Packet Forwarding Research Articles

Maximizing SDN resilience to node‐targeted attacks through joint optimization of the primary and backup controllers placements

AbstractIn software defined networks (SDN) packet data switches are configured by a limited number of SDN controllers, which respond to queries for packet forwarding decisions from the switches. To enable optimal control of switches in real time the placement of controllers at network nodes must guarantee that the controller‐to‐controller and switch‐to‐controller communications delays are bounded. Apart from the primary controllers that control the switches in the nominal state, separate backup controllers can be introduced that take over when the primary controllers are unavailable, and whose delay bounds are relaxed. In this paper, we present optimization models to jointly optimize the placement of primary and backup controllers in long‐distance SDN networks, aimed at maximizing the network's resilience to node‐targeted attacks. Applying the models to two well‐known network topologies and running a broad numerical study we show that, when compared with the standard approach of using only primary controllers, the use of backup controllers provides significant resilience gains, in particular in case of tight delay bounds.

The number of spanning trees in a k5 chain graph

Spanning trees (ST) have numerous applications in various fields, including computer science, graph theory, network design, and optimization. ST uses in designing efficient network topologies. In computer networks, a ST ensures that all nodes are connected while avoiding loops and redundant connections. This helps in minimizing network congestion and ensuring reliable communication. In routing protocols the ST’s play a crucial role such as the Spanning Tree Protocol (STP) and Rapid Spanning Tree Protocol (RSTP). These protocols are used to prevent network loops and establish a loop-free topology for efficient packet forwarding. In image processing the ST’s have applications in algorithms such as image segmentation and region merging. By constructing a minimum spanning tree based on pixel intensities or other image features, regions or objects can be efficiently grouped together. In wireless sensor networks, ST’s are employed to organize the network structure, reduce energy consumption, and enable efficient data collection. By constructing a spanning tree, sensor nodes can communicate with a central node or sink node while minimizing energy consumption and prolonging network lifetime. Motivated by the above applications and by the normalized Laplacian (NL) matrix, we obtained the spectrums of the n copies of K 5 chain graph, and is denoted by . By utilizing these spectrums, we have successfully calculated the number of spanning trees for .

A Novel Incentive Routing Protocol with Virtual Projection for Mobile Packet Forwarding Nodes in Wireless Sensor Networks

The size of the Packet Forwarding Nodes (PFNs) is becoming very small as the technology advances in Wireless Sensor Networks (WSNs). The node has an additional parameter with low energy levels. The PFNs are distributed in a square cross-sectional area with each node acting as a Sensing Point (SP) that can be used for various kinds of applications like temperature, atmospheric humidity, acoustic, and pressure measurements. The packet is divided into several fragments where each fragment is considered as fixed or variable length. Each of these packets is sent over multiple PFNs toward the data center using PFNs. The selection of PFNs in the path is picked based on the trust level. In the network even special PFNs are placed which are responsible to deliver the packets toward the data center without losing the data during the transmission. The selection of special PFNs is done by computing the meeting probability, remaining energy computation, computation of data weight, and security value computation. The proposed Incentive Routing Protocol with Virtual Projection (IRPVP) method is compared with the conventional approaches concerning the parameters like delay, link count, resource energy, healthy PFNs, non-healthy PFNs, health ratio computation, remaining energy, control to data ratio, and balancing factor. The simulation outcomes show that the performance of the proposed IRPVP algorithm is better than the other conventional algorithms.

TBDD: Territory-Bound Data Delivery for Large-Scale Mobile Sink Wireless Sensor Networks

