Search Results (129)

A Transmission Control Protocol (TCP) throughput map represents communication quality over road networks and supports communication-aware applications in intelligent transportation systems. Maintaining such a map online is challenging because vehicular measurements are sparse and unevenly distributed, network conditions vary rapidly, and sensing-budget constraints limit the number of vehicles from which onboard communication measurements can be uploaded at each time step. This work addresses online TCP throughput map maintenance under sparse vehicular observations and sensing-budget constraints. To support budget-constrained sensing, we combine discoverability-guided vehicle selection and probabilistic map updating within a digital twin (DT)-assisted vehicular sensing architecture. The resulting sensing-and-mapping method, referred to as Discoverability-aware and Statistical Mapping (DISMAP), maintains a spatio-temporal discoverability map to characterize historical sensing coverage and select vehicles that improve the coverage of under-represented regions. It then uses Gaussian Process Regression (GPR) as a probabilistic mapping engine to estimate the mean TCP throughput and predictive standard deviation, where the standard deviation is adjusted using local vehicle density. Simulation results show that DISMAP reduces the mean absolute error (MAE) and mean standard deviation (MSTD) by up to 23.7% and 37.5%, respectively, and achieves a prediction-interval miss rate (PIMR) of 0.048, which is close to the nominal value of 0.05. These results indicate a favorable balance among prediction accuracy, interval sharpness, calibration, and spatial representativeness across different traffic-density conditions. Full article

This work proposes a vendor-independent integration method for International Electrotechnical Commission (IEC) 61850 Manufacturing Message Specification (MMS) communication protocol into Programmable Logic Controller (PLC) systems that support an open network communication interface available for the PLC program. IEC 61850 is globally well accepted for electrical substation control, and the protocol MMS is used for integrating the electrical substation bay level into the station level, where the PLC orchestrates the process level of the substation and parallel processes. This method was created because most PLCs lines do not natively support any protocol of IEC 61850, although it often needs to be used for the control of electrical substations. For the development of the prototype presented in this paper, PLCs from the Siemens AG families S7-1500 and S7-410, which support open communication over Transmission Control Protocol/Internet Protocol (TCP/IP) with external systems, were used for validation. Different results regarding network communication and PLC program performance are presented in this paper. The implemented solution presents a meaningful implementation of the MMS application layer into the PLC program and was successfully validated with real industrial, single and redundant PLC systems. Full article

With the widespread adoption of Wi-Fi 7 in campus networks, high-density access and large-scale research data transmission challenge traditional congestion control algorithms. TCP-bottleneck bandwidth and round-trip propagation time (BBR) lacks deep link awareness and service semantic breadth, leading to misinterpreting non-congestive packet loss and inter-flow unfairness in complex wireless scenarios. To address this, this paper proposes semantic-aware and cross-layer collaborative optimized BBR (SAC-BBR), a semantic-aware cross-layer optimization mechanism for high-density heterogeneous campus networks. It leverages an Extended Berkeley Packet Filter (eBPF) to capture physical link characteristics in real time within the Linux kernel, accurately distinguishing random loss from congestion loss. It then constructs a lightweight semantic identification engine to classify traffic and establish a service satisfaction utility model. Finally, a deep reinforcement learning-based dynamic gain regulator maps cross-layer states and service priorities to the action space, enabling millisecond-level intelligent tuning of pacing_gain and cwnd_gain. Experimental results show that SAC-BBR improves throughput by over 22% compared to BBRv3 and reduces average round-trip time (RTT) by 17% while suppressing RTT jitter by over 60% in high-density scenarios. Furthermore, it enhances the Jain fairness index to 0.93 under multi-protocol competition, ensuring high-performance and equitable transmission. Full article

