Search Results (41)

The traditional TCP sender-driven approach to data communication in transport protocols can lead to ambiguity between the sender and receiver regarding packet delivery status. This issue stems primarily from the sender relying on explicit feedback from the receiver in the form of cumulative acknowledgments. While optimizations such as SACK can mitigate this issue to some extent, ambiguity may still arise due to receiver reneging or under high-loss environments, including retransmission loss. Recent research in transport protocols and new architectures has highlighted the advantages of using a receiver-driven approach over a sender-driven one for Internet communication. This shifts the traditional push-based data retrieval paradigm to a pull-based paradigm, allowing the creation of new transport services such as transparent caching and multicasting. This paper builds on these efforts to abstract and formalize a receiver-driven ARQ (RDQ) that follows established end-to-end principles in transport protocols, providing in-order reliability from the perspective of the receiver. We present the design of RDQ, layered on top of UDP, leveraging sender-driven and receiver-driven protocol elements. RDQ is implemented in the ns-3 simulator and evaluated against TCP- and SACK-style sender-driven ARQ under high-loss conditions. The preliminary results indicate the feasibility of incorporating a receiver-driven ARQ with a classic retransmission strategy in transport protocols, offering positive gains in reduced recovery delay and transmission efficiency relative to TCP/SACK-style sender-driven ARQ. Full article

The operational range and reliability of most commercially available UAVs employed in surveillance, agriculture, and infrastructure inspection missions are limited due to the use of short-range radio frequency connections. To alleviate this issue, the present work investigates the possibility of real-time long-distance UAV control using a commercial 4G LTE network. The proposed system setup consists of a Raspberry Pi 4B as the onboard computer, connected to a Pixhawk-2.4 flight controller mounted on an F450 quadcopter platform. Flight tests were carried out in open-field conditions at altitudes up to 50 m above ground level (AGL). Communication between the UAV and the ground control station is established using TCP and UDP protocols. The flight tests demonstrated stable remote control operation, maintaining an average control delay of under 150 ms and a video quality resolution of 640×480, while the LTE bandwidth ranging from 3 Mbps to 55 Mbps. The farthest recorded test distance of around 4200 km from the UAV to the operator also indicates the capability of LTE systems for beyond-visual-line-of-sight operations. The results show that 4G LTE offers an effective method for extending UAV range at a reasonable cost, but there are limitations in terms of network performance, flight time and regulatory compliance. This study establishes essential groundwork for future UAV operations that will utilize 5G/6G and satellite communication systems. Full article

IEEE 802.11ax (Wi-Fi 6) technologies provide high capacity, low latency, and increased security. While many network researchers have examined Wi-Fi security issues, the security implications of 802.11ax have not been fully explored yet. Therefore, in this paper, we investigate how security protocols (WPA2, WPA3) affect TCP/UDP throughput in IEEE 802.11ax client–server networks using a testbed approach. Through an extensive performance study, we analyze the effect of security on transport layer protocol (TCP/UDP), internet protocol layer (IPV4/IPV6), and operating systems (MS Windows and Linux) on system performance. The impact of packet length on system performance is also investigated. The obtained results show that WPA3 offers greater security, and its impact on TCP/UDP throughput is insignificant, highlighting the robustness of WPA3 encryption in maintaining throughput even in secure environments. With WPA3, UDP offers higher throughput than TCP and IPv6 consistently outperforms IPv4 in terms of both TCP and UDP throughput. Linux outperforms Windows in all scenarios, especially with larger packet sizes and IPv6 traffic. These results suggest that WPA3 provides optimized throughput performance in both Linux and MS Windows in 802.11ax client–server environments. Our research provides some insights into the security issues in Gigabit Wi-Fi that can help network researchers and engineers to contribute further towards developing greater security for next-generation wireless networks. Full article

The original Modbus specification for RS-485 and RS-232 buses supported broadcast transmission. As the protocol evolved into Modbus-TCP, to use the TCP transport, this useful feature was lost, likely due to the point-to-point nature of TCP connections. Later proposals did not restore the broadcast transmission capability, although they used UDP as transport and UDP, by itself, would have supported it. Moreover, they did not address the inherent lack of reliable delivery of UDP, leaving datagram loss detection and recovery to the application layer. This paper describes a novel redesign of Modbus-UDP that addresses the aforementioned shortcomings. It achieves a mean round-trip time of only 38% with respect to Modbus-TCP and seamlessly supports a previously published protocol based on Modbus broadcast. In addition, the built-in retransmission of Modbus-UDP reacts more efficiently than the equivalent Modbus-TCP mechanism, exhibiting 50% of its round-trip standard deviation when subject to a 1% two-way IP datagram loss probability. Combined with the lower overhead of UDP versus TCP, this makes the redesigned Modbus-UDP protocol better suited for a variety of Industrial Internet of Things systems with limited computing and communication resources. Full article

