UNITED STATES PATENT AND TRADEMARK OFFICE
`_______________
`BEFORE THE PATENT TRIAL AND APPEAL BOARD
`_____________
`
`SPLUNK INC.
`Petitioner,
`v.
`SABLE NETWORKS, INC.
`Patent Owner.
`
`Patent No. 8,243,593
`_______________
`
`Inter Partes Review No. IPR2022-00228
`____________________________________________________________
`PETITION FOR INTER PARTES REVIEW
`
`UNDER 35 U.S.C. §§ 311-319 AND 37 C.F.R. § 42.100 et seq.
`
`

`

`Inter Partes Review of USP 8,243,593
`
`TABLE OF CONTENTS
`
`Page
`
`V.
`
`B.
`
`C.
`
`D.
`
`INTRODUCTION .......................................................................................... 1
`I.
`II. GROUNDS FOR STANDING ....................................................................... 2
`III. TECHNICAL BACKGROUND .................................................................... 2
`IV. THE CHALLENGED PATENT .................................................................... 7
`A. Overview of the ’593 Patent ................................................................. 7
`B.
`Prosecution History .............................................................................. 9
`Person of Ordinary Skill in the Art .................................................... 11
`C.
`CLAIM CONSTRUCTION ......................................................................... 11
`A.
`“means for maintaining a set of behavioral statistics for the
`flow…” (claims 25 and 29) ................................................................ 12
`“means for determining…whether the flow is exhibiting
`undesirable behavior” (claim 25) ....................................................... 12
`“means for enforcing…[a/the] penalty on the flow” (claims 25
`and 32) ................................................................................................ 12
`“means for computing…a badness factor for the flow” (claim
`29) ....................................................................................................... 13
`“means for determining…a penalty to impose on the flow”
`(claim 31) ........................................................................................... 13
`“means for determining an increased drop rate to impose on one
`or more information packets belonging to the flow” (claim 37) ....... 13
`“means for imposing [an/the] increased drop rate on the flow”
`(claims 27 and 38) .............................................................................. 14
`“means for receiving a particular information packet belonging
`to the flow” (claims 43 and 44) .......................................................... 14
`“means for determining whether to forward the particular
`information packet to a destination” (claim 43) ................................. 14
`
`E.
`
`F.
`
`G.
`
`H.
`
`I.
`
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`Inter Partes Review of USP 8,243,593
`TABLE OF CONTENTS
`(continued)
`
`Page
`
`J.
`
`“means for updating […] the set of behavioral statistics to
`reflect processing of the particular information packet” (claims
`43 and 44) ........................................................................................... 15
`VI. OVERVIEW OF THE PRIOR ART ............................................................ 15
`VII. GROUNDS OF UNPATENTABILITY ....................................................... 17
`A.
`Ground 1: Claims 1, 2, 4-7, 17, 18, 25-27, 37, and 38 Are
`Obvious Over Yung ........................................................................... 17
`1.
`Overview: Yung Discloses a System for Classifying and
`Controlling Flows Using Behavioral Statistics ........................ 17
`Independent Claim 1 ................................................................ 19
`a.
`Yung Discloses the Preamble of Claim 1 ...................... 19
`b.
`Yung Discloses the “Creating” Limitation .................... 21
`c.
`Yung Stores Payload-Content-Agnostic Behavioral
`Statistics Regardless of the Presence or Absence of
`Congestion ..................................................................... 25
`Yung Discloses the “Updating” Limitation ................... 27
`Yung Discloses the “Determining” Limitation ............. 29
`Yung Discloses the “Enforcing” Limitation ................. 32
`Yung Discloses Performing the Steps on a Router
`Without Requiring Use of Inter-Router Data ................ 33
`Independent Claim 2 ................................................................ 35
`a.
`Yung Discloses the Preamble of Claim 2 ...................... 35
`b.
`Yung Discloses the Limitations of Claim 2 .................. 36
`Independent Claims 4 and 5 ..................................................... 37
`Independent Claim 25 .............................................................. 38
`a.
`Yung Discloses the Preamble of Claim 25 .................... 38
`b.
`Yung Discloses the “Means for Maintaining”
`Limitation ...................................................................... 38
`
`2.
`
`d.
`e.
`f.
