IP Networks Research Articles

Benefits of Using Network Modeling Platforms When Studying IP Networks and Traffic Characterization

This article addresses the benefits of using IP network modeling platforms to study IP networks. For the purposes of this study, several models of IP networks were created, through which various hypotheses were studied. Additionally, different operational variants of the modeled IP networks were created. The use of the GNS3 platform was proposed, as well as several tools for monitoring the processes in IP networks. The application of IP network modeling platforms to study power electronic devices was also addressed. IP network modeling platforms greatly facilitate both the process of studying IP networks and the process of training professionals to design, install, and maintain different types of IP network. Thanks to the GNS3 IP network modeling platform, it was possible to implement different models of IP networks with different functionalities. It was very easy to determine the answers to posed hypotheses/questions through the capabilities of the IP network modeling platforms. The questions posed by the hypotheses addressed in this paper were answered thanks to the results obtained from the research carried out with the IP network modeling platform GNS3. The present study confirmed that the use of these platforms, in particular the GNS3 platform, for the modeling of IP networks is an excellent substitute for expensive network equipment, and the IP network models created in the platform performed almost like networks made of real devices.

Quality of Service (QoS) Performance Analysis in a Traffic Engineering Model for Next-Generation Wireless Sensor Networks

Quality of Service (QoS) refers to techniques that function on a network to dependably execute high-priority applications and traffic reliably run high-priority applications and traffic even when the network’s capacity is limited. It is expected that data transmission over next-generation WSNs (Wireless Sensor Networks) 5G (5th generation) and beyond will increase significantly, especially for multimedia content such as video. Installing multiple IoT (Internet of Things refers to the network of devices that are all connected to each other) nodes on top of 5G networks makes the design more challenging. Maintaining a minimal level of service quality becomes more challenging as data volume and network density rise. QoS is critical in modern networks because it ensures critical performance metrics and improves end-user experience. Every client attempts to fulfill QoS access needs by selecting the optimal access device(s). Controllers will then identify optimum routes to meet clients’ core QoS needs in their core network. QoS-aware delivery is one of the most important aspects of wireless communications. Various models are proposed in the literature; however, an adaptive buffer size according to service type, priority, and incoming communication requests is required to ensure QoS-aware wireless communication. This article offers a hybrid end-to-end QoS delivery method involving customers and controllers and proposes a QoS-aware service delivery model for various types of communication with an adaptive buffer size according to the priority of the incoming service requests. For this purpose, this paper evaluates various QoS delivery models devised for service delivery in real time over IP networks. Multiple vulnerabilities are outlined that weaken QoS delivery in different models. Performance optimization is needed to ensure QoS delivery in next-generation WSN networks. This paper addresses the shortcomings of the existing service delivery models for real-time communication. An efficient queuing mechanism is adopted that assigns priorities based on input data type and queue length. This queuing mechanism ensures QoS efficiency in limited bandwidth networks and real-time traffic. The model reduces the over-provisioning of resources, delay, and packet loss ratio. The paper contributes a symmetrically-designed traffic engineering model for QoS-ensured service delivery for next-generation WSNs. A dynamic queuing mechanism that assigns priorities based on input data type and queue length is proposed to ensure QoS for wireless next-generation networks. The proposed queuing mechanism discusses topological symmetry to ensure QoS efficiency in limited bandwidth networks with real-time communication. The experimental results describe that the proposed model reduces the over-provisioning of resources, delay, and packet loss ratio.

Design and analysis of lightweight anonymity protocol for host- and AS-level anonymity

Lightweight anonymity protocols in the network layer are promising in terms of high throughput and low latency. The realistic and weak assumption of local adversaries deletes the need for hop-by-hop encryption of onion routing, and this contributes to high throughput and low latency. Among them, PHI and its successor dPHI are promising due to the fact that path-setup packets for anonymous paths are forwarded according to IP routing. This feature enables easy deployment of the protocol on the Internet infrastructure. However, PHI and dPHI are vulnerable to adversaries such as malicious ASes who compromise servers for path setup, called helpers, and malicious ASes who leverage topological information and routing policies of the IP network. The paper resolves the vulnerabilities in the two steps. In the first step, we design attacks that leverage the vulnerabilities to break anonymity. In the second step, we extend dPHI to mitigate such attacks by adding a new server called a guard. The extended protocol is called gPHI, and gPHI is resilient against adversaries who perform such attacks. This paper designs gPHI and validates its resilience through formal proof and simulation.

