UNITED STATES PATENT AND TRADEMARK OFFICE
`
`
`
`BEFORE THE PATENT TRIAL AND APPEAL BOARD
`
`
`
`DELL INC.; RIVERBED TECHNOLOGY, INC.; SAP AMERICA, INC.;
`SYBASE, INC.; HEWLETT-PACKARD ENTERPRISE CO.; HP
`ENTERPRISE SERVICES, LLC; TERADATA OPERATIONS, INC.;
`ECHOSTAR CORPORATION; AND HUGHES NETWORK SYSTEMS,
`LLC
`VERITAS TECHNOLOGIES LLC
`Petitioner
`
`v.
`
`REALTIME DATA LLC d/b/a IXO
`Patent Owner
`
`
`
`Case: IPR2016-00972Unassigned
`U.S. Patent No. 7,415,530
`
`
`
`DECLARATION OF CHARLES D. CREUSERE, Ph.D.
`
`
`
`
`
`Mail Stop PATENT BOARD
`Patent Trial and Appeal Board
`United States Patent and Trademark Office
`PO Box 1450
`
`Veritas Techs. LLC
`Exhibit 1019
`Page 001
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`
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`Alexandria, Virginia 22313–1450
`Submitted Electronically via the Patent Review Processing SystemE2E
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`-2-
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`Veritas Techs. LLC
`Exhibit 1019
`Page 002
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`TABLE OF CONTENTS
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`
`
`INTRODUCTION .......................................................................................... 1
`I.
`EXECUTIVE SUMMARY ............................................................................ 2
`II.
`III. MY BACKGROUND AND QUALIFICATIONS ........................................ 4
`A. Educational Background ................................................................................. 4
`B. Professional Experience ................................................................................. 4
`C. Patents and Publications ................................................................................. 7
`D. Other Relevant Qualifications ........................................................................ 8
`E. Materials Considered ...................................................................................... 9
`IV.
`LEVEL OF ORDINARY SKILL IN THE ART ............................................ 9
`V.
`BACKGROUND KNOWLEDGE HELD BY A PERSON OF ORDINARY
`SKILL REGARDING THE FIELD OF THE ’530 PATENT ................................. 12
`VI. OVERVIEW OF THE ’530 PATENT ......................................................... 18
`VII. OVERVIEW OF THE PRIOR ART REFERENCES I RELY UPON ........ 21
`A. U.S. Patent No. 5,870,036 to Franaszek ....................................................... 22
`B. U.S. Patent No. 5,247,646 to Osterlund ....................................................... 26
`C. U.S. Patent No. 5,563,961 to Rynderman .................................................... 30
`D. U.S. Patent No. 5,991,515 to Fall ................................................................. 33
`E. U.S. Patent No. 5,319,682 to Clark .............................................................. 36
`F. U.S. Patent No. 5,771,354 to Crawford ........................................................ 38
`G. U.S. Patent No. 5,479,638 to Assar .............................................................. 39
`VIII. LEGAL PRINCIPLES USED IN MY ANALYSIS ..................................... 39
`A. Prior Art ........................................................................................................ 40
`B. Anticipation .................................................................................................. 40
`C. Obviousness .................................................................................................. 41
`IX. CLAIM CONSTRUCTION ......................................................................... 43
`X.
`UNPATENTABILITY ANALYSIS ............................................................ 46
`A. The Claims of the ’530 Patent ...................................................................... 47
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`-i-
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`Exhibit 1019
`Page 003
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`B. Claims 1, 9-11, 14, and 18 Would Have Been Obvious Over Franaszek in
`View of Osterlund ........................................................................................ 50
`1. Claim 1 would have been obvious over Franaszek in view of Osterlund50
`a. “A system comprising:” ........................................................................ 50
`b. a memory device; and ........................................................................... 51
`c. a data accelerator, wherein said data accelerator is coupled to said
`memory device, ............................................................................................ 52
`d. a data stream is received by said data accelerator in received form, .... 56
`e.
`said data stream includes a first data block and a second data block,
`5857
`
`f.
`said data stream is compressed by said data accelerator to provide a
`compressed data stream by compressing said first data block with a first
`compression technique and said second data block with a second
`compression technique, ........................................................................... 5958
`g. said first and second compression techniques are different ............. 6362
`h. said compressed data stream is stored on said memory device, ...... 6564
`i.