`g.
`
`3.
`
`4.
`5.
`
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`Inter Partes Review of USP 8,243,593
`TABLE OF CONTENTS
`(continued)
`
`Page
`
`c.
`
`d.
`
`c.
`
`Yung Discloses the “Means for Determining”
`Limitation ...................................................................... 39
`Yung Discloses the “Means for Enforcing”
`Limitation. ..................................................................... 40
`Dependent Claims 6 and 26 ..................................................... 40
`6.
`Dependent Claims 7 and 27 ..................................................... 41
`7.
`Dependent Claims 17 and 37 ................................................... 41
`8.
`Dependent Claims 18 and 38 ................................................... 42
`9.
`Ground 2: Claims 9-13, 19-24, 29-33, and 39-44 Are Obvious
`Over Yung and Copeland ................................................................... 42
`1.
`Overview: Yung Discloses a System for Classifying and
`Controlling Flows Using Behavioral Statistics, and
`Copeland Calculates a Flow-Based Concern Index ................. 42
`2. Motivation to Combine ............................................................ 45
`3.
`Independent Claim 9 ................................................................ 47
`a.
`Yung Discloses the Preamble of Claim 9 ...................... 47
`Yung Discloses the “Maintaining” Limitation .............. 47
`b.
`c.
`Yung in View of Copeland Discloses the
`“Computing” Limitation ................................................ 48
`Independent Claim 29 .............................................................. 50
`Yung Discloses the Preamble of Claim 29 .................... 50
`a.
`b.
`Yung Discloses the “Means for Maintaining”
`Limitation ...................................................................... 50
`Yung Discloses the “Means for Computing”
`Limitation ...................................................................... 51
`Dependent Claims 10 and 30 ................................................... 51
`Dependent Claims 11 and 31 ................................................... 52
`Dependent Claims 12 and 32 ................................................... 52
`Dependent Claims 13 and 33 ................................................... 53
`
`B.
`
`4.
`
`5.
`6.
`7.
`8.
`
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`Inter Partes Review of USP 8,243,593
`TABLE OF CONTENTS
`(continued)
`
`Page
`
`Dependent Claims 19 and 39 ................................................... 53
`9.
`10. Dependent Claims 20 and 40 ................................................... 54
`11. Dependent Claims 21 and 41 ................................................... 54
`12. Dependent Claims 22 and 42 ................................................... 55
`13. Dependent Claims 23 and 43 ................................................... 56
`14. Dependent Claims 24 and 44 ................................................... 57
`Ground 3: Claim 3 Is Obvious Over Yung and Four-Steps
`Whitepaper ......................................................................................... 59
`1.
`Overview: Yung Discloses a System for Classifying and
`Controlling Flows Using Behavioral Statistics, and Four-
`Steps Whitepaper Discloses Tracking Dropped Packets ......... 59
`2. Motivation to Combine ............................................................ 59
`3.
`Independent Claim 3 ................................................................ 61
`a.
`Yung Discloses the Preamble of Claim 3 ...................... 61
`b.
`Yung Discloses a Medium Storing a Data
`Structure ......................................................................... 62
`Yung Discloses the “First Field” ................................... 63
`Yung in View of Four-Steps Whitepaper Discloses
`the “Second Field” ......................................................... 63
`Yung Discloses the “Third Field” ................................. 64
`e.
`Yung Discloses the “Fourth Field” ................................ 65
`f.
`Yung Discloses the “Fifth Field” .................................. 65
`g.
`Ground 4: Claims 8, 14-16, 28, and 34-36 Are Obvious Over
`Yung and Copeland in View of Ye .................................................... 66
`Overview: Yung-Copeland Discloses a System for
`1.
`Classifying Flows Using Behavioral Statistics, and Ye
`Describes a Congestion Condition ........................................... 66
`2. Motivation to Combine ............................................................ 67
`3.
`Dependent Claims 8, 14, 28, and 34 ........................................ 69
`
`c.
`d.
`
`C.
`
`D.
`
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`

`Inter Partes Review of USP 8,243,593
`TABLE OF CONTENTS
`(continued)
`
`Page
`
`Dependent Claims 15 and 35 ................................................... 71
`4.
`Dependent Claims 16 and 36 ................................................... 72
`5.
