Intermediate Routers Research Articles

ZR 400 Gbit/s and 800 Gbit/s use cases, trials, deployments, and future prospects [Invited

As bandwidth grows operators are moving from 100 Gbit/s to 400 Gbit/s ports on core routers with wavelengths on underlying transmission also increasing to 400 Gbit/s and higher. Developments in pluggable coherent optical transceivers such as ZR optics present different optical layer architectures: pluggable coherent transceivers inserted into the router versus external transponders and “hop-by-hop” architectures, in which packets pass through multiple intermediate routers, versus “optical express” architectures via ROADMs. The paper describes using a bespoke modeling tool to compare cost and power consumption for various 400 Gbit/s architectures, applied to the core network of a major operator as total bandwidth increases from current levels ∼28Tbit/s to a future 220 Tbit/s scenario. The model shows that, as bandwidths increase, “optical express” architectures become lower cost compared to “hop-by-hop” architectures. The paper describes a field trial of pluggable 400 Gbit/s ZR+ transceivers directly deployed in routers and transported over a ROADM network and reviews architectural options likely to arise as bandwidths increase to 800 Gbit/s. For 400 Gbit/s and higher, operators face a range of optical layer architectures: the best outcome gives the lowest cost and power consumption while enabling efficient network operations, and it could be that different solutions are best for different networks.

Irregularity Behaviour Detection - Ad-hoc On-Demand Distance Vector Routing Protocol (IBD - AODV): A Novel Method for Determining Unusual Behaviour in Mobile Ad-hoc Networks (MANET)

All the communication in the mobile ad-hoc network (MANET) will depend on the intermediate neighbour nodes or router nodes. Routing protocol is very important in MANET, because all the communication will be done in the MANET depending on the neighbour or intermediate node. If the intermediate node is a malicious node, all the data will be lost or changed by the intermediate or malicious node. Ad-hoc On-demand Distance Vector routing protocol is one of the moderate routing protocol in MANET. The Ad-hoc On-demand Distance Vector Routing protocol does not have any security mechanism. This work is going to find the Irregularity Behaviour Detection (IBD) over the Ad-hoc On-Demand Distance Vector Routing (AODV) protocol. IBD is finding a trusted node by using the trust value (TV) of the node. This TV includes network performance, node energy level, and node position value. IBD-AODV is implemented and tested in the OmNetpp 6.0 simulator.

Blockchain-Enabled On-Path Caching for Efficient and Reliable Content Delivery in Information-Centric Networks

As the demand for online content continues to grow, traditional Content Distribution Networks (CDNs) are facing significant challenges in terms of scalability and performance. Information-Centric Networking (ICN) is a promising new approach to content delivery that aims to address these issues by placing content at the center of the network architecture. One of the key features of ICNs is on-path caching, which allows content to be cached at intermediate routers along the path from the source to the destination. On-path caching in ICNs still faces some challenges, such as the scalability of the cache and the management of cache consistency. To address these challenges, this paper proposes several alternative caching schemes that can be integrated into ICNs using blockchain technology. These schemes include Bloom filters, content-based routing, and hybrid caching, which combine the advantages of off-path and on-path cachings. The proposed blockchain-enabled on-path caching mechanism ensures the integrity and authenticity of cached content, and smart contracts automate the caching process and incentivize caching nodes. To evaluate the performance of these caching alternatives, the authors conduct experiments using real-world datasets. The results show that on-path caching can significantly reduce network congestion and improve content delivery efficiency. The Bloom filter caching scheme achieved a cache hit rate of over 90% while reducing the cache size by up to 80% compared to traditional caching. The content-based routing scheme also achieved high cache hit rates while maintaining low latency.