`said compression and storage occurs faster than said data stream is able
`to be stored on said memory device in said received form, ................... 6665
`j.
`a first data descriptor is stored on said memory device indicative of
`said first compression technique, and said first descriptor is utilized to
`decompress the portion of said compressed data stream associated with said
`first data block. ........................................................................................ 6968
`k. Motivation to Combine Franaszek and Osterlund and the Obviousness
`of the Combination of Claimed Features ................................................ 7170
`2. Claims 9, 10, and 11 Would Have Been Obvious Over Franaszek in view
`of Osterlund ................................................................................................. 7877
`3. Claim 14 Would Have Been Obvious Over Franaszek in view of
`Osterlund ..................................................................................................... 7978
`4. Claim 18 Would Have Been Obvious Over Franaszek in view of
`Osterlund ..................................................................................................... 8180
`C. Claims 2-5 Would Have Been Obvious Over Franaszek in View of
`Osterlund and Further in View of Fall .................................................... 8281
`1. Claim 2 Would Have been Obvious Over Franaszek in View of
`Osterlund and Further in View of Fall ........................................................ 8281
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`Exhibit 1019
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`2. Claims 3 and 4 Would Have Been Obvious Over Franaszek in view of
`Osterlund and Further in View of Fall ........................................................ 8887
`3. Claim 5 Would Have Been Obvious Over Franaszek in view of
`Osterlund and Further in View of Fall ........................................................ 9291
`D. Claim 12 Would Have Been Obvious Over Franaszek in View of Osterlund
`and Further in View of Assar .................................................................. 9594
`1. Claim 12 Would Have Been Obvious Over Franaszek in View of
`Osterlund and Further in View of Assar ..................................................... 9594
`E. Claim 19 Would Have Been Obvious Over Franaszek in View of Osterlund
`and Further in View of Crawford ............................................................ 9897
`1. Claim 19 Would Have Been Obvious Over Franaszek in View of
`Osterlund and Further in View of Crawford ............................................... 9897
`F. Claim 24 Would Have Been Obvious Over Franaszek in view of Osterlund,
`Clark, and Rynderman ......................................................................... 101100
`1. The Teachings of Franaszek, Osterlund, Clark, and Rynderman ... 101100
`2. Claim 24 Would Have Been Obvious Over Franaszek in view of
`Osterlund, Clark, and Rynderman. ................................................................101
`a. A system comprising: ..........................................................................101
`b. a memory device; and .................................................................. 102101
`c. a data accelerator, wherein said data accelerator is coupled to said
`memory device, ................................................................................... 102101
`d. a data stream is received by said data accelerator in received form,
`102101
`
`e. wherein a bandwidth of the received data stream is determined, 102101
`f.
`said data stream includes a first data block and a second data block, 104
`g. said data stream is compressed by said data accelerator to provide a
`compressed data stream by compressing said first data block with a first
`compression technique and said second data block with a second
`compression technique, ....................................................................... 105104
`h. said first and second compression techniques are different, ........ 105104
`i. wherein a data rate of the compressed data stream is adjusted, by
`modifying a system parameter, to make a bandwidth of the compressed
`data stream compatible with a bandwidth of the memory device, ............105
`j.
`said compressed data stream is stored on said memory device, .........107
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`Exhibit 1019
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`k. said compression and storage occurs faster than said data stream is able
`to be stored on said memory device in said received form, ............... 108107
`l.
`a first data descriptor is stored on said memory device indicative of
`said first compression technique, and said first descriptor is utilized to
`decompress the portion of said compressed data stream associated with said
`first data block. .................................................................................... 108107
`3. Motivation to Combine Franaszek, Osterlund, Clark and Rynderman and
`the Obviousness of the Combination of Claimed Features ...........................108
`XI. CONCLUSION ...........................................................................................114
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`Exhibit 1019
`Page 006
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`PETITIONER’S EXHIBIT LIST
`
`Ex. No.
