Star Network Topology Research Articles

A WLAN-oriented distributed hierarchical parallel simulation method

To solve the problem that the efficiency decreases with the increase of terminal nodes in wireless local area network(WLAN) distributed parallel simulation, a WLAN-oriented distributed hierarchical parallel simulation method is proposed. Firstly, considering the WLAN star network topology, the process of the simulated access point (AP) is denoted as the main process, which is responsible for time synchronization with the other processes of the simulated station (STA) nodes in the WLAN network. Secondly, the processes of all simulated STAs are then evenly divided into groups, and the group leader is responsible for the synchronization of processes within the group. Then, after the main process broadcasts the simulation start event, the group leader process firstly collects the end message of the group member's terminal node, and then reports to the main process. A three-layer hierarchical structure is constructed, consisting of the main process layer, the group leader process layer and the group member process layer. Finally, the time gain factor of the hierarchical simulation method is analyzed and obtained in closed-form expression, under the different computational loads. Simulation results show that comparing to the existing non-hierarchical simulation method, when the average computational load is 1.2x time unit and the nodes number is 100, the gain of the proposed method can reach 50%.

Medical Data in Wireless Body Area Networks: Device Authentication Techniques and Threat Mitigation Strategies Based on a Token-Based Communication Approach

Wireless Body Area Networks (WBANs), low power, and short-range wireless communication in a near-body area provide advantages, particularly in the medical and healthcare sector: (i) they enable continuous monitoring of patients and (ii) the recording and correlation of physical and biological information. Along with the utilization and integration of these (sensitive) private and personal data, there are substantial requirements concerning security and privacy, as well as protection during processing and transmission. Contrary to the star topology frequently used in various standards, the overall concept of a novel low-data rate token-based WBAN framework is proposed. This work further comprises the evaluation of strategies for handling medical data with WBANs and emphasizes the importance and necessity of encryption and security strategies in the context of sensitive information. Furthermore, this work considers the recent advancements in Artificial Intelligence (AI), which are opening up opportunities for enhancing cyber resilience, but on the other hand, also new attack vectors. Moreover, the implications of targeted regulatory measures, such as the European AI Act, are considered. In contrast to, for instance, the proposed star network topologies of the IEEE 802.15.6 WBAN standard or the Technical Committee (TC) SmartBAN of the European Telecommunication Standards Institute (ETSI), the concept of a ring topology is proposed which concatenates information in the form of a ‘data train’ and thus results in faster and more efficient communication. Beyond that, the conductivity of human skin is included in the approach presented to incorporate a supplementary channel. This direct contact requirement not only fortifies the security of the system but also facilitates a reliable means of secure communication, pivotal in maintaining the integrity of sensitive health data. The work identifies different threat models associated with the WBAN system and evaluates potential data vulnerabilities and risks to maximize security. It highlights the crucial balance between security and efficiency in WBANs, using the token-based approach as a case study. Further, it sets a foundation for future healthcare technology advancements, aiming to ensure the secure and efficient integration of patient data.

Continuous variable quantum teleportation network with star topology

Quantum network allows communication among more than two users with quantum teleportation and high quantum fidelity enabled by non-classical resources. As one of the most versatile architectures, all users are connected mediated by the central station in the star topology network, leading to the realization of the information interconnection and interoperability. In this work, we experimentally demonstrate a 4-branch continuous variable (CV) quantum teleportation network with star topology by employing entangled sideband modes from one squeezed state of light. Here, multiple pairs of entangled sideband modes are distributed on demand to central station and four nodes, respectively. Each node linked to the network has its own communication channel with the central station, where the deterministic CV quantum teleportation protocol is implemented with the fidelities above 0.830.

