streaming Erasure Codes Over Multi-Access Relayed Networks

Many emerging multimedia streaming applications involve multiple users communicating under strict latency constraints. In this paper we study streaming codes for a network involving two source nodes, one relay node and a destination node. In this paper’s setting, each source node transmits a stream of messages, through the relay, to a destination, who is required to decode the messages under a strict delay constraint. For the case of a single source node, a class of streaming codes has been proposed by Fong et al., using the concept of delay-spectrum. The current paper presents a novel framework, which constructs streaming codes for a relayed multi-user setting by sequentially constructing the codes for each link. This requires a characterization of the set of all achievable delay spectra for a given rate, blocklength and number of erasures, beyond the specific choice considered by Fong et al. This characterization is presented in the paper for systematic codes. Using this novel framework, the first proposed scheme involves greedily selecting the rate on the link from relay to destination and using properties of the delay-spectrum to find feasible streaming codes that satisfy the required delay constraints. A closed form expression for the achievable rate region is provided, and conditions for when the proposed scheme is optimal are established by a natural outer bound. The second proposed scheme builds upon this approach, but uses a numerical optimization-based approach to improve the achievable rate region over the first scheme. Experimental results show that the proposed schemes achieve significant improvements over baseline schemes based on single-user codes.

A Game-Theoretic Approach for Cost-Effective Multicast Routing in the Internet of Things

Internet of Things (IoT) devices have enabled communications in resource-limited computing environments. Sensor nodes from the multiple IoT devices collectively work for many applications, such as disaster management, border security management, smart farming, smart cities, etc. In such applications, the data from a single source node is often destined for multiple nodes. Multicast communication is preferred over unicast or broadcast communication for such applications, as multicast uses fewer resources. Efficient construction of the multicast tree leads to cost-effective multicast transmission. This article introduces a path selection game (PSGame), a game-theoretic approach that formulates the construction problem of the least-cost multicast tree as a potential game. Our proposed path selection algorithm (PSA) quickly converges to the pure Nash equilibrium (PNE), bringing the least cost multicast tree. Our findings show that the overhead incurred in terms of energy consumption and delay is minimal in the proposed algorithm compared to other mechanisms. The theoretical analysis proves that the proposed algorithm quickly converges to PNE in <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$O(n.r_{\max })$ </tex-math></inline-formula> steps. It also proves that the cost ratio between the proposed solution and the centralized optimum will be bounded by <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\log (n)$ </tex-math></inline-formula> . The numerical analysis substantiates the theoretical analysis.

A newly treated boundary conditions to enhance accuracy of finite element analysis for orifice-type aerostatic bearings

Although numerical approaches have been extensively employed for solving the Reynolds equation in order to predict the performance of air bearings, we found inappropriate boundary settings can cause significant numerical errors if the grid-dependent condition is ignored. The current scrutiny is focused on crucial procedures for adopting the finite element method to assess the performance of orifice-type aerostatic bearings. To this end, numerical models for a single orifice-type are established and then checked by varying mesh sizes, mesh types, and boundary conditions (BCs). The obtained results reveal that those numerical models with a single-source node are grid-dependent, and the relative error is so large that the results are not credible compared with the analytical solution and becomes worse with denser meshes. This peculiar phenomenon can be mathematically interpreted by a one-dimension finite difference model calculated manually and auxiliary sources have proved to be an effective technique to reduce single-source numerical error to an acceptable level. Additionally, a physical explanation is given based on engineering systems modeling. By this view, rules of setting high pressure on the edge of recess are proposed and three types of grid-independent BC settings are proposed. Stiffness test experiments based on manufacturing a rotary table adopting multi-orifice aerostatic thrust bearings are further carried out to validate these numerical models, and the discrepancy between measured and calculated stiffness is reported to be lower than 5%.

A novel developmental trajectory discovery approach by integrating main path analysis and intermediacy

As a widely used technique for discovering developmental trajectory of a specific field of science and technology, main path analysis armed with global search strategy prefers longer citation paths rather than shorter ones. An obvious feature of longer main paths is that the theme of documents may not be so coherent, though longer paths may provide more details on the development of a field than shorter ones. Thereupon, a new measure, named as intermediacy, was proposed in the literature for recognising important scientific publications. However, the intermediacy is only applicable to the citation network with one single target node and one single source node. For purpose of loosening this limitation of the intermediacy and benefitting from main path analysis and intermediacy, this work raises an alternative approach for discovering developmental trajectory by combining node importance and edge importance via edge and node integrated modes. Extensive experimental results on the weak signals and education fields indicate that similar trajectories can be obtained through these two integrated modes, and richer implications can be encoded in our discovered trajectories than those from main path analysis and intermediacy. In addition, our framework is able to scale very well to a large citation network.

