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Journal articles on the topic 'Network topology discovery'

Author: Grafiati

Published: 4 June 2021

Last updated: 12 February 2022

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1

Jian, Feng, and Zhu Li. "WebNMS-Based Topology Discovery in EPON Network." International Journal of Future Generation Communication and Networking 6, no. 6 (December 31, 2013): 161–68. http://dx.doi.org/10.14257/ijfgcn.2013.6.6.17.

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2

FU, Hua Sen. "Practical Enhanced Topology Discovery Algorithm for MANET." Advanced Materials Research 760-762 (September 2013): 599–606. http://dx.doi.org/10.4028/www.scientific.net/amr.760-762.599.

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In order to effectively manage the communication nodes in Mobile Ad Hoc Network (MANET), it is important to know the topology of such networks. Traditional Ad-hoc On-demand Distance Vector (AODV) protocol can not get the MANET topology due to the lack of the topology discovery mechanism. Aiming at this problem, an enhanced topology discovery algorithm based on AODV (AODV-TD) is proposed. AODV-TD can not only obtain the topology of dynamic network by topology discovery request, but also realize route discovery among nodes. Finally, the proposed algorithm is implemented on a hardware platform using CC1100, and the experiment results show that, even the network changes dynamically, AODV-TD can still discover the network topology rapidly and accurately, so that contribute to reducing the route discovery time and the RREQ forwarding packets.

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3

Ge, Jian Xia, and Wen Ya Xiao. "Network Layer Network Topology Discovery Algorithm Research." Applied Mechanics and Materials 347-350 (August 2013): 2071–76. http://dx.doi.org/10.4028/www.scientific.net/amm.347-350.2071.

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Along with the development of the network information age, people on the dependence of the computer network is more and more high, the computer network itself the security and reliability of becomes very important, the network management put forward higher request. This paper analyzes two algorithms of the network layer topology discovery based on the SNMP and ICMP protocol, based on this, this paper puts forward a improved algorithm of the comprehensive two algorithm, and makes the discovery process that has a simple, efficient, and has a strong generalization, and solved in the discovery process met the subnet judge, multiple access routers identification.

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4

Ge, Jian Xia, and Wen Ya Xiao. "Network Layer Network Topology Discovery Algorithm Research." Applied Mechanics and Materials 380-384 (August 2013): 1327–32. http://dx.doi.org/10.4028/www.scientific.net/amm.380-384.1327.

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Along with the development of the network information age, people on the dependence of the computer network is more and more high, the computer network itself the security and reliability of becomes very important, the network management put forward higher request. This paper analyzes two algorithms of the network layer topology discovery based on the SNMP and ICMP protocol, based on this, this paper puts forward a improved algorithm of the comprehensive two algorithm, and makes the discovery process that has a simple, efficient, and has a strong generalization, and solved in the discovery process met the subnet judge, multiple access routers identification.

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5

Zhao, Ruiqin, Yuan Liu, Octavia A. Dobre, Haiyan Wang, and Xiaohong Shen. "An Efficient Topology Discovery Protocol with Node ID Assignment Based on Layered Model for Underwater Acoustic Networks." Sensors 20, no. 22 (November 18, 2020): 6601. http://dx.doi.org/10.3390/s20226601.

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Underwater acoustic networks are widely used in survey missions and environmental monitoring. When an underwater acoustic network (UAN) is deployed in a marine region or two UANs merge, each node hardly knows the entire network and may not have a unique node ID. Therefore, a network topology discovery protocol that can complete node discovery, link discovery, and node ID assignment are necessary and important. Considering the limited node energy and long propagation delay in UANs, it is challenging to obtain the network topology with reduced overheads and a short delay in this initial network state. In this paper, an efficient topology discovery protocol (ETDP) is proposed to achieve adaptive node ID assignment and topology discovery simultaneously. To avoiding packet collision in this initial network state, ETDP controls the transmission of topology discovery (TD) packets, based on a local timer, and divides the network into different layers to make nodes transmit TD packets orderly. Exploiting the received TD packets, each node could obtain the network topology and assign its node ID independently. Simulation results show that ETDP completes network topology discovery for all nodes in the network with significantly reduced energy consumption and short delay; meanwhile, it assigns the shortest unique IDs to all nodes with reduced overheads.

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6

Wazirali, Raniyah, Rami Ahmad, and Suheib Alhiyari. "SDN-OpenFlow Topology Discovery: An Overview of Performance Issues." Applied Sciences 11, no. 15 (July 29, 2021): 6999. http://dx.doi.org/10.3390/app11156999.