Analisis dan Perancangan Jaringan Local Area Network Pada Labolatorium Komputer SMA Negeri 1 Long Iram

Computer networks have become one of the important needs for a school. now. Due to the transfer of the computer laboratory at SMA Negeri 1 Long Iram. In this project, the author wants to create a LAN-based network system (Local Area Network) with a star topology network model. to achieve the target of preparing for ANBK (Computer-Based National Assessment) at the high school. This project uses stage methods, namely problem identification, site observation, data collection, system analysis, system design and testing stages. The purpose of the project is to meet the needs of school facilities in the form of LAN networks that will be used for ANBK and Minimum Competency Assessment and Character Survey so that schools can successfully follow the agenda. The result of the project made is a LAN (Local Area Network) network system with a star topology network model successfully running smoothly as evidenced by the ANBK simulation a week before the implementation of ANBK itself. The benefits of this project are so that schools can participate in ANBK activities and Minimum Competency Assessment and Character Survey, and can maximize the learning process with technology facilities in the computer laboratory.

In-Network Computation for Large-Scale Federated Learning Over Wireless Edge Networks

Most conventional Federated Learning (FL) models are using a star network topology where all users aggregate their local models at a single server (e.g., a cloud server). That causes significant overhead in terms of both communications and computing at the server, delaying the training process, especially for large scale FL systems with straggling nodes. This paper proposes a novel edge network architecture that enables decentralizing the model aggregation process at the server, thereby significantly reducing the training delay for the whole FL network. Specifically, we design a highly-effective in-network computation framework (INC) consisting of a user scheduling mechanism, an in-network aggregation process (INA) which is designed for both primal- and primal-dual methods in distributed machine learning problems, and a network routing algorithm with theoretical performance bounds. The in-network aggregation process, which is implemented at edge nodes and cloud node, can adapt two typical methods to allow edge networks to effectively solve the distributed machine learning problems. Under the proposed INA, we then formulate a joint routing and resource optimization problem, aiming to minimize the aggregation latency. The problem turns out to be NP-hard, and thus we propose a polynomial time routing algorithm which can achieve near optimal performance with a theoretical bound. Simulation results showed that the proposed algorithm can achieve more than 99<inline-formula><tex-math notation="LaTeX">$\%$</tex-math></inline-formula> of the optimal solution and reduce the FL training latency, up to 5.6 times w.r.t other baselines. The proposed INC framework can not only help reduce the FL training latency but also significantly decrease cloud&#x2019;s traffic and computing overhead. By embedding the computing/aggregation tasks at the edge nodes and leveraging the multi-layer edge-network architecture, the INC framework can liberate FL from the star topology to enable large-scale FL.

An Efficient Adaptive Data-Link-Layer Architecture for LoRa Networks

LoRa is one of the most popular low-power wireless network technologies for implementation of the Internet of Things, with the advantage of providing long-range communication, but lower data rates, when compared with technologies such as Zigbee or Bluetooth. LoRa is a single-channel physical layer technology on top of which LoRaWAN implements a more complex multi-channel network with enhanced functionalities, such as adaptive data rate. However, LoRaWAN relies on expensive hardware to support these functionalities. This paper proposes a LoRa data-link-layer architecture based on a multi-layer star network topology that adapts relevant LoRa parameters for each end node dynamically taking into account its link distance and quality in order to balance communication range and energy consumption. The developed solution is comprised of multiple components, including a LoRa parameter calculator to help the user to configure the network parameters, a contention-free MAC protocol to avoid collisions, and an adaptive spreading factor and transmission power mechanism. These components work together to ensure a more efficient use of the chosen ISM band and end node resources, but with low-cost implementation and operation requirements.

Mango Fruit Fly Trap Detection Using Different Wireless Communications

Fruit flies cause production losses in mango orchards affecting fruit quality. A National Campaign against Fruit Flies (NCFF) evaluates farm status using the fruit flies per trap per day index (FTD). Traps with attractant are installed manually within orchards in Mexico, but counting the flies trapped every week requires excessive numbers of trained personal. Electronic traps (e-traps) use sensors to monitor fruit fly population, saving labor and obtaining the real-time orchard infestation. The objective of this work was to acquire an image within a e-trap at 17:00 when an insect was detected and binarize the information in real-time to count the number of flies. Each e-trap was implemented with a polyethylene PET bottle screwed to a tap containing an ESP32-CAM camera. E-traps from several hectares of mango trees were sampled and transmitted through WSN wireless sensor networks. This original system presents a star topology network within each hectare with the long range LoRa transceiver at the central tower. It receives the fly count from five e-traps and finally transmits data to the house tower end point. Another contribution of this research was the use of a DJI mini2 for acquiring the e-trap data, and the 8-ha flight took 15 min and 35 s. This period can be reduced if the drone flies higher.

