Savior: A Reliable Fault Resilient Router Architecture for Network-on-Chip

Hussain, Ayaz; Irfan, Muhammad; Baloch, Naveed Khan; Draz, Umar; Ali, Tariq; Głowacz, Adam; Dunai, Larisa; Antonino-Daviu, José A.

doi:10.3390/electronics9111783

Cited by 5 publications

(3 citation statements)

References 31 publications

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“…Antonio et al purposed an algorithm hour that integrated image processing technology with fuzzy logic to detect fire [28]. In order to increase the efficiency of the system and in order to reduce false positives the algorithm uses dynamic motion test by analyzing the result produced by fuzzy logic when applied to analyze the motion of such areas that resemble fire colors [29].…”

Section: Related Workmentioning

confidence: 99%

Smart Fire Detection and Deterrent System for Human Savior by Using Internet of Things (IoT)

et al. 2021

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Fire monitoring systems have usually been based on a single sensor such as smoke or flame. These single sensor systems have been unable to distinguish between true and false presence of fire, such as a smoke from a cigarette which might cause the fire alarm to go off. Consuming energy all day long and being dependent on one sensor that might end with false alert is not efficient and environmentally friendly. We need a system that is efficient not only in sensing fire accurately, but we also need a solution which is smart. In order to improve upon the results of existing single sensor systems, our system uses a combination of three sensors to increase the efficiency. The result from the sensor is then analyzed by a specified rule-set using an AI-based fuzzy logic algorithm; defined in the purposed research, our system detects the presence of fire. Our system is designed to make smart decisions based on the situation; it provides feature updated alerts and hardware controls such as enabling a mechanism to start ventilation if the fire is causing suffocation, and also providing water support to minimize the damage. The purposed system keeps updating the management about the current severity of the environment by continually sensing any change in the environment during fire. The purposed system proved to provide accurate results in the entire 15 test performed around different intensities of a fire situation. The simulation work for the SMDD is done using MATLAB and the result of the experiments is satisfactory.

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Section: Related Workmentioning

confidence: 99%

Smart Fire Detection and Deterrent System for Human Savior by Using Internet of Things (IoT)

et al. 2021

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“…The P-value specifies the retrieved relevant outcomes; it deals with the accuracy of a system [20]. The R-value specifies relevant outcomes retrieved; it deals with the coverage of the appropriate information of a system along with fault tolerance same as in [21].…”

Section: Problem Statementmentioning

confidence: 99%

Integration of Discrete Wavelet Transform, DBSCAN, and Classifiers for Efficient Content Based Image Retrieval

et al. 2020

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In the domain of computer vision, the efficient representation of an image feature vector for the retrieval of images remains a significant problem. Extensive research has been undertaken on Content-Based Image Retrieval (CBIR) using various descriptors, and machine learning algorithms with certain descriptors have significantly improved the performance of these systems. In this proposed research, a new scheme for CBIR was implemented to address the semantic gap issue and to form an efficient feature vector. This technique was based on the histogram formation of query and dataset images. The auto-correlogram of the images was computed w.r.t RGB format, followed by a moment’s extraction. To form efficient feature vectors, Discrete Wavelet Transform (DWT) in a multi-resolution framework was applied. A codebook was formed using a density-based clustering approach known as Density-Based Spatial Clustering of Applications with Noise (DBSCAN). The similarity index was computed using the Euclidean distance between the feature vector of the query image and the dataset images. Different classifiers, like Support Vector (SVM), K-Nearest Neighbor (KNN), and Decision Tree, were used for the classification of images. The set experiment was performed on three publicly available datasets, and the performance of the proposed framework was compared with another state of the proposed frameworks which have had a positive performance in terms of accuracy.

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“…In Ref. [5], which is in pursuit of Ref. [4], a technique for tolerating a series of permanent and transient faults with a flooding algorithm and random walk is proposed.…”

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confidence: 99%

A novel buffering fault‐tolerance approach for network on chip (NoC)

Jafarzadeh

Jalili

Alzubi

et al. 2022

IET Circuits, Devices & Syst

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Network-on-Chip (NoC) is a key component in chip multiprocessors (CMPs) as it supports communication between many cores. NoC is a network-based communication subsystem on an integrated circuit, most typically between modules in a system on a chip (SoC). Designing a reliable NoC against failures that can prevent failure using some measures or preventing error or system failure while failure happens and proper performance became a significant concern. For a reliable design against failures, first, the system should be analysed to discover the critical points. Hence, in this research, it is tried first to investigate the scale of fault tolerance effect on the mechanism in the router on the network by injecting simulated errors, and then these errors are prevented. As the major novelty, the authors implemented a router on a synchronised network and calculated the network buffering fault tolerance by injecting error in the buffer. Specifically, a new method for improving fault tolerance is proposed, which uses the existing resources efficiently. So, it does not impose any overhead on hardware and improves the error tolerance scale. The authors also evaluate it from different perspectives to show its superior performance. K E Y W O R D S buffering, error injection, network on chip (NoC), router, virtual channel | INTRODUCTIONNetwork-on-chip (NoC) refers to closed-switch communication in a large VLSI system implemented on a single silicon chip. This concept was introduced to improve the bandwidth of the electrical connections of recent system-on-chips (SoCs). The superiority of NoC interconnects mitigates the challenges of growing to interconnect complexity and power budget requirements, making it significant for scalable architectures. Fault-tolerant routing algorithms are primarily designed to fortify the network against permanent errors. The first valuable designs for NoCs are introduced in Ref. [1][2][3]. In most previous studies, the routing algorithms are designed for situations when one or more areas of the network faceThis is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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Savior: A Reliable Fault Resilient Router Architecture for Network-on-Chip

Cited by 5 publications

References 31 publications

Smart Fire Detection and Deterrent System for Human Savior by Using Internet of Things (IoT)

Smart Fire Detection and Deterrent System for Human Savior by Using Internet of Things (IoT)

Integration of Discrete Wavelet Transform, DBSCAN, and Classifiers for Efficient Content Based Image Retrieval

A novel buffering fault‐tolerance approach for network on chip (NoC)

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