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Software-defined networking (SDN) is an innovative architecture that separates the control plane from the data plane to simplify and speed up the management of large networks. This means the control logic has been moved from the network hardware level to the centralized control management level. Therefore, the use of the OpenFlow Discovery Protocol (OFDP) is one of the most common protocols used to discover the network topology in a data plane and then transmit it to the control plane for management. However, OFDP has various shortcomings in its performance such as exchanging too many messages between both levels (control and data), which in turn increases the load on the SDN-Controller. Additionally, since the application layer depends entirely on the network topologies plotted in the control plane, it is very important to obtain accurate network topology information from data plane. Therefore, after providing background on topology discovery protocols to the reader, we will concentrate on performance issues. The present study identifies and discuss the primary concerns involved in the complex query process, infrastructure, influencing factors, and challenges for the topology discovery process. Furthermore, this paper will present several recent studies that have overcome and enhanced these issues. In addition, open discussion and future work concerning these issues are also discussed.

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7

He, Hui, Chi Xin Li, and Cheng Ying Gong. "Network Topology Discovery Algorithm Based on MIB." Applied Mechanics and Materials 496-500 (January 2014): 2134–37. http://dx.doi.org/10.4028/www.scientific.net/amm.496-500.2134.

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Network topology is the core of configuration management and the infrastructure of resource management.And it is based on the detection of a network failure and the analysis of network performance.This requires the network topology complete, accurate and friendly interface with visualization.This article describes the classification of the physical network topology discovery.Based on Bridge-MIB and MIB-II of SNMP devices, designed topology discovery algorithm in data link layer and network layer.Test results show that the algorithm can accurately find the device and connection on the network layer and the data link layer.

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8

Wenxing, Liao, Shi Xiaofei, and Chen Xinying. "The impacts of weak links on topology discovery process in large-scale wireless multi-hop networks." International Journal of Distributed Sensor Networks 16, no. 11 (November 2020): 155014772097452. http://dx.doi.org/10.1177/1550147720974526.

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In wireless multi-hop networks, especially large-scale wireless multi-hop networks, obtaining the network topology is of vital significance. In fact, in both proactive and reactive routing protocols, before establishing an appropriate end-to-end route, the source node needs to obtain the global or local topology. Our previous research has studied the impacts of weak links on reactive routing protocols, which can also be considered as local topology discovery process. In this article, in order to get insight of the impacts of weak links on topology discovery process, especially the global topology discovery on which the proactive routing protocols rely, we apply a Markov chain to model the most common used topology discovery process in large-scale wireless multi-hop networks. Considering the fading characteristics of wireless channel, we analyze the impacts of weak links on topology discovery algorithms. Simulation and theoretical results show that, with the increase in the network scale, the weak links have great impacts on the stability and even on the feasibility of wireless multi-hop networks.

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9

LIAO chunsheng. "Complex Network Based Computer Network Topology Discovery Optimization Algorithm." Journal of Convergence Information Technology 8, no. 9 (May 15, 2013): 348–55. http://dx.doi.org/10.4156/jcit.vol8.issue9.44.

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10

Chen, Song, Shan Wang, and Ming-tian Zhou. "A New Physical Network Topology Discovery Algorithm." JOURNAL OF ELECTRONICS INFORMATION & TECHNOLOGY 2010, no. 1 (February 8, 2010): 172–77. http://dx.doi.org/10.3724/sp.j.1146.2008.01783.

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11

Pandey, Suman, Mi-Jung Choi, Young J. Won, and James Won-Ki Hong. "SNMP-based enterprise IP network topology discovery." International Journal of Network Management 21, no. 3 (August 26, 2010): 169–84. http://dx.doi.org/10.1002/nem.756.

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12

Eriksson, Brian, Gautam Dasarathy, Paul Barford, and Robert Nowak. "Efficient Network Tomography for Internet Topology Discovery." IEEE/ACM Transactions on Networking 20, no. 3 (June 2012): 931–43. http://dx.doi.org/10.1109/tnet.2011.2175747.

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13

Shen, Zhe Jian, and Yun Sheng Ge. "Network Topology Discovery Algorithm Based on OSPF Link State Advertisement." Applied Mechanics and Materials 644-650 (September 2014): 3203–7. http://dx.doi.org/10.4028/www.scientific.net/amm.644-650.3203.

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In large scale network, the problem that network in an area topology accurately be discovered should be solved. The traditional network discovery algorithms mainly use ICMP and SNMP. But these two algorithms allow routers or other devices to send request packets to other devices. It may cause the low utilization rate of network. However, OSPF routing protocol, when it exchange routing tables, it will send LSUs to other routers and receive them from the remote routers. According to analyzing the LSAs, which are encapsulated in LSUs, we can obtain the network topology. We use GNS3 to simulate OSPF environment. Experiment shows that this algorithm can obtain the network topology rapidly and accurately.

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14

Chou, Li-Der, Chien-Chang Liu, Meng-Sheng Lai, Kai-Cheng Chiu, Hsuan-Hao Tu, Sen Su, Chun-Lin Lai, Chia-Kuan Yen, and Wei-Hsiang Tsai. "Behavior Anomaly Detection in SDN Control Plane: A Case Study of Topology Discovery Attacks." Wireless Communications and Mobile Computing 2020 (November 20, 2020): 1–16. http://dx.doi.org/10.1155/2020/8898949.