QoS-Aware Resource Management in 5G and 6G Cloud-Based Architectures with Priorities

Fifth-generation and more importantly the forthcoming sixth-generation networks have been given special care for latency and are designed to support low latency applications including a high flexibility New Radio (NR) interface that can be configured to utilize different subcarrier spacings (SCS), slot durations, special scheduling optional features (mini-slot scheduling), cloud- and virtual-based transport network infrastructures including slicing, and finally intelligent radio and transport packet retransmissions mechanisms. QoS analysis with emphasis on the determination of the transmitted packets’ average waiting time is therefore crucial for both network performance and user applications. Most preferred implementations to optimize transmission network rely on the cloud architectures with star network topology. In this paper, as part of our original and innovative contribution, a two-stage queue model is proposed and analytically investigated. Firstly, a two-dimension queue is proposed in order to estimate the expected delay on priority scheduling decisions over the IP/Ethernet MAC layer of IP packet transmissions between gNB and the core network. Furthermore, a one-dimension queue is proposed to estimate the average packet waiting time on the RLC radio buffer before being scheduled mainly due to excessive traffic load and designed transmission bandwidth availability.

Effect of congestion avoidance due to congestion information provision on optimizing agent dynamics on an endogenous star network topology

This study elucidates the effect of congestion avoidance of agents given congestion information on optimizing traffic in a star topology in which the central node is connected to isolated secondary nodes with different preferences. Each agent at the central node stochastically selects a secondary node by referring to the declining preferences based on the congestion rate of the secondary nodes. We investigated two scenarios: (1) repeated visits and (2) a single visit for each node. For (1), we found that multivariate statistics describe well the nonlinear dependence of agent distribution on the number of secondaries, demonstrating the existence of the number of secondaries that makes the distribution the most uniform. For (2), we discovered that congestion avoidance linearizes the travel time for all agents visiting all nodes; in contrast, the travel time increases exponentially with secondaries when not referring to congestion information. Health examination epitomizes this finding; by allowing patients to be preferentially selected for examination in vacant examination sites, we can linearize the time it takes for everyone to complete their examination. We successfully described the optimization effect of congestion avoidance on the collective dynamics of agents in star topologies.

Multiparty Threshold Private Set Intersection Protocol with Low Communication Complexity

Multiparty threshold private set intersection (MP-TPSI) protocol allows n mutually untrusted parties P 1 , P 2 , … , P n holding data sets A 1 , A 2 , … , A n of size m respectively to jointly compute the intersection I = A 1 ∩ A 2 ∩ ⋯ ∩ A n over all their private data sets only if the size of intersection is larger than m − t , while ensuring that no other private information of the data sets other than the intersection is revealed, where t is the threshold. In the MP-TPSI protocol, multiple parties first decide whether the size of the intersection is larger than the threshold t ; then, they compute the intersection if the size of the intersection is larger than the threshold t . However, the existing MP-TPSI protocols use different forms of evaluation polynomials in the cardinality testing and intersection computing phases, so that parties need to transmit and calculate a large number of evaluation values, which leads to high communication and computational complexity. In addition, the existing MP-TPSI protocols cannot guarantee the security and the correctness of the results, that is, an adversary can know the additional information beyond the intersection, and the elements that are not in the intersection are calculated as the intersection. To solve these issues, based on the threshold fully homomorphic encryption (TFHE) and sparse polynomial interpolation, we propose an MP-TPSI protocol. In the star network topology, the theoretical communication complexity of the proposed MP-TPSI protocol depends on the threshold t and the number of parties n , not on the size of set m . Moreover, the proposed MP-TPSI protocol outperforms other related MP-TPSI protocols in terms of computational and communication overheads. Furthermore, the proposed MP-TPSI protocol tolerates up to n − 1 corrupted parties in the semi-honest model, where no set of colluding parties can learn the input of an honest party in the strictest dishonest majority setting.