`VIII. DISCRETIONARY DENIAL WOULD BE INAPPROPRIATE AND
`INEQUITABLE ............................................................................................ 72
`IX. GROUNDS FOR STANDING (37 C.F.R. § 42.104(a)) .............................. 76
`X. NOTICES AND STATEMENTS ................................................................. 76
`XI. CONCLUSION ............................................................................................. 78
`
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`

`Inter Partes Review of USP 8,243,593
`
`TABLE OF AUTHORITIES
`
` Page(s)
`
`Cases
`Apple Inc. v. Fintiv, Inc.,
`IPR2020-00019, Paper 11 (PTAB Mar. 20, 2020) ....................................... 72, 75
`Apple Inc. v. Parus Holdings, Inc.,
`IPR2020-00686, Paper 9 (PTAB Sept. 23, 2020) ............................................... 73
`Cisco Sys., Inc. v. Ramot at Tel Aviv Univ. Ltd.,
`IPR2020-00122, Paper 15 (P.T.A.B. May 15, 2020) ......................................... 75
`Cloudflare Inc. v. Sable Networks, Inc.,
`IPR2021-00909, Paper 16 (P.T.A.B. Nov. 19, 2021) ................................... 75, 76
`Ericsson v. Uniloc,
`IPR2020-00376, Paper 16 (P.T.A.B. May 22, 2020) ........................................... 1
`Phillips v. AWH Corp.,
`415 F.3d 1303 (Fed. Cir. 2015) (en banc) .................................................... 11, 12
`Sable Networks, Inc. v. Splunk Inc.,
`No. 5:21-cv-00040-RWS, Dkt. No. 65 (E.D. Tex. Sept. 21, 2021) ................... 73
`Sable Networks, Inc. v. Splunk Inc.,
`No. 5:21-cv-00040-RWS, Dkt. No. 77 (E.D. Tex. Nov. 1, 2021) ...................... 73
`Sand Revolution II, LLC v. Cont’l Intermodal Grp. – Trucking LLC,
`IPR2019-01393, Paper 24 (PTAB June 16, 2020) ....................................... 73, 74
`Sotera Wireless, Inc. v. Masimo Corp.,
`IPR2020-01019, Paper 12 (P.T.A.B. Dec. 1, 2020) ........................................... 74
`Williamson v. Citrix Online, LLC,
`792 F.3d 1339 (Fed. Cir. 2015) .......................................................................... 11
`Statutes
`35 U.S.C. § 102(a) ................................................................................................... 15
`35 U.S.C. § 102 (b) .................................................................................................. 15
`
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`Inter Partes Review of USP 8,243,593
`
`35 U.S.C. § 102 (e) ............................................................................................ 15, 17
`35 U.S.C. § 112(6) ................................................................................................... 11
`35 U.S.C. § 314 ........................................................................................................ 72
`35 U.S.C. § 315(b) ................................................................................................... 76
`Other Authorities
`37 C.F.R. § 42.8(b)(1) .............................................................................................. 76
`37 C.F.R. § 42.8(b)(2) .............................................................................................. 77
`37 C.F.R. § 42.8(b)(3) .............................................................................................. 77
`37 C.F.R. § 42.8(b)(4) .............................................................................................. 77
`37 C.F.R. § 42.15(a) ................................................................................................. 78
`37 C.F.R. § 42.100(b) .............................................................................................. 11
`37 C.F.R. § 42.104(a) ............................................................................................... 76
