Low overhead optimal parity codes

Neelima, K.; Subhas, C.

doi:10.12928/telkomnika.v20i3.23301

Cited by 6 publications

(4 citation statements)

References 29 publications

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“…In method -1, we use only the extended parity bits and vertical bits for decoding and the hamming bits remain as hidden bits and are not used. Consider the data to be "00000000" as the data to be encoded [23]. Then by using the encoding equations the corresponding parity bits are also all zeros as shown below.…”

Section: Methodsmentioning

confidence: 99%

Modified Matrix Codes for Shielding Memories Against Adjacent Errors

Subhas

2024

AEJ

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Soft errors are caused in memories due to radiation effects as the technology scales down. This paper concentrates on correcting adjacent errors in memories using indirect decoding mechanisms. Several matrix codes were also used to correct a maximum of two adjacent and random errors. In this paper, matrix representation of two rows for half the data bits matrix representations is used and each row is encoded with extended hamming code parity bits. Three ways of decoding are proposed. Among them, the method-1 uses only extended hamming bits of rows and vertical parity bits for decoding which is capable of correcting odd number of adjacent bits in half of data bits. The method-2 uses all parity bits and is capable of correcting 1 bit less than half the data bits. The method-3 uses all parity bits and with a change in decoding mechanism allows correction of half erroneous data bits. The method-3 based decoder proves to be more reliable either in lower half or upper half of Data, enabling it to be used in image processing applications. But method-3 compromises with decrease in code rate, increase in bit overhead, area and power delay product by atleast 26.38%, 10.76%, 9.6% and 5%.

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Section: Methodsmentioning

confidence: 99%

Modified Matrix Codes for Shielding Memories Against Adjacent Errors

Subhas

2024

AEJ

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“…The codes considered in this paper for evaluating the proposed proficient matrix code are decimal matrix code, modified decimal matrix code and parity matrix code. The data matrix codes (DMC) code is based on a proportional divider symbol and uses the decimal integer addition and subtraction for detecting errors [23], [24] as shown in Figure 3. This encoding approach in each row and column assumes a symbol treated as decimal integer to obtain a corrected word.…”

Section: Methodsmentioning

confidence: 99%

Proficient matrix codes for error detection and correctionin 8-port network on chip routers

Neelima¹,

Kumar²,

Satyam³

et al. 2023

IJEECS

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This paper verifies the applicability of the proposed code to dynamic Network on Chips that have variable faulty blocks with runtime suggesting an online error detection mechanism with adaptive routing algorithm that bypasses faulty components dynamically and the router architecture uses additional diagonal state indications for the reliable network on chip (NoC) operation. In NoC, the permanently faulty routers are disconnected to enable high runtime throughput as data packets are not lost due to self-loopback mechanism. The proposed proficient matrix codes use the capabilities of decimal matrix code technique with minimum check bits for maximum error correction capability. The proposed code is compared with existing codes such as decimal matrix codes, modified decimal matrix codes and parity matrix codes. The codes are developed in verilog hardware description language and simulated in the Xilinx ISE 14.5 tool. This proficient matrix code proves to be efficient for multiple adjacent error detection and correction with trade off in delay. Also 65% code rate is achieved with 22.73% less redundant bits that occupy less area by atleast 11.78%. The codes when used for increased data sizes like 8, 16, 32, and 64 bits, the power delay product decreased by atleast 1.74%.

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“…Work [9] is also devoted to the development of an improved reliable method of error detection and correction codes with minimum redundant bits and maximum coding speed. The advantage of the developed semi-diagonal code is greater efficiency compared to existing matrix codes.…”

Section: Literature Review and Problem Statementmentioning

confidence: 99%

Development of the method of detecting and correcting data transmission errors in IoT systems for monitoring the state of objects

Sokolovskyi,

Zharikov,

Telenyk

2024

EEJET

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The object of the study is the IOT system for monitoring the state of objects. The problem being solved is the development of an innovative method of detecting and correcting data transmission errors in the networks of Internet of Things systems. The essence of the results is that a method of detecting and correcting multiple transmission errors during byte-by-byte transmission of a block of information has been developed. The method is distinguished by an original coding scheme, which involves the calculation of control bits, as well as the shuffling of block bits by performing bit shift operations. The peculiarity of the method is that any bit can be distorted when transmitting a code word, but it belongs to different code combinations of the Hamming code. This allows multiple data transmission errors to be detected and corrected during decoding, and multiple errors of different bytes belonging to the same block can be corrected. Simple algorithms for encoding and decoding procedures have been developed, and programs for information block encoding procedures and decoding procedures with error detection and correction have been developed. A software model of the data transmission channel was also developed with the possibility of introducing multiple errors when simulating the data transmission process. All programs are developed in Python, although other languages are possible. An experiment was conducted using the developed software model of the data transmission channel. The efficiency of the developed method has been experimentally confirmed and it has been proven that its use increases the immunity of the data transmission channel. This is due to the fact that the developed method allows detecting and correcting all code word transmission errors with a multiplicity from 1 to 8, which was confirmed experimentally. The main field of use of the developed method is considered to be IoT system networks. First of all, systems for monitoring the state of objects

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Low overhead optimal parity codes

Cited by 6 publications

References 29 publications

Modified Matrix Codes for Shielding Memories Against Adjacent Errors

Modified Matrix Codes for Shielding Memories Against Adjacent Errors

Proficient matrix codes for error detection and correctionin 8-port network on chip routers

Development of the method of detecting and correcting data transmission errors in IoT systems for monitoring the state of objects

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