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King Saud Univ. Comput. Inf. Sci."],"published-print":{"date-parts":[[2025,10]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>\n                    The rapid growth of IoT devices and data in edge computing applications has created a pressing need for efficient lossless compression of end-edge data. The Lempel-Ziv-Welch (LZW) algorithm, widely used in these scenarios, faces bottlenecks in compression speed due to its inherent data dependency. Unlike existing multi-cycle architectures, we propose PLZW, a pipeline-based LZW acceleration architecture with three novel mechanisms: a data bypass mechanism that allows data to pass directly between pipeline stages, minimizing stalls; a multi-level caching mechanism to reduce pipeline stalls caused by long dictionary update times; and a hash prediction mechanism to improve dictionary lookup hit rates and reduce stall frequency. Our field-programmable gate array (FPGA) implementation demonstrates a 2.5\n                    <jats:inline-formula>\n                      <jats:alternatives>\n                        <jats:tex-math>$$\\times $$<\/jats:tex-math>\n                        <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\">\n                          <mml:mo>\u00d7<\/mml:mo>\n                        <\/mml:math>\n                      <\/jats:alternatives>\n                    <\/jats:inline-formula>\n                    speedup over existing state-of-the-art methods while maintaining competitive power consumption, resource utilization, and compression ratio. Furthermore, the resource utilization remains below 1% of total FPGA resources, and the proposed mechanisms improve the dictionary first-hit rate by 35.8%. This work offers a high-speed, lightweight, generic solution for lossless compression of end-edge data. PLZW provides a reference implementation for optimizing hardware-based data compression in real-time and resource-constrained applications.\n                  <\/jats:p>","DOI":"10.1007\/s44443-025-00243-8","type":"journal-article","created":{"date-parts":[[2025,9,24]],"date-time":"2025-09-24T15:08:05Z","timestamp":1758726485000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["PLZW: FPGA-based Pipelined LZW for lossless compression of edge data"],"prefix":"10.1007","volume":"37","author":[{"given":"Xiao","family":"Liu","sequence":"first","affiliation":[]},{"given":"Akram Y.","family":"Sarhan","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0694-0856","authenticated-orcid":false,"given":"Shubo","family":"Liu","sequence":"additional","affiliation":[]},{"given":"Zhaohui","family":"Cai","sequence":"additional","affiliation":[]},{"given":"Guoqing","family":"Tu","sequence":"additional","affiliation":[]},{"given":"Faisal S.","family":"Alsubaei","sequence":"additional","affiliation":[]},{"given":"Yousef S.","family":"Alsahafi","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,9,24]]},"reference":[{"key":"243_CR1","doi-asserted-by":"publisher","first-page":"2830","DOI":"10.1007\/s12083-024-01725-8","volume":"17","author":"O Arshi","year":"2024","unstructured":"Arshi O, Rai A, Gupta G, Pandey JK, Mondal S (2024) IoT in energy: a comprehensive review of technologies, applications, and future directions. 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