`157 Cong. Rec. S5429 (daily ed. Sept. 8, 2011). ..................................................... 76
`
`sf-4592262
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`

`

`Inter Partes Review of USP 8,243,593
`
`EXHIBIT LIST
`
`Exhibit Description
`
`U.S. Patent No. 8,243,593 (the “’593 Patent”)
`
`Prosecution history of U.S. Application No. 11/022,599, which led
`to the issuance of the ’593 Patent (“File History”)
`
`Declaration of Kevin Jeffay, Ph.D. in Support of Petition for Inter
`Partes Review of U.S. Patent No. 8,243,593
`
`Curriculum Vitae of Kevin Jeffay
`
`U.S. Patent No. 7,664,048 (“Yung”)
`
`“Four Steps to Application Performance Across the Network with
`Packeteer’s PacketShaper®,” archived by web.archive.org on
`March 17, 2003, with Affidavit of Elizabeth Rosenberg attached
`(“Four-Steps Whitepaper”)
`
`U.S. Patent No. 7,185,368 (“Copeland”)
`
`U.S. Patent No. 7,295,516 (“Ye”)
`
`U.S. Patent Publication No. 2004/0090923 (“Kan”)
`
`Gerber, A., et al., “P2P, the Gorilla in the Cable,” Proceedings of
`National Cable & Telecommunications Association, NCTA, 2003
`(“Gerber”)
`
`U.S. Patent No. 7,225,271 (“DiBiasio”)
`
`U.S. Patent No. 7,561,515 (“Ross”)
`
`Ben-Nun, M., “Taming the Peer to Peer Monster Using Service
`Control,” Fall Technical Forum (2003) (“Ben-Nun”)
`
`U.S. Patent No. 6,839,321 (“Chiruvolu”)
`
`U.S. Patent No. 7,088,678 (“Freed”)
`
`sf-4592262
`
`viii
`
`Exhibit #
`
`EX-1001
`
`EX-1002
`
`EX-1003
`
`EX-1004
`
`EX-1005
`
`EX-1006
`
`EX-1007
`
`EX-1008
`
`EX-1009
`
`EX-1010
`
`EX-1011
`
`EX-1012
`
`EX-1013
`
`EX-1014
`
`EX-1015
`
`

`

`Inter Partes Review of USP 8,243,593
`
`Exhibit Description
`
`“NetEnforcerTM, QoS/SLA Enforcement for Service Providers,”
`Allot Communications (2001)
`
`“PacketShaper® Features for PacketWise 5.2,” Packeteer, Inc.
`
`U.S. Patent No. 7,366,101 (“Varier”)
`
`Andrikopoulos, I., Pavlou, G., “Supporting Differentiated Services
`in MPLS Networks,” 1999 Seventh International Workshop on
`Quality of Service, including Declaration from Rachel J. Watters,
`Librarian and Director of Wisconsin TechSearch (“Andrikopoulos”)
`
`U.S. Patent No. 7,385,924 (“Riddle-924”)
`
`U.S. Patent No. 7,660,248 (“Duffield”)
`
`Sen, S., et al., “Accurate, Scalable In-Network Identification of P2P
`Traffic Using Application Signatures,” Proceedings of the 13th
`International Conference on World Wide Web (2004) (“Sen”)
`
`U.S. Patent No. 7,313,100 (“Turner”)
`
`U.S. Patent Publication No. 2002/0186661 (“Santiago”)
`
`U.S. Patent Publication No. 2003/0118029 (“Maher”)
`
`U.S. Patent No. 7,296,288 (“Hill”)
`
`U.S. Patent No. 6,904,529 (“Swander”)
`
`U.S. Patent No. 6,385,170 (“Chiu”)
`
`U.S. Patent No. 6,934,256 (“Jacobson”)
`
`U.S. Patent No. 7,342,929 (“Bremler-Barr”)
`
`PacketShaper® System Datasheet
`
`sf-4592262
`
`ix
`
`Exhibit #
`
`EX-1016
`
`EX-1017
`
`EX-1018
`
`EX-1019
`
`EX-1020
`
`EX-1021
`
`EX-1022
`
`EX-1023
`
`EX-1024
`
`EX-1025
`
`EX-1026
`
`EX-1027
`
`EX-1028
`
`EX-1029
`
`EX-1030
`
`EX-1031
`
`

`

`Inter Partes Review of USP 8,243,593
`
`Exhibit Description
`
`Boniforti, C., “Securing a University’s Bandwidth with
`PacketShaper,” SANS Institute (2003) (“Boniforti”)
`
`Braden, R., Postel, J., “RFC 1009 – Requirements for Internet
`Gateways” (1987) (“Braden”)
`
`Roughan, M., et al., “Class-of-Service Mapping for QoS: A
`Statistical Signature-based Approach to IP Traffic Classification,”
`Proceedings of the 4th ACM SIGCOMM Conference on Internet
`Measurement (2004) (“Roughan”)
`
`U.S. Patent No. 7,027,393 (“Cheriton”)
`
`U.S. Patent No. 7,433,304 (“Galloway”)
`
`U.S. Patent No. 6,115,357 (“Packer”)
`
`Exhibit #
`
`EX-1032
`
`EX-1033
`
`EX-1034
`
`EX-1035
`
`EX-1036
`
`EX-1037
`
`Szigeti, T., “QoS Best Practices,” Cisco Systems (2004) (“Szigeti”)
`
`EX-1038
`
`U.S. Patent No. 6,412,000 (“Riddle-000”)
`
`Long L., et al., “Differential Congestion Notification: Taming the