The hierarchical structure-based data dissemination is the most popular technique in mobile sink wireless sensor networks (MS-WSNs). An ingenious virtual structure design combined with a precise routing management strategy is significant to attaining efficient data dissemination in hierarchical approaches. This paper proposes a hierarchical protocol called TBDD that divides the network into multiple partitions called Regions, and spots the location of the mobile sink (MS) according to these partitions. TBDD dynamically assigns a defined role to each division by adopting the mobility of the sink. Thus, the protocol takes advantage of the sink’s movement and the Regions’ flexible role in balancing energy consumption throughout the network. A Region is designated as active if it contains the sink node or passive otherwise. By using the territory of the active region as a temporal location of the MS, the proposed protocol hides the local movements (i.e., moves inside the active region) of the sink from the rest of the network. In such a way, regardless of the exact position of the sink, sensed data flows from different network ends to the sink’s temporal location. Therefore, TBDD reduces the query request and response burden employed to get the position of the sink. Besides, TBDD implements a spanning tree to report the location information of the MS. Last; we applied an opportunistic routing technique that captures multiple network criteria to elect packet forwarder nodes. The proposed protocol is mathematically analyzed and experimentally evaluated and shows outstanding performance in terms of the number of hops, energy consumption, delay, network lifetime, and success ratio.

Multi-agent reinforcement learning for network routing in integrated access backhaul networks

In this study, we examine the problem of downlink wireless routing in integrated access backhaul (IAB) networks involving fiber-connected base stations, wireless base stations, and multiple users. Physical constraints prevent the use of a central controller, leaving base stations with limited access to real-time network conditions. These networks operate in a time-slotted regime, where base stations monitor network conditions and forward packets accordingly. Our objective is to maximize the arrival ratio of packets, while simultaneously minimizing their latency. To accomplish this, we formulate this problem as a multi-agent partially observed Markov Decision Process (POMDP). Moreover, we develop an algorithm that uses Multi-Agent Reinforcement Learning (MARL) combined with Advantage Actor Critic (A2C) to derive a joint routing policy on a distributed basis. Due to the importance of packet destinations for successful routing decisions, we utilize information about similar destinations as a basis for selecting specific-destination routing decisions. For portraying the similarity between those destinations, we rely on their relational base-station associations, i.e., which base station they are currently connected to. Therefore, the algorithm is referred to as Relational Advantage Actor Critic (Relational A2C). To the best of our knowledge, this is the first work that optimizes routing strategy for IAB networks. Further, we present three types of training paradigms for this algorithm in order to provide flexibility in terms of its performance and throughput. Through numerical experiments with different network scenarios, Relational A2C algorithms were demonstrated to be capable of achieving near-centralized performance even though they operate in a decentralized manner in the network of interest. Based on the results of those experiments, we compare Relational A2C to other reinforcement learning algorithms, like Q-Routing and Hybrid Routing. This comparison illustrates that solving the joint optimization problem increases network efficiency and reduces selfish agent behavior.

Load Balancing between Paths using Software Defined Networks

Small networks usually use Ethernet devices that apply solutions such as the Spanning Tree Protocol (STP) to forward packets through a single path with no loops. However, this prevents the use of idle links that may reduce congestion and augment the aggregate bandwidth of the network. This work proposes a load balancing mechanism between paths using Software Defined Networks (SDNs). The proposed mechanism, named MLB (Multipath Load Balance), computes multiple paths with disjoint links that have the smallest number of hops between source and destination. Moreover, MLB has a “switching control” function that verifies whether the current occupation of the path exceeds a percentage of its capacity and if the potential new path computed by MLB has an occupation at least a percentage value smaller than that of the current path. MLB is implemented in Python and evaluated in Mininet. The results show that it is possible to increase the aggregate bandwidth by 95% and decrease the packet loss by about 95.5% compared with the standard operating mode of the OpenDaylight SDN controller.

Security of software defined networks: evolution and challenges

<span>In software-defined networking (SDN), network traffic is managed by software controllers or application programming interfaces (APIs) rather than hardware components. It differs from traditional networks, which use switches and routers to control traffic. Using SDN, you can create and control virtual networks or traditional hardware networks. Furthermore, OpenFlow allows network administrators to control exact network behavior through centralized control of packet forwarding. For these reasons, SDN has advantages over certain security issues, unlike traditional networks. However, most of the existing vulnerabilities and security threats in the traditional network also impact the SDN network. This document presents the attacks targeting the SDN network and the solutions that protect against these attacks. In addition, we introduce a variety of SDN security controls, such as intrusion detection systems (IDS)/intrusion prevention system (IPS), and firewalls. Towards the end, we outline a conclusion and perspectives.</span>