Source node detection in social networks based on Trust–GMLA algorithm

In order to solve the problem of source node detection when privacy information leakage occurs in social networks, especially in the case of asynchronous propagation and low forwarding rate, this paper proposes a single source node detection algorithm named Trust–GMLA(Trust-Gradient Maximum Likelihood Algorithm) based on trust network and GMLA(gradient maximum likelihood algorithm). According to the randomness of asynchronous propagation, the hysteresis matrix of GMLA algorithm is reconstructed, and the matrix parameters are automatically adjusted according to the forwarding rate, which improves the success rate of asynchronous diffusion source node detection. Also, aiming at the problem that a large number of repeated paths need to be calculated in GMLA, a trust inference matrix is proposed to infer the trust value between nodes, determine the trust propagation path, reduce unnecessary path calculation, and improve the speed of the algorithm. Experiments on several social networks datasets show that the proposed Trust–GMLA algorithm can effectively improve the source node detection accuracy and speed.

Optimizing the Age of Information for Multi-Source Information Update in Internet of Things

Age of Information (AoI) has recently become a new performance metric that captures the freshness/timeliness of information at end users in Internet of Things (IoT). Most existing information update mechanisms mainly consider the status information from a single Source Node (SN) or from multiple SNs with independent observations. However, in a practical IoT system, each status could be observed by multiple SNs, which brings new challenge in optimizing the AoI. To consider this issue, this paper formulates two optimization problems, named AoI-aware Multi-source Information Update problem (<i>AoI-MSIU</i>) and AoI-Reduction-aware Multi-source Information Update problem (<i>AoIR-MSIU</i>) problem, respectively. Specifically, AoI-MSIU problem assumes that the status are the first time to be uploaded to the BS, while AoIR-MSIU problem supposes that the BS already maintains the status that it has received before. Besides maximizing the revenue of information update, both problems consider how to optimize the AoI of the status. For AoI-MSIU problem, we prove that it is NP-hard, and propose an efficient greedy algorithm with a guaranteed approximation ratio. For AoIR-MSIU problem, we propose a polynomial-time optimal solution, which is based on a maximum weight bipartite matching on an auxiliary graph. Finally, we evaluate the performance of the proposed schemes through simulations.

Mobile Ad-hoc Networks: A Survey on multipath routing protocols

A Mobile Ad Hoc Network (MANETs) connects mobile nodes without any base station. These nodes in the network can change the topology dynamically and transfer the data among themselves. The nodes in the MANET are categorized based on the resource factors like memory, computation, and power levels. The dynamic change in route makes the connection of the destination node more complex. Sometimes, it results in link failure, and hence the primary route is failed, which means an alternative route is required to transmit the packets. It required multiple paths from the source node to destination node with a stable path connecting the source node. This issue makes MANET routing a crucial task. To address these problems, multipath routing in MANET is discussed in this paper. Multipath routing provides various paths for a single source node to a single destination node. It is more important to consider load balancing and fault tolerance when establishing the multipath routing mechanism. This paper describes the various type of challenges along with their respective multipath routing protocols in MANETs.

Atrophy patterns in sporadic and genetic behavioral variant frontotemporal dementia reflect brain network architecture