`
`BRIEF DESCRIPTION
`
`1001
`
`1002
`
`1003
`
`1004
`
`1005
`
`1006
`
`1007
`
`1008
`
`1009
`
`1010
`
`1011
`
`1012
`
`1013
`
`1014
`
`1015
`
`U.S. Patent No. 7,415,530
`
`Declaration of Dr. Charles Creusere
`
`Curriculum Vitae of Dr. Charles Creusere
`
`U.S. Patent No. 5,870,036
`(“Franaszek”)
`
`U.S. Patent No. 5,247,646
`(“Osterlund”)
`
`U.S. Patent No. 5,563,961
`(“Rynderman”)
`
`to Franaszek et al.
`
`to Osterlund et al.
`
`to Rynderman et al.
`
`U.S. Patent No. 5,991,515 to Fall et al. (“Fall”)
`
`U.S. Patent No. 5,319,682 to Clark (“Clark”)
`
`U.S. Patent No. 5,771,354 to Crawford (“Crawford”)
`
`‘927 Reexamination File History, 5/31/13 Right of
`Appeal Notice
`
`U.S. Patent No. 7,415,530 Inter Partes Reexamination
`Certificate Issued Under U.S.C. 316
`
`Mark Nelson, The Data Compression Book (1992)
`
`STAC 9704 Data Compression Coprocessor Data Sheet,
`Rev. 2.00(9/91).
`
`RESERVED
`
`Tarek M. Sobh, et al., A Comparison of Compressed and
`Uncompressed Transmission Modes, Dept, of Computer
`and Information Sci., School of Eng’g and Applied Sci.,
`Univ. of Penn. (May 1991) (“Sobh”)
`
`-v-
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`Veritas Techs. LLC
`Exhibit 1019
`Page 007
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`1016
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`1017
`
`1018
`
`1019
`
`U.S. Patent No. 5,479,638 to Assar et al. (“Assar”)
`
`RANDOM HOUSE WEBSTER’S, COMPUTER & INTERNET
`DICTIONARY at 45 (3d ed. 1999)
`
`Redline comparison between Dell’s Petition (IPR2016-
`00972) and Veritas’s Joinder Petition
`
`Redline comparison between Dell’s Ex. 1002
`(Creusere Declaration) (IPR216-00972) and Veritas’s
`Ex. 1002 (Creusere Declaration)
`
`
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`-vi-
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`Veritas Techs. LLC
`Exhibit 1019
`Page 008
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`I, Charles D. Creusere, Ph.D., do hereby declare as follows:
`I.
`
`INTRODUCTION
`1.
`
`I understand that this Declaration will accompany Dell Inc.;
`
`Riverbed Technology, Inc.; SAP America, Inc.; Sybase, Inc.; Hewlett-Packard
`
`Enterprise Co.; HP Enterprise Services, LLC; Teradata Operations, Inc.;
`
`EchoStar Corporation; and Hughes Network Systems, LLC’s (collectively
`
`“DellVeritas Technologies LLC’s (“Veritas”) Petition for Inter Partes Review of
`
`U.S. Patent No. 7,415,5301. As part of my work, I was asked to review certain
`
`materials and give my opinion about whether claims 1-5, 9-12, 14, 18, 19, and 24
`
`of the ’530 patent are valid over certain patents, patent applications, and
`
`publications. I was also asked for my opinions regarding the level of ordinary skill
`
`in the art to which the ’530 patent pertains as of March 11, 1999. I made an
`
`essentially identical declaration regarding the ’530 Patent in support of the
`
`petition in IPR2016-00972.
`
`2.
`
`I have been retained by DellVeritas as an expert in the field of data
`
`compression and storage systems. I am being compensated at my normal
`
`
`1 I have been informed that the ’530 patent is attached to Dell’sVeritas’s Petition
`
`as Exhibit 1001. I am informed that a complete listing of exhibits and their
`
`accompanying numbers appears at the table of exhibits to my declaration. I have
`
`reviewed and considered each of these exhibits in formulating my opinions.
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`1
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`Veritas Techs. LLC
`Exhibit 1019
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`consulting rate of $350 per hour for my time. My compensation is not dependent
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`on the outcome of this proceeding, the results of my analysis, or on the substance
`
`of my opinions and testimony. I have no interest in the outcome of this matter, or
`
`in any other matter between DellVeritas and the Patent Owner.
`
`3.
`
`I have no financial interest in DellVeritas. I similarly have no
`
`financial interest in the ’530 patent or the owner of the ’530 patent, and I have had
`
`no contact with the named inventor of the ’530 patent.