An Efficient Controller Placement Algorithm using Clustering in Software Defined Networks

Software-defined networking (SDN) is an emerging network paradigm that separates the control plane from data plane and provides programmable network management. The control plane within SDN is responsible for decision-making, while packet forwarding is handled by the data plane based on flow entries defined by the control plane. The placement of controllers is an important research issue that significantly impacts performance of SDN. In this work, we utilize clustering algorithms to group networks into multiple clusters and propose an algorithm for optimal controller placement within each cluster. Initially, using the silhouette score, we determine the optimal number of controllers for various topologies. Additionally, to enhance network performance, we employ the meeting point algorithm to calculate the optimal location for placing the controller within each cluster. We implement the proposed work in the Mininet emulator with POX as the SDN controller. Furthermore, we compare our proposed approach to existing work in terms of throughput, delay, and jitter using six topologies from the Internet Zoo dataset.

Canary: Congestion-aware in-network allreduce using dynamic trees

The allreduce operation is an essential building block for many distributed applications, ranging from the training of deep learning models to scientific computing. In an allreduce operation, data from multiple hosts is aggregated together and then broadcasted to each host participating in the operation. Allreduce performance can be improved by a factor of two by aggregating the data directly in the network. Switches aggregate data coming from multiple ports before forwarding the partially aggregated result to the next hop. In all existing solutions, each switch needs to know the ports from which it will receive the data to aggregate. However, this forces packets to traverse a predefined set of switches, making these solutions prone to congestion. For this reason, we design Canary, the first congestion-aware in-network allreduce algorithm. Canary uses load balancing algorithms to forward packets on the least congested paths. Because switches do not know from which ports they will receive the data to aggregate, they use timeouts to aggregate the data in a best-effort way. We develop a P4 Canary prototype and evaluate it on a Tofino switch. We then validate Canary through simulations on large networks, showing performance improvements up to 40% compared to the state-of-the-art.

Fuzzy-based optimization of AODV routing for efficient route in wireless mesh networks

The performance of any communication system heavily relies on the efficient routing of interventions. This article addresses the significant issue of routing protocol selection for optimal path determination in networks. Particularly, when wireless communication occurs among mobile nodes with limited resources, such as batteries, the routing problem becomes even more challenging. This article proposes the Fuzzy Control Energy Efficient (FCEE) routing protocol to overcome these challenges. The FCEE protocol combines the Ad-Hoc On-Demand Distance Vector (AODV) protocol with fuzzy logic techniques to enhance network lifetime and performance. The proposed approach introduces a memory-based channel integrated with fuzzy logic methodologies, which effectively restricts the forwarding of unnecessary broadcast packets based on the energy availability of the operating node. Through extensive simulations, demonstrate the promising capabilities of FCEE as a routing protocol for wireless mesh networks. To further assess the effectiveness of the FCEE protocol, the proposed article compares it with two existing routing protocols: AODV and Intelligent Routing AODV (IRAODV). The simulation results shows that the FCEE routing protocol significantly enhances the reliability of the conventional AODV, providing improved link connectivity and longer route lifetimes. Additionally, our proposed protocol enhances the quality of service (QoS) for mesh routing, with an average throughput of 351.374 (Kbps) compared to 90 (Kbps) for IRAODV and 39 (Kbps) for AODV. Moreover, FCEE exhibits superior energy efficiency with an average energy consumption of 14, while IRAODV and AODV consume 40 and 90 joules, respectively. In conclusion, the FCEE routing protocol demonstrates its potential to address the challenges of efficient routing in wireless mesh networks. By leveraging fuzzy logic and integrating it with AODV, FCEE enhances network lifetime, performance, and energy efficiency, making it a promising solution for future wireless communication systems.

