Optimal Selective Huffman Coding for Test-Data Compression

Kavousianos, X.; Kalligeros, Emmanouil; Nikolos, D.

doi:10.1109/tc.2007.1057

Cited by 104 publications

(52 citation statements)

References 17 publications

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“…So, the number of samples remain constant for every second. These data rate patterns are not detected by the classical compression methods (Huffman coding, Dictionary coders or prediction by partial matching [5]- [7]), and thus compression of PMUs data can yield better lossless compression ratios compared to other classical software compression. Figure 1 shows the proposed architecture for efficient data storage for PMU data at PDC level.…”

Section: Optimal Encoded Pmu Measurementsmentioning

confidence: 99%

Data Compression for Next Generation Phasor Data Concentrators (PDCs) in a Smart Grid

Olivo¹,

Campion²,

Ranganathan³

2016

JIS

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The storage space and cost for Smart Grid datasets has been growing exponentially due to its high data-rate of various sensor readings from Automated Metering Infrastructure (AMI), and Phasor Measurement Units (PMUs). The paper focuses on Phasor Data Concentrators (PDCs) that aggregate data from PMUs. PMUs measure real-time voltage, current and frequency parameters across the electrical grid. A typical PDC can process data from anywhere ten to forty PMUs. The paper exploits the need for appropriate security and data compression challenges simultaneously. As a result, an optimal compression method ER1c is investigated for efficient storage of IREG and C37.118 timestamped PDC data sets. We expect that our approach can greatly reduce the storage cost requirements of commercial available PDCs (SEL 3373, GE Multilin P30) by 80%. For example, 2 years of PDC data storage space can be easily replaced with only 10 days of storage space. In addition, our approach in combination with AES 256 encryption can protect PDC data to larger degree as per National Institute of Standards and Technology (NIST) standards.

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Section: Optimal Encoded Pmu Measurementsmentioning

confidence: 99%

Data Compression for Next Generation Phasor Data Concentrators (PDCs) in a Smart Grid

Olivo¹,

Campion²,

Ranganathan³

2016

JIS

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“…Symbol-based techniques first divide the test data into several types of symbols and then they utilize codewords to encode these symbols [2]- [15]. An attractive technique is the selective Huffman code [3], [5] that offers low-cost decompressors and high compression at the same time. Symbol-based schemes are very effective in exploiting correlations in test cubes and they do not depend on the automatic test pattern generation (ATPG) process used.…”

Section: T He Main Objective Of Test Data Compression (Tdc)mentioning

confidence: 99%

“…The optimal selective Huffman (OSH) code encodes only the m most frequent blocks [3], while the rest of the blocks remain unencoded and are distinguished by using an extra Huffman codeword [5]. Let us assume a core with n scan chains of length r (we assume a balanced scan structure where the shorter scan chains are padded with x logic values).…”

Section: Motivationmentioning

confidence: 99%

“…T is partitioned into |T |/l data blocks of size l. Among these blocks, the m most frequent distinct blocks, b 1 , b 2 , ..., b m , with frequencies (probabilities) of occurrence f 1 ≥ f 2 ≥ · · · ≥ f m , respectively, are stored in a dictionary and they are encoded using m Huffman codewords. The rest of the blocks with an aggregate frequency f un = f m+1 + f m+2 + · · · remain nonencoded and a single codeword is used to precede them as (they are stored in a raw form in the compressed test data [5]). A binary tree is constructed beginning from the leaves and moving toward the root.…”

Section: Motivationmentioning

confidence: 99%

See 1 more Smart Citation

High-Quality Statistical Test Compression With Narrow ATE Interface

Tenentes

Kavousianos

2013

IEEE Trans. Comput.-Aided Des. Integr. Circuits Syst.

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Abstract-In this paper, we present a novel compression method and a low-cost decompression architecture that combine the advantages of both symbol-based and linear-based techniques and offer a very attractive unified solution that removes the barriers of existing test data compression techniques. Besides the traditional goals of high compression and short test application time, the proposed method also offers low shift switching activity and high unmodeled defect coverage at the same time. In addition, it favors multi-site testing as requires a very low pincount interface to the automatic test equipment. Finally, contrary to existing techniques, it provides an integrated solution for testing multi-core system on chips (SoCs) as it is suitable for cores of both known and unknown structures that usually coexist in SoCs.Index Terms-Defect-oriented testing, design for testability, dft, IP cores, low-power scan-based testing, multi-core SoC, selective Huffman, test data compression, unmodeled defect coverage.

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“…In [6], a technique based on variation of Huffman coding is presented to offer better compression. Run Length Encoding is a simple data compression algorithm and is based on replacing a long sequence of the same symbol by a shorter sequence [7].…”

Section: Introductionmentioning

confidence: 99%