MEDUSA: A Multi-Resolution Machine Learning Congestion Estimation Method for 2D and 3D Global Routing

Routing congestion is one of the many factors that need to be minimized during the physical design phase of large integrated circuits. In this article, we propose a novel congestion estimation method, called MEDUSA , that consists of three parts: (1) a feature extraction and “hyper-image” encoding; (2) a congestion estimation method using a fixed-resolution convolutional neural network model that takes a tile of this hyper-image as input and makes accurate congestion predictions for a small region of the circuit; and (3) a sliding-window method for repeatedly applying this convolutional neural network on a layout, thereby producing higher-resolution congestion maps for arbitrarily large circuits. The proposed congestion estimation approach works with both 2D (collapsed) and 3D global routing. Using both quantitative metrics and qualitative visual inspection, congestion maps produced with MEDUSA show better accuracy than prior estimation techniques. Global routers typically use estimation techniques during their first router iteration and then switch to using actual congestion information extracted from the intermediate router solutions. Experimental results within the same global router infrastructure show a significant impact on quality after the first routing iteration; other estimation techniques result in an average of 22% to 54% higher initial overflow counts. This initial quality improvement carries through to the final global routing solution, with other estimation techniques needing up to 5% more routing iterations and up to 3× more runtime, on average. Compared with other global routers, MEDUSA achieves comparable wire length results and lower total overflow counts (more legal global routing solutions) and is typically faster.

TNT: A Modular Approach to Traversing Physically Heterogeneous NOCs at Bare-wire Latency

The ideal latency for on-chip network traversal would be the delay incurred from wire traversal alone. Unfortunately, in a realistic modular network, the latency for a packet to traverse the network is significantly higher than this wire delay. The main limiter to achieving lower latency is the modular quantization of network traversal into hops. Beyond this, the physical heterogeneity in real-world systems further complicate the ability to reach ideal wire-only delay. In this work, we propose TNT or Transparent Network Traversal . TNT targets ideal network latency by attempting source to destination network traversal as a single multi-cycle ‘long-hop’, bypassing the quantization effects of intermediate routers via transparent data/information flow. TNT is built in a modular tile-scalable manner via a novel control path performing neighbor-to-neighbor interactions but enabling end-to-end transparent flit traversal. Further, TNT’s fine grained on-the-fly delay tracking allows it to cope with physical NOC heterogeneity across the chip. Analysis on Ligra graph workloads shows that TNT can reduce NOC latency by as much as 43% compared to the state of the art and allows efficiency gains up to 38%. Further, it can achieve more than 3x the benefits of the best/closest alternative research proposal, SMART [ 43 ].

A congestion control scheme based on path recovery for smart grid communication

In order to solve the problem that the original path forwarding traffic caused by congestion that cannot be recovered in time in Smart Grid Communication, a congestion control scheme RFCC (Router Forwarding Congestion Control) based on path recovery is proposed, which not only supports the receiving end combined with router nodes to relieve congestion, it can also solve the problem of low transmission performance caused by not being able to restore the original path in time after the traffic is transferred. Active queue management technology is used to detect congestion and notify downflow nodes (users and routers) in time, which trigger downflow users to adjust the request sending window and intermediate routers to transfer packets. In addition, the original path traffic is restored in time through the path recovery policy. Firstly, the path traffic is recovered according to the congestion mark carried by the subsequent content packets. Secondly, the transmission frequency of the probe packets is calculated according to the information such as the packet queue length of routers and the available bandwidth of the congested path, and the probe packets are periodically sent to the congested path, and the traffic is sent to the congested path in time. The alternate path is transferred back to the original path. This paper implements the scheme in NS-3, and extensive experiments show that the proposed scheme outperforms the comparison schemes, which not only higher and more stable throughput can be obtained, but also shorter and more stable transmission delay can be obtained. In addition, the optimal path transmission volume and link utilization are improved.

Design a robust controller for congestion avoidance in TCP/AQM system

The development of the life, increasing the internet users and circulated data on the computer network caused the network congestion. Accordingly, some essential issues arose in terms of packets time delay, packets loss, and buffer overflow in the intermediate routers. In order to tackle those issues, Transmission Control Protocol and Active Queue Management (TCP/AQM) has been introduced. AQM is the main approach used to control congestion and overcome those problems to improve network performance. In this study, an adaptive controller is suggested to achieve robust AQM system based on a smart Whale Optimization Algorithm (WOA) to enhance the system performance, then to test its efficiency and superiority with other controllers a comparison with two classical PI controller is done which indicates that the suggested controller is more desirable performance than other controllers. The simulation of TCP/AQM are carried out using MATLAB (R2020a), simulation results reflect an efficient and robust response in facing different matters may happens during simulation like change model parameters (±20%) or facing disturbance signal, in all types of robustness analysis system need small duration time to return to its desired response, 15 s when changing the no. of sessions and the no. of packets and need 3 s when adding the disturbance signal. The results obtained indicate the robust controller behavior and its adaptability to achieve stable system response.

