Topology Discovery Research Articles

IeHDDP: An Integrated Solution for Topology Discovery and Automatic In-Band Control Channel Establishment for Hybrid SDN Environments

In-Band enhanced Hybrid Domain Discovery Protocol (ieHDDP) is a novel integral approach for hybrid Software-Defined Networking (SDN) environments that simultaneously provides a topology discovery service and an autonomous control channel configuration in the band. This contribution is particularly relevant since, to the best of our knowledge, it is the first all-in-one proposal for SDN capable of collecting the entire topology information (type of devices, links, etc.) and establishing in-band control channels at once in hybrid SDN environments (composed by SDN/no-SDN, wired/wireless devices), even with isolated SDN devices. ieHDDP facilitates the integration of heterogeneous networks, for example, in 5G/6G scenarios, and the deployment of SDN devices by using a simple exploration mechanism to gather all the required topological information and learn the necessary routes between the control and data planes at the same time. ieHDDP has been implemented in a well-known SDN software switch and evaluated in a comprehensive set of randomized topologies, acknowledging that ieHDDP is scalable in representative scenarios.

Efficient topology discovery protocol using IT-SDN for software-defined wireless sensor network

The internet of things (IoT) and wireless sensor networks (WSNs) are two promising technologies for supporting new services and applications. However, because IoT and WSN entail interaction and transaction of device topology discovery protocols, WSN facing some challenges. Topology discovery (TD) is important for WSN in IoT since sensor nodes (SNs) are the main points of this network. Networking these SN (IoT-devices) has a few difficulties such as energy and bandwidth consumption, and data storage issues resulting from frequent interactions and transactions between devices. Because these challenges cannot be resolved by one solution, we focused on reducing the energy consumption associated with a WSN. We proposed software-defined networking (SDN) model to tackle energy-efficiency issue in a WSN setup by integrating SDN and WSN, which gave rise to a more robust system, software-defined wireless sensor network (SDWSN). In this direction, we proposed an improved fuzzy-logic-based strategy, fuzzy topology discovery protocol (FTDP). It used IT-SDN (an SDN-based WSN framework) to increase the network’s lifepan due to its low energy consumption. The link layer discovery protocol (LLDP) to build the SDN controller’s topology. The system’s performance was presented and compared, demonstrating that with an effective SDWSN discovery policy, energy efficiency is achievable.

Zeph & Iris map the internet

We describe a new system for distributed tracing at the IP level of the routes that packets take through the IPv4 internet. Our Zeph algorithm coordinates route tracing efforts across agents at multiple vantage points, assigning to each agent a number of /24 destination prefixes in proportion to its probing budget and chosen according to a reinforcement learning heuristic that aims to maximize the number of multipath links discovered. Zeph runs on top of Iris, our fault tolerant system for orchestrating internet measurements across distributed agents of heterogeneous probing capacities. Iris is built around third party free open source software and modern containerization technology, thereby presenting a new model for assembling a resilient and maintainable internet measurement architecture. We show that carefully choosing the destinations to probe from which vantage point matters to optimize topology discovery and that a system can learn which assignment will maximize the overall discovery based on previous measurements. After 10 cycles of probing, Zeph is capable of discovering 2.4M nodes and 10M links in a cycle of 6 hours, when deployed on 5 Iris agents. This is at least 2 times more nodes and 5 times more links than other production systems for the same number of prefixes probed.

Design of the Wireless Network Hierarchy System of Intelligent City Industrial Data Management Based on SDN Network Architecture

With the rapid development of the industrial Internet of Things and the comprehensive popularization of mobile intelligent devices, the construction of smart city and economic development of wireless network demand are increasingly high. SDN has the advantages of control separation, programmable interface, and centralized control logic. Therefore, integrating this technical concept into the smart city data management WLAN network not only can effectively solve the problems existing in the previous wireless network operation but also provide more functions according to different user needs. In this case, the traditional WLAN network is of low cost and is simple to operate, but it cannot guarantee network compatibility and performance. From a practical perspective, further network compatibility and security are a key part of industrial IoT applications. This paper designs the network architecture of smart city industrial IoT based on SDN, summarizes the access control requirements and research status of industrial IoT, and puts forward the access control requirements and objectives of industrial IoT based on SDN. The characteristics of the industrial Internet of Things are regularly associated with data resources. In the framework of SDN industrial Internet of Things, gateway protocol is simplified and topology discovery algorithm is designed. The access control policy is configured on the gateway. The access control rule can be dynamically adjusted in real time. An SDN-based intelligent city industrial Internet of Things access control function test platform was built, and the system was simulated. The proposed method is compared with other methods in terms of extension protocol and channel allocation algorithm. Experimental results verify the feasibility of the proposed scheme. Finally, on the basis of performance analysis, the practical significance of the design of a smart city wireless network hierarchical data management system based on SDN industrial Internet of Things architecture is expounded.