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Software-defined networking controllers use the OpenFlow discovery protocol (OFDP) to collect network topology status. The OFDP detects the link between switches by generating link layer discovery protocol (LLDP) packets. However, OFDP is not a security protocol. Attackers can use it to perform topology discovery via injection, man-in-the-middle, and flooding attacks to confuse the network topology. This study proposes a correlation-based topology anomaly detection mechanism. Spearman’s rank correlation is used to analyze the network traffic between links and measure the round-trip time of each LLDP frame to determine whether a topology discovery via man-in-the-middle attack exists. This study also adds a dynamic authentication key and counting mechanism in the LLDP frame to prevent attackers from using topology discovery via injection attack to generate fake links and topology discovery via flooding attack to cause network routing or switching abnormalities.

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15

Xue, Su Jing. "Discuss the Design Method of Topology Discovery System Based on SNMP." Advanced Materials Research 267 (June 2011): 594–98. http://dx.doi.org/10.4028/www.scientific.net/amr.267.594.

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Since the network was born, the network management has been the material effect factor which the computer network develops. Taking the reasonable network topology technology has already become the entire network management foundation,and for the isomerism, diverse and changeable network, the importance of network topology survey discovery is also enhancing. studying the highly effective network topology discovery method has the quite vital significance and the value to guarantee the network effective and safe operation.

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16

Wang, Jie, Bing Chen, and Cheng Xiang Tan. "Design and Implementation of Network Topology Discovery System Based on OSPF." Advanced Materials Research 760-762 (September 2013): 2100–2103. http://dx.doi.org/10.4028/www.scientific.net/amr.760-762.2100.

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This paper presents an algorithm of network topology discovery based on OSPF protocol and introduces the implementation. It is different than the traditional topology discovery algorithms which are mostly based on SNMP and ICMP protocols. The test results show that it has made an efficient and useful solution to network topology discovery.

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17

Du, Jiang, and Yu Li. "A Solution for Anonymous Routers Discovery Based on Source-Routing Traceroute." Advanced Materials Research 765-767 (September 2013): 1050–54. http://dx.doi.org/10.4028/www.scientific.net/amr.765-767.1050.

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Discovery of computer networks topology is always an important basement for network management. As IPv6 becomes the official standard, topology discovery methods should be changed as well. In IPv6 network, Anonymous Routers (AR) is one problem that we must deal with. AR is one kind of router we dont know its interface information, which makes it very difficult to find out their interconnections through common ways. This paper introduces a solution to deal with it, using source-routing traceroute command and nodes degree to merge ARs or find out their relation, and finally get the topology graph.

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18

Zhao, Anping, Suresh Manandhar, and Lei Yu. "Topology and semantic based topic dependency structure discovery." Filomat 32, no. 5 (2018): 1843–51. http://dx.doi.org/10.2298/fil1805843z.

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As an important enabler in achieving the maximum potential of text data analysis, topic relationship dependency structure discovery is employed to effectively support the advanced text data analysis intelligent application. The proposed framework combines an analysis approach of complex network and the Latent Dirichlet Allocation (LDA) model for topic relationship network discovery. The approach is to identify topics of the text data based on the LDA and to discover the graphical semantic structure of the intrinsic association dependency between topics. This not only exploits the association dependency between topics but also leverages a series of upper-level semantic topics covered by the text data. The results of evaluation and experimental analysis show that the proposed method is effective and feasible. The results of the proposed work imply that the topics and relationships between them can be detected by this approach. It also provides complete semantic interpretation.

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19

Han, Xing Ye, and Xin Ming Li. "A Service Discovery Algorithm Based on Network Topology Management." Applied Mechanics and Materials 513-517 (February 2014): 1182–86. http://dx.doi.org/10.4028/www.scientific.net/amm.513-517.1182.

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In view of the current development trend of Web service discovery technology and based on the service discovery method of formal concept analysis, the paper puts forward a service discovery algorithm based on QuickPeer, which exploits the idea of P2P network topology management to manage the formal concept of Web service in order to optimize the existing service discovery algorithm.

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20

Musser, Jeremy, Ezra Kissel, Martin Swany, Joe Breen, Jason Stidd, Shawn McKee, and Benjeman Meekhof. "Applying OSiRIS NMAL to Network Slices on SLATE." EPJ Web of Conferences 245 (2020): 07055. http://dx.doi.org/10.1051/epjconf/202024507055.