SWEEPER: Secure Waterfall Energy-Efficient Protocol-Enabled Routing in FANET

The recent advancements in ad-hoc networks have resulted in innovations like FANETs. FANETs (Flying Ad hoc Networks) have become diversified in its applications ranging from agriculture, military, emergency services etc. The FANET environment needs to be dynamic and is populated by UAVs. The highly mobile UAVs are responsible for data transmission between nodes. If unchecked, this results in packet loss. Reliable data transmission in FANETs is possible, if effective routing protocols are in place. In this research, a Secure Waterfall Energy-Efficient Protocol-Enabled Routing (SWEEPER) has been proposed which helps conserve the node energy throughout the transmission process. The framework uses a waterfall model approach which includes group key management as an underlying process governing the security aspect of the protocol. Asymmetric key cryptography is applied to our technique, which involves two unique nodes, labeled the Computed Key (CKey) and the Dissemination Key (DKey). The two nodes will generate, verify, and distribute the secret keys. This will help other nodes concentrate on transmission alone and needn’t waste time in computational activities or key handling. Security breaches and malignant nodes are also handled efficiently. The nodes along the route are selected based on a trust factor, which allows our protocol to select only genuine nodes to forward packets along the discovered path. Our work is analyzed with existing protocols of FANETS like SecRIP and MDRMA. The analysis reveals that our protocol outperforms the existing protocols in terms of minimal delay, maximum energy conservation and PDR, which contributes towards a maximized throughput.

Quality of Service Aware Dynamic Bandwidth Allocation for Rate Control in WSN

Different types of data can be generated by Wireless Sensor Networks (WSNs) in both Real-Time (RT) and Non-RT (NRT) scenarios. The combination of these factors, along with the limited bandwidth available, necessitates careful management of these categories in order to reduce congestion. Due to this, a Proficient Rate Control and Fair Bandwidth Allocation (PRC-FBA) method has been created that prioritizes certain types of traffic and creates a virtual queue for them.In PRC-FBA, the Signal-to-Noise and Interference Ratio (SINR) model is applied to the problem of bandwidth allocation in WSN in an effort to find a compromise between equity and performance. Then, a brand-new bandwidth utility factor is defined with regard to equity and effectivenes. The FBA method in PRC-FBA is devoped for only improving throughput, but not considering delay. However, delay is the main factors for trasnmiitng NRT packets. This paper offers a PRC with Quality of Service (QoS) aware Dynamic Bandwidth Allocation (PRC-QDBA) approach for allocating bandwidth while prioritizing packets based on their traffic classes. This model employs a QoS associated dynamic bandwidth allocation strategy which efficiently distributes the unused time slots among the required nodes. The distribution technique is performed based on hierarchical manner utilizing a parent-child association of tree topology. The parent node receives traffic indication maps (TIMs) from the children nodes and adopts them to allocate time slots based on their demamds. If the parent node is unable to allocate the required slots, it creates a TIM that indicating the demands and transfer it to its immediate parent node. This increases the entire performance rate of RT traffic. Furthermore, this model assures the packet forwarding for previously accepted flows by allowing node transmission based on ancestral connection capabilities. Finally, simulation results demonstartes that the suggested model significantly increases the throughput and delay for bandwidth allocation while also enabling QoS support for RT traffic in WSNs.

A high-performance fully adaptive routing based on software defined network-on-chip

Adaptive routing techniques have been proven to be effective solutions for handling network congestion and enhancing the performance of Network-on-Chip (NoC). Traditional adaptive routing algorithms may degrade flexibility and lead to the issue of high hardware implementation overhead. In this paper, we propose a fully adaptive routing (FAR) based on Software Defined NoC (SDNoC) to address these issues. The proposed FAR decouples path selection from packet forwarding. The routing path is determined by software techniques in the control layer according to the global congestion status and is encapsulated into the packet to control the forwarding of the packet. Evaluation results show that the proposed FAR yields an improvement of performance over the typical routing schemes in average packet latency and saturation throughput up to 8.2% and 6.1% respectively. The layout area and power consumption are at least 6.2% and 3.9% less compared with the typical routing schemes as well.