Fundamentals and Advancements of Topology Discovery in Underwater Acoustic Sensor Networks: A Review

With the extensive application of underwater acoustic sensor networks (UANs) in various fields such as commerce, marine environmental research, and national defense, the need for an autonomous and well-organized underwater acoustic network has been increasing. Topology discovery is a crucial step in constructing an underwater acoustic network, and node discovery and topology establishment are the essential components of the topology discovery process in UANs. This paper introduces the characteristics of underwater acoustic channels and networks and highlights their influences on topology discovery. We discuss the topology discovery protocol development in terrestrial networks (i.e., duty-cycle ad hoc network, Internet of things). The main focus of this paper is to study the topology discovery protocols of UANs. This paper also classifies and introduces the existing topology discovery protocols and compared their advantages and disadvantages to understand the current topology discovery methods. Furthermore, we also discuss the topology discovery protocol’s influence on different layers’ functions in the UAN protocol stack. Analyze the current research challenges in this field, followed by important open issues in UAN protocol development, which provide new opportunities for further research.

A Fast Hierarchical Physical Topology Update Scheme for Edge-Cloud Collaborative IoT Systems

The awareness of physical network topology in a large-scale Internet of Things (IoT) system is critical to enable location-based service provisioning and performance optimization. However, due to the dynamics and complexity of IoT networks, it is usually very difficult to discover and update the physical topology of the large-scale IoT systems in real-time. Considering the stringent latency requirements in IoT systems, while the initial processing time for topology discovery can be tolerated, latency due to real-time topology update constitutes an even higher level of challenge. In this paper, a novel fast hierarchical topology update scheme is proposed for the large-scale IoT systems enabled by using the edge-cloud collaborative architecture. Specifically, an event-driven neighbor update algorithm, termed as TriggerOn, is firstly developed to update the local neighbor table of the end devices when device association or disassociation occurs. Based on the updated neighbor tables, the physical topology update of the subnet is conducted at the coordinated edge device, where a hybrid multidimensional scaling (MDS) based 3D localization algorithm is developed to locate the newly associated devices. Simulation results have indicated that as compared to the benchmark methods, the neighbor discovery latency has been reduced dramatically, and the 3D localization accuracy has been improved. Furthermore, the overall latency incurred by the proposed hierarchical physical topology update scheme is significantly lower than the distributed consensus-based update scheme, especially for the large-scale IoT subnets.

ASR-FANET: An adaptive SDN-based routing framework for FANET

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.

A Software Defined Network Scheme for Intra Datacenter Network Based on Fat-Tree Topology

Nowadays datacenters face a big challenge, because the development of cloud services requests a large amount of capital input, high maintenance skills and cost. The major disadvantages of current datacenter network include the high cost of equipment and maintenance, QoS, failure recovery time, network virtualization etc. In this paper, we proposed a software defined datacenter network. The programmable controller is responsible for the management of the traffic scheduling including topology discovery, routing and Quality of Service. The SDN is based on Fat-tree network architecture and max-min fairness. A Genetic Algorithm optimized Radial Basis Function neural network is used to compute the service weight for maximizing the utilization of network resource. An experiment of the network bearing different kinds of services based on Openflow is described. This well-designed fat-tree network has high efficiency in traffic distribution, and has integrated the traditional network architecture and new SDN technology.

Yazılım Tanımlı Ağlarda Bağlantı Katmanı Keşif Protokolünün İstismarına Dayalı Topoloji Zehirleme Saldırılarının İncelenmesi

In software defined networks (SDNs), data plane and control plane on the conventional network devices are separated and packet forwarding decisions are taken by the controller in charge of the entire network. The necessity of managing all the network operations not only facilitates control for the controller but also causes some security vulnerabilities and new attack surfaces in SDNs. In this study, Link Layer Discovery Protocol (LLDP), which forms the basis of OpenFlow Discovery Protocol (OFDP) for topology discovery in SDNs, is exploited to poison the topology by adding fabricated links to the controller. Fake LLDP Injection and LLDP replay techniques are used to create fake links on the controller and network access status of end devices are evaluated during attacks. Our findings demonstrate that the Floodlight controller is vulnerable to attacks based on LLDP exploitation and it is possible to create fake links on the controller. Due to the fake links, it is determined that invalid routes are created on controller and despite having other active links, end devices subject to invalid routes lost their access to network. Thus, attacks on the data link layer affect the performance of the network negatively.