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The Network Management Abstraction Layer (NMAL) extends perfSONAR capabilities to include automated network topology discovery and tracking in the Unified Network Information Service (UNIS), and incorporate Software Defined Networking (SDN) into overall operations of the OSiRIS distributed Ceph infrastructure. We deploy perfSONAR components both within OSiRIS and at our “client” locations to allow monitoring and measuring the networks interconnecting science domain users and OSiRIS components. Topology discovery (using an SDN controller application) and Flange Network Orchestration (NOS) rules are used to dynamically manage network pathing in our testbed environments. NMAL components have been containerized to operate within the Services Layer at the Edge (SLATE) infrastructure, and we describe our experiences in packaging and deploying our services.

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21

Elzain and Wu. "Software Defined Wireless Mesh Network Flat Distribution Control Plane." Future Internet 11, no. 8 (July 25, 2019): 166. http://dx.doi.org/10.3390/fi11080166.

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Wireless Mesh Networks (WMNs), have a potential offering relatively stable Internet broadband access. The rapid development and growth of WMNs attract ISPs to support users’ coverage anywhere anytime. To achieve this goal network architecture must be addressed carefully. Software Defined Networking (SDN) proposes new network architecture for wired and wireless networks. Software Defined Wireless Networking (SDWN) has a great potential to increase efficiency, ease the complexity of control and management, and accelerate technology innovation rate of wireless networking. An SDN controller is the core component of an SDN network. It needs to have updated reports of the network status change, as in network topology and quality of service (QoS) in order to effectively configure and manage the network it controls. In this paper, we propose Flat Distributed Software Defined Wireless Mesh Network architecture where the controller aggregates entire topology discovery and monitors QoS properties of extended WMN nodes using Link Layer Discovery Protocol (LLDP) protocol, which is not possible in multi-hop ordinary architectures. The proposed architecture has been implemented on top of POX controller and Advanced Message Queuing Protocol (AMQP) protocol. The experiments were conducted in a Mininet-wifi emulator, the results present the architecture control plane consistency and two application cases: topology discovery and QoS monitoring. The current results push us to study QoS-routing for video streaming over WMN.

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22

Radi, Marjan, Behnam Dezfouli, Kamalrulnizam Abu Bakar, and Shukor Abd Razak. "Integration and Analysis of Neighbor Discovery and Link Quality Estimation in Wireless Sensor Networks." Scientific World Journal 2014 (2014): 1–23. http://dx.doi.org/10.1155/2014/789642.

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Network connectivity and link quality information are the fundamental requirements of wireless sensor network protocols to perform their desired functionality. Most of the existing discovery protocols have only focused on the neighbor discovery problem, while a few number of them provide an integrated neighbor search and link estimation. As these protocols require a careful parameter adjustment before network deployment, they cannot provide scalable and accurate network initialization in large-scale dense wireless sensor networks with random topology. Furthermore, performance of these protocols has not entirely been evaluated yet. In this paper, we perform a comprehensive simulation study on the efficiency of employing adaptive protocols compared to the existing nonadaptive protocols for initializing sensor networks with random topology. In this regard, we propose adaptive network initialization protocols which integrate the initial neighbor discovery with link quality estimation process to initialize large-scale dense wireless sensor networks without requiring any parameter adjustment before network deployment. To the best of our knowledge, this work is the first attempt to provide a detailed simulation study on the performance of integrated neighbor discovery and link quality estimation protocols for initializing sensor networks. This study can help system designers to determine the most appropriate approach for different applications.

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23

Park, Hyunsu, Jinsoo Kim, Moosung Park, Youngbae Jeon, and Jiwon Yoon. "Network Topology Discovery with Load Balancing for IoT Environment." Journal of KIISE 44, no. 10 (October 31, 2017): 1071–80. http://dx.doi.org/10.5626/jok.2017.44.10.1071.

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24

Saeed, Bilal, Tarek Sheltami, and Elhadi Shakshuki. "A Network Topology Discovery Tool for Android Smart Phones." Procedia Computer Science 63 (2015): 104–11. http://dx.doi.org/10.1016/j.procs.2015.08.318.

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25

Roh, Heejun, and Wonjun Lee. "Tree-Based Neighbor Discovery in Urban Vehicular Sensor Networks." International Journal of Distributed Sensor Networks 8, no. 1 (January 1, 2012): 156590. http://dx.doi.org/10.1155/2012/156590.

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In urban vehicular sensor networks, vehicles equipped with onboard sensors monitor some area, and the result can be shared to neighbor vehicles to correct their own sensing data. However, due to the frequent change of vehicle topology compared to the wireless sensor network, it is required for a vehicle to discover neighboring vehicles. Therefore, efficient neighbor discovery algorithm should be designed for vehicular sensor networks. In this paper, two efficient tree-based neighbor discovery algorithms in vehicular sensor networks are proposed and analyzed. After suggesting detailed scenario and its system model, we show that the expected value of neighbor discovery delay has different characteristics depending on neighbor discovery algorithms. An interesting observation of our result is that M-binary tree-based neighbor discovery shows better performance than M-ary tree-based neighbor discovery in the parking lot scenario, which is a counterintuitive result. We analyze why such result appears extensively.