Industrial control systems (ICSs) increasingly rely on legacy communication protocols such as ModbusTCP, which lack built-in security mechanisms and remain widely exposed to network-based attacks. This paper investigates the security limitations of authentication mechanisms in ModbusTCP-enabled programmable logic controllers (PLCs) and demonstrates how plaintext credential transmission and limited connection handling capabilities can be exploited to perform brute-force and denial-of-service (DoS) attacks. An experimental testbed based on two industrial Delta PLC families (DVP-13SE and DVP-311SV3) was developed to systematically evaluate these vulnerabilities under realistic conditions. The results show that authentication credentials can be easily captured through network sniffing, while the PLC communication stack supports a maximum of 16 concurrent connections and can process up to approximately 8600 Modbus operations per second, making it susceptible to resource exhaustion and performance degradation under distributed attack scenarios. To address these limitations, this paper proposes a lightweight deception-based protection mechanism, termed the PLC misleading algorithm (PMA), which is implemented directly within the PLC ladder logic. Unlike traditional network-level defenses, PMA operates at the device level and dynamically misleads attackers by generating controlled randomized responses while preserving consistent behavior for legitimate clients. Experimental results demonstrate that PMA significantly mitigates brute-force effectiveness by preventing reliable password extraction while introducing minimal overhead (2.2% memory usage) and maintaining acceptable communication latency. Additionally, the proposed approach significantly reduces observable attack traffic, with only 0.246 Modbus operations per second observed during the attack phase, thereby limiting the effectiveness of automated exploitation tools. These findings highlight the potential of in-device deception mechanisms as a practical and deployable security layer for legacy industrial systems, and provide new insights into the resilience of PLC-based infrastructures against network-level attacks. This work bridges the gap between lightweight PLC-level protections and the growing need for robust cybersecurity mechanisms in industrial IoT environments. Full article

In HPC systems and hyper-scale data centers, the adoption of high-performance NVMe SSDs and high-speed networks has shifted storage bottlenecks to the network stack. Under high-concurrency workloads, frequent interrupt processing exhausts CPU resources while protocol-level control–data dependencies in the NVMe over TCP write path introduce additional serialization penalties. Existing optimizations either require specialized hardware, dedicate CPU cores to user-space polling, or apply semantically blind batching that delays time-sensitive control messages. We present SENS, a Semantic-aware NVMe over TCP Scheduler embedded within the NVMe over TCP driver of the Linux kernel. SENS combines two mechanisms: (1) PDU vectorization, which aggregates discrete Protocol Data Units into memory vectors before network transmission, amortizing per-I/O system call overhead and reducing soft-interrupt frequency; and (2) instruction-aware dispatch, which detects control PDUs such as R2T and triggers an early flush of the aggregation window, mitigating the serialization penalty on the write path. A prototype evaluation with physical NVMe SSDs and 100 GbE networks shows that SENS saturates the SSD throughput ceiling using 4–5 CPU cores, halving the host-side core budget compared to the native TCP driver. With a RAMDisk backend that removes storage-media constraints, SENS sustains up to 2.5× higher concurrent IOPS. These results show that exposing storage-protocol semantics to the batching layer improves the scalability of NVMe over TCP without additional hardware. Full article

One of the challenges in managing mobility in a heterogeneous network domain remains a significant challenge in Software-Defined Networking (SDN). While SDN has effectively facilitated intra-domain mobility, inter-domain mobility has been a major issue, leading to service interruptions, packet loss, and unstable communication sessions. This article presents a new concept in mobility management: a hybrid SDN-LISP network that facilitates inter-domain communication by integrating SDN with the Locator/Identifier Separation Protocol (LISP). The main idea is to introduce a new event-based orchestration model that uses OpenFlow Packet-In messages to provide instantaneous updates to Endpoint Identifiers-to-Routing Locators (EID-to-RLOC) mappings, unlike traditional LISP, which relies on timers for updates. The proposed framework has been implemented and evaluated on a Mininet-WiFi testbed under various mobility conditions. The results obtained from the experimental evaluation reveal that packet loss is reduced by 92.32% when using the proposed framework over the conventional SDN Mobility approach. Although there is a slight increase in jitter overhead due to LISP encapsulation of 0.628 ms, the framework does not compromise Transmission Control Protocol (TCP) session continuity. In addition, the control plane synchronization time is also minimized to 277.5 ms. This reveals that the proposed framework is a stable mobility solution that does not depend on any conventional IP mobility solutions and can be used in future network environments requiring seamless inter-domain connectivity. Full article