SDN-OpenFlow Topology Discovery: An Overview of Performance Issues

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.

EDiPSo: An Efficient Scalable Topology Discovery Protocol for Software-Defined Vehicular Networks

With the vast data loads produced by numerous applications and services, network softwarization became a vital addition to the design of intelligent heterogeneous vehicular networks. Smart Software-Defined Vehicular Networks (S-SDVN) are promising solutions that support various applications and protocols such as network mobility management, routing, traffic control and provides a centralized innovative decision-making protocol. SDVNs remove the limitations imposed by traditional hardware-based network devices to offer a global view of the networks’ status and give a standard framework for heterogeneous wireless technologies (WiMAX, WiFi/6, 5G, 6G). However, to capture the network’s topology and manage data traffic, an efficient discovery protocol is needed to mitigate the challenges under vehicles’ rapid mobility. In this article, we present an efficient and scalable topology discovery protocol for distributed software-defined vehicular networks, which we refer to as EDiPSo. The proposed protocol reduces the overhead and time complexity of the discovery process based on the centrality score measurements and vehicle traffic densities over switch-enabled roadside units. EDiPSo protocol is evaluated and compared to existing benchmark solutions using realistic mobility traces of Shenzhen City. The results showed that the proposed distributed discovery process significantly reduces the overhead compared to other protocols and decreases the time required to complete a discovery cycle as the number of locally distributed controllers increases.

Distributed Algorithms for Multiple Path Backbone Discovery in Thick Linear Sensor Networks

Continued advancements in microprocessors, electronics, and communication technology have led to the design and development of sensing devices with increased functionalities, smaller sizes, larger processing, storage, and communication capabilities, and decreased cost. A large number of these sensor nodes are used in many environmental, infrastructure, commercial, and military monitoring applications. Due to the linearity of a good number of the monitored structures such as oil, gas, and water pipelines, borders, rivers, and roads, the wireless sensor networks (WSNs) that are used to monitor them have a linear topology. This type of WSN is called a linear sensor network (LSN). In this paper, two distributed algorithms for topology discovery in thick LSNs are presented: the linear backbone discovery algorithm (LBD) and the linear backbone discovery algorithm with x backbone paths (LBDx). Both of them try to construct a linear backbone for efficient routing in LSNs. However, the LBD algorithm has the objective of minimizing the number of messages used during the backbone discovery process. On the other hand, the LBDx algorithm focuses on reducing the number of hops of the data messages transmitted from the nodes to the sink. LBD and LBDx exhibit good properties and efficient performance, which are confirmed by extensive simulations.

DIVE: A distributed ID assignment and topology discovery protocol for underwater acoustic networks

This paper presents the DIVE protocol, which is designed to self assign unique node IDs in an underwater acoustic network. DIVE, which stands for Distributed Id assignment and topology discoVEry, is fully distributed and does not assume any prior knowledge of the network. One of the objectives of the DIVE protocol is the assignment of short IDs to the node, thus reducing the number of bits required to encode this information. Link quality information is explored to increase the robustness of the protocol against message losses. While discovering the network and assigning short node IDs, control data is shared to collect additional information about the network nodes, such as the type (static or mobile) and the number of hops to reach them. This information then can be used to support network operations. The protocol performance has been evaluated via simulations and during two at-sea campaigns: the 2016 Recognized Environmental Picture exercise (REP16), conducted in the Atlantic Ocean, and the 2017 Communications Network trial (CommsNet17), conducted by the NATO Science and Technology Organization Centre for Maritime Research and Experimentation (CMRE) in the Gulf of La Spezia, Italy. A variety of networking scenarios have been explored to validate the proposed solution, including node mobility as well as node addition and removal. The results show that DIVE is an efficient and reliable solution for node ID assignment and network discovery that scales with the network size in the presence of an unreliable communication channel. Additionally, when compared to a state-of-the-art solution, the usage of short IDs can significantly reduce the energy consumption and prolong the network lifetime.