Large-Area Saline-Alkali-Tolerant Rice Growth Environment Monitoring System Based on LoRa+UAV

A wireless sensor network (WSN) monitoring system for saline-alkali-tolerant rice based on long-range + unmanned aerial vehicle (LoRa + UAV) has been proposed in this paper to meet the requirements of difficult deployment, low scalability, and poor network reliability of traditional farmland environmental monitoring systems. The system automatically forms a double-layer star topology network through the terminal node and central node (intranet), central node, and UAV mobile node (extranet). Data transmission is carried out through LoRa technology, routing planning is carried out for UAV mobile receiving nodes at different flight altitudes, and an early warning mechanism for UAV energy is added. It effectively prevents the UAV from destroying the communication capability of the external network due to energy exhaustion during operation. The system transmits information remotely to the server of the management center through a 5G network, which analyzes and processes the data and publishes it on the Web. The system has been tested in the field, and the reliable communication range of the node is 1∼4 km under the saline-alkali-tolerant rice environment, and the service life of the terminal node can reach more than 3 months. During continuous operation, the maximum packet loss rate of the internal and external integrated networks is 1.45%. The system can stably and real-time monitor saline-alkali-tolerant rice environmental information, and the error rate is less than 10%, which can meet the performance requirements of the saline-alkali-tolerant rice environmental monitoring systems, such as low power consumption, wide coverage, stability, and reliability, and has a good engineering significance.

Self-healing WDM-based point-to-multipoint coherent passive optical network system with ONU-collaborative star topology for access-span robustness.

This study proposed a new small star topology network architecture connecting a secondary fiber link between adjacent small cell base stations for disaster tolerance in the access span of a short-reach point-to-multipoint optical communication system. Compared to the edge-side optical node independent architecture, the proposed network architecture exhibits a high robustness and small number of optical components. We compared the conventional and proposed configurations for survivability in the case of a major disaster with a triple-link failure. The proposed method made it easy to add a small star-shaped network with secondary links for significant edge-side optical nodes while maintaining the basic configuration of the conventional passive optical network.

A New-Dynamic Adaptive Data Rate Algorithm of LoRaWAN in Harsh Environment

The adaptive data rate (ADR) algorithm is used in LoRaWAN, allocating an appropriate transmission rate for terminal equipment to improve channel utilization and reduce power consumption. However, the standard ADR algorithm is only suitable for static terminal equipment. In addition, due to the complexity of the external environment, the selected data rate will not match the new environment and communication packets will be lost. Therefore, this article proposed a novel and more effective ADR algorithm called new-dynamic ADR (ND-ADR). The algorithm mainly solves two problems, i.e., the standard ADR algorithm cannot be applied to mobile terminal devices and the poor communication quality and high packet loss rate in harsh environments. In this study, we also developed a frame for LoRaWAN (FLoRaWAN), a simulation framework for the star network topology LoRaWAN in OPNET. Furthermore, we built an OKUMURA–HATA model and additionally introduced a noise factor <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\beta$ </tex-math></inline-formula> to simulate the loss of wireless communication in harsh environments. Finally, extensive simulation results showed that the number of data packets required by different end nodes for rate allocation was different. Compared with the standard ADR algorithm, even for mobile nodes in harsh environments, the ND-ADR algorithm reduced network energy consumption by about 13%, reduced network delay by about 18%, and increased effective throughput by about 15%. Therefore, the improved ND-ADR algorithm is more suitable for wireless communication of removable nodes in harsh environments. Its advantages are better awareness of link environment, faster data rate regulation, improved channel utilization, and further reduction of network energy consumption.