`
`II. EXECUTIVE SUMMARY
`4.
`Based on my analysis of the ’530 patent and the materials discussed
`
`herein, it is my opinion that claims 1-5, 9-12, 14, 18, 19, and 24 of the ’530 patent
`
`would have been obvious to a person of ordinary skill in the art as of the earliest
`
`filing date of the ’530 patent: March 11, 1999. I provide a detailed explanation of
`
`my conclusions below.
`
`5.
`
`The
`
`’530 patent
`
`relates
`
`to data compression, storage, and
`
`decompression, see, e.g., Ex. 1001 at Abst., and describes a “data storage
`
`accelerator” that includes “one or a plurality of high speed data compression
`
`encoders.” Id. The data storage accelerator compresses data and stores it in
`
`memory. Id. The independent claims of the ’530 patent recite that data
`
`compression and storage occur faster than storage alone would occur if the data
`
`were left in uncompressed form. See id. at 18:36-38; Ex. 1011 at 1:21-2:18.
`
`2
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`Exhibit 1019
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`6.
`
`As described in more detail below, the concepts of providing
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`accelerated data storage and retrieval by utilizing data compression and
`
`decompression along with the use of multiple compression techniques were known
`
`and understood by those working in the field before March 11, 1999. Accelerated
`
`data storage and retrieval through data compression and decompression was
`
`described in patents and other publications years before the ’530 patent was filed.
`
`7.
`
`As set forth in detail below, it is my opinion that each of claims 1-5,
`
`9-12, 14, 18, 19, and 24 would have been obvious to a person of ordinary skill in
`
`the art based on the teachings of various references. To summarize:
`
`• Claims 1, 9-11, 14, and 18 would have been obvious over Franaszek in
`
`view of Osterlund;
`
`• Claims 2-5 would have been obvious over Franaszek in view of
`
`Osterlund and further in view of Fall;
`
`• Claim 12 would have been obvious over Franaszek in view of Osterlund
`
`and further in view of Assar;
`
`• Claims 19 would have been obvious over Franaszek in view of Osterlund
`
`and further in view of Crawford; and
`
`• Claim 24 would have been obvious over Franaszek in view of Osterlund,
`
`Clark, and Rynderman.
`
`3
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`Exhibit 1019
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`III. MY BACKGROUND AND QUALIFICATIONS
`A. Educational Background
`8.
`I received a bachelor of science degree in Electrical and Computer
`
`Engineering from the University of California at Davis in 1985. I received a
`
`masters of science degree in electrical and Computer Engineering from the
`
`University of California at Santa Barbara in 1990, and I received my PhD. in
`
`Electrical and Computer Engineering, also from the University of California at
`
`Santa Barbara in 1993.
`
`B.
`9.
`
`Professional Experience
`
`I have more than 30 years of experience with data compression,
`
`decompression, and data storage.
`
`10.
`
`I am currently a Full Professor in the Klipsch School of Electrical &
`
`Computer Engineering at New Mexico State University. I was an Assistant
`
`Professor at New Mexico State from January 2000 until I became an Associate
`
`Professor in 2004. I have been a Full Professor since August 2010. My research
`
`and coursework at New Mexico State have focused on digital signal and image and
`
`video processing and, in particular, compression. My general area of expertise is
`
`in digital signal processing with a particular focus on applications related to
`
`compression: image, video, and audio.
`
`11. My first exposure to the field of signal compression came in the fall of
`
`1989, when I took a course entitled Vector Quantization and Signal Compression
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`4
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`at UCSB from Prof. Allen Gersho—an internationally renowned researcher in the
`
`area of speech compression. As my Ph.D. research progressed, I began to focus on
`
`transform-based compression as my main application area. My first paper dealing
`
`with image compression was published in 1991. I have since written 24 other
`
`journal and conference papers directly related to compression, and I am the named
`
`inventor on two issued United States patents related to compression.
`
`12. Since joining the faculty of New Mexico State University in 2000, I
`
`have taught numerous classes at both the graduate and undergraduate levels. At
`
`the graduate level, I have taught the following: Image Processing (EE596), Digital
`
`Signal Processing (EE545), Signal Compression (EE573), Pattern Recognition
`
`(EE565), Advanced Linear Systems (EE555), Telemetering Systems (EE585),
`
`Information Theory (EE586), Adaptive Signal Processing (EE594), Multirate
`
`Signal Processing and Wavelets (EE595), and Neural Signal Processing (EE590).
