Legacy Networks Research Articles

ERT-EDR: Online defense framework for TCP-targeted LDoS attacks in SDN

The Low-rate denial of service (LDoS) attack is a variant of denial of service (DoS) attack that exploits low overhead to render target services unreachable for legitimate users. Unlike legacy networks, software-defined networking (SDN) separates the behavior of controlling and forwarding, providing excellent programmability to achieve real-time defense against LDoS attacks. Leveraging the potential of SDN’s programmability, we propose a real-time anomaly defense framework tailored for SDN, named ERT-EDR. This framework is capable of detecting and mitigating TCP-targeted LDoS Attacks and comprises three modules: (1) The Information Collection Module. It periodically samples the traffic statistics for analysis. (2) The LDoS Attack Detection Module. It combines six features of traffic statistics and utilizes the Extremely Randomized Trees (ERT) algorithm to detect. (3) LDoS Attack Mitigation Module. It locates attacked ports with the Edit Distance on Real sequence (EDR) algorithm and installs flow table entries to filter attack traffic.Extensive experiments are conducted under various background traffic scenarios to validate the effectiveness and scalability of ERT-EDR. The results demonstrate that ERT-EDR can effectively detect TCP-targeted LDoS attacks with 96.4667% accuracy and 96.4977% F1score. Furthermore, it accurately identifies the attacked port and successfully mitigates attacks.

A measurement-based approach to analyze the power consumption of the softwarized 5G core

In light of the ever growing energy needs of the ICT sector, a value that is becoming increasingly important for a mobile network is its power consumption. However, the transition away from legacy network deployments tightly coupled with the underlying hardware and the adoption of the Network Function Virtualization (NFV) paradigm has made more difficult to accurately evaluate their energy and carbon footprint. In this paper, we propose and validate a measurement-based approach to analyze the power consumption of a virtualized 5G core network (5GC) deployment. We design an experimental testbed using commercial off-the-shelf (COTS) hardware and open-source software as a sample architecture simulating an edge computing node and supporting three different virtualization options. We make use of both hardware-based and software-based power meters to investigate the power consumption trends associated with increasing levels of traffic and multiple 5GC deployment types. The results show the feasibility of a real-time power monitoring system and highlight how deployment choices, such as virtualization framework and 5GC software, can significantly impact on the power consumption of the network.

An Enhanced Dynamic Multi-Path Routing Algorithm for Software Defined Networks

Software-defined networking (SDN) is an emerging technology that addresses the limitations of legacy networks when handling the growing traffic demands. Legacy networks face issues like heavy traffic loads, congestion and delays. SDN offers a solution to these challenges. However, an efficient routing algorithm is required to transmit data packets through the network. While there are existing routing algorithms, there remains a need for a highly efficient one that minimizes packet loss and optimizes link utilization. One commonly used routing for mitigating issues, such as packet loss, delay and bandwidth allocation, is multipath routing. The inherent flexibility of SDN, which provides a comprehensive overview of network status, empowers routing algorithms to generate efficient routing paths. We introduce the enhanced dynamic multipath routing (EDMR) algorithm in this context. This algorithm dynamically generates and updates routing paths within the network's switches. Its dynamic nature significantly reduces packet loss and minimizes end-to-end delays.

Effectiveness of Legacy Network Governance through Pre-event Legacy Planning: The World Masters Games 2021 Kansai

Effectiveness of Legacy Network Governance through Pre-event Legacy Planning: The World Masters Games 2021 Kansai

Malay Ulama in Deli Land: The Life, Manuscripts, and Intellectual Networks of Shaykh Hasan Ma‘sum (d. 1936)

Abstract: This article examines the life, manuscript legacy, and intellectual network of Shaykh Hasan Ma‘sum, one of the most influential Malay scholars in the early 20th century in East Sumatra. He was one of the finest disciples of Syekh Ahmad Khatib al-Minangkabawi at Masjidil Haram and the esteemed mentor of the founders and scholars of Al Washliyah, Al Ittihadiyah, and Nahdlatul Ulama in East Sumatra. This study adopts a biographical research approach within a historical framework. The primary sources for this research are the works of Shaykh Hasan Ma‘sum, which are subsequently analyzed using content analysis methodology. The findings of the study reinforce Azra’s thesis regarding the pattern of intellectual relations among Nusantara scholars, where Shaykh Hasan Ma‘sum studied under several prominent scholars in Haramain, and later had numerous disciples in East Sumatra. Shaykh Hasan Ma‘sum also enriched the traditional Islamic literature by writing and publishing numerous manuscripts. All of his works, which were penned in Malay with Arabic script, and some in Arabic, encompass various fields including creed, jurisprudence, mysticism, and astronomy. Keywords: Malay, ulama, East Sumatra, manuscripts, intellectual networks

Coexistence in future optical access networks from an operator’s perspective [Invited