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26

Andreev, Anton, and Anton Shabaev. "Models and methods for local area network topology discovery with incomplete data." Informatics and Automation 20, no. 1 (January 27, 2021): 160–80. http://dx.doi.org/10.15622/ia.2021.20.1.6.

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A lot of network management tasks require a description of the logical and physical computer network topology. Obtaining such a description in an automatic way is complicated due to the possibility of incompleteness and incorrectness of the initial data on the network structure. This article provides a study on the properties of incomplete initial data on network device connectivity on the link layer. Methods for generalized handling of the heterogeneous input data on the link layer are included. We describe models and methods for deriving a missing part of the data, as well as the condition in which it is possible to get a single correct network topology description. The article includes algorithms for building a link layer topology description from incomplete data when this data is possible to fulfill up to the required level. Also, we provide methods for detecting and resolving an ambiguity in the data and methods for improving incorrect initial data. Tests and evaluations provided in the article demonstrate the applicability and effectiveness of the build methods for discovering various heterogeneous real-life networks. Additionally, we show advantages of the provided methods over the previous analogs: our methods are able to derive up to 99\% data on link layer connectivity in polynomial time; able to provide a correct solution from an ambiguous data.

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27

Tempelmeier, Nicolas, Udo Feuerhake, Oskar Wage, and Elena Demidova. "Mining Topological Dependencies of Recurrent Congestion in Road Networks." ISPRS International Journal of Geo-Information 10, no. 4 (April 8, 2021): 248. http://dx.doi.org/10.3390/ijgi10040248.

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The discovery of spatio-temporal dependencies within urban road networks that cause Recurrent Congestion (RC) patterns is crucial for numerous real-world applications, including urban planning and the scheduling of public transportation services. While most existing studies investigate temporal patterns of RC phenomena, the influence of the road network topology on RC is often overlooked. This article proposes the ST-Discovery algorithm, a novel unsupervised spatio-temporal data mining algorithm that facilitates effective data-driven discovery of RC dependencies induced by the road network topology using real-world traffic data. We factor out regularly reoccurring traffic phenomena, such as rush hours, mainly induced by the daytime, by modelling and systematically exploiting temporal traffic load outliers. We present an algorithm that first constructs connected subgraphs of the road network based on the traffic speed outliers. Second, the algorithm identifies pairs of subgraphs that indicate spatio-temporal correlations in their traffic load behaviour to identify topological dependencies within the road network. Finally, we rank the identified subgraph pairs based on the dependency score determined by our algorithm. Our experimental results demonstrate that ST-Discovery can effectively reveal topological dependencies in urban road networks.

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28

Huang, Rui, and Jun Feng Wang. "Research on the Algorithm of Topology Discovery Based on Switch MAC's Self-Learning." Advanced Materials Research 756-759 (September 2013): 3952–57. http://dx.doi.org/10.4028/www.scientific.net/amr.756-759.3952.

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The switch is applied into topology discovery areas has become a hot research topic in network management technology. Through summarizing many defects of the SNMP (simple network) for the link layer discovery protocol, this paper presents a new topology discovery algorithm based on self-learning switch MAC. Research on the algorithm is about assumptions, definitions, principles and process. Through compare advantages and disadvantages in SNMP and MACs self-learning, the theoretical support will be provided for other scholars in the field of network management.

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29

Aleshkin, Andrey, Stanislav Balakirev, Valery Nevzorov, and Pavel Savochkin. "Models and Methods for Discovery of Local Area Network Topology with Incomplete Data." Informatics and Automation 20, no. 1 (February 1, 2021): 68–93. http://dx.doi.org/10.15622/ia.2021.20.1.3.

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A lot of network management tasks require a description of the logical and physical computer network topology. Obtaining such a description in an automatic way is complicated due to the possibility of incompleteness and incorrectness of the initial data on the network structure. This article provides a study on the properties of incomplete initial data on network device connectivity on the link layer. Methods for generalized handling of the heterogeneous input data on the link layer are included. We describe models and methods for deriving a missing part of the data, as well as the condition in which it is possible to get a single correct network topology description. The article includes algorithms for building a link layer topology description from incomplete data when this data is possible to fulfill up to the required level. Also, we provide methods for detecting and resolving an ambiguity in the data and methods for improving incorrect initial data. The tests and evaluations provided in the article demonstrate the applicability and effectiveness of the build methods for discovering various heterogeneous real-life networks. Additionally, we show the advantages of the provided methods over the previous analogs: our methods are able to derive up to 99% data on link layer connectivity in polynomial time; able to provide a correct solution from an ambiguous data.

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30

LIU, Jie. "ICMP-based method for logical network topology discovery and analysis." Journal of Computer Applications 28, no. 6 (October 21, 2008): 1498–500. http://dx.doi.org/10.3724/sp.j.1087.2008.01498.