IEACC: An Intelligent Edge-Aided Congestion Control Scheme for Named Data Networking With Deep Reinforcement Learning

As a promising implementation of Information-Centric Networking (ICN), Named Data Networking (NDN) has potential advantages over the TCP/IP network in content distribution, mobility support, etc. However, the research on NDN is still in its infancy, and congestion control, NDN’s most important functional element, poses many challenges, such as congestion detection, excessive window reduction for non-congested paths, and unfairness. In this paper, we propose an Intelligent Edge-Aided Congestion Control (IEACC) scheme for the NDN network based on Deep Reinforcement Learning (DRL). The proposed IEACC provides a proactive congestion detector that utilizes intermediate routers to transmit accurate congestion information along the path to consumers through data packets. Furthermore, considering the multi-source transmission in NDN, IEACC divides data packets into different congestion degrees by a lightweight clustering algorithm and provides suitable inputs for DRL, thereby obtaining a reasonable transmission rate. Then, it distributes the estimated bandwidth resources to consumers with transmission needs to maintain fairness. Finally, we implement our proposed scheme in the simulation platform and evaluate the performance in different scenarios. The results show that it can improve data transmission rate, reduce packet loss, and maintain fairness compared with others.

A lightweight deployment of TD routing based on SD-WANs

Multipath routing conforms to the evolution principle of network development and is a trend of routing architectures. It can not only meet the needs but also enhance the performance and security of a network. However, deploying multipath routing further increases the scale of the forwarding information base (FIB) and the cost of forwarding devices. Therefore, to realize the lightweight deployment of multipath routing with a distributed architecture, this paper takes two-dimensional routing (TD routing) as an example to provide a solution. We propose a distributed storage mechanism of TD routing in combination with SRv6 (TDSR) and the corresponding SRv6 header (SRH) compression (CARD) method. The main methods are as follows: Inspired by a software-defined wide area network (SD-WAN), this paper introduces segment routing (SR) in the data plane, which can disperse TD-FIBs in different ingress nodes. The ingress routers push path information into the stack, and the intermediate routers forward the packets according to the SRH. Second, for the bandwidth waste of the SRH, compression is attempted by comparing the difference between the the shortest path first (SPF) path and the SRv6 path. Only a few hops in the TD path that are different from those in the one-dimensional (OD) path are kept. Finally, we sort out several typical application scenes of multipath routing and discuss several simplification algorithms. The experimental results show that the TDSR can reduce TD entries by 69%, and the average compression rate of CARD can reach 70%. In addition, CARD can be combined with existing methods to improve their effect.

A bargain game theory assisted interest packet forwarding strategy for information centric network

In Information Centric Network (ICN), when implemented using NDN (Named Data Network) architecture, a client generates an ‘interest’ packet to retrieve a content. The interest packet carries the name of the searched content and may pull the data from any intermediate router that holds the requested content. An efficient interest packet forwarding mechanism is highly desirable in ICN to make the content retrieval faster. This paper describes an interest forwarding technique aiming at minimizing content retrieval time and network overhead. The process of interest forwarding is modelled as bargain game with data seeker as seller and content provider as buyer. Intermediate Content Routers (CRs) between the consumer and the actual producer is classified as either capable or incapable CRs represented as cCR and iCR respectively. Initially all CRs holds certain currency value based on their attributes. The cCRs are capable of serving interests and they are rewarded with a pre agreed trading price. The iCRs on the other hand are not capable of serving any content and hence they are rewarded by a fraction of the trading price based on the assistance provided in forming the data transmission path. To evaluate the strength of the new scheme the proposed bargain game theory (BGT) based technique is integrated with three existing protocols, namely, the Cache Less for More (CL4M), Characteristic Time Routing (CTR), and Probability based caching (pCache). The performance of new variations of these protocols are compared with their base versions. The simulation is performed in ns-3 based ndnSim-2.0. Performance parameters observed in the simulation are, content search latency, server hit ratio, network load, overhead and throughput. Simulation observation reveals that the integration of the proposed scheme significantly improves the performance in terms of aforementioned parameters.

