Case 2:21-cv-00072-JRG Document 25-7 Filed 04/23/21 Page 1 of 29 PageID #: 399
`Case 2:21-cv-00072-JRG Document 25-7 Filed 04/23/21 Page 1 of 29 PageID #: 399
`
`
`
`
`
`
`
`EXHIBIT 6
`
`EXHIBIT 6
`
`
`

`

`Case 2:21-cv-00072-JRG Document 25-7 Filed 04/23/21 Page 2 of 29 PageID #: 400
`
`
`
`Mark Reiter
`Direct: +1 214.698.3360
`Fax: +1 214.571.2907
`MReiter@gibsondunn.com
`
`
`
`
`
`
`
`
`
`
`
`April 2, 2021
`
`VIA ELECTRONIC MAIL
`
`Alfred R. Fabricant
`Fabricant LLP
`411 Theodore Fremd Road, Suite 206 South
`Rye, NY 10580
`
`Re:
`
`AGIS Software Development LLC v. Uber Technologies Inc. d/b/a Uber,
`No. 2:21-cv-00026 (E.D. Tex.)
`
`Dear Counsel:
`
`We write regarding U.S. Patent Nos. 7,630,724 (“’724 Patent”), 10,299,100 (“’100 Patent”),
`and 10,341,838 (“’838 Patent”) (collectively, “the Asserted Patents”), which AGIS Software
`Development LLC (“AGIS”) has included in its complaint against Uber in the above
`referenced case. Our investigation has revealed facts demonstrating that Microsoft is a
`co-owner of the Asserted Patents, and, as a result, AGIS cannot on its own satisfy the statutory
`requirements to allege infringement of the Asserted Patents. The claims with respect to the
`Asserted Patents must be dismissed.
`
`More specifically, we have learned that named inventor Christopher R. Rice was employed by
`Microsoft at the time he purportedly assigned his rights to the Asserted Patents to a predecessor
`AGIS entity. Based on Mr. Rice’s LinkedIn Profile, Mr. Rice was employed by Microsoft at
`least as early as August 2005 and until March 2016. In that same profile, Mr. Rice states that
`while at Microsoft, he developed, among other things, “networking systems” and “location
`determination cloud services.” Consistent with that statement, at least one Microsoft patent,
`which identifies Mr. Rice as a named inventor, confirms that Mr. Rice’s work at Microsoft
`included location-based technologies. See, e.g., U.S. Patent No. 8,618,984, titled “Selecting
`Beacons for Location Inference.” In its Complaint, AGIS alleges the Asserted Patents disclose
`and claim location-based technologies. See, e.g., Complaint at ¶¶ 24, 50, 51, 82, 84, 99, 101,
`102.
`
`On April 14, 2006 and later on October 30, 2014, while employed by Microsoft, Mr. Rice
`executed inventor declarations that pertain to the Asserted Patents. On June 19, 2006 and
`subsequently on April 23, 2015, Mr. Rice purported to assign his rights to the alleged
`inventions disclosed in the Asserted Patents to a predecessor AGIS entity. This assignment,
`however, was invalid as Mr. Rice had already assigned such rights to Microsoft. When he
`
`
`
`
`
`

`

`Case 2:21-cv-00072-JRG Document 25-7 Filed 04/23/21 Page 3 of 29 PageID #: 401
`
`Alfred R. Fabricant
`April 2, 2021
`Page 2
`
`began his employment at Microsoft, Mr. Rice assigned to Microsoft all inventions he
`developed while employed with Microsoft. In 2005, the Microsoft Employment Agreement
`contained a provision in which the employee, at the time of his or her employment, assigned
`to Microsoft all inventions “conceive[d], develop[ed], reduce[d] to practice, or otherwise
`produce[d]” during his or her employment. Specifically, the relevant provision provides:
`
`I will promptly and fully disclose to MICROSOFT any and all inventions,
`discoveries, designs, developments, improvements and trade secrets, whether or not
`patentable (collectively “Inventions”) that I solely or jointly may conceive, develop,
`reduce to practice or otherwise produce during my employment with MICROSOFT.
`Subject to the NOTICE below, I agree to grant and I hereby grant, transfer, and
`assign to MICROSOFT all my rights, title and interest in and to such inventions.
`
`Thus, pursuant to this agreement, Mr. Rice assigned to Microsoft all of his inventions,
`including those disclosed in the Asserted Patents. When an employment agreement includes
`the language “hereby assign” like the relevant provision above, the Federal Circuit has held
`that language indicates a present assignment of future inventions. See Bd. of Trustees of Leland
`Stanford Junior Univ. v. Roche Molecular Sys., Inc., 583 F.3d 832, 842 (Fed. Cir. 2009), aff’d,
`563 U.S. 776, 131 S. Ct. 2188, 180 L. Ed. 2d 1 (2011) (“[T]he VCA’s language of ‘do hereby
`assign’ effected a present assignment of Holodniy’s future inventions to Cetus.”). Thus,
`pursuant to this agreement, Microsoft “immediately gained equitable title” to Mr. Rice’s
`inventions, and “once the invention[s] came into being[,] the transfer of title would occur by
`operation of law.” See id.; see also FilmTec Corp. v. Allied-Signal, Inc., 939 F.2d 1568, 1573
`(Fed. Cir. 1991).
`
`As Microsoft is a co-owner of the Asserted Patents, AGIS fails to satisfy the statutory
`requirements for bringing an infringement suit on its own, and these claims should be
`immediately dismissed. See, e.g., Israel Bio-Engineering Project v. Amgen, Inc., 475 F.3d
`1256, 1264-65 (Fed. Cir. 2007) (“Where one co-owner