In this paper, we address the challenges related to the simultaneous operation of legacy and future network technologies in passive optical networks (PONs) and point-to-point topologies. We explore the coexistence issues for various user categories, including residential, enterprise, factories, and mobile users. The future access networks will need to accommodate multiple technologies concurrently. Our paper demonstrates how G-PON, XGS-PON, and 50G-PON can coexist on the same optical distribution network using triple coexistence multi-PON modules. However, there are certain limitations that need to be considered, such as achieving a high optical budget and the associated costs, both in terms of monetary investment and CO2 emissions for technology deployment by operators. Additionally, we emphasize the significance of optical line terminals (OLTs) as crucial network components in the future. OLTs play a central role in supporting the traffic evolution with optimal efficiency in terms of throughput, latency, jitter, and adherence to CO2 emission constraints. Finally, we experimentally demonstrate the first assessment, to our knowledge, of a 50G-PON prototype with optical budget reaching 23.9 dB limited by the downstream (DS). Furthermore, we evaluate the potential limitations regarding coexistence by examining the effects of stimulated Raman scattering between the DS of 50G-PON and the upstream of XGS-PON for the first time with real PON systems.

Fifth Generation Non-Standalone to Standalone Wireless Architecture Reconstruction Solution and Implementation: South Africa Context

The wireless mobile communication industry has evolved immensely over the past five decades, starting from the voice-centric 1G technology to the current data-centric 5G technology because of the increasing data traffic and the need for higher data speed rates. To provide the initial experience of 5G technology, many network operators worldwide started their deployment with the Non-Standalone (NSA) solution to mainly reduce the cost and time. 5G NSA solution already provides lower latency, higher network capacity, and bandwidth compared to the legacy network, however, there is growing oncern about its reliance on the 4G core network, capability, and the long-term migration plan to 5G Standalone (SA) network solution. This paper discusses a brief review of 5G evolution, standardization formulation, deployment strategies, security enhancement, challenges, and presents the reconstruction of 5G NSA to SA solution implementation. Furthermore, a 5G field test will be performed to analyze the user experience under the NSA NR in South Africa, and key practical challenges facing the South African MNOs from the perspective of business and technical challenges will be discussed with recommendations.

AI Empowered Net-RCA for 6G

6G is envisioned to offer higher data rate, improved reliability, ubiquitous AI services, and support massive scale of connected devices. As a consequence, 6G will be much more complex than its predecessors. The growth of the system scale and complexity as well as the coexistence with the legacy networks and the diversified service requirements will inevitably incur huge maintenance cost and efforts for future 6G networks. Network Root Cause Analysis (Net-RCA) plays a critical role in identifying root causes of network faults. In this article, we first give an introduction about the envisioned 6G networks. Next, we discuss the challenges and potential solutions of 6G network operation and management, and comprehensively survey existing RCA methods. Then we propose an artificial intelligence (AI)- empowered Net-RCA framework for 6G. Performance comparisons on both synthetic and real-world network data are carried out to demonstrate that the proposed method outperforms the existing method considerably.

Performance Assessment of QoS metrics in Software Defined Networking using Floodlight Controller

The quality of service is not the same in all parts of the network. Some areas experience a low level and others a higher level of fixed quality services. The shortcomings in legacy networks encouraged researchers to find a new paradigm of the network to obviate legacy networks' deficiencies. The effort to create network services is called Quality of Service (QoS). Software-Defined Networking (SDN) focuses on separating the control layer from the data layer, and their communication is done through a central controller named SDN controller. After separation, the data layer moves the packets through the network according to the commands it receives from the controller. The controller obtains applications (QoS requests), translates them to low-level instructions, and implements them in the data layer. In this paper, we create an infrastructure for Quality of Service (QoS) in tree topology using a meter table per flow in Software Defined Networking Floodlight open-source controller. Meters are introduced into the OpenFlow protocol version 1.3, which calculates the packet rates allocated to them and allows control of those packet rates. Meters are directly connected to flow entry. Any flow entry can determine a meter in its command collection, which calculates and supervises the sum of all flow entries to which it is connected. When we get statistics from the meter table in each switch, we manage the network and affect the routing algorithms.

EXPLORING ROUTING AND QUALITY OF SERVICE IN SOFTWARE-DEFINED NETWORKS: INTERACTIONS WITH LEGACY SYSTEMS AND FLOW MANAGEMENT

The following article presents the most important aspects of routing technologies and the QoS (Quality of Service) of the SDN architecture. The interaction of SDN with traditional or legacy networks is discussed in depth and concepts related to flow management are developed. Additionally, the analysis of the Open Flow protocol is included.