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31

Mahmuddin, M., Mowafaq Salem Alzboon, and Suki Arif. "Dynamic Network Topology for Resource Discovery in Shared Computing Infrastructure." Advanced Science Letters 23, no. 6 (June 1, 2017): 5402–5. http://dx.doi.org/10.1166/asl.2017.7385.

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32

Ma, Xiaobo, and Tingting Yu. "An Algorithm of Physical Network Topology Discovery in Multi-VLANs." TELKOMNIKA (Telecommunication Computing Electronics and Control) 14, no. 3A (September 1, 2016): 375. http://dx.doi.org/10.12928/telkomnika.v14i3a.4416.

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33

Bitam, Salim, and Mohamed Chawki Bat. "Bees’ System Based Topology Discovery for Mobile Ad-hoc Network." Information Technology Journal 7, no. 1 (December 15, 2007): 77–83. http://dx.doi.org/10.3923/itj.2008.77.83.

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34

Khedr, Ahmed M., and Walid Osamy. "A topology discovery algorithm for sensor network using smart antennas." Computer Communications 29, no. 12 (August 2006): 2261–68. http://dx.doi.org/10.1016/j.comcom.2006.03.002.

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35

Catania, Vincenzo, Andrea Mineo, Salvatore Monteleone, and Davide Patti. "Distributed topology discovery in self-assembled nano network-on-chip." Computers & Electrical Engineering 40, no. 8 (November 2014): 292–306. http://dx.doi.org/10.1016/j.compeleceng.2014.09.003.

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36

Azodi, Amir, Feng Cheng, and Christoph Meinel. "Event Driven Network Topology Discovery and Inventory Listing Using REAMS." Wireless Personal Communications 94, no. 3 (September 10, 2015): 415–30. http://dx.doi.org/10.1007/s11277-015-3061-3.

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37

Safrianti, Ery, Linna Oktaviana Sari, and Tulus Rahayu. "Discovery Routing Time Speed Comparison of AODV, OLSR and ZRP protocols on MANET." International Journal of Electrical, Energy and Power System Engineering 3, no. 3 (October 20, 2020): 100–106. http://dx.doi.org/10.31258/ijeepse.3.3.100-106.

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Mobile Ad hoc Network (MANET) is a wireless network that contains a collection of nodes without infrastructure and interconnected to communicate. MANET works dynamically when a group of nodes moves spontaneously, so the network topology can change quickly and cannot be predicted. It causes changes in wireless network topology according to existing conditions. The node functions in determining the route to be selected. Ad Hoc networks have limited transmission range, so routing is needed to send data over the network. The problem with mobile nodes is that routing must provide a path when the node changes. The speed of a node obtaining information is affected by the routing protocol used in the network. Each routing protocol has different capabilities in network speed, so the discovery routing time for each routing is also different. The selected routing protocols are Ad Hoc On-Demand Distance Vector (AODV), Optimized Link-state (OLSR), and Zone Routing Protocol (ZRP). The study will conduct a comparative analysis of ad hoc network initialization speeds on AODV, OLSR, and ZRP routing protocols. The parameter tested is the speed of routing discovery. After the data is collected, an analysis is carried out by looking at the routing discovery speed of each routing protocol. The test results show that each of the routing protocols examined, the AODV routing protocol, has a faster routing discovery time than the OLSR and ZRP routing protocols.

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38

Malek, Al Gabri, Chun Lin Li, Yun Chang Liu, Yan Pei Liu, and Al Museelem Wleed. "Performance Analysis of Improving ZigBee Wireless Network Using AODV Mesh Routing Model." Advanced Materials Research 756-759 (September 2013): 828–32. http://dx.doi.org/10.4028/www.scientific.net/amr.756-759.828.

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ZigBee is an emerging standard for the low cost, low power and low rate wireless networks and the ZigBee technology is well suited to a wide range of energy management and efficiency applications in areas such as building automation, industrial, medical and home automation. ZigBee is a version of AODV routing protocol, where the routes are discovered RREQ through the network by the source broadcasting and sending RREP back the destination, so make ZigBee routing efficient, we used AODV mesh topology methods to send and receive data from source to destination and vice versa. In this paper we present an improved version of ZigBee-AODV mesh network, which utilizes and divide the topology of network into one or more logical clusters and restricts the flooding of route request outside the cluster. ZigBee-AODV mesh network uses nodes of the same cluster to share routing information, which significantly reduces the route path discovery and created cluster formation to decrease the routing path. The proposed protocol has higher reliability and lower overhead than AODV.

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Ye, Zhiwen, Hui Zhang, Libo Feng, and Zhangming Shan. "CDCN: A New NMF-Based Community Detection Method with Community Structures and Node Attributes." Wireless Communications and Mobile Computing 2021 (May 25, 2021): 1–12. http://dx.doi.org/10.1155/2021/5517204.