Low delay network attributes randomization to proactively mitigate reconnaissance attacks in industrial control systems

Industrial Control Systems are used in a wide variety of industrial facilities, including critical infrastructures, becoming the main target of multiple security attacks. A malicious and successful attack against these infrastructures could cause serious economic and environmental consequences, including the loss of human lives. Static networks configurations and topologies, which characterize Industrial Control Systems, represent an advantage for attackers, allowing them to scan for vulnerable devices or services before carrying out the attack. Identifying active devices and services is often the first step for many attacks. This paper presents a proactive network reconnaissance defense mechanism based on the temporal randomization of network IP addresses, MAC addresses and port numbers. The obtained information distortion minimizes the knowledge acquired by the attackers, hindering any attack that relies on network addressing. The temporal randomization of network attributes is performed in an adaptive way, minimizing the overhead introduced in the network and avoiding any error and latency in communications. The implementation as well as the tests have been carried out in a laboratory with real industrial equipment, demonstrating the effectiveness of the presented solution.

CS-SPT: Secure and Packet Loss-Resilient Audio Transmission Based on Compressive Sensing

Packet loss-resilient and security are two major challenges faced by real-time audio transmission over IP networks. Due to the capability of recovering the signal from a small set of samplings and the randomness in the acquisition process, compressive sensing (CS) has a vast prospect in dealing with these problems. In this paper, we propose a secure and packet loss-resistant real-time audio transmission framework (CS-SPT) based on the principle of CS. Inspired by the interleaving technique, an ultralow complexity scrambling matrix was adopted in the proposed CS-SPT to improve its packet loss-resilient capability by increasing the information redundancy. Moreover, the energy of ciphertext is homogenized using a diffusion operation. Experimental results show that compared with existing methods, the proposed CS-SPT not only improves the packet loss-resilient ability significantly but also can resist several major attacks, such as COAs and KPAs.

Traffic Classification in IP Networks Through Machine Learning Techniques in Final Systems

Traffic Classification in IP Networks Through Machine Learning Techniques in Final Systems

WAYS OF THE ASTERISK SOFTWARE PBX PROTECTION

Network protection of the Asterisk software PBX widely used in modern info-communication networks is considered. This particular telephone exchange is used to set up telephone communications at the Moscow Technical University of Communications and Informatics. When connecting this software telephone exchange to IP networks, it is necessary to provide its protection to prevent it from being attacked by intruders. The Asterisk IP PBX has powerful protection tools. If properly applied, they can make the protection more reliable than that of some hardware IP PBXs. The protection system can be built in different ways. The most popular ones are the following types of protection: the iptables utility, the development of a proper network design involving the use of VLAN and VPN technologies, the utilization of Fail2Ban log file analyzer. Protection can also be implemented by means of DialPlan and developing a proper configuration of the Asterisk IP PBX.

Existing Fast Reroute Mechanisms in SDN

Nowadays, the implementation of networks using software-defined resource environments is becoming more and more widespread. As with classic IP networks, it is necessary to consider possible complications that occur during connectivity failures (packet loss, unavailable services, congestion). A critical aspect when a connection fails is the time required to restore it. In Software-Defined Networks (SDN), where topologies are large, there are several ways to look for ways to improve network recovery speed. Fast Reroute solutions have been developed to solve negative impacts after link or node failure in SDN.This paper introduces current Fast Reroute mechanisms in Software-defined networking (SDN). The most used mechanisms include Openflow Fast Failover groups, OpenState failover technique, Loop-free Alternate (LFA) and Remote LFA (RLFA).