This article aims to evaluate the runtime effectiveness of various one-class classification (OCC) techniques for anomaly detection in an industrial scenario reproduced in a laboratory setting. To address the limitations posed by restricted access to proprietary data, the study explores OCC methods that learn solely from legitimate network traffic, without requiring labeled malicious samples. After analyzing major publicly available datasets, such as KDD Cup 1999 and TON-IoT, as well as the most widely used OCC techniques, a lightweight and modular intrusion detection system (IDS) was developed in Python. The system was tested in real time on an experimental platform based on Raspberry Pi, within a simulated client–server environment using the NFSv4 protocol over TCP/UDP. Several OCC models were compared, including One-Class SVM, Autoencoder, VAE, and Isolation Forest. The results showed strong performance in terms of detection accuracy and low latency, with the best outcomes achieved using the UNSW-NB15 dataset. The article concludes with a discussion of additional strategies to enhance the runtime analysis of these algorithms, offering insights into potential future applications and improvement directions. Full article

There are workloads that do not need the total data ordering enforced by the Transmission Control Protocol (TCP). For example, Virtual Network Computing (VNC) has a sequence of pixel-based updates in which the order of rectangles can be relaxed. However, VNC runs over the TCP and can have higher latency due to unnecessary blocking to ensure total ordering. By using Quick UDP Internet Connections (QUIC) as the underlying protocol, we are able to implement a partial order delivery approach, which can be combined with Forward Error Correction (FEC) to reduce data latency. Our earlier work on consistency fences provides a mechanism and semantic foundation for partial ordering. Our new evaluation on the Emulab testbed, with two different synthetic workloads for streaming and non-streaming updates, shows that our partial order and FEC strategy can reduce the blocking time and inter-delivery time of rectangles compared to total delivery. For one workload, partially ordered data with FEC can reduce the 99-percentile message-blocking time to 0.4 ms versus 230 ms with totally ordered data. That workload was with 0.5% packet loss, 100 ms Round-Trip Time (RTT), and 100 Mbps bandwidth. We study the impact of varying the packet-loss rate, RTT, bandwidth, and CCA and demonstrate that partial order and FEC latency improvements grow as we increase packet loss and RTT, especially with the emerging Bottleneck Bandwidth and Round-Trip propagation time (BBR) congestion control algorithm. Full article

In the Industrial Internet of Things (IIoT) field, the diversity of devices and protocols leads to interconnection challenges. Conventional Modbus Transmission Control Protocol (TCP) to Remote Terminal Unit (RTU) gateways suffer from high overhead and latency of the TCP protocol stack. To enhance real-time communication while ensuring reliability, this study applies Markov chain theory to analyze User Datagram Protocol (UDP) transmission characteristics. An Advanced UDP (AUDP) protocol is proposed by integrating a Cyclic Redundancy Check (CRC) check mechanism, retransmission mechanism, Transaction ID matching mechanism, and exponential backoff mechanism at the UDP application layer. Based on AUDP, a Modbus AUDP-RTU gateway is designed with a lightweight architecture to achieve bidirectional conversion between Modbus AUDP and Modbus RTU. Experimental validation and Markov chain-based modeling demonstrate that the proposed gateway significantly reduces communication latency compared to Modbus TCP-RTU and exhibits higher reliability than Modbus UDP-RTU. Full article