AbstractBackgroundConnections among brain regions allow pathological perturbations to spread from a single source node to multiple nodes. Patterns of neurodegeneration in multiple diseases, including behavioral variant of frontotemporal dementia (bvFTD), resemble the network architecture (Seeley et al., 2009, Neuron), but how bvFTD‐related atrophy patterns relate to the network organization remains unknown. Here we investigate whether neurodegeneration patterns in sporadic and genetic bvFTD are conditioned by connectome architecture, such that connected regions display similar atrophy patterns.MethodDeformation‐based morphometry (DBM) was used to estimate regional changes in tissue volume density from T1‐weighted magnetic resonance images of 75 genetic bvFTD patients and 247 healthy controls (GENFI, http://genfi.org.uk/). We used linear mixed effects model to obtain a bvFTD‐related atrophy map, controlling for age, sex and aquision site. Structural and functional connectivity (SC and FC), derived from an independent sample of 70 healthy participants (Griffa et al., 2019, Zenodo), were used to estimate mean neighbor atrophy values of each region. Relationship between node and neighbor atrophy was examined by correlating neighbor atrophy with nodal atrophy. Statistical significance of the analyses was assessed using a spatial autocorrelation‐preserving null model. Analyses were replicated in an independent dataset (FTLDNI, AG032306) with 70 sporadic bvFTD patients and 123 healthy controls.ResultDistributed atrophy patterns were observed in bvFTD, mainly targeting areas associated with limbic intrinsic network and insular cytoarchitectonic class (Fig 1a). A node’s atrophy was significantly correlated with atrophy of its connected neighbors (e.g. high resolution: r=0.58, p=0.006 and r=0.54, p=0.0006, for SC‐ and FC‐ defined neighbors respectively) (Fig 2c). Relationship between node and neighbor atrophy was consistent across resolutions and greater in empirical networks compared to null networks. While a number of frontotemporal regions were identified as potential disease epicenters, anterior insula was the most likely one. Results were consistent in the sporadic cohort (Fig 1b&amp;2d).ConclusionUsing connectivity models and rigorous statistical analyses that account for spatial autocorrelation, we demonstrate that bvFTD‐related neurodegeneration is conditioned by connectome architecture, accounting for 30‐40% of variance in atrophy. Atrophy is most profound in regions associated with insular cortex.

Regulatory Dynamics of Cell Differentiation Revealed by True Time Series From Multinucleate Single Cells.

Dynamics of cell fate decisions are commonly investigated by inferring temporal sequences of gene expression states by assembling snapshots of individual cells where each cell is measured once. Ordering cells according to minimal differences in expression patterns and assuming that differentiation occurs by a sequence of irreversible steps, yields unidirectional, eventually branching Markov chains with a single source node. In an alternative approach, we used multi-nucleate cells to follow gene expression taking true time series. Assembling state machines, each made from single-cell trajectories, gives a network of highly structured Markov chains of states with different source and sink nodes including cycles, revealing essential information on the dynamics of regulatory events. We argue that the obtained networks depict aspects of the Waddington landscape of cell differentiation and characterize them as reachability graphs that provide the basis for the reconstruction of the underlying gene regulatory network.

Adjustable robust counterpart optimization model for internet shopping online problem

In this paper, a discussion on deriving the Adjustable Robust Counterpart for Internet Shopping Online (ARC-ISO) is discussed. The problem on Internet Shopping Online is considered as an application of Robust Maximum Flow Problem (RMFP) with circular demand. The decision variables which considered as the adjustable variable is the maximum flow from a destination node in a flow network which back to the source node. In this paper, when the source nodes is multiple, then it is possible to add a dummy node as a single source node. For the multiple destinations, the same design is done. The main challenge is when and how we assume the data can be uncertain and assumed to be lies within a box, an ellipsoidal or polyhedral uncertainty set. In this paper, the uncertain delivering time is assumed to be lied in a polyhedral uncertainty set.

Pyramid graph cut: Integrating intensity and gradient information for grayscale medical image segmentation

Segmentation of grayscale medical images is challenging because of the similarity of pixel intensities and poor gradient strength between adjacent regions. The existing image segmentation approaches based on either intensity or gradient information alone often fail to produce accurate segmentation results. Previous approaches in the literature have approached the problem by embedded or sequential integration of different information types to improve the performance of the image segmentation on specific tasks. However, an effective combination or integration of such information is difficult to implement and not sufficiently generic for closely related tasks. Integration of the two information sources in a single graph structure is a potentially more effective way to solve the problem. In this paper we introduce a novel technique for grayscale medical image segmentation called pyramid graph cut, which combines intensity and gradient sources of information in a pyramid-shaped graph structure using a single source node and multiple sink nodes. The source node, which is the top of the pyramid graph, embeds intensity information into its linked edges. The sink nodes, which are the base of the pyramid graph, embed gradient information into their linked edges. The min-cut uses intensity information and gradient information, depending on which one is more useful or has a higher influence in each cutting location of each iteration. The experimental results demonstrate the effectiveness of the proposed method over intensity-based segmentation alone (i.e. Gaussian mixture model) and gradient-based segmentation alone (i.e. distance regularized level set evolution) on grayscale medical image datasets, including the public 3DIRCADb-01 dataset. The proposed method archives excellent segmentation results on the sample CT of abdominal aortic aneurysm, MRI of liver tumor and US of liver tumor, with dice scores of 90.49±5.23%, 88.86±11.77%, 90.68±2.45%, respectively.