`
`At the undergraduate level, I have taught the following courses: Engineering
`
`Analysis I (EE210), Signals and Systems I (EE312), Image Processing (EE446),
`
`Introduction to Digital Signal Processing (EE395), and Digital Communications
`
`(EE497).
`
`13. From 1993 through 1999, I was a Researcher and Team Leader, at the
`
`Naval Air Warfare Center, China Lake. At China Lake, my research efforts
`
`focused on high speed image and video compression technologies including
`
`5
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`Exhibit 1019
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`embedded compression. I also developed improved encoders that enable the most
`
`critical data in images to be transmitted more efficiently over TCP/IP networks
`
`while retaining the highest possible fidelity.
`
`14. From 1990 through 1993, I worked as a Research Assistant in the
`
`Department of Electrical and Computer Engineering at the University of
`
`California, Santa Barbara. In this position, I worked on subband coding
`
`(compression) and multirate filter bank theory. I also implemented real-time filter
`
`banks on a digital signal processer. In the summer of 1992, I worked at AT&T
`
`Bell labs where I developed and simulated new methods of extremely low bit rate
`
`video coding for video telephone applications.
`
`15. From 1985 through 1989, I worked as a Design Engineer at the Naval
`
`Weapons Center, China Lake. In this role, I built and tested the guidance
`
`electronics for various laser guided munitions. This project included mixed analog
`
`and digital circuit design as well as the programming of an embedded digital signal
`
`processor. I also developed software for an advanced video processor and studied
`
`ground target tracking.
`
`16. A list of the cases (including trials before the Patent Trial and Appeal
`
`Board) in which I have testified within the last four years is found in my CV,
`
`which is Exhibit 1003.
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`6
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`Exhibit 1019
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`1003.
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`Patents and Publications
`C.
`17. A listing of my publications is found in my curriculum vitae. See Ex.
`
`18.
`
`I have published numerous peer-reviewed journal articles and
`
`conference papers, including 9 journal articles and 30 conference papers directly
`
`related to data compression; the following are representative:
`
`• C.D. Creusere, “A new method of robust image compression based on the
`
`embedded zerotree wavelet algorithm,” IEEE Trans. on Image Processing,
`
`Vol 6, No. 10, Oct. 1997, pp. 1436-1442.
`
`• C.D. Creusere, “Fast embedded compression for video,” IEEE Trans. on
`
`Image Processing, Vol. 8, No. 12, pp. 1811-16, December 1999.
`
`• S. Kandadai and C.D. Creusere, “Scalable Audio Compression at Low
`
`Bitrates,” Audio, Speech, and Language Processing, IEEE Transactions on
`
`[see also Speech and Audio Processing, IEEE Transactions on] , vol.16,
`
`no.5, pp.969-979, July 2008.
`
`19.
`
`I am a named co-inventor on two issued patents, both relating
`
`specifically to data compression. I am the listed inventor on U.S. Patent No.
`
`6,148,111 entitled “Parallel digital image compression system which exploits
`
`7
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`Exhibit 1019
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`zerotree redundancies in wavelet coefficients” and U.S. Patent No. 6,466,698
`
`entitled “Efficient embedded image and video compression using lifted wavelets.”
`
`D. Other Relevant Qualifications
`20.
`In addition to the experience and publications listed above, I have also
`
`received the following awards and distinctions that are relevant to the subject
`
`matter of this declaration. I am currently a Senior Area Editor for IEEE
`
`Transactions on Image Processing and have previously served as an Associate
`
`Editor for IEEE Transactions on Image Processing from 2010 through 2014. I
`
`have also served in this capacity from 2002 through 2005. From 2008-2013, I
`
`served as an Associate Editor for IEEE Transactions on Multimedia.
`
`21.
`
`In 2004, I served as the co-general chair for the IEEE Digital Signal
`
`Processing Workshop in Taos, New Mexico. In 2012 and 2014, I served as the co-
`
`technical chair for the Southwest Symposium on Image Analysis and Interpretation
`
`held in Santa Fe, New Mexico and San Diego, CA, respectively. In addition, I
`
`served as the technical chair for the 2015 International Telemetering Conference
`
`held in Las Vegas, NV in October. I am also a member of the technical program
`
`committees for the IEEE International Conference on Image Processing and the
`
`IEEE Data Compression Conference.