Industrial control systems (ICSs) are a critical component of key infrastructure. However, as ICSs transition from isolated systems to modern networked environments, they face increasing security risks. Traditional anomaly detection methods struggle with complex ICS traffic due to their failure to fully utilize both low-frequency and high-frequency traffic information, and their poor performance in heterogeneous and non-stationary data environments. Moreover, fixed threshold methods lack adaptability and fail to respond in real time to dynamic changes in traffic, resulting in false positives and false negatives. To address these issues, this paper proposes a deep learning-based traffic anomaly detection algorithm. The algorithm employs the Hilbert–Huang Transform (HHT) to decompose traffic features and extract multi-frequency information. By integrating feature and temporal attention mechanisms, it enhances modeling capabilities and improves prediction accuracy. Additionally, the deep probabilistic estimation approach dynamically adjusts confidence intervals, enabling synchronized prediction and detection, which significantly enhances both real-time performance and accuracy. Experimental results demonstrate that our method outperforms existing baseline models in both prediction and anomaly detection performance on a real-world industrial control traffic dataset collected from an oilfield in China. The dataset consists of approximately 260,000 records covering Transmission Control Protocol/User Datagram Protocol (TCP/UDP) traffic between Remote Terminal Unit (RTU), Programmable Logic Controller (PLC), and Supervisory Control and Data Acquisition (SCADA) devices. This study has practical implications for improving the cybersecurity of ICSs and provides a theoretical foundation for the efficient management of industrial control networks. Full article

Domain Name Server (DNS) amplification Distributed Reflection Denial of Service (DRDoS) attacks are a Distributed Denial of Service (DDoS) attack technique in which multiple IT systems forge the original IP of the target system, send a request to the DNS server, and then send a large number of response packets to the target system. In this attack, it is difficult to identify the attacker because of its ability to deceive the source, and unlike TCP-based DDoS attacks, it usually uses the UDP protocol, which has a fast communication speed and amplifies network traffic by simple manipulating options, making it one of the most widely used DDoS techniques. In this study, we propose a simple convolutional neural network (CNN) model that is designed to detect DNS amplification DRDoS attack traffic and has hyperparameters adjusted through experiments. As a result of evaluating the accuracy of the proposed CNN model for detecting DNS amplification DRDoS attacks, the average accuracy of the experiment was 0.9995, which was significantly better than several machine learning (ML) models in terms of performance. It also showed good performance compared to other deep learning (DL) models, and, in particular, it was confirmed that this simple CNN had the fastest time in terms of execution compared to other deep learning models by experimentation. Full article

One of the most important developments in the energy industry is the evolution of smart grids, which record minute details of voltage levels, energy usage, and other critical electrical variables through General Packet Radio Service (GPRS)-enabled meters. This phenomenon creates an extensive dataset for the optimization of the grid system. However, the minute-by-minute energy details recorded by GPRS meters are challenging to store and manage in physical storage resources (old techniques lead to a memory shortage). This study investigates using the distributed file system, replicated Gluster, as a reliable storage option for handling and protecting the enormous volumes of data produced by smart grid components. This study performs two essential tasks. (1) The storage of virtual data received from GPRS meters and load flow analysis of SynerGee Electric 4.0 software from the smart grid (we have extracted electrical data from 16 outgoing feeders, distributed lines, in this manuscript). (2) Tele-trafficking is performed to check the performance of replicated Gluster (RG) for virtual data (electrical data received from the smart grid) storage in terms of User Datagram Protocol (UDP), Transmission Control Protocol (TCP), data flow, and jitter delays. This storage technique provides more opportuni11ty to analyze and perform smart techniques efficiently for future requirement, analysis, and load estimation in smart grids compared to traditional storage methods. Full article

With the proliferation of mobile devices and various mobile services, ensuring smooth mobility for users has become a major challenge. The future internet is expected to be more mobile-friendly, with advancing technologies that will transform internet management in the coming decades. These technological advancements will help address mobility issues and provide a better internet experience for mobile devices and users. The transport layer plays a crucial role in the internet protocol suite by enabling communication between applications running on different servers. However, the widely used protocols, TCP and UDP, have several limitations, such as unreliability and slow performance due to three-way handshakes. To tackle these issues, Google introduced quick UDP internet connections (QUIC). QUIC aims to enhance latency, delay, and data transmission reliability. Q-MOFI, a future internet architecture focused on mobile devices and based on QUIC, strives to achieve these goals. Moreover, it enhances throughput by implementing multiplexing. Q-MOFI outperforms traditional UDP-based MOFI in terms of throughput gains, minimizing packet loss, and reducing binding operation latency, even when the number of hosts increases. The efficiency of this model has been validated through experimental testing. Full article