A cooperative phase-steering technique in spectrum sharing-based military mobile ad hoc networks

Abstract In military applications, mobile ad hoc networks are commonly used due to the autonomy, self-configuration, and flexibility. In addition, spectrum sharing-based communication protocols are being actively considered due to spectrum shortage. We propose a cooperative phase-steering (CPS) technique for a spectrum sharing-based military mobile ad hoc network which consists of a single secondary source (SS) node, multiple secondary relay (SR) nodes, a single secondary destination (SD) node, and multiple primary destination (PD) nodes. In the proposed technique, the SR nodes that succeeded the packet decoding cooperatively adjust the phase of their transmit signals such that the received signals at the SD node from the SR nodes are aligned to a certain angle, while the SR nodes control the transmit power such that the received power at all PD nodes is lower than a certain threshold. Through extensive computer simulations, it is shown that the proposed technique outperforms the conventional cooperative relaying scheme in terms of outage probability.

A Cooperative Phase-Steering Technique with On-Off Power Control for Spectrum Sharing-Based Wireless Sensor Networks.

With the growth of the number of Internet of Things (IoT) devices, a wide range of wireless sensor networks (WSNs) will be deployed for various applications. In general, WSNs are constrained by limitations in spectrum and energy resources. In order to circumvent these technical challenges, we propose a novel cooperative phase-steering (CPS) technique with a simple on-off power control for generic spectrum sharing-based WSNs, which consists of a single secondary source (SS) node, multiple secondary relay (SR) nodes, a single secondary destination (SD) node, and multiple primary destination (PD) nodes. In the proposed technique, each SR node that succeeds in packet decoding from the SS and for which its interference power to the PD nodes is lower than a certain threshold is allowed to transmit the signal to the SD node. All SR nodes that are allowed to transmit signals to the SD node adjust the phase of their transmit signal such that the phase of received signals at the SD node from the SR nodes is aligned to a certain angle. Moreover, we mathematically analyze the outage probability of the proposed scheme. Our analytical and simulation results show that the proposed technique outperforms the conventional cooperative relaying schemes in terms of outage probability. Through extensive computer simulations, it is shown that the analytical results match well with the simulated outage probability as a lower bound.

Broadcasting a file in a communication network

We study the problem of distributing a file, initially located at a server, among a set of n nodes. The file is divided into mge 1 equally sized packets. After downloading a packet, nodes can upload it to other nodes, possibly to multiple nodes in parallel. Each node, however, may receive each packet from a single source node only. The upload and download rates between nodes are constrained by node- and server-specific upload and download capacities. The objective is to minimize the makespan. This problem has been proposed and analyzed first by Mundinger et al. (J Sched 11:105–120, 2008. https://doi.org/10.1007/s10951-007-0017-9) under the assumption that uploads obey the fair sharing principle, that is, concurrent upload rates from a common source are equal at any point in time. Under this assumption, the authors devised an optimal polynomial time algorithm for the case where the upload capacity of the server and the nodes’ upload and download capacities are all equal. In this work, we drop the fair sharing assumption and derive an exact polynomial time algorithm for the case when upload and download capacities per node and among nodes are equal. We further show that the problem becomes strongly NP-hard for equal upload and download capacities per node that may differ among nodes, even for a single packet. For this case, we devise a polynomial time smash {(1+2sqrt{2})}-approximation algorithm. Finally, we devise two polynomial time algorithms with approximation guarantees of 5 and 2 + lceil log _2 lceil n/mrceil rceil /m, respectively, for the general case of m packets.