`Elephants,” Proceedings of the 12th IEEE International Conference
`on Network Protocols (Oct. 2004) (“Long”)
`
`Parris M., et al., “Lightweight Active Router-Queue Management
`for Multimedia Networking,” Multimedia Computing and
`Networking” (Jan. 1999) (“Parris”)
`
`U.S. Patent Publication No. 2002/0023168 (“Bass”)
`
`U.S. Application Publication No. 2002/0097719 (“Chaskar”)
`
`Bernaille, L., et al, “Traffic Classification on the Fly,” ACM
`SIGCOMM Computer Communication Review (2006) (“Bernaille”)
`
`U.S. Patent No. 7,782,793 (“Olesinski”)
`
`U.S. Patent No. 8,693,348 (“Wei”)
`
`sf-4592262
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`x
`
`EX-1039
`
`EX-1040
`
`EX-1041
`
`EX-1042
`
`EX-1043
`
`EX-1044
`
`EX-1045
`
`EX-1046
`
`

`

`Inter Partes Review of USP 8,243,593
`
`Exhibit Description
`
`Karagiannis, T., et al, “Transport Layer Identification of P2P
`Traffic,” IMC 04: Proceedings of the 4th ACM SIGCOMM
`conference on Internet measurement, October 2004 (“Karagiannis”)
`
`Supplemental Order Regarding Court Operations Under the Exigent
`Circumstances Created by the COVID-19 Pandemic, United States
`District Court for the Western District of Texas dated May 8, 2020
`
`Supplemental Order Regarding Court Operations Under the Exigent
`Circumstances Created by the COVID-19 Pandemic, United States
`District Court for the Western District of Texas dated June 18, 2020
`
`Supplemental Order Regarding Court Operations Under the Exigent
`Circumstances Created by the COVID-19 Pandemic, United States
`District Court for the Western District of Texas dated July 2, 2020
`
`Seventh Supplemental Order Regarding Court Operations Under the
`Exigent Circumstances Created by the COVID-19 Pandemic, United
`States District Court for the Western District of Texas dated
`August 6, 2020
`
`Eighth Supplemental Order Regarding Court Operations Under the
`Exigent Circumstances Created by the COVID-19 Pandemic, United
`States District Court for the Western District of Texas dated
`September 21, 2020
`
`Ninth Supplemental Order Regarding Court Operations Under the
`Exigent Circumstances Created by the COVID-19 Pandemic, United
`States District Court for the Western District of Texas dated October
`14, 2020
`
`Tenth Supplemental Order Regarding Court Operations Under the
`Exigent Circumstances Created by the COVID-19 Pandemic, United
`States District Court for the Western District of Texas dated
`November 18, 2020
`
`Exhibit #
`
`EX-1047
`
`EX-1048
`
`EX-1049
`
`EX-1050
`
`EX-1051
`
`EX-1052
`
`EX-1053
`
`EX-1054
`
`sf-4592262
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`Inter Partes Review of USP 8,243,593
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`Exhibit Description
`
`Eleventh Supplemental Order Regarding Court Operations Under
`the Exigent Circumstances Created by the COVID-19 Pandemic,
`United States District Court for the Western District of Texas dated
`December 10, 2020
`
`Twelfth Supplemental Order Regarding Court Operations Under the
`Exigent Circumstances Created by the COVID-19 Pandemic, United
`States District Court for the Western District of Texas dated
`January 7, 2021
`
`Thirteenth Supplemental Order Regarding Court Operations Under
`the Exigent Circumstances Created by the COVID-19 Pandemic,
`United States District Court for the Western District of Texas dated
`February 2, 2021
`
`Fourteenth Supplemental Order Regarding Court Operations Under
`the Exigent Circumstances Created by the COVID-19 Pandemic,
`United States District Court for the Western District of Texas dated
`March 17, 2021
`
`Exhibit #
`
`EX-1055
`
`EX-1056
`
`EX-1057
`
`EX-1058
`
`U.S. Patent No. 6,038,216 (“Packer-216”)
`
`EX-1059
`
`
`
`sf-4592262
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`Inter Partes Review of USP 8,243,593
`
`I.