Analytical Design of Synchrophasor Communication Networks with Resiliency Analysis Framework for Smart Grid

The advent of synchrophasor technology has completely revolutionized the modern smart grid, enabling futuristic wide-area monitoring protection and control. The Synchrophasor Communication Network (SCN) is a backbone that supports communication of synchrophasor data among Phasor Measurement Units (PMUs) and Phasor Data Concentrators (PDCs). The operator at the control center can visualize the health of the smart grid using synchrophasor data aggregated at PDCs from several PMUs. Since the core of the SCN is the existing IP network as an underlying communication infrastructure, the synchrophasor data is subjected to attacks that can compromise its security. The attacks, such as denial-of-service (DoS), can result in degradation of performance and even can disrupt the entire operation of the smart grid, if not controlled. Thus, a resilient SCN is a pertinent requirement in which the system continues to operate with accepted levels of performance even in response to the DoS. This article endeavors to propose a comprehensive resiliency framework for the SCN with enhanced resiliency metrics based on hardware reliability and data reliability. The proposed framework is deployed for a SCN pertaining to a practical power grid in India for its resiliency analysis. The proposed work can be regarded as a significant contribution to smart grid technology, as it provides a framework for resiliency analysis covering different aspects such as hardware reliability, data reliability, and parameters validation using the QualNet network simulator. Nevertheless, an analytical design of the hybrid SCN proposed in this work can even be extended to other topological designs of SCN.

Novel Modification of the Collective Dynamic Routing Method for Sensors' Communication in Wi-Fi Public Networks.

The widespread use of the Internet of Things makes it relevant to use public IP networks for simultaneous access by both users and wireless sensors. To achieve this, a significant reduction in the subscriber devices' energy consumption is required. This paper analyzes the application features of the collective dynamic routing method both with and without the use of a robust method for estimating the channel data rate for sensors' communication in wireless public networks. Based on the analysis, a novel modification of the collective dynamic routing method has been developed that reduces the sensors' energy consumption while keeping a high data rate and short delivery time for users. An analysis of the network load, the total data transfer rate over the network, and the parameters affecting the sensors' energy consumption was carried out for a segment of a seamless IEEE 802.11ax network. The simulation demonstrated a high efficiency of using a novel modification of the collective dynamic routing method for access to users and wireless sensors.

A Multimodel-Based Approach for Estimating Cause of Scanning Failure and Delay in IoT Wireless Network

The rapid growth in the IoT network comes with a huge security threat. Network scanning is considered necessary to identify vulnerable IoT devices connected to IP networks. However, most existing network scanning tools or system do not consider the burden of scan packet traffic on the network, especially in the IoT network where resources are limited. It is necessary to know the status of the communication environment and the reason why network scanning failed. Therefore, this paper proposes a multimodel-based approach which can be utilized to estimate the cause of failure/delay of network scanning over wireless networks where a scan packet or its response may sometimes be dropped or delayed. Specifically, the factors that cause network scanning failure/delay were identified and categorized. Then, using a machine learning algorithm, we introduced a multimodel linear discriminant analysis (MM-LDA) to estimate the cause of scan failure/delay based on the results of network scanning. In addition, a one-to-many model and a training data filtering technique were adopted to ensure that the estimation error was drastically reduced. The goal of our proposed method was to correctly estimate the causes of scan failure/delay in IP-connected devices. The performance of the proposed method was evaluated using computer simulation assuming a cellular (LTE) network as the targeted IoT wireless network and using LTE-connected devices as the targeted IoT devices. The proposed MM-LDA correctly estimates the cause of failure/delay of the network scan at an average probability of 98% in various scenarios. In comparison to other conventional machine learning classifiers, the proposed MM-LDA outperforms various classification methods in the estimation of the cause of scan failure/delay.