Secrecy Performance Analysis of Hybrid AF-DF Relaying Under Multi Hop Environment

In this work, a three-hop wireless relaying model comprising of a single source and destination node, along with two relay nodes and an eavesdropper is considered. We made a detailed performance analysis comparison between the multi-hop network and the conventional single-hop model by considering different parameters. Due to the broadcast behaviour of a wireless communication network the propagated message from the source is captured by both intended and an unintended receiver. This will lead to severe security breaches in a wireless medium, so providing fully secure communication is a critical issue. Physical layer security developed as a new archetype to afford security to a wireless communication network. Multi-hop networks are favourite over single-hop networks for better coverage extension and lower interference levels. To use the benefits of both, amplify and forward and decode and forward protocol collectively, a new scheme known as hybrid amplify decode and forward relaying based on signal to noise ratio is presented. The scheme is proposed for multi hop environment with secrecy capacity as a performance metric. Secrecy capacity of proposed scheme outperforms both AF and DF for different distance parameters and path loss exponent under multi-hop environment.

Age of information in multihop multicast networks

We consider the age of information in a multihop multicast network where there is a single source node sending time-sensitive updates to nL end nodes, and L denotes the number of hops. In the first hop, the source node sends updates to n first-hop receiver nodes, and in the second hop each first-hop receiver node relays the update packets that it has received to n further users that are connected to it. This network architecture continues in further hops such that each receiver node in hop I is connected to n further receiver nodes in hop l +1. We study the age of information experienced by the end nodes, and in particular, its scaling as a function of n. We show that, using an earliest k transmission scheme in each hop, the age of information at the end nodes can be made a constant independent of n. In particular, the source node transmits each update packet to the earliest k1 of the n first-hop nodes, and each first-hop node that receives the update relays it to the earliest k2 out of n second-hop nodes that are connected to it and so on. We determine the optimum kl stopping value for each hop l for arbitrary shifted exponential link delays.

A study on the Development of a Korean Metabolic Syndrome Questionnaire

Segmentation of grayscale medical images is challenging because of the similarity of pixel intensities and poor gradient strength between adjacent regions. The existing image segmentation approaches based on either intensity or gradient information alone often fail to produce accurate segmentation results. Previous approaches in the literature have approached the problem by embedded or sequential integration of different information types to improve the performance of the image segmentation on specific tasks. However, an effective combination or integration of such information is difficult to implement and not sufficiently generic for closely related tasks. Integration of the two information sources in a single graph structure is a potentially more effective way to solve the problem. In this paper we introduce a novel technique for grayscale medical image segmentation called pyramid graph cut, which combines intensity and gradient sources of information in a pyramid-shaped graph structure using a single source node and multiple sink nodes. The source node, which is the top of the pyramid graph, embeds intensity information into its linked edges. The sink nodes, which are the base of the pyramid graph, embed gradient information into their linked edges. The min-cut uses intensity information and gradient information, depending on which one is more useful or has a higher influence in each cutting location of each iteration. The experimental results demonstrate the effectiveness of the proposed method over intensity-based segmentation alone (i.e. Gaussian mixture model) and gradient-based segmentation alone (i.e. distance regularized level set evolution) on grayscale medical image datasets, including the public 3DIRCADb-01 dataset. The proposed method archives excellent segmentation results on the sample CT of abdominal aortic aneurysm, MRI of liver tumor and US of liver tumor, with dice scores of 90.49±5.23%, 88.86±11.77%, 90.68±2.45%, respectively.

Minimum-cost forest for uncertain multicast with delay constraints

The use of multicast transmission can efficiently reduce the consumption of network resources by jointly serving multiple destinations with a single source node. Currently, many multicast applications impose the constraint wherein multicast flows must be processed by a series of Virtual Network Functions (VNFs) before reaching their destinations. Given a multicast transmission, there are usually multiple server nodes, each of which is able to host all the required VNFs. Thus, the multicast flow should be initially steered to one or a few selected server nodes that act as pseudo sources, and the destinations will then retrieve new flow from any of these pseudo sources. In this paper, we model this kind of multicast as an uncertain multicast with multiple pseudo sources, whose routing structure is usually a forest consisting of multiple isolated trees. We then characterize and construct the Delay-guaranteed Minimum Cost Forest (D-MCF) such that each path from the source to the destination satisfies the end-to-end delay constraint. To tackle this NP-hard problem, we design two efficient methods, the Partition Algorithm (PA) and the Combination Algorithm (CA), to approximate the optimal solution. Theoretical analyses and evaluations indicate that these two methods can generate the desired routing forest for any multicast transfer. Moreover, the PA method achieves a better balance between performance and time consumption than the CA method. The evaluation results show that PA-(Ω+ 20) can reduce total cost by 49:02% while consuming 12:59% more time, thus significantly outperforming the CA-(Ω+ 20) method.