`
`8
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`Exhibit 1019
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`E. Materials Considered
`22.
`I have reviewed the materials listed on the Exhibit List at the front of
`
`this declaration. I have also reviewed and considered the ’530 patent’s file history,
`
`as well as the file histories for U.S. Patent Application No. 10/628,795 (now Patent
`
`No. 7,130,913) and U.S. Patent Application No. 09/266,394 (now Patent No.
`
`6,601,104) since the ’530 patent claims entitlement to the filing dates of these
`
`earlier applications. I have further relied on my knowledge, education, and
`
`experience in rendering my opinions.
`
`IV. LEVEL OF ORDINARY SKILL IN THE ART
`23.
`I have been informed and understand that certain issues like claim
`
`interpretation and obviousness are viewed from the perspective of “a person of
`
`ordinary skill in the art” in question at the time of the alleged invention. I have
`
`been asked to assume, for the purpose of this Petition, that the time-frame of the
`
`alleged invention is March 11, 1999. I may change my opinions if this assumption
`
`does not hold true.
`
`24. The ’530 patent describes the field as “data storage and retrieval, and
`
`more particularly . . . systems and methods for improving data storage and retrieval
`
`bandwidth utilizing lossless data compression and decompression.” Ex. 1001 at
`
`1:15-18. Looking at claim 1, the field of the invention includes compressing a data
`
`9
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`Exhibit 1019
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`stream utilizing at least one of several compression techniques for each data block
`
`in the data stream. See, e.g., Ex. 1001 at 18:24-42.
`
`25. The ’530 patent summary describes using data compression in
`
`“systems and methods for providing accelerated data storage and retrieval . . . .”
`
`Ex. 1001 at 2:58-64 (Summary). The ’530 patent says that the invention “provides
`
`an effective increase of the data storage and retrieval bandwidth of a memory
`
`storage device.” Id.
`
`26. Based on my education and experience, I am familiar with the level of
`
`knowledge that a person of ordinary skill would have possessed in early 1999,
`
`including on March 11, 1999. In my opinion, a person of “ordinary skill in the art”
`
`would have had at least a bachelor’s degree in computer science, computer
`
`engineering, electrical and computer engineering, electrical engineering, or
`
`electronics and at least two years of experience working with data compression or
`
`a graduate degree focusing in the field of data compression. Such experience
`
`would have led to familiarity with data compression systems using multiple data
`
`compression and decompression techniques to increase data storage and retrieval
`
`bandwidth. As such, individuals with additional education or additional industrial
`
`experience could still be of ordinary skill in the art if that additional aspect
`
`compensates for a deficit in one of the other aspects of the requirements stated
`
`above.
`
`10
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`Veritas Techs. LLC
`Exhibit 1019
`Page 018
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`27.
`
`In reaching this opinion as to the qualifications of the hypothetical
`
`person of ordinary skill in the art, I have considered the types of problems
`
`encountered in the art including determining whether compressing data is worth
`
`the “cost” of doing so, the prior art solutions to those problems including those
`
`found in the materials I discuss below in further detail, the rapidity with which
`
`innovations are made including the fact that data compression is a mature art
`
`whose continued growth has been spurred, at least in part by increases in processor
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`speeds and memory capacities with corresponding decreases in their costs, the
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`sophistication of the technology, and the educational level of active developers,
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`engineers, and workers in the field. In addition, I have taken into account my own
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`personal experience as a developer, a scientist, an engineer, and an educator
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`teaching relevant subject matter, as well as my experience working with persons of
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`ordinary skill in the art.
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`28. By March 1999, I had more than ordinary skill in the art. For the
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`purposes of my work in conducting my analysis of the issues in this proceeding, I
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`have considered the knowledge that would have been available to a person of
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`ordinary skill in the art as of March 1999, and I have conducted my analysis from
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`that perspective.
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`V. BACKGROUND KNOWLEDGE HELD BY A PERSON OF
`ORDINARY SKILL REGARDING THE FIELD OF THE ’530
`PATENT
`29. The ’530 patent relates to the compression and decompression of data
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`as generally used in data storage systems. The ’530 patent describes techniques
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`intended to speed up the rate at which data can be stored. See Ex. 1001 at 1:15-18,
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`2:58-62, 4:42-61, 18:24-42.