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Community discovery can discover the community structure in a network, and it provides consumers with personalized services and information pushing. It plays an important role in promoting the intelligence of the network society. Most community networks have a community structure whose vertices are gathered into groups which is significant for network data mining and identification. Existing community detection methods explore the original network topology, but they do not make the full use of the inherent semantic information on nodes, e.g., node attributes. To solve the problem, we explore networks by considering both the original network topology and inherent community structures. In this paper, we propose a novel nonnegative matrix factorization (NMF) model that is divided into two parts, the community structure matrix and the node attribute matrix, and we present a matrix updating method to deal with the nonnegative matrix factorization optimization problem. NMF can achieve large-scale multidimensional data reduction processing to discover the internal relationships between networks and find the degree of network association. The community structure matrix that we proposed provides more information about the network structure by considering the relationships between nodes that connect directly or share similar neighboring nodes. The use of node attributes provides a semantic interpretation for the community structure. We conduct experiments on attributed graph datasets with overlapping and nonoverlapping communities. The results of the experiments show that the performances of the F1-Score and Jaccard-Similarity in the overlapping community and the performances of normalized mutual information (NMI) and accuracy (AC) in the nonoverlapping community are significantly improved. Our proposed model achieves significant improvements in terms of its accuracy and relevance compared with the state-of-the-art approaches.

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Wu, Qing Xiu, and Jun Ou. "Research on Wireless Sensor Network Transmission System." Applied Mechanics and Materials 496-500 (January 2014): 2019–22. http://dx.doi.org/10.4028/www.scientific.net/amm.496-500.2019.

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In this paper, network layer is based on ZigBee standard. Network establishment and routing of wireless sensor network have been detailed in ZigBee network transmission. It has described data in tree topology and routing in mesh topology network respectively. It has provided with an example. There is no corresponding route in its routing table information, when the source device needs to send a message to the destination device. Source network layer initiates route discovery process. The programming examples are verified on this basis of the theory.

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Zhang, Xuliang. "An Optimization Algorithm of Network Topology Discovery Based on SNMP Protocol." Journal of Computer and Communications 06, no. 01 (2018): 104–11. http://dx.doi.org/10.4236/jcc.2018.61011.

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Zhao, Xu, Zhai Wen-yan, and Zhang Lin. "Automatic topology discovery mechanism for ring-based mine next generation network." Procedia Earth and Planetary Science 1, no. 1 (September 2009): 1325–31. http://dx.doi.org/10.1016/j.proeps.2009.09.204.

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Yang, Zengyin, Hewu Li, Qian Wu, and Jianping Wu. "Topology discovery sub-layer for integrated terrestrial-satellite network routing schemes." China Communications 15, no. 6 (June 2018): 42–57. http://dx.doi.org/10.1109/cc.2018.8398503.

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Pignolet, Yvonne Anne, Stefan Schmid, and Gilles Tredan. "Adversarial topology discovery in network virtualization environments: a threat for ISPs?" Distributed Computing 28, no. 2 (April 23, 2014): 91–109. http://dx.doi.org/10.1007/s00446-014-0217-4.

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Zhong, Sheng. "An efficient algorithm for topology discovery of a blackbox communication network." Applied Mathematics and Computation 186, no. 1 (March 2007): 506–8. http://dx.doi.org/10.1016/j.amc.2006.07.122.

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Ali, Tariq, Muhammad Irfan, Ahmad Shaf, Abdullah Saeed Alwadie, Ahthasham Sajid, Muhammad Awais, and Muhammad Aamir. "A Secure Communication in IoT Enabled Underwater and Wireless Sensor Network for Smart Cities." Sensors 20, no. 15 (August 2, 2020): 4309. http://dx.doi.org/10.3390/s20154309.

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Nowadays, there is a growing trend in smart cities. Therefore, the Internet of Things (IoT) enabled Underwater and Wireless Sensor Networks (I-UWSN) are mostly used for monitoring and exploring the environment with the help of smart technology, such as smart cities. The acoustic medium is used in underwater communication and radio frequency is mostly used for wireless sensor networks to make communication more reliable. Therefore, some challenging tasks still exist in I-UWSN, i.e., selection of multiple nodes’ reliable paths towards the sink nodes; and efficient topology of the network. In this research, the novel routing protocol, namely Time Based Reliable Link (TBRL), for dynamic topology is proposed to support smart city. TBRL works in three phases. In the first phase, it discovers the topology of each node in network area using a topology discovery algorithm. In the second phase, the reliability of each established link has been determined while using two nodes reliable model for a smart environment. This reliability model reduces the chances of horizontal and higher depth level communication between nodes and selects next reliable forwarders. In the third phase, all paths are examined and the most reliable path is selected to send data packets. TBRL is simulated with the help of a network simulator tool (NS-2 AquaSim). The TBRL is compared with other well known routing protocols, i.e., Depth Based Routing (DBR) and Reliable Energy-efficient Routing Protocol (R-ERP2R), to check the performance in terms of end to end delay, packet delivery ratio, and energy consumption of a network. Furthermore, the reliability of TBRL is compared with 2H-ACK and 3H-RM. The simulation results proved that TBRL performs approximately 15% better as compared to DBR and 10% better as compared to R-ERP2R in terms of aforementioned performance metrics.