Coherence Analysis of Symmetric Star Topology Networks

The dynamics of complex networks are closely related to the topological structure. As an important research branch, the problem of network consensus has attracted more attention. In this paper, the first-order coherence of three kinds of symmetric star topology networks are studied by using the theory of network science. Firstly, three kinds of symmetric star topology network models are given. Secondly, the first-order coherence of these networks are calculated by using matrix theory. The relationships among the first-order coherence of the network and branch length and the number of branches change are obtained by numerical simulation. Finally, we found that the third network has the best consensus, and the change of branch length has more effective impact on network consensus.

Characterizing nonlocal correlations through various n -locality inequalities in a quantum network

The multipartite quantum networks feature multiple independent sources, in contrast to the conventional multipartite Bell experiment involving a single source. Despite the initial independence of resources, the multiple observers in the network can suitably choose measurements on their local subsystems and generate a form of quantum nonlocality across the network. So far, network nonlocality has been explored when each source produces a two-qubit entangled state. In this work we demonstrate the network nonlocality when each party performs a black-box measurement, and the dimension of the system remains unspecified. In an interesting work, by considering each source produces two-qubit entangled states in the conventional bilocal scenario, Gisin et al. [Phys. Rev. A 96, 020304 (2017)] demonstrated a correspondence between the violations of bipartite Clauser-Horne-Shimony-Halt inequality and the bilocality inequality. We introduce a variant of the sum-of-squares approach to reproduce their results without assuming the dimension of the system. We then generalize the argument for network nonlocality in star-network topology. Furthermore, we propose a set of $n$-locality inequalities in a star-network configuration where each of the $n$ parties performs an arbitrary number of dichotomic measurements and demonstrates the above correspondence between the quantum violations of the $n$-locality inequalities and the chained Bell inequalities. A similar correspondence is demonstrated based on a recently formulated family of $n$-locality inequalities whose optimal quantum violation cannot be obtained when each source emits a two-qubit entangled state and requires multiple copies of two-qubit entangled states. Throughout this paper, each party in the network performs black-box measurements, and the dimension of the system remains unspecified.

Evaluation Of Mobile ZigBee Technology Performance With Simulation Techniques

ZigBee technology adaptation and use is an emerging wireless communication technology with low power consumption and long battery life. These technology applications include controlling industrial systems, automating home systems, embedded sensing, and many more. Due to ZigBee's low bit rate and low transmission rate, it is necessary to investigate how ZigBee will perform in a heterogeneous situation using a simulation approach. This paper goes on to describe the design and modelling of mobile ZigBee networks with 5, 10, 15, 20, and 25 nodes to evaluate and compare the performance of this wireless sensor network for star topology networks over time. For the resourceful operation of WSN, mobile ZigBee networks with 5, 10, 15, 20, and 25-star topologies were considered. Certain network parameters such as throughput (bits/sec), delay (sec), end-to-end delay (sec), traffic sent (bits/sec), and traffic received (bits/sec) were explored and compared for smooth WSN operation when ZigBee communication protocol was used and modelled with the OPNET simulator. After evaluating all of the required parameters for various scenarios, an acceptable result was obtained for the mobile ZigBee WSN.

Multi-hop communication protocol for LoRa with software-defined networking extension

Long Range (LoRa) is a leading low-power wide-area networking technology, and LoRaWAN is the open MAC layer specification for LoRa technology. LoRaWAN operates in a star network topology, thus LoRaWAN forms single-hop network. LoRa technology allows customization of its PHY layer transmission parameters, such as bandwidth, spreading factor, transmission power, and coding rate, therefore long coverage can be achieved by using a lower bandwidth. However, a single-hop LoRaWAN network cannot achieve high data rate and long coverage simultaneous. To simultaneously achieve high data rate and long coverage, the LoRa PHY layer setting that yields the fastest data rate can be used, however it reduces coverage. To makeup for the reduced coverage multi-hop communication can be used. To enable multi-hop communication here a routing protocol for LoRa-based networks is presented. Moreover, to enable traffic engineering in LoRa-based networks, such as traffic load balancing a software-defined networking (SDN) extension for the protocol is also presented. Performance evaluation has shown that the proposed protocol and its SDN-based extension can match the coverage of LoRa PHY layer setting that offers maximum coverage at a relatively very high data rate and lower energy consumption. The protocol demonstrates up to 5 times higher packet reception ratio, and 63% lower energy consumption compared to the LoRa PHY layer setting that offers maximum coverage and reliability. Moreover, the protocols also outperform an existing state-of-the-are routing protocol for low-power wireless networks.