`
`INTRODUCTION
`Petitioner Splunk Inc. petitions for inter partes review of claims 1-44
`
`(“challenged claims”) of U.S. Patent No. 8,243,593 (“the ’593 Patent” (EX1001)).1
`
`The challenged claims are directed to identifying and controlling network traffic
`
`using behavioral statistics of packets in the flows, which was known in the art as
`
`evidenced by this petition and the supporting declaration of Kevin Jeffay, Ph.D.
`
`(EX1003). The challenged claims are unpatentable as obvious based on the
`
`following grounds:
`
`Ground
`
`Claim(s)
`
`Prior Art
`
`1
`
`2
`
`1, 2, 4-7, 17, 18, 25-27, 37, 38 Yung (EX1005)
`
`9-13, 19-24, 29-33, 39-44
`
`Yung and Copeland (EX1007)
`
`1 Petitioner is concurrently filing a Motion for Joinder (Paper 3) to the petition
`
`in Cloudflare Inc. v. Sable Networks, Inc., IPR2021-00909, Paper 1 (P.T.A.B. May
`
`7, 2021), along with this “me-too” or “copycat” petition. Ericsson v. Uniloc,
`
`IPR2020-00376, Paper 16 at 13 (P.T.A.B. May 22, 2020) (granting motion for
`
`joinder where “me-too” petition was “substantively identical” to the instituted
`
`petition because “[i]t is not unexpected, given Petitioner’s ‘understudy role’ and
`
`the joinder nature of the Petition, that the first filed petition serves as a roadmap for
`
`the joinder petition.”).
`
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`Inter Partes Review of USP 8,243,593
`
`Ground
`
`Claim(s)
`
`Prior Art
`
`3
`
`4
`
`3
`
`Yung and Four-Steps Whitepaper
`(EX1006)
`
`8, 14-16, 28, 34-36
`
`Yung, Copeland, and Ye (EX1008)
`
`II. GROUNDS FOR STANDING
`Petitioner certifies that the ’593 Patent is available for inter partes review
`
`and that Petitioner is not barred or estopped from requesting review.
`
`III. TECHNICAL BACKGROUND
`By the early 2000s, the ever-increasing popularity of online applications and
`
`services brought significantly increased network traffic on the Internet and other
`
`computer networks. The Internet provided an “exploding amount of remote
`
`information” to users worldwide and enabled a variety of new applications (e.g.,
`
`e-mail, e-commerce, file-transfer, remote database access, etc.) that added load to
`
`existing networks already strained by increasing levels of network traffic.
`
`(EX1042, [0019]-[0020].) The problem of quickly-growing demand for the
`
`limited existing bandwidth was exacerbated by the widespread emergence of
`
`peer-to-peer (P2P) applications (EX1010, 1-2; EX1013, 1-2), growing use of
`
`voice-over-IP (VOIP) systems (EX1011, 1:62-2:21), and increase in
`
`denial-of-service attacks against network infrastructures (EX1012, 1:12-18). (See
`
`also EX1003, ¶¶32-37.)
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`Inter Partes Review of USP 8,243,593
`
`Because existing networks had finite capacity for ever-increasing network
`
`traffic, it became necessary to monitor network performance and to employ
`
`corrective measures when performance fell. (EX1009, [0004].) Various
`
`techniques were developed to identify network traffic and handle it appropriately
`
`in an effort to efficiently allocate existing bandwidth. (EX1021, 2:43-3:6;
`
`EX1003, ¶¶38-40.) For example, a network administrator might prioritize database
`
`transactions over external web-browsing or ensure low latency for interactive
`
`applications and high throughput for file downloads. (EX1021, 1:9-29.)
