258 research outputs found
Energy Management in Wireless Networked Embedded Systems
No full textReal-time systems have undergone an evolution in the last several years in terms of their number and variety of applications, as well as in complexity. A natural result of these advances, coupled with those in sensor techniques and networking, have led to the rise of a new class of applications that fall into the distributed real-time embedded systems category (Loyall, Schantz, Corman, Paunicka, & Fernandez, 2005; Report, 2006). Recent technological advancements in device scaling have been instrumental in enabling the mass production of such devices at reduced costs. As a result, applications with a number of internetworked embedded systems have become prominent. At the same time, there has been a need to move from stand-alone real-time unit into a network of units that collaborate to achieve a real-time functionality. Extensive research has been carried out to achieve real-time guarantees over a set of nodes distributed over wired networks (Siva Ram Murthy & Manimaran, 2001). However, there exist a number of realtime applications in domains, such as industrial processing, military, robotics and tracking, that require the nodes to communicate over the wireless medium where the application dynamics prevent the existence of a wired communication infrastructure. These applications present challenges beyond those of traditional embedded or networked systems, since they involve many heterogeneous nodes and links, shared and constrained resources, and are deployed in dynamic environments where resource contention is dynamic and communication channel is noisy (Report, 2006, Loyall et al., 2005). Hence, resource management in embedded realtime networks requires efficient algorithms and strategies that achieve competing requirements, such as time sensitive energy-efficient reliable message delivery. In what follows, we discuss some applications in this category, and discuss their requirements and the research challenges. </jats:p
An Efficient Backup-Overloading for Fault-Tolerant Scheduling of Real-Time Tasks
No full textMany time-critical applications require dynamic scheduling with predictable performance. Tasks corresponding to these applications have deadlines to be met despite the presence of faults. In this paper, we propose a technique called dynamic grouping, to be used with backup overloading in a primary-backup based fault-tolerant dynamic scheduling algorithm in multiprocessor real-time systems. In dynamic grouping, the processors are dynamically grouped into logical groups in order to achieve efficient overloading of backups, there by improving the schedulability. We compare the performance of dynamic grouping with that of static grouping and no-grouping schemes through extensive simulation studies and show the effectiveness of dynamic grouping.This is a post-peer-review, pre-copyedit version of a proceeding published as Al-Omari R., Manimaran G., Somani A.K. (2000) An Efficient Backup-Overloading for Fault-Tolerant Scheduling of Real-Time Tasks. In: Rolim J. (eds) Parallel and Distributed Processing. IPDPS 2000. Lecture Notes in Computer Science, vol 1800. Springer, Berlin, Heidelberg. The final authenticated version is available online at DOI: 10.1007/3-540-45591-4_177. Posted with permission.</p
ML-based Anomaly Detection for CAN Bus Network in Agriculture Machinery
No full textThe adoption of advanced automation and next-generation technologies like the Internet of Things (IoT) and modern communication networks has revolutionized the food and agriculture sector, boosting the efficiency and precision of farm machinery. However, this increased inter-connectivity has also exposed significant vulnerabilities, particularly in Controller Area Network (CAN) protocols, widely used in advanced agricultural machinery and equipment. Due to its lack of inherent security features, CAN is susceptible to various cyber-attacks, potentially leading to severe consequences if these attacks remain undetected and unmitigated. This paper introduces a supervised machine learning (ML)-based anomaly detection system (CAN-ADS) designed to detect various cyber-attacks on CAN-based agricultural machinery. The system leverages network traffic augmentation and data balancing techniques to train ML algorithms on CAN-specific datasets. Experimental results show that CAN-ADS achieves high accuracy (≈ 98%) and true-positive rates with low false-negative rates (≈ 1%).This is a manuscript of a proceeding published as Bhattacharya, Souradeep, Ranuka G. Gallolukankanamalage, Brian L. Steward, and Manimaran Govindarasu. 2024. “ML-Based Anomaly Detection for CAN Bus Network in Agriculture Machinery”. Proceedings of the AAAI Symposium Series 4 (1):416-23. doi: https://doi.org/10.1609/aaaiss.v4i1.31826