Oriented diameter of star graphs

An orientation of an undirected graph G is an assignment of exactly one direction to each edge of G . Converting two-way traffic networks to one-way traffic networks and bidirectional communication networks to unidirectional communication networks are practical instances of graph orientations. In these contexts minimising the diameter of the resulting oriented graph is of prime interest. The n -star network topology was proposed as an alternative to the hypercube network topology for multiprocessor systems by Akers and Krishnamurthy (1989). The n -star graph S n consists of n ! vertices, each labelled with a distinct permutation of [ n ] . Two vertices are adjacent if their labels differ exactly in the first and one other position. S n is an ( n − 1 ) -regular, vertex-transitive graph with diameter ⌊ 3 ( n − 1 ) / 2 ⌋ . Orientations of S n , called unidirectional star graphs and distributed routing protocols over them were studied by Day and Tripathi (1993) and Fujita (2013). Fujita showed that the (directed) diameter of this unidirectional star graph S n ⃗ is at most ⌈ 5 n / 2 ⌉ + 2 . In this paper, we propose a new distributed routing algorithm for the same S n ⃗ analysed by Fujita, which routes a packet from any node s to any node t at an undirected distance d from s using at most min { 4 d + 4 , 2 n + 4 } hops. This shows that the (directed) diameter of S n ⃗ is at most 2 n + 4 . We also show that the diameter of S n ⃗ is at least 2 n when n ≥ 7 , thereby showing that our upper bound is tight up to an additive factor.

Post-quantum secure multi-party private set-intersection in star network topology

In many realistic scenarios, participants wish to perform some secret set operations such as intersection, union, cardinality of intersection, etc. on their private data sets. Private Set Intersection (PSI) plays a major role in addressing such problems. PSI is one of the widely used secure multi-party computation technique that allows the participants to securely compute the intersection of their private input sets and nothing beyond that. It is generally executed between two parties. When the number of entities is more than two, it is known as multi-party PSI (MPSI). Today, the security of all the existing MPSI protocols are based on number theoretic assumptions. However, these will become insecure once large enough quantum computers are built. As a consequence, designing of quantum computer resistant MPSI becomes an interesting direction of research work. This paper addresses the issue by presenting the first post-quantum MPSI protocol in the so-called star network topology, using lattice-based public key encryption scheme. We utilize space-efficient probabilistic data structure (Bloom filter) as building blocks of our design. It attains security in standard model (without random oracles) under the decisional learning with errors (DLWE) assumption.

From Federated to Fog Learning: Distributed Machine Learning over Heterogeneous Wireless Networks

Machine learning (ML) tasks are becoming ubiquitous in today's network applications. Federated learning has emerged recently as a technique for training ML models at the network edge by leveraging processing capabilities across the nodes that collect the data. There are several challenges with employing conventional federated learning in contemporary networks, due to the significant heterogeneity in compute and communication capabilities that exist across devices. To address this, we advocate a new learning paradigm called fog learning, which will intelligently distribute ML model training across the continuum of nodes from edge devices to cloud servers. Fog learning enhances federated learning along three major dimensions: network, heterogeneity, and proximity. It considers a multi-layer hybrid learning framework consisting of heterogeneous devices with various proximities. It accounts for the topology structures of the local networks among the heterogeneous nodes at each network layer, orchestrating them for collaborative/cooperative learning through device-to-device communications. This migrates from star network topologies used for parameter transfers in federated learning to more distributed topologies at scale. We discuss several open research directions toward realizing fog learning.