On Fast and Exact Computation of Error Metrics in Approximate LSB Adders

Roy, Avishek Sinha; Biswas, Rajdeep; Dhar, Anindya Sundar

doi:10.1109/tvlsi.2020.2967149

Cited by 9 publications

(3 citation statements)

References 27 publications

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“…LOA is an area and computation-efficient implementation of the adder among the various approximate adders in the literature ever found. Still, the research is progressed in the same approach for striving better accuracy [36][37][38][39]. Our work is unique in this; we hardly bother about accuracy since in this encryption domain adder is used for translation purpose.…”

Section: Proposed Renovated Xtea Mutual Authentication Protocol Archi...mentioning

confidence: 99%

Renovated XTEA Encoder Architecture-Based Lightweight Mutual Authentication Protocol for RFID and Green Wireless Sensor Network Applications

Nagarajan

Muthaiah

Teekaraman

et al. 2022

Wireless Communications and Mobile Computing

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Wireless sensor networks find applications everywhere in day to day activities right from attendance entry systems to healthcare monitoring systems. The evolution of the Internet of Things (IoT) as the Internet of Everything (IoET) makes the wireless sensor network omnipresent and increases the use of Radio Frequency Identification (RFID) for the proper identification of devices and sensor nodes which are mostly battery operated. As technology evolves, security threats also increase rapidly. This mandates a strong and energy-efficient green solution. This work attempted to address these issues by effectively deploying the lightweight encryption scheme called Extended Tiny Encryption Algorithm (XTEA). Though the XTEA is lightweight and famous, it is commonly known for various attacks. Our work patches the security threats in the XTEA by applying domain-specific customization, random number utilization, and undisclosed key renewal techniques. Two custom Renovated XTEA Mutual Authentication Protocol (RXMAP) encoder architectures, namely, RXMAP-1 and RXMAP-2, are proposed based on the replacement of accurate computational blocks with approximate blocks. The proposed RXMAP protocol is evaluated for its computational and storage overhead and verified against various security threats using BAN logic formal verification and informal verification. The proposed encoder architectures are simulated for functional verification, and ASIC implementation is done with a 132 nm process node. ASIC implementation results show that the proposed designs RXMAP-1 and RXMAP-2 occupy 53.11% and 53.31% lesser area compared to XTEA I and 52.97% and 53.18% lesser area compared to XTEA II implementation. The total power consumed by the proposed encoder architectures RXMAP-1 and RXMAP-2 is 68.76% and 71.64% lesser than XTEA II implementation, respectively, while maintaining the equal throughput.

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Section: Proposed Renovated Xtea Mutual Authentication Protocol Archi...mentioning

confidence: 99%

Renovated XTEA Encoder Architecture-Based Lightweight Mutual Authentication Protocol for RFID and Green Wireless Sensor Network Applications

Nagarajan

Muthaiah

Teekaraman

et al. 2022

Wireless Communications and Mobile Computing

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“…It consists of 50% energy efficiency when compared to other schemes and the error distance consists of 2. A. Sinha Roy et al, [15] created an approximation of Least Significant Bit (LSB) adders analyzed error metrics, and compared it with 216 samples of Monte Carlo simulation. Though these schemes offer better error metrics, in several schemes low power metrics and real-time image processing applications are not mentioned.…”

Section: Background Workmentioning

confidence: 99%

Low Power Adders for Efficient Image Processing Applications

L.Sowmiya,

Ramesh SM,

Arul A

et al. 2023

Int Res J Adv Engg Hub

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In the world of digitalization, low-power circuits are necessary for building fast operating processors. Additionally, low-power circuits consume less energy and the lifetime of the electronic devices can extended to the maximum. Adders are significantly used in digital image processing techniques and for many Very Large-Scale Integration (VLSI) applications. Due to this, demand for creating efficient adders has become high in recent years. Using approximate adders is much more convenient than exact adders and the results of approximation adders are better than exact adders. Approximation adders can be executed for many signal-processing applications and are mainly considered for image-processing applications. SESA and SEDA are very good in providing efficiently lower energy when compared to other mirror adder circuits and are cost-efficient. Improvements and further extensions of the proposed model can easily make for building efficient microprocessor chips and these adders are used in next-generation electronic devices.

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“…N, F, and L represent instances' numbers, attributes' numbers contained in each instance, and labels' numbers in the dataset, respectively. Te notation label cardinality (LCard) represents the normal measure as shown in [49]. LCard denotes the average label number associated with an instance.…”

Section: Test Datasetsmentioning

confidence: 99%

Improved Double‐Layer Structure Multilabel Classification Model via Optimal Sequence and Attention Mechanism

Liu

Tan

2022

Complexity

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Multilabel classification is a key research topic in the machine learning field. In this study, the author put forward a two/two-layer chain classification algorithm with optimal sequence based on the attention mechanism. This algorithm is a classification model with a two-layer structure. By introducing an attention mechanism, this study analyzes the key attributes to achieve the goal of classification. To solve the problem of algorithm accuracy degradation caused by the order of classifiers, we adopt the OSS (optimal sequence selection) algorithm to find the optimal sequence of tags. The test results based on the actual dataset show that the ATDCC-OS algorithm has good performance on all performance evaluation metrics. The average accuracy of this algorithm is over 80%. The microaverage AUC performance reaches 0.96. In terms of coverage performance, its coverage performance is below 10%. The comprehensive result of single error performance is the best. The loss performance is about 0.03. The purpose of the ATDCC-OS algorithm proposed in the study is to help improve the accuracy of multilabel classification so as to obtain more effective data information.

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On Fast and Exact Computation of Error Metrics in Approximate LSB Adders

Cited by 9 publications

References 27 publications

Renovated XTEA Encoder Architecture-Based Lightweight Mutual Authentication Protocol for RFID and Green Wireless Sensor Network Applications

Renovated XTEA Encoder Architecture-Based Lightweight Mutual Authentication Protocol for RFID and Green Wireless Sensor Network Applications

Low Power Adders for Efficient Image Processing Applications

Improved Double‐Layer Structure Multilabel Classification Model via Optimal Sequence and Attention Mechanism

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