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Albu-slaih, Alaa Taima, and Hayder Ayad Khudhair. "ASR-FANET: An adaptive SDN-based routing framework for FANET." International Journal of Electrical and Computer Engineering (IJECE) 11, no. 5 (October 1, 2021): 4403. http://dx.doi.org/10.11591/ijece.v11i5.pp4403-4412.

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Flying ad hoc network (FANET) is widely used in many military, commercial and civilian applications. Compared with mobile adhoc network (MANET) and vehicular ad hoc network (VANET), FANET holds unique characteristics such as high mobility, intermittent links and frequent topology changes, which cause a challenging task in the design of routing protocols. A novel adaptive software defined networking (SDN)-based routing framework for FANET called ASR-FANET is proposed in this article to solve the above challenges. The ASR-FANET framework is mainly composed of three important parts, which are the topology discovery mechanism, statistics gathering mechanism and route computation mechanism. In topology discovery mechanism, the periodic information about network topology is collected, including nodes and links. In statistics gathering mechanism, the status of the wireless network connection and flight statistics are collected. In route computation mechanism, the optimal path is calculated based on link costs. The performance of ASR-FANET framework is also has been evaluated by comprehensive simulations. The simulation results show that proposed framework is much better than other traditional protocols in packet delivery fraction, average end to end delay, normalized routing load, packet loss and throughput.

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Li, Haipeng, and Zhen Xu. "Routing Protocol in VANETs Equipped with Directional Antennas: Topology-Based Neighbor Discovery and Routing Analysis." Wireless Communications and Mobile Computing 2018 (2018): 1–13. http://dx.doi.org/10.1155/2018/7635143.

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In Vehicular Ad Hoc Networks (VANETs), directional antenna is a good solution if a longer transmission distance is needed. When vehicles are equipped with directional antennas, however, complete paths from the sources to the destinations there may not exist. Epidemic routing protocol is considered as one of the well-performed routing protocols when the networks are intermittently connected but it can cause a heavy load to the network and great energy consumption to the nodes. First in this paper, we propose a novel neighbor discovery algorithm which makes nodes be able to sense the topology changes around them and arrange their directional antennas accordingly. Secondly, we propose a routing protocol which is based on the conventional epidemic routing protocol, and nodes make their routing decisions according to the information collected during the neighbor discovery process. Experimental results show that the proposed neighbor discovery algorithm has better performance especially in the scenario where the node density is low. Moreover, the matching routing protocol can effectively reduce the load of the network and successfully deliver the packets to its destination in a reasonable short delay.

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Mishra, Deepak, Tristan Bepler, Brian Teague, Bonnie Berger, Jim Broach, and Ron Weiss. "An engineered protein-phosphorylation toggle network with implications for endogenous network discovery." Science 373, no. 6550 (July 1, 2021): eaav0780. http://dx.doi.org/10.1126/science.aav0780.

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Synthetic biological networks comprising fast, reversible reactions could enable engineering of new cellular behaviors that are not possible with slower regulation. Here, we created a bistable toggle switch in Saccharomyces cerevisiae using a cross-repression topology comprising 11 protein-protein phosphorylation elements. The toggle is ultrasensitive, can be induced to switch states in seconds, and exhibits long-term bistability. Motivated by our toggle’s architecture and size, we developed a computational framework to search endogenous protein pathways for other large and similar bistable networks. Our framework helped us to identify and experimentally verify five formerly unreported endogenous networks that exhibit bistability. Building synthetic protein-protein networks will enable bioengineers to design fast sensing and processing systems, allow sophisticated regulation of cellular processes, and aid discovery of endogenous networks with particular functions.

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He, Tong Zhou, and Yan Jun Shen. "The Topology Stability of Vehicular Ad Hoc Network." Advanced Engineering Forum 6-7 (September 2012): 1004–9. http://dx.doi.org/10.4028/www.scientific.net/aef.6-7.1004.

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The goal of this paper is to look for relatively stable area in the Vehicular Ad hoc Network (VANET), thereby helping for developing more stable routing protocols. We built a theoretical model to analysis the stability of the VANET topology, and provided the simulation experiment to verify the correctness of the theoretical analysis. Results show that the vehicle traveling in the same direction is easier to maintain the stability of the topology of a VANET, and the valid time of the path will decrease with the increase of the intersection angle in the direction of the vehicle movement, the vehicle movement velocity and the time. In addition, the simulation results also show that the bigger the initial distance among the vehicles is, the less stable the network topology is. The discovery of this phenomenon is important to develop zoned routing protocols.

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