Design and implementation of the data acquisition system of a large scale network based on four-in-one meters

For households, water supply, power supply, pipeline gas and centralized heating are necessaries to maintain the normal life of a family. For Chinese urban families, water, electricity, gas, warm services are often provided by different government utility companies. Aimed at the shortage of the manual measurement of the above mentioned services‘ consumptions, a new mechanism using network metering devices is proposed in this paper. Based on the general network measurement mechanism and through analysis, this paper proposes using meter communication network as the public communication network of various metering devices, forming wireless mesh network by metering devices, constituting a virtual private network by the power company's network, and accessing to metering network based on SCEP protocol and certificates of devices. Under this new network measurement mechanism, a network routing optimization strategy, a data acquisition protocol based on IPv6 and a mesh network management system are designed, and preliminary experiments have been carried on. Experimental results show that the proposed mechanism can realize functions through the network, including the control of multi-measuring devices, topology discovery, data acquisition, fulfilling the multi-meter data acquisition system via network.

Deployment Management and Topology Discovery of Microservice Applications in the Multicloud Environment

Cloud computing enables the evolution of modern software application design. Applications based on microservice architecture are an example. Meanwhile, multiclouds are widely accepted by enterprise as an infrastructure strategy; however, challenges remain. The autonomous and distributable nature of modern applications, as well as the complexity of multicloud infrastructure, often make universal application deployment management impractical. This phenomenon may further hinder application quality and efficiency. Therefore, deployment resource control and topology discovery in the multicloud infrastructure environment is an intriguing area of cloud computing research. This paper proposes a framework to manage application deployment in the multicloud environment. The framework uses a policy-based deployment control to automatically select and provide deployment resources from the multicloud infrastructure, and it subsequently uses topology discovery to visualize and verify the actual deployment. The proposed framework design is introduced in the paper, and a proof-of-concept prototype is implemented. Experiments in empirical scenarios are conducted. The experimental results indicate that the proposed framework is effective in controlling deployment resources and presenting actual deployment across clouds.

Models and methods for local area network topology discovery with incomplete data

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.

Research of information dissemination processes in decentralized networks

The article presents the results of the analysis of the processes of node propagation, which create a decentralized network, store and generate information of this network, and interact with each other influencing the general state of the system. A modeling study of the effectiveness of the experimental algorithm of the system of monitoring and analysis of the behavior of the nodes of the corresponding system was carried out. A comparison of the obtained results with existing solutions is given. To study the topology, a test version of the program was used, which allows to collect information about functioning nodes by direct interaction. The research was conducted on the example of peer-to-peer decentralized Bitcoin network systems. As a result of the work, a software product was created that analyzes the Bitcoin network, builds its topology, and tracks the changes that have taken place dreamed in the network, and provides visualization of results in real time. During the study of the existing implementations of distribution processes in decentralized systems, the issues concerning the opening of peers and their management were investigated. The problem of topology discovery in bitcoin network and basic methods of topology detection are considered. An alternative method of solving this problem is proposed.

Efficient Topology Discovery for Software-Defined Networks

OpenFlow discovery protocol (OFDP) is the standard protocol for discovering network topologies for OpenFlow. Each controller generates and receives OFDP messages for each switch to yield a network topology. However, for a network with a large number of switches, the controller may suffer from high overhead to perform OFDP even though the network topology remains unchanged. In this article, we improve the efficiency of network topology discovery by implementing a delegated function in OpenFlow switches. Our mechanism can reduce controller’s overhead for topology discovery to shorten the time of discovering a network topology. It also provides with the interoperability with switches which only perform OFDP. The experimental results demonstrate that the proposed scheme can improve the time for discovering a new network topology by decreasing the number of messages. Our scheme also eliminates unnecessary Packet-Out and Packet-In messages when the network topology remains unchanged. As a result, the controller overhead, including CPU usage and traffic load, is greatly reduced to shorten the response latency of controllers. Hence, the proposed scheme improves the feasibility of achieving scalable OpenFlow networking.

DESIGN OF A MINIMAL OVERHEAD CONTROL TRAFFIC TOPOLOGY DISCOVERY AND DATA FORWARDING PROTOCOL FOR SOFTWARE-DEFINED WIRELESS SENSOR NETWORKS

Software-defined networking is a novel concept that is ported into wireless sensor networks to make them more manageable and customizable. unfortunately, the topology discovery and maintenance processes generate high overhead control packet exchange between the sensor nodes and the central controller leading to a deterioration of the network's performance. In this paper, a novel minimal overhead control traffic topology discovery and data forwarding protocol is proposed and detailed. The proposed protocol requires some changes to the topology discovery protocol implemented in SDN-WISE to improve its performance. The proposed protocol has been implemented within the IT-SDN framework for evaluation. The results show reduced overhead control traffic and increase, of about 20%, data packet delivery rate over the protocol in SDN-WISE.

Behavior Anomaly Detection in SDN Control Plane: A Case Study of Topology Discovery Attacks

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.