SCD2: Secure Content Delivery and Deduplication With Multiple Content Providers in Information Centric Networking

As one of the promising next generation network architectures, information centric networking (ICN) is highly anticipated to improve the bandwidth usage of the Internet and reduce duplicate traffic. Since contents in ICN are disseminated in the whole network, ICN is much more vulnerable and the issue of how to deliver contents securely has been intensively discussed. However, the scalability of the existing schemes is limited. A scalable scheme is expected to be able to achieve fine-grained access control and at the same time also support multiple content providers scenario with efficient key management at user side. Besides, different content providers may publish some identical contents and these contents may be cached in the same intermediate routers, which causes high data redundancy and in turn exerts an adverse impact on the performance of ICN. In this paper, we propose a Secure Content Delivery and Deduplication scheme, called SCD2, to achieve secure and efficient fine-grained access control in ICN with multiple content providers. We first propose a scalable key-policy attribute-based encryption (SKP-ABE) to provide fine-grained access control and allow different attribute authorities to share some public attributes to simplify the key management. Furthermore, based on SKP-ABE, we design a simple but effective mechanism to conduct content deduplication. Finally, we implement a prototype of SCD2 to test its performance and compare it with some existing schemes. The results show that SCD2 has lower storage overhead, a higher degree of deduplication, and better retrieval efficiency.

Simulation Model of Enhancing Performance of TCP/AQM Networks by Using Matlab

Internet networks are becoming more crowded every day due to the rapid development of modern life, which causes an increase in the demand for data circulating on the Internet. This creates several problems, such as buffer overflow of intermediate routers, and packet loss and time delay in packet delivery. The solution to these problems is to use a TCP/AQM system. The simulation results showed that there were differences in performance between the different controllers used. The proposed methods were simulated along with the required conditions in nonlinear systems to determine the best performance. It was found that the use of optimization Department of Electro-mechanical Engineering, University of Technology - Iraq tools (GA, FL) with a controller could achieve the best performance. The simulation results demonstrated the ability of the proposed methods to control the behavior of the system. The controller systems were simulated using Matlab/Simulink. The simulation results showed that the performance was better with the use of GA-PIDC compared to both FL-PIDC and PIDC in terms of stability time, height, and overrun ratio for a network with a variable queue that was targeted for comparison. The results were: the bypass ratio was 0, 3.3 and 21.8 the settling time was 0.002, 0.055, and 0.135; and the rise time was 0.001, 0.004 and 0.008 for GA-PIDC, FL-PIDC and PIDC, respectively. These results made it possible to compare the three control techniques.

Federated Learning Over Multihop Wireless Networks With In-Network Aggregation

Communication limitation at the edge is widely recognized as a major bottleneck for federated learning (FL). Multi-hop wireless networking provides a cost-effective solution to enhance service coverage and spectrum efficiency at the edge, which could facilitate large-scale and efficient machine learning (ML) model aggregation. However, FL over multi-hop wireless networks has rarely been investigated. In this paper, we optimize FL over wireless mesh networks by taking into account the heterogeneity in communication and computing resources at mesh routers and clients. We present a framework that each intermediate router performs <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">in-network</i> model aggregation before sending the data to the next hop, so as to reduce the outgoing data traffic and hence aggregate more models under limited communication resources. To accelerate model training, we formulate our optimization problem by jointly considering model aggregation, routing, and spectrum allocation. Although the problem is a non-convex mixed-integer nonlinear programming, we transform it into a mixed-integer linear programming (MILP), and develop a coarse-grained fixing procedure to solve it efficiently. Simulation results demonstrate the effectiveness of the solution approach, and the superiority of the in-network aggregation scheme over the counterpart without in-network aggregation.