Integrated QoS management technique for internet protocol storage area networks

The increasing number of Information Technology Users around the world has led to tremendous increase in the amount of data that requires storage. Traditional implementations of storage area networks are not able to meet the increasing demand for storage capacity as well as a reduction in the operational and capital expenditures. In response to this challenge, new storage area network architectures based on Ethernet (IP) have evolved. IP storage network is a network of storage devices where the underlying technology is based on IP protocol. The creation Internet protocol storage SANS is enabled by the use of iSCSI protocol which makes it possible for SCSI commands to be transmitted over IP network. Meanwhile, storage QoS has become of great importance with the need of assuring a suitable storage service to the clients who share the same pool of IP storage. With the coexistence of storage traffic with other types of traffic in the same IP network, it is important to offer storage traffic QoS guarantees to prevent performance degradation for storage users. Regrettably, the storage device itself does not provide any capability of guaranteeing storage QoS. The research process involved four stages: This first stage involved systematics review of literature to determine techniques for providing QoS in IP networks and then categorized based on performance isolation, bandwidth management and burst handling. However most of the techniques reviewed were found to implement QoS techniques in the storage devices themselves which means the same algorithm run on different devices. In addition, the reviewed techniques did not put into consideration the network statistics when assigning resources. The second stage involved the optimization of QoS techniques for performance isolation, bandwidth management and burst handling for users in IP SANs. Third phase involved the integration of performance isolation, bandwidth management and burst handling techniques for QoS in IP SANs. The fourth stage involved the validation of the integration of the QoS techniques of performance isolation, bandwidth management and validation of the integrated technique based on the response time, throughput and jitter QoS metrics. To optimize the performance isolation, the study formulates an optimization problem to find optimal performance isolation schedule and use it to bind resources to class of users. The study optimized the process of matching packets to rules by sorting rules based on priority, splitting rules and use of a linear tree rue structure. Experimental results generated proves that the proposed performance isolation technique show significant reduction in response time and increase in throughput.To optimize bandwidth management also formulate an optimization problem to find out the optimal bandwidth allocation for optimal burst handling using network statistics. The research put forward HPDDRR a hierarchical priority based scheduling technique that used a quantum generated based network statistics and priority of users. Experiments results proves that HPDDRR is able to allocated bandwidth proportionate to the user’s priority and when there is idle bandwidth is shared based on priority. The results further show that users that generate burst within their allowed limits do not miss deadlines.

Proposal and Simulation with NS3 of a New offloading Algorithm between LTE/LTE-Advanced and Wi-Fi

The field of mobile telecommunications is an integral part of our society. In the wake of IT, it is implemented and used in all areas of society. This deep anchoring, which mobile networks use today, poses significant problems for operators in terms of speed, capacity demands and customer satisfaction, particularly for the quality of services, but also in terms of profitability and cost of services investments. Reports from Ericsson and Cisco which are representative bases for calculating world total data traffic in cellular mobile networks predict that the number of devices connected to IP networks will be more than three times the global population by 2023. There will be 3.6 networked devices per capita by 2023, up from 2.4 networked devices per capita in 2018. There will be 29.3 billion networked devices by 2023, up from 18.4 billion in 2018. To answer these challenges, two choices are offered to the operators the evolution of the standards or the interconnection of several networks. In this order of idea, we carried out an 4G/4G+ -Wi-Fi offloading simulation algorithm. It was up to us to design an offloading algorithm and then to simulate through a dedicated environment in a scenario allowing to implement it. To achieve this, it was first necessary for us to understand the concept of mobile data offload, to know the types of mobile data offload and to choose one on which the present work will be based. Later we carried out an analysis of the existing data offload algorithms to be able to bring out the limits. From these limits we have designed and proposed a new traffic offloading algorithm with a different approach compared to the existing one studied in the literature. After all this, we have developed and simulated a scenario comprising a 3GPP network in this case the 4G + network, a non 3GPP network in this case the WiFi network, and we have implemented our algorithm via NS3 network simulation software. With this work, we have proposed a solution to overcome an investment deemed expensive to deploy 5G in Africa.

Joint energy efficiency and load balancing optimization in hybrid IP/SDN networks

Software-defined networking (SDN) is a paradigm that provides flexibility and programmability to computer networks. By introducing SDN nodes in a legacy IP network topology, network operators can benefit on higher control over the infrastructure. However, this migration is not a fast or straightforward process. Furthermore, to provide an adequate quality of service in hybrid IP/SDN networks, the coordination of both IP and SDN paradigm is fundamental. In this paper, this coordination is used to solve two optimization problems that are typically solved separately: (i) traffic load balancing and (ii) power consumption minimization. Each of these problems has opposing objectives, and thus, their joint consideration implies striking a balance between them. Therefore, this paper proposes the Hybrid Spreading Load Algorithm (HSLA) heuristic that jointly faces the problems of balancing traffic by minimizing link utilization and network’s power consumption in a hybrid IP/SDN network. HSLA is evaluated over differently sized topologies using different methods to select which nodes are migrated from IP to SDN. These evaluations reveal that alternative approaches that only address one of the objectives are outperformed by HSLA.