Investigation of application layer DDoS attacks in legacy and software-defined networks: A comprehensive review

Investigation of application layer DDoS attacks in legacy and software-defined networks: A comprehensive review

A Comprehensive Survey on Knowledge-Defined Networking

Traditional networking is hardware-based, having the control plane coupled with the data plane. Software-Defined Networking (SDN), which has a logically centralized control plane, has been introduced to increase the programmability and flexibility of networks. Knowledge-Defined Networking (KDN) is an advanced version of SDN that takes one step forward by decoupling the management plane from control logic and introducing a new plane, called a knowledge plane, decoupled from control logic for generating knowledge based on data collected from the network. KDN is the next-generation architecture for self-learning, self-organizing, and self-evolving networks with high automation and intelligence. Even though KDN was introduced about two decades ago, it had not gained much attention among researchers until recently. The reasons for delayed recognition could be due to the technology gap and difficulty in direct transformation from traditional networks to KDN. Communication networks around the globe have already begun to transform from SDNs into KDNs. Machine learning models are typically used to generate knowledge using the data collected from network devices and sensors, where the generated knowledge may be further composed to create knowledge ontologies that can be used in generating rules, where rules and/or knowledge can be provided to the control, management, and application planes for use in decision-making processes, for network monitoring and configuration, and for dynamic adjustment of network policies, respectively. Among the numerous advantages that KDN brings compared to SDN, enhanced automation and intelligence, higher flexibility, and improved security stand tall. However, KDN also has a set of challenges, such as reliance on large quantities of high-quality data, difficulty in integration with legacy networks, the high cost of upgrading to KDN, etc. In this survey, we first present an overview of the KDN architecture and then discuss each plane of the KDN in detail, such as sub-planes and interfaces, functions of each plane, existing standards and protocols, different models of the planes, etc., with respect to examples from the existing literature. Existing works are qualitatively reviewed and assessed by grouping them into categories and assessing the individual performance of the literature where possible. We further compare and contrast traditional networks and SDN against KDN. Finally, we discuss the benefits, challenges, design guidelines, and ongoing research of KDNs. Design guidelines and recommendations are provided so that identified challenges can be mitigated. Therefore, this survey is a comprehensive review of architecture, operation, applications, and existing works of knowledge-defined networks.

Survey on Applications of Machine Learning in Low-Cost Non-Coherent Optical Systems: Potentials, Challenges, and Perspective

Direct Detection (DD) optical performance monitoring (OPM), Modulation Format Identification (MFI), and Baud Rate Identification (BRI) are envisioned as crucial components of future-generation optical networks. They bring to optical nodes and receivers a form of adaptability and intelligent control that are not available in legacy networks. Both are critical to managing the increasing data demands and data diversity in modern and future communication networks (e.g., 5G and 6G), for which optical networks are the backbone. Machine learning (ML) has been playing a growing role in enabling the sought-after adaptability and intelligent control, and thus, many OPM, MFI, and BRI solutions are being developed with ML algorithms at their core. This paper presents a comprehensive survey of the available ML-based solutions for OPM, MFI, and BFI in non-coherent optical networks. The survey is conducted from a machine learning perspective with an eye on the following aspects: (i) what machine learning paradigms have been followed; (ii) what learning algorithms are used to develop DD solutions; and (iii) what types of DD monitoring tasks have been commonly defined and addressed. The paper surveys the most widely used features and ML-based solutions that have been considered in DD optical communication systems. This results in a few observations, insights, and lessons. It highlights some issues regarding the ML development procedure, the dataset construction and training process, and the solution benchmarking dataset. Based on those observations, the paper shares a few insights and lessons that could help guide future research.

The new trends in networking: IOT, 5G and cognitive radio

The domain of networking and wireless communication is rapidly expanding to the point where traditional legacy networks research is nearly complete, and they are supposed to be an elder. IoT, the Internet of Things, and the 5G radio communications are the newest networking advancements. These two technologies fulfil all of the researchers' goals of improving people's quality of life. IoT is a framework that allows everyday devices to become smarter, processing to become more intelligent, and communication to become more relevant. The Internet of Things (IoT) has already made huge progress as a ubiquitous solution platform for the linked world. We also discussed the Radio Cognitive RC, which allows people to connect to networks as secondary users at no cost while the service provided is not as good as that provided to primary users who pay a license to use the network. RC can provide a solution for best-effort IoT applications that do not require constant connectivity and high QoS requirements. This study describes all of these technologies and concludes with a recommendation for using IoT and RC in our further works.