To meet the increasingly strict requirements of modern communication, radar detection and electronic measurement systems for wide-bandwidth, low-insertion-loss and high-isolation signal routing, this paper presents a 16 × 16 programmable switch matrix that simultaneously achieves wideband operation (DC-40 GHz), low insertion loss (≤0.9 dB maximum), high isolation (>50 dB typical), and systematic modular scalability, a combination not found in existing implementations. The matrix, constructed with high-quality coaxial switches and optimized RF circuitry and electromagnetic structures, provides flexible and stable single-pole multi-throw (SPMT) signal routing across an ultra-wide frequency range from DC to 40 GHz. The switch matrix features a modular architecture, integrating multiple RF switching units, drive control circuits, and communication interface modules. This architecture achieves minimal signal path depth while maintaining full connectivity between any input and output port, directly minimizing cumulative insertion loss. Through precise impedance matching design and isolation structure optimization, the system still exhibits outstanding transmission characteristics at the 40 GHz high-frequency end: typical insertion loss does not exceed 0.9 dB, and the isolation between channels is better than 50 dB, effectively ensuring the integrity of signals in complex multi-channel environments. To meet the requirements of automated testing and remote control, the equipment integrates dual communication interfaces (serial port/network port), supports the SCPI command set and TCP/IP protocol, and can be conveniently embedded in various test platforms to achieve instrument interconnection and test process automation. Experimental verification shows that this matrix exhibits excellent switching stability and signal consistency across the entire 40 GHz, with a switching action time of less than 10 ms. Furthermore, it is capable of real-time topology reconfiguration via a microcontroller or FPGA. These innovations collectively deliver a switch matrix that meets the demanding requirements of 5G communication, millimeter-wave radar, and aerospace defense systems—applications where bandwidth, signal integrity, and system flexibility are paramount. Full article

When devices equipped with multiple wireless network interfaces access the Internet via Wi-Fi, 4G, and 5G, external factors such as radio interference can increase packet loss rates, resulting in reduced communication speed. To address this issue, two approaches exist: the use of Bottleneck Bandwidth and Round-trip propagation time (BBR), a congestion control algorithm designed to mitigate the impact of packet loss and bicasting in multihomed networks. Bicasting in multihomed networks exploits multiple network paths by transmitting identical packets simultaneously over different networks, thereby reducing effective packet loss and mitigating throughput reduction. In this paper, we introduce a novel network architecture that effectively operates in lossy networks by combining bicasting with BBR. By utilizing QUIC and OpenFlow, the proposed architecture enables the construction of a multihomed network that is independent of the operating system (OS), allowing flexible configuration of congestion control algorithms. Furthermore, the introduction of a QUIC proxy enables the use of existing server-side applications without requiring any modifications. Using the proposed multihomed network, we evaluate communication performance for unicasting and bicasting under varying packet loss rates, and we also analyze fairness with competing Transmission control protocol (TCP) flows. The results indicate that the combination of BBRv3 and bicasting achieves fivefold higher throughput than TCP unicasting at a 1% packet loss rate while preserving fairness with competing TCP flows. Full article

Manual alignment between the trocar, surgical instrument, and robot during minimally invasive surgery (MIS) can be time-consuming and error-prone, and many existing systems do not provide autonomous localization and pose estimation. This paper presents an artificial intelligence (AI)-assisted, vision-guided framework for automated localization and positioning of the ATHENA parallel surgical robot. The proposed approach combines an Intel RealSense RGB–depth (RGB-D) camera with a You Only Look Once version 11 (YOLO11) object detection model to estimate the 3D spatial coordinates of key surgical components in real time. The estimated coordinates are streamed over Transmission Control Protocol/Internet Protocol (TCP/IP) to a programmable logic controller (PLC) using Modbus/TCP, enabling closed-loop robot positioning for automated docking. Experimental validation in a controlled setup designed to replicate key intraoperative constraints demonstrated submillimeter positioning accuracy (≤0.8 mm), an average end-to-end latency of 67 ms, and a 42% reduction in setup time compared with manual alignment, while remaining robust under variable lighting. These results indicate that the proposed perception-to-control pipeline is a practical step toward reliable autonomous robotic docking in MIS workflows. Full article

In the classic energy sector, as well as in the manufacturing and process industries, Programmable Logic Controller (PLC) systems are used for electrical substation control. However, PLCs frequently do not support the communication protocols defined on the standard International Electrotechnical Commission (IEC) 61850. Therefore, this paper presents a vendor-independent method for the integration of Protection and Control (P&C) Intelligent Electronic Devices (IEDs), components of the substation bay level, in PLCs from the substation station level. The method can be used with legacy and modern controllers that offer an open communication interface, where the use of Transmission Control Protocol/Internet Protocol (TCP/IP) is supported. Since many legacy systems offer an open communication interface, this method makes it possible to reuse PLCs, bringing cost efficiency and ecological benefits. The method can be used in a single or redundant way since redundancy is always required in power distribution control. A prototype was developed for the integration over IEC 61850 Manufacturing Message Specification (MMS), and its functional validation is presented in this paper. This solution, besides reducing hardware and software acquisition costs, also contributes to a reduction in electronic waste (E-Waste) and the achievement of Sustainable Development Goals (SDGs). Full article