Analysis and Collection Data from IP Network

Abstract The rapid deployment of technologies that can share data brings, in addition to the positive aspects, also technologies that an attacker can use to misuse personal data. Vulnerabilities in the network can be divided according to the type of attack into horizontal attacks from the perspective of the attacker and vertical attacks from the perspective of the victim. An important goal of organizations is to successfully defend against such an attack. The search for attacks on the network infrastructure can be ensured by implementing machine learning that can capture the current attack. This work describes methods of searching for attacks using graphical representation of data and also using machine learning of the high count type at different sizes of the investigated segments.

Improving the Energy Efficiency of Software-Defined Networks through the Prediction of Network Configurations

During the last years, huge efforts have been conducted to reduce the Information and Communication Technology (ICT) sector energy consumption due to its impact on the carbon footprint, in particular, the one coming from networking equipment. Although the irruption of programmable and softwarized networks has opened new perspectives to improve the energy-efficient solutions already defined for traditional IP networks, the centralized control of the Software-Defined Networking (SDN) paradigm entails an increase in the time required to compute a change in the network configuration and the corresponding actions to be carried out (e.g., installing/removing rules, putting links to sleep, etc.). In this paper, a Machine Learning solution based on Logistic Regression is proposed to predict energy-efficient network configurations in SDN. This solution does not require executing optimal or heuristic solutions at the SDN controller, which otherwise would result in higher computation times. Experimental results over a realistic network topology show that our solution is able to predict network configurations with a high feasibility (>95%), hence improving the energy savings achieved by a benchmark heuristic based on Genetic Algorithms. Moreover, the time required for computation is reduced by a factor of more than 500,000 times.

High Capacity and Resilient Large-Scale Deterministic IP Networks

High Capacity and Resilient Large-Scale Deterministic IP Networks

The Usage of MPLS in Voice over IP Network

The Usage of MPLS in Voice over IP Network

Research on High Performance Intrusion Prevention System Based on Suricata

Suricata is an open source, high-performance network IDS, IPS and network security monitoring engine. Based on Suricata and AF-PACKET technology, this paper research on the Suricata IPS applied to Huawei Kunpeng 920 CPU and Galaxy Kylin operating system, designs defense rules for common network threats at present, and tuning the performance of Suricata IPS in a high-traffic network environment. Using Ixia network tester, the results show that the design scheme can fully adapt to the relevant hardware system and software environment, the network throughput can reach 20Gbps.

Construction of Dual-CISTs on an Infinite Class of Networks

The main method to achieve fault-tolerant network systems is by exploiting and effectively utilizing the edge-disjoint and/or inner-vertex-disjoint paths between pairs of source and destination vertices. Completely independent spanning trees (CISTs for short) are powerful tools for reliable broadcasting/unicasting and secure message distribution. Particularly, it has been shown that two CISTs have an application on configuring a protection routing in IP networks, such as mobile ad hoc networks and relatively large (static) network topologies with scalability in [IEEE/ACM Trans. Netw., 27 (2019) 1112-1123]. Many results focus on CISTs in specific networks in the literature, however, few results are given on an infinite class of networks having common properties. In this article, we prove the existence of dual-CISTs in an infinite number of networks satisfying some Hamilton sufficient conditions. A unique algorithm to construct a CIST-partition is proposed, which can be applied to not only many kinds of networks, but our algorithm can also be implemented very easily in parallel or distributed systems satisfying the conditions. In addition, we make a comparative analysis between the proposed conditions and several known results on an infinite number of networks, the advantage of our result is significant. In particular, the bound in our conditions is sharp. The results will provide a powerful framework for the design of fault-tolerant network topologies and routing protocols for future networks.