`
`One way to understand network traffic was to identify (i.e., classify)
`
`network “flows.” The concept of a flow would have been well-known to a person
`
`of ordinary skill in the art. (EX1003, ¶40.) A flow is essentially a sequence of
`
`related packets; for example, packets sent from the same application or packets
`
`sent on the same network connection. (Id.; see also EX1001, 5:15-19 (describing a
`
`flow as “a series of packets that are related in some manner” and stating that
`
`“packets are grouped into a flow if they share a sufficient amount of header
`
`information”).) Network elements, such as routers, track network flows using flow
`
`tables to record the existence of the flow and to capture information about it.
`
`(EX1043, [0002]-[0006], [0013].)
`
`By 2004, when the ’593 Patent was filed, various prior art approaches had
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`been developed for classifying flows. Given a flow classification, an administrator
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`could apply rules to take action on the packets of the flow to adhere to desired
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`policies (e.g., priority, security, rate control, etc.). (EX1003, ¶45.) For example,
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`network congestion and delays could be addressed by “shaping” network traffic,
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`which could include dropping packets or using other quality of service (“QoS”)
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`measures (e.g., prioritizing certain flows, re-routing flows, etc.). (EX1014, 1:6-32;
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`EX1029, 2:21-40.)
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`Industry participants offered various products (i.e., network appliances)
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`providing traffic management capabilities. (EX1003, ¶¶41-43; EX1016; EX1017.)
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`For example, Packeteer, Inc. was an industry leader and offered a network
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`appliance called PacketShaper® that allowed network administrators to “control
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`traffic to ensure that latency-sensitive, customer-critical applications get the
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`bandwidth they need to perform at their peak.” (EX1031, 3; see also id., 1
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`(“Seventy-four percent of the world’s largest companies rely on Packeteer®
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`innovation to solve their WAN application performance problems.”); EX1032
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`(“Securing a University’s Bandwidth with PacketShaper”).) For reasons of trust
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`and scalability of administration and management, however, traffic management
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`functionality was typically implemented in network routers. (EX1021, 3:19-24;
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`see also EX1029, 2:21-40; EX1020, 16:37-40; EX1023, 2:41-54; EX1015, 1:58-
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`2:3; EX1018, Abstract; EX1028, Abstract; EX1030, 20:9-12; EX1036, 21:1-7;
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`EX1037, 5:3-6; EX1003, ¶44.)
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`Network practitioners recognized, by the early 2000s, that better
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`classification techniques (i.e., improved mechanisms for identifying the type of
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`traffic represented by particular network flows) would lead to wider adoption of
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`QoS-based traffic shaping. (EX1021, 2:31-39.) It had become particularly
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`important to accurately identify peer-to-peer traffic because it had come to
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`monopolize a large portion of available network bandwidth. (EX1022, 512; see
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`also EX1003, ¶45.)
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`Some traffic classification techniques examined packet header information,
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`such as the port number, or scanned packet payloads (i.e., data carried by the
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`packet) in an effort to identify a “signature” for a particular type of network traffic.
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`(EX1022, 512; EX1045, 1:31-42; EX1046, 1:42-50; EX1005, 4:51-55; EX1001,
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`1:19-45; EX1003, ¶46.) Because some applications, such as peer-to-peer
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`applications, sought to avoid identification through encryption, dynamic port-
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`hopping, and other means, traffic classification techniques were developed that
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`focused on the flow’s behavioral statistics and empirically observable flow data.
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`(EX1021, Abstract; EX1045, 2:51-3:30; EX1007, Abstract; EX1047, 121-122;
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`EX1034, 139-140 (§4.2); EX1005, Abstract; EX1003, ¶47.) For example, some
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`prior art techniques considered packet sizes, number of packets, inter-packet
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`arrival delay, and so forth in classifying network flows. (EX1045, 6:29-35
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`(“Beside flow durations, traffic flows can be characterized based on statistical
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`traffic flow parameters such as: average/median packet size, packet size variance,
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`root-means-square packet size, largest packet sampled so far, shortest packet
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`sampled so far, average/median inter-packet arrival delay, inter-packet arrival
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`delay variance, bytes per flow, packets per flow, etc.”); EX1021, 6:28-32, 7:18-20
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`(“A simple example is the statistics of the inter-arrival times between packets in
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`flows.”); EX1047, 134 (“We also want to consider additional heuristics that use
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`knowledge of specific packet sizes that may reflect control traffic of P2P
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`protocols.”).) These approaches did not rely on packet headers or payload
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`contents. EX1047, 121-122 (“We develop a systematic methodology for P2P
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`traffic profiling by identifying flow patterns and characteristics of P2P behavior,
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`without examination of user payload.”).) Instead, they applied heuristics to map
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`measured statistics onto established classes (e.g., P2P). (Id., 125 (“These two
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`simple heuristics efficiently classify most pairs as P2P or nonP2P.”).)