Multimedia video streaming, identified as the dominant internet data consumption service, brings forth challenges in consistently delivering optimal video quality. Dynamic Adaptive Streaming over HTTP (DASH), while prevalent, often encounters buffering problems, causing video pauses due to empty video buffers. This study introduces the Adaptive Scalable Video Streaming (ASViS) protocol as a solution. ASViS incorporates scalable video coding, a flow-controlled User Datagram Protocol (UDP), and deadline-based criteria. A model is developed to predict the behavior of ASViS across varying network conditions. Additionally, the effects of diverse parameters on ASViS performance are evaluated. ASViS adjusts data flow similarly to the Transmission Control Protocol (TCP), based on bandwidth availability. Data are designed to be discarded by ASViS according to video frame deadlines, preventing outdated information transmission. Compliance with RFC 8085 ensures the internet is not overwhelmed. With its scalability feature, ASViS achieves the highest possible image quality per frame, aligning with Scalable Video Coding (SVC) and the available data layers. The introduction of ASViS offers a promising approach to address the challenges faced by DASH, potentially providing more consistent and higher-quality video streaming. Full article

The ever-increasing number of plug-in electric vehicles (PEVs) requires appropriate electric vehicle grid integration (EVGI) for charging coordination to maintain grid stability and enhance PEV user convenience. As such, the widespread adoption of electric mobility can be successful. EVGI is facilitated through charging stations and empowers PEV users to manage their charging demand by using smart charging solutions. This makes PEV grids assets that provide flexibility to the power grid. The Internet of Things (IoT) feature can make smooth EVGI possible through a supporting communication infrastructure. In this regard, the selection of an appropriate communication protocol is essential for the successful implementation of EVGI. This study assesses the efficacy of the UK’s 4G network with TCP and 4G UDP protocols for potential EVGI operations. For this, an EVGI emulation test bed is developed, featuring three charging parking lots with the capacity to accommodate up to 64 PEVs. The network’s performance is assessed in terms of data packet loss (e.g., the data-exchange capability between EVGI entities) and latency metrics. The findings reveal that while 4G TCP often outperforms 4G UDP, both achieve latencies of less than 1 s with confidence intervals of 90% or greater for single PEV cases. However, it is observed that the high penetration of PEVs introduces a pronounced latency due to queuing delays in the network including routers and the base station servers, highlighting the challenges associated with maintaining efficient EVGI coordination, which in turn affects the efficient use of grid assets. Full article

The Quick UDP Internet Connections (QUIC) protocol provides advantages over traditional TCP, but its encryption functionality reduces the visibility for operators into network traffic. Many studies deploy machine learning and deep learning algorithms on QUIC traffic classification. However, standalone machine learning models are subject to overfitting and poor predictability in complex network traffic environments. Deep learning on the other hand requires a huge dataset and intensive parameter fine-tuning. On the contrary, ensemble techniques provide reliability, better prediction, and robustness of the trained model, thereby reducing the chance of overfitting. In this paper, we approach the QUIC network traffic classification problem by utilizing five different ensemble machine learning techniques, namely: Random Forest, Extra Trees, Gradient Boosting Tree, Extreme Gradient Boosting Tree, and Light Gradient Boosting Model. We used the publicly available dataset with five different services such as Google Drive, YouTube, Google Docs, Google Search, and Google Music. The models were trained using a different number of features on different scenarios and evaluated using several performance metrics. The results show that Extreme Gradient Boosting Tree and Light Gradient Boosting Model outperform the other models and achieve one of the highest results among the state-of-the-art models found in the literature with a simpler model and features. Full article

Optimizing routes and paths improves network performance. Due to the encapsulation and tunneling of the packets, mobile IP-based communication contributes to packet drops or significant delays between the sender and receiver. Packet loss during handoff reduces TCP throughput as well. One solution is to use the IEEE 802.11 Medium Access Control (MAC) protocol and TCP or UDP models to increase routing protocol performance. In the linkage of homogeneous networks, it is challenging to determine route failure. In addition, the 802.11 MAC also uses a link connection. As a result, re-covering the entire route path takes a longer time. Thus, improving wired and wireless mobile node communication and handover is both challenging and critical. To overcome this challenge, we propose to use the Versatile Resilience Packet Ring protocol (VRPR)-based model. In this paper, we propose a novel VRPR-based network model that allows uninterrupted communication in both wired and wireless media. VRPR is used in the network layer to avoid buffer overflow and client mobility. Our new model also identifies the cause of the route failure, whether it is due to client mobility (handover), due to link breakage (channel degradation), or due to buffer overflow. We evaluate our network model based on three performance factors, namely, the delay, packet, and packet loss, and compared it between wired and wireless media. Our Enhanced-VRPR-based network model outperforms the current VRPR wired and wireless network models. We validate our model through OMNet++ simulations. Full article