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`30. The field of data compression came about in the 1940s with Claude
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`Shannon’s work at Bell Laboratories on information theory. See Ex. 1012 at 15-16.
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`By 1999, data compression was a well-established and well-documented field.
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`Those working in the field at that time were aware of a variety of problems
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`associated with the use of data compression systems.
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`31. By 1999, numerous solutions and proposed optimizations had been
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`propagated through the field. For example, as early as 1952, a technique called
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`“Huffman coding” was first described and began to gain popularity, Ex. 1012 at
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`18. In 1977 and 1978, Lempel and Ziv published papers describing the “Lempel-
`
`Ziv” compression scheme, see Ex. 1004 at 2:22-30, Ex. 1012 at 23-24, a popular
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`variant on dictionary based compression. Both are also described in the ’530
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`patent. See Ex. 1001 at 19:7-8, 7:28-32. Over time, several variations of the
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`Lempel-Ziv compression scheme were publicized. For example, in 1984, Terry
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`Welch released his paper on his Lempel-Ziv method, referred to now as LZW. Ex.
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`1012 at 226.
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`32. Regardless of the specific compression technique used, compression
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`began to emerge as a popular way to enhance data storage. Specifically,
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`compressing data prior to its storage may effectively increase the storage capacity
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`of the storage device. This is described in both the Franaszek patent and the
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`Nelson book, see Ex. 1004 at 4:14-17 (Compression can “increase the number of
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`data blocks that can be stored in” memory); Ex. 1012 at 223 (Data compression
`
`“reduces the use of magnetic tape.”). Those working in the field knew that
`
`compressing data results in less data. More specifically, when data is compressed,
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`the resulting data is smaller (contains fewer bits than the original data). See id. at
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`219. This is accomplished by finding various ways to encode redundant data using
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`a less data-intensive code. This may be understood by using abbreviations as a
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`rudimentary example. For example, rather than saying “United States Patent
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`Number 7,415,530,” I may “compress” the data such that it is referred to as “the
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`’530 patent,” or even further as “the ’530 pat.” If taken to an extreme, this
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`compression process can reduce the data to the point where it is no longer able to
`
`identify the original set of information, such as if I were to encode “United States
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`Patent Number 7,415,530” as “5.” The compressed representation of “5” may be
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`insufficient to identify the original string, depending on context. While this is a
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`simplified example of how data compression may work, the concept is what is
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`important: data compression takes data representing information and reduces it to
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`some smaller set of data. The example above is simply intended to make the
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`concept more relatable.
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`33. Not only does compressing data reduce the amount of data to be
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`stored, but it can also reduce the time it takes to store and retrieve the data.
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`Because compressed data results in fewer bits to convey the same information, the
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`information can be transmitted to memory and written and read more quickly.
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`More specifically, when there is less data to transmit, store, and read, the overall
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`process can take less time because transmitting, storing, or reading fewer bits of
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`compressed data takes less time than transmitting the original number of bits. This
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`is taught by Osterlund and Nelson. See Ex. 1005 at Abst., 1:16-20, 5:20-29; Ex.
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`1012 at 223 (“[T]he effective transfer rate to and from the tape is increased,” and
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`that software compression is “in a sense ‘free.’”). Data compression was also well
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`known for enhancing or speeding up the transmission of data in communications
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`systems. See Ex. 1013 at 1 (data compressor is used in both “[h]igh-speed data
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`communications systems” and “[d]irect-access storage devices”); Ex. 1008 at 1:7-
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`10 (“Data compression systems improve the performance of communication or
`
`storage systems . . . .”). Data compression is applicable to both storage and
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`communications systems because data compression reduces the size of the data,
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`thus often making the operation of the chosen system more efficient. See Ex. 1008
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`at 1:7-10 (compression can “improve the performance of communication or
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`storage systems”). A person working on data compression techniques would have
`
`been aware that the techniques were applicable to both data storage and data
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`transmission systems.
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`34. Those in the field spent decades prior to the filing of the parent to the
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`’530 patent identifying and solving problems related to data compression. In
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`particular, one concern was often whether the benefits of compressing the data
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`wer