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`After classifying the flow as a particular type of traffic, network traffic
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`management devices could enforce policies on packets in the flow as appropriate.
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`(EX1025, [0008]-[0010], [0059]; EX1005, 24:27-25:8.) For instance, packets
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`could be prioritized, delayed, or dropped depending on the type of traffic and the
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`particular rules adopted by network administrators. Flow identification and
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`management of this type could be implemented in various network devices
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`including IP routers, as noted above. (EX1003, ¶48.)
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`IV. THE CHALLENGED PATENT
`A. Overview of the ’593 Patent
`The ’593 Patent is entitled “Mechanism for Identifying and Penalizing
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`Misbehaving Flows in a Network.” (EX1001.) It describes identifying network
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`data flows based on behavioral statistics and penalizing “misbehaving” flows such
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`as peer-to-peer traffic. (Id., Abstract, 1:53-2:51.) As others in the industry had
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`already recognized (e.g., EX1021, 2:31-39; EX1045, 1:31-42), then-existing
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`systems were inadequate for classifying traffic as applications became more
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`sophisticated and elusive. (EX1001, 1:7-49.) The named-inventor addressed the
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`problem—again as others in the industry already had (e.g., EX1021, 6:23-7:40;
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`EX1045, 6:18-35)—by identifying flows based on their observed, empirical
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`behavior. (EX1001, 1:58-59, 2:4-5.) The specification explains that “because their
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`behavior cannot be hidden, misbehaving flows cannot avoid detection. . . .
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`regardless of which protocols they use, or how those protocols try to
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`hide/obfuscate their nature. . . .” (Id., 1:61-66.) “Once identified/detected, they
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`can be controlled and/or penalized.” (Id., 1:66-67.)
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`The ’593 Patent describes a “misbehaving flow manager (MFM) 210 for
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`keeping track of flows, determining whether the flows are exhibiting undesirable
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`behavior, and enforcing a penalty on the flows if they are exhibiting undesirable
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`behavior.” (EX1001, 5:44-48.) The misbehaving flow manager empirically tracks
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`behavioral statistics such as byte count, life duration, flow rate, average packet
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`size, etc. and stores these statistics in a “flow block.” (Id., 2:4-5, 2:63-64, 6:5-19,
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`Fig. 4.)
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`(EX1001, Fig. 4.)
`As each packet in the flow is processed, the behavioral statistics in the flow
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`block are updated to “provide an up[-]to[-]date reflection of the flow’s behavior.”
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`(Id., 6:20- 24.)
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`Legacy systems classified flows using heuristic methods, and it was typical
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`to calculate gradients, ranges, or other quantitative indicators of a degree of
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`misbehavior. (See, e.g., EX1007, Abstract; EX1030, 7:2-5.) Similarly, the
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`’593 Patent computes a “badness factor” used to determine whether a flow exhibits
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`undesirable behavior and indicating a degree of misbehavior. EX1001, 2:18-26,
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`6:25-33.) Figure 5 illustrates one function for computing the badness factor
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`considering flow rate, duration, total bytes, and average packet size as compared to
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`thresholds. (Id., 2:65-67, 7:51-67.)
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`
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`(EX1001, Fig. 5.)
`After identifying an undesirable flow, the misbehaving flow manager applies
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`standard techniques for flow control (e.g., increasing drop rate). (EX1001, 2:28-
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`30, 6:34-43, 9:7-14.) The flow manager then updates the statistics to reflect the
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`processing. (Id., 7:37-45.)
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`B.
`Prosecution History
`The application that issued as the ’593 Patent was filed on December 22,
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`2004. In an initial Office Action, the Examiner rejected all a