An End-Host-Importance-Aware Secure Service-Enabled Hybrid SDN Deployment

Security is critical to networks, but TCP/IP-based legacy networks are difficult to advance new security functions due to the use of costly inflexible hardware devices and error-prone network configurations. Recent literature explores the paradigm of consolidating security services with the forwarding functionality using Software-defined Networking (SDN). Existing full SDN deployment, replacing all legacy network devices with SDN devices, is cost-prohibitive. Whereas the hybrid SDN that only upgrades partial legacy devices to SDN switches is considered practical. However, the challenge is to minimize threats and deployment expenses simultaneously under heterogeneous end-host businesses that have various importance. In this paper, we study the challenge and propose the (EASON) problem. We mathematically formulate the EASON problem as an integer programming problem, prove its non-polynomial time complexity, and propose a heuristic algorithm called BonSéc. We conduct rigorous simulations on real-world topologies and traces. Experimental results show that BonSéc achieves comparable security and cost performances to the optimal solution on small topologies. Meanwhile, it is scalable on larger topologies.

P4Tune: Enabling Programmability in Non-Programmable Networks

Data plane programmability has attracted significant attention, permitting network operators to run customized packet processing functions. Unfortunately, networks today are still largely dominated by proprietary fixed-function devices. It is challenging for operators to completely migrate to programmable data planes (PDPs) due to the economical costs of replacing equipment and limited expertise in maintaining and operating programmable networks. This article introduces P4Tune, a cost-efficient architecture that uses passive PDPs coupled with optical taps. P4Tune runs customized packet processing functions operating at line rate and collects network information with nanosecond resolution. This visibility enables intelligent algorithms residing in the control plane to construct configuration rules and apply them on the legacy devices, thus creating a closed control loop. P4Tune brings the benefits of processing traffic at line rate to legacy networks. Additionally, by using PDPs passively, the architecture can be safely deployed without disrupting current network operations, fostering incremental use of PDPs (i.e., no need to deploy complex code at once). The article demonstrates three applications of the proposed architecture related to Quality of Service (QoS) and cybersecurity.

Enabling Dynamic Autoscaling for NFV in a Non-Standalone Virtual EPC: Design and Analysis

Network function virtualization (NFV) is a novel concept that enables an architectural transition from dedicated hardware to orchestrated resource and function management. As an integral part of the core network, NFV offers a fine-grained network capability to cellular operators by scaling out or scaling in network resources in an on-demand manner to meet the performance requirements. However, designing an autoscaling algorithm with low operation cost and low latency in non-standalone networks, where legacy network equipment coexists with a virtual evolved packet core (EPC), is a challenging task. In this paper, we propose a dynamic NFV instance autoscaling algorithm that considers the tradeoff between performance and operation cost. Furthermore, we develop an analytical framework to assess the performance of the scheme by modeling the hybrid network as a queueing system that includes both legacy network equipment and NFV instances. The virtualized network function (VNF) instances are powered on or off according to the number of job requests. Numerical results based on extensive simulations validate the correctness of the model and the effectiveness of the algorithm.

Evolution of Hybrid LiFi-WiFi Networks: A Survey.

Given the growing number of devices and their need for internet access, researchers are focusing on integrating various network technologies. Concerning indoor wireless services, a promising approach in this regard is to combine light fidelity (LiFi) and wireless fidelity (WiFi) technologies into a hybrid LiFi and WiFi network (HLWNet). Such a network benefits from LiFi's distinct capability for high-speed data transmission and from the wide radio coverage offered by WiFi technologies. In this paper, we describe the framework for the HWLNet architecture, providing an overview of the handover methods used in HLWNets and presenting the basic architecture of hybrid LiFi/WiFi networks, optimization of cell deployment, relevant modulation schemes, illumination constraints, and backhaul device design. The survey also reviews the performance and recent achievements of HLWNets compared to legacy networks with an emphasis on signal to noise and interference ratio (SINR), spectral and power efficiency, and quality of service (QoS). In addition, user behaviour is discussed, considering interference in a LiFi channel is due to user movement, handover frequency, and load balancing. Furthermore, recent advances in indoor positioning and the security of hybrid networks are presented, and finally, directions of the hybrid network's evolution in the foreseeable future are discussed.

Fountain Codes for Reliable and Deterministic Packet Transmission in Industrial Cloud Control Systems

With the thriving of digitalization in industry and the rapid development of cloud computing and Internet of Things (IoT), it has become a growing trend to integrate industrial control with the cloud platform to form industrial cloud control systems (ICCSs). However, ICCSs bring great challenges to legacy communication networks, especially, wireless networks, on reliability and determinacy. This article utilizes fountain code as application-layer coding to provide high-reliability low-latency deterministic communication for ICCSs. According to the simulation results, fountain code scheme, especially, RaptorQ code significantly improves communication reliability. The performance difference of fountain codes between time-critical use cases and nontime-critical use cases provides another perspective to analyze and evaluate fountain codes. Then, we propose a self-adaptive coding parameter selection method based on different industrial use cases, to better meet the communication requirements and reduce the coding cost.

Comparison of Flow Forwarding Between Software-Defined and Legacy Networks Based on Fixed Routing and QoS Conditions

Comparison of Flow Forwarding Between Software-Defined and Legacy Networks Based on Fixed Routing and QoS Conditions