Effective algorithms to detect stepping-stone intrusion by removing outliers of packet RTTs

An effective method to detect stepping-stone intrusion (SSI) is to estimate the length of a connection chain. This type of detection method is referred to as a network-based detection approach. Existing network-based SSI detection methods are either ineffective in the context of the Internet because of the presence of outliers in the packet round-trip times (RTTs) or inefficient, as many packets must be captured and processed. Because of the high fluctuation caused by the intermediate routers on the Internet, it is unavoidable that the RTTs of the captured packets contain outlier values. In this paper, we first propose an efficient algorithm to eliminate most of the possible RTT outliers of the packets captured in the Internet environment. We then develop an efficient SSI detection algorithm by mining network traffic using an improved version of k-Means clustering. Our proposed detection algorithm for SSI is accurate, effective, and efficient in the context of the Internet. Well-designed network experiments are conducted in the Internet environment to verify the effectiveness, correctness, and efficiency of our proposed algorithms. Our experiments show that the effective rate of our proposed SSI detection algorithm is higher than 85.7% in the context of the Internet.

An accurate retransmission timeout estimator for content-centric networking based on the Jacobson algorithm

Accurately estimating of Retransmission TimeOut (RTO) in Content-Centric Networking (CCN) is crucial for efficient rate control in end nodes and effective interface ranking in intermediate routers. Toward this end, the Jacobson algorithm, which is an Exponentially Weighted Moving Average (EWMA) on the Round Trip Time (RTT) of previous packets, is a promising scheme. Assigning the lower bound to RTO, determining how an EWMA rapidly adapts to changes, and setting the multiplier of variance RTT have the most impact on the accuracy of this estimator for which several evaluations have been performed to set them in Transmission Control Protocol/Internet Protocol (TCP/IP) networks. However, the performance of this estimator in CCN has not been explored yet, despite CCN having a significant architectural difference with TCP/IP networks. In this study, two new metrics for assessing the performance of RTO estimators in CCN are defined and the performance of the Jacobson algorithm in CCN is evaluated. This evaluation is performed by varying the minimum RTO, EWMA parameters, and multiplier of variance RTT against different content popularity distribution gains. The obtained results are used to reconsider the Jacobson algorithm for accurately estimating RTO in CCN. Comparing the performance of the reconsidered Jacobson estimator with the existing solutions shows that it can estimate RTO simply and more accurately without any additional information or computation overhead.

A Novel Routing Strategy Towards Achieving Ultra-Low End-to-End Latency in 6G Networks

Compared to 5G, 6G networks will demand even more ambitious reduction in endto-end latency for packet communication. Recent attempts at breaking the barrier of end-to-end millisecond latencies have focused on re-engineering networks using a hybrid approach consisting of an optical-fiber based backbone network architecture coupled with high-speed wireless networks to connect end-devices to the backbone network. In our approach, a wide area network (WAN) is considered with a high-speed optical fiber grid network as its backbone. After messages from a source node enter the backbone network through a local wireless network, these are delivered very fast to an access point in the backbone network closest to the destination node, followed by its transfer to the local wireless network for delivery to the destination node. We propose a novel routing strategy which is based on distributing the messages in the network in such a way that the average queuing delay of the messages through the backbone network is minimized, and also the route discovery time at each router in the backbone network is drastically reduced. Also, multiple messages destined towards a particular destination router in the backbone network are packed together to form a mailbag, allowing further reductions in processing overheads at intermediate routers and pipelining of mailbag formation and route discovery operations in each router. The performance of the proposed approach green based on these ideas has been theoretically analyzed and then simulated using the ns-3 simulator. Our results show that the average end-to-end latency is less than 380 µs (with only 46-79 µs within the backbone network under varying traffic conditions) for a 1 KB packet size, when using a 500 Gbps optical fiber based backbone network laid over a 15 Km × 15 Km area, a 50 Mbps uplink channel from the source to the backbone network, and a 1 Gbps downlink channel from the backbone network to the destination. The significant reduction in end-to-end latency as compared to existing routing solutions clearly demonstrates the potential of our proposed routing strategy for meeting the ultra-low latency requirements of current 5G and future 6G networks, particularly for mobile edge computing (MEC) application scenarios.