Generating full-stack 5G security datasets: IP-layer and core network persistent PDU session attacks

With the increasing number of users accessing the Internet over 5G systems, security concerns have become a major challenge that needs to be addressed. This paper proposes a solution to this challenge by proposing a system to train defenders to handle cyber attacks and develop intrusion detection systems that can timely notify of security events, also within the 5G core itself. This paper builds on our previous contributions on a containerized 5G testbed and proposes a novel set of full-stack attacks targeting networked hosts and 5G Network Functions (NFs) alike. Importantly, we identify the potential to generate persistent Packet Forwarding and Control Protocol (PFCP) Denial of Service (DoS) attacks to deprive end users of connectivity to the data network, even in the event of a handover to another gNodeB. This framework is envisaged to facilitate the generation of highly diverse and realistic datasets, containing malicious GPRS Tunneling Protocol (GTP) and PFCP traffic captured over 5G interfaces, thereby enhancing the security of next-generation networks.

FTODefender: An efficient flow table overflow attacks defending system in SDN

Software-Defined Networking (SDN) is a promising architecture that disentangles the control plane from the data plane. A mainstream southbound protocol for controller-to-switch communication in SDN is OpenFlow. In an OpenFlow-enabled network, SDN switches are connected to the logically centralized control plane, which issues control messages to direct packet forwarding and processing in the data plane. Given that the finite capacity of physical flow tables of switches, typically implemented with ternary content addressable memory (TCAM), attackers have the ability to carry out Denial-of-Service (DoS) attacks aimed at depleting the TCAM’s resources and causing an overflow of the flow table. In this paper, we propose FTODefender, a method combining eviction and cut-off attack sources to detect Low-rate Flow Table Overflow (LFTO) attacks and mitigate this kind of attacks in time. FTODefender consists of two modules: Detector and Mitigator. Detector periodically examines the flow table and extract four specific detection features. It then employs the trained CRITIC weights to calculate the detection score based on these extracted features to verify if the LFTO attack has happened. Mitigator computes the features for each flow and utilizes the LightGBM-LR classification model to identify attack flows among all flows. Then, the module evicts the malicious rules to mitigate attacks. Finally, Mitigator counts the occurrence of each source IP address in the eviction list, determines the attacker IP based on a predefined threshold, and issues a flow rule to drop all packets originating from the attacker’s IPs to sever the attack sources. Simulations show the effectiveness of FTODefender in mitigating the LFTO attacks, which proves that FTODefender is a practical solution to flow table overflow attacks.

Developing a Novel Hierarchical VPLS Architecture Using Q-in-Q Tunneling in Router and Switch Design

Virtual Private LAN Services (VPLS) is an ethernet-based Virtual Private Network (VPN) service that provides multipoint-to-multipoint Layer 2 VPN service, where each site is geographically dispersed across a Wide Area Network (WAN). The adaptability and scalability of VPLS are limited despite the fact that they provide a flexible solution for connecting geographically dispersed sites. Furthermore, the construction of tunnels connecting customer locations that are separated by great distances adds a substantial amount of latency to the user traffic transportation. To address these issues, a novel Hierarchical VPLS (H-VPLS) architecture has been developed using 802.1Q tunneling (also known as Q-in-Q) on high-speed and commodity routers to satisfy the additional requirements of new VPLS applications. The Vector Packet Processing (VPP) performs as the router’s data plane, and FRRouting (FRR), an open-source network routing software suite, acts as the router’s control plane. The router is designed to seamlessly forward VPLS packets using the Request For Comments (RFCs) 4762, 4446, 4447, 4448, and 4385 from The Internet Engineering Task Force (IETF) integrated with VPP. In addition, the Label Distribution Protocol (LDP) is used for Multi-Protocol Label Switching (MPLS) Pseudo-Wire (PW) signaling in FRR. The proposed mechanism has been implemented on a software-based router in the Linux environment and tested for its functionality, signaling, and control plane processes. The router is also implemented on commodity hardware for testing the functionality of VPLS in the real world. Finally, the analysis of the results verifies the efficiency of the proposed mechanism in terms of throughput, latency, and packet loss ratio.