In this paper, we propose two control approaches based on sliding mode control (SMC) to address the congestion problem in transmission control protocol (TCP) systems. First, a nonlinear sliding variable is introduced using a ${\mathcal{K}}_1$ function, which ensures robustness and finite-time convergence. Based on this sliding variable, a suitable switching controller is designed. Additionally, a continuous version of the controller is developed using the arctangent function to reduce chattering. Two simulation scenarios are presented to validate the effectiveness of the proposed control schemes in terms of congestion control and tracking performance. Full article

IoT (Internet of Things)-enabled solar irradiance sensors are evolving toward energy harvesting, interoperability, and open-source availability, yet current solutions remain either costly, closed, or limited in robustness. Based on a thorough literature review and identification of future trends, we propose an open-source smart wireless sensor that employs a small photovoltaic module simultaneously as sensing element and energy harvester. The device integrates an ESP32 microcontroller, precision ADC (Analog-to-Digital converter), and programmable load to sweep the PV (photovoltaic) I–V (Current–Voltage) curve and compute irradiance from electrical power and solar-cell temperature via a calibrated third-order polynomial. Supporting Modbus RTU (Remote Terminal Unit)/TCP (Transmission Control Protocol), MQTT (Message Queuing Telemetry Transport), and ZigBee, the sensor operates from batteries or supercapacitors through sleep–wake cycles. Validation against industrial irradiance meters across 0–1200 W/m² showed average errors below 5%, with deviations correlated to irradiance volatility and sampling cadence. All hardware, firmware, and data-processing tools are released as open source to enable reproducibility and distributed PV monitoring applications. Full article

This paper presents an intelligent communication architecture, designed to manage multiple power devices operating within a shared Low-Voltage Direct Current (LVDC) bus. These devices act either as energy consumers, e.g., Electric Vehicle (EV) chargers, Power Distribution Units (PDUs), or as sources and regulators, e.g., Alternating Current-to-Direct Current (AC/DC) converters, energy storage system (ESS) units. Communication is established using industrial protocols such as Modular Digital Bus (MODBUS) over Transmission Control Protocol (TCP) or Remote Terminal Unit (RTU), and Controller Area Network (CAN). The proposed system supports both data acquisition and configuration of field devices. It exposes their information to an Energy Management System (EMS) via a MODBUS TCP server. A key contribution of this work is the integration of a lightweight Machine Learning (ML)-based data prioritization mechanism that dynamically adjusts the update frequency of each MODBUS parameter based on its current relevance. This ML-based method has been prototyped and evaluated within a virtualized Internet of Things (IoT) gateway environment. It enables real-time, efficient, and scalable communication without altering the EMS or disrupting legacy protocol operations. Furthermore, the proposed approach allows for early testing and validation of the prioritization strategy before full hardware integration in the demonstrators planned as part of the SHIFT2DC project under the Horizon Europe program. Full article

This study introduces an enhanced Intrusion Detection System (IDS) framework for Denial-of-Service (DoS) attacks, utilizing network traffic inter-arrival time (IAT) analysis. By examining the timing between packets and other statistical features, we detected patterns of malicious activity, allowing early and effective DoS threat mitigation. We generate real DoS traffic, including normal, Internet Control Message Protocol (ICMP), Smurf attack, and Transmission Control Protocol (TCP) classes, and develop nine predictive algorithms, combining traditional machine learning and advanced deep learning techniques with optimization methods, including the synthetic minority sampling technique (SMOTE) and grid search (GS). Our findings reveal that while traditional machine learning achieved moderate accuracy, it struggled with imbalanced datasets. In contrast, Deep Neural Network (DNN) models showed significant improvements with optimization, with DNN combined with GS (DNN-GS) reaching 89% accuracy. However, we also used Recurrent Neural Networks (RNNs) combined with SMOTE and GS (RNN-SMOTE-GS), which emerged as the best-performing with a precision of 97%, demonstrating the effectiveness of combining SMOTE and GS and highlighting the critical role of advanced optimization techniques in enhancing the detection capabilities of IDS models for the accurate classification of various types of network traffic and attacks. 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