Discrete-time simulation for performance modelling of FIFO single-server queuing system

Optimal queue management is crucial for improving the network operation since packet loss is commonly attributed to the likelihood of buffer overflow at intermediate routers on end-to-end communication path. In this paper, a transient discrete-time simulation model is proposed based on queuing theory served by single-server system and single first-in first-out (FIFO) queue. This queuing service framework effectively enforces the best-effort service to the streams of incoming data packets across the network with disparate quality of service (QoS) requirements. We plot the network performance measures such as queue length, delay, server utilisation and packet lifetime to validate the practical wireless systems. Besides, we employ conventional multiple-objective genetic algorithm to model the trade-off among key queuing system parameters including queuing delay, packet drop rate and network bandwidth. Finally, the efficiency of our queuing optimisation model is significantly compared with previous works in terms of bandwidth utilisation, delay, and packet loss rate.

An New Efficient Cluster Based Detection Mechanisms for Distributed Denial of Services (DDoS) Attacks

Cluster aggregation of statistical anomaly detection is a mechanism for defending against denial of service attack (dos) and distributed denial-of-service (DDoS) attacks. DDoS attacks are treated as a congestioncontrol problem; because most of the congestion is occurred in the malicious hosts not follow the normal endto- end congestion control. Upstream routers are also notified to drop such packets in order that the router’s resources are used to route legitimate traffic hence term cluster aggregation. If the victim suspects that the cluster aggregations are solved by most of the clients, it increases the complexity of the cluster aggregation. This aggregation solving technique allows the traversal of the attack traffic throughout the intermediate routers before reaching the destination. In this proposal, the aggregation solving mechanism is cluster aggregation to the core routers rather than having at the victim. The router based cluster aggregation mechanism checks the host system whether it is legitimate or not by providing a aggregation to be solved by the suspected host.

Simulation of a vessel sensor network of ZigBee standard

The subject of the paper is a vessel sensor network designed to collect data from wireless sensors for various purposes. The peculiarity of this network application is the presence of a large number of premises, wireless communication between which is complicated. One of the possible approaches to solving this problem is to use coordinators connected by a switch into a local network, and a large number of routers that provide data relaying along the chain. Studies of the proposed vessel wireless network in the OMNeT ++ simulation modeling environment using Castalia framework are carried out in the paper. The process of modeling both the network itself and its individual components, and various modes of their operation is shown. The interaction of network nodes through intermediate routers is considered. Estimation of losses during packet delivery along a chain of routers, the time spent on processing packets in routers and delays in packet delivery to the network coordinator from the sending node is based on the compiled model. It is concluded that with the increasing complexity of the network structure (growth in the number of routers), there is a proportional rise of the packets delivery delay over the wireless network to the vessel local network. However, all transmitted packets are delivered to the addressee.

Routing Issues And Challenges for Mobile ad-hoc Networks (MANETs): A Review

Mobile ad-hoc networks also referred to as MANETs belong to a collaborative collection of different cellular devices from a heterogeneous community, the prolific characteristic is the capability to enroll in and give up the community at any time. This results in a creation of a decentralized community of cell nodes that could connect, talk and bypass messages to each different without the requirement of an intermediate router. MANETs are usually used in numerous sets of packages like military operations, emergency or catastrophe relief operations, commercial enterprise conferences, political conferences, mine site operations. In those forms of networks, the maximum crucial trouble is that of locating the first-class direction available between the 2 nodes consistent with the consumer necessities. Despite many fascinating future programs of cellular ad-hoc networks (MANETs), There are nevertheless a few crucial challenges and open issues to be solved. As a consequence, extensively on this paper, we present an outline of MANETs, and their routing protocols. Then we present numerous tough issues and the future work.