A Negotiation-Based Scheme for Interconnecting Heterogeneous Networks With Enhanced Services

Although the TCP/IP protocols have made great contributions to the development of the Internet, there is a consensus that the Internet needs improvement to solve the address space exhausted, content-oriented service, and so on. The academic community has proposed lots of valuable but heterogeneous network protocols, which provide better network services but split the Internet. To connect these heterogeneous networks, many middleboxes (e.g.,NAT and Tunnel) are deployed on the Internet, but these middleboxes mask the communication peers and shield various network services that are provided by these heterogeneous networks. In this article, we propose the HNN (heterogeneous networks negotiation), which provides transparent end-to-end communication and connects heterogeneous networks stateless in the data plane. What's more, HNN enables the host to perceive the available network service provided by heterogeneous networks and helps the host structure appropriate packet header and packet forwarding path to take advantage of these heterogeneous network services. We implement and evaluate an HNN prototype with commodity Barefoot Tofino programmable switch S9180-32X. The evaluation results demonstrate that HNN introduces little processing time overhead (no more than 3%) compared to well-known heterogeneous connectivity techniques (i.e.,NAT and Tunnel) and allows hosts to utilize heterogeneous network services.

Congestion Detection and Mitigation Technique for Multi-Hop Communication in WSN

The primary function of a network system is to gather information from the observation region and transmit it to the base station. The network life span and congestion are the two major concerns in wireless networks. To enhance the lifespan of the sensor system; multi-hopping has been proved as best in class. Congestion is an important factor to be taken, where multiple nodes forward data to one another in the process of communication. Hence to overcome the issue of congestion in WSN, we proposed a congestion detection and mitigation method along with the multi-hop concept. In this technique, we have considered different routes among communication units that were classified on distance, relative attainment rate (RAR) and node storage occupancy. A utility function (U) has been proposed and calculated using the above illustrated factors for every node that acts as a neighbour to the transmitting node. Neighbour node with highest U-valued will be considered as the packet forwarding node's next hop. In this manner congestion free nodes are selected for data transmission.

K-nearest neighbor algorithm analysis for path determination in network simulation using software defined network

Software defined network (SDN) is a new approach concept for planning, developing, and operating computer networks. Routing is the process of selecting paths on a network system to send or forward packets to the destination network. This study aims to obtain the results of the calculation analysis using the k-nearest neighbor (k-NN) method as the implementation of the recommendations. The results of the analysis use a mesh topology design approach with predicted values of throughput, jitter, delay, and packet loss. This value is used as a recommendation to the network manager to determine the best path. The best path selection from the analysis results is i) path-1 (very good) which includes switch 1, switch 2, and switch 4; ii) path-2 (good) to switch 1, switch 3 and switch 4 switch 4; iii) channel-3 (moderate) through switch 1, switch 2, switch 3 and switch 4; and iv) channel-4 (bad) through switch 1, switch 3, switch 2, and switch 4. While the calculation using the confusion matrix is accuracy=72.31%, precision=96.08% and recall=87.84%.

K-nearest neighbor algorithm analysis for path determination in network simulation using software defined network

Software defined network (SDN) is a new approach concept for planning, developing, and operating computer networks. Routing is the process of selecting paths on a network system to send or forward packets to the destination network. This study aims to obtain the results of the calculation analysis using the k-nearest neighbor (k-NN) method as the implementation of the recommendations. The results of the analysis use a mesh topology design approach with predicted values of throughput, jitter, delay, and packet loss. This value is used as a recommendation to the network manager to determine the best path. The best path selection from the analysis results is i) path-1 (very good) which includes switch 1, switch 2, and switch 4; ii) path-2 (good) to switch 1, switch 3 and switch 4 switch 4; iii) channel-3 (moderate) through switch 1, switch 2, switch 3 and switch 4; and iv) channel-4 (bad) through switch 1, switch 3, switch 2, and switch 4. While the calculation using the confusion matrix is accuracy=72.31%, precision=96.08% and recall=87.84%.