Assessing the cybersecurity of connected 3D printers using large language models (LLMs)
No full textAdditive manufacturing (AM) is transforming industries by enabling complex, cost-effective production, yet its integration with Industry 4.0 introduces significant cybersecurity vulnerabilities. This paper examines potential cyber threats in AM workflows, focusing on attacks that manipulate G-code instructions, such as Man-in-the-Middle (MITM) exploits, which could compromise the integrity of critical components. We introduce Large Language Models (LLMs) as a novel tool for detecting malicious alterations in G-code, showcasing their potential for real-time threat detection. Our findings underscore both the risks within AM and the promise of AI-driven cybersecurity solutions to protect evolving intelligent manufacturing systems.This article is published as Goh, Shi Yong, Ankush Mishra, Manimaran Govindarasu, Baskar Ganapathysubramanian, and Adarsh Krishnamurthy. "Assessing the cybersecurity of connected 3D printers using large language models (LLMs)." Manufacturing Letters 44 (2025): 1187-1197. doi: https://doi.org/10.1016/j.mfglet.2025.06.138
Moving Target Defense Routing for SDN-enabled Smart Grid
No full textThe increasing attack surface area in the smart grid communication networks is making the grid more susceptible to cyber attacks that can lead to instability of the grid and even blackouts. While there are multiple types of cyber attacks that can impact the grid, Denial of Service (DoS) attacks are relatively easier to inject as they require lesser knowledge about the system as compared to data integrity attacks. Various research works showcase methods to prevent or mitigate the impacts of DoS attacks in the smart grid but the research still lacks in demonstrating the feasibility and efficacy of the solutions in a real-world environment. In this paper, we propose a Moving Target Defense (MTD)-enabled Software Defined Network (SDN) for the Smart Grid communication implemented on a Hardware-in-the-Loop (HIL) Testbed. We showcase the implementation of the proposed architecture of MTD-enabled SDN using Mininet 2.3.0 which enables communication between the physical grid and the control center. The results show the advantages of using MTD based on SDN for the wide-area network (WAN) with much lower packet drop percentages in the case of MTD-based routing in the SDN WAN.This is a manuscript of a proceeding published as Abdelkhalek, Moataz, Burhan Hyder, Manimaran Govindarasu, and Craig G. Rieger. "Moving Target Defense Routing for SDN-enabled Smart Grid." In 2022 IEEE International Conference on Cyber Security and Resilience (CSR), pp. 215-220. IEEE, 2022.
DOI: 10.1109/CSR54599.2022.9850341.
Copyright 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Posted with permission
Malignant Pleural Effusion: A Study on Clinical and Investigative Profiles - A Prospective Study
No full textBackground and Objective: Malignant pleural effusion (MPE) is a known complication of both thoracic and extrathoracic malignancies. A detailed clinical and investigative profile of patients presenting with MPE would allow us to intervene early in the disease and would ensure a better prognosis. Materials and Methods: A prospective study of 60 cases of MPE was carried out in the Department of Thoracic Medicine and Cardiothoracic surgery, Thanjavur Medical College Hospital, Thanjavur, from October 2017 to May 2018, with respect to age, sex, clinical findings, biochemical analysis, radiological, cytological investigations, and histopathology. Results: The most common age group of MPE is between 60 and 70 years, male-to-female ratio was 1:1. The right-sided pleural effusion was a more common finding compared to the left-sided effusion; pleural fluid biochemical analysis revealed a mean adenosine deaminase of 23.97 u/l, mean pleural fluid protein/serum protein ratio was 0.95, and mean pleural fluid glucose was 38.75 mg/dl. Of 60 cases, the most common cause of MPE was adenocarcinoma of lung which accounted for 30 cases, followed by metastatic carcinoma 24 cases and squamous cell carcinoma lung 3 cases and pleural mesothelioma in 3 cases. Conclusion: Pleural fluid cytology analysis for malignant cells was sufficient to diagnose MPE in 85% of cases, and in remaining cases, pleural biopsy can be helpful. The most common primary in cases of MPE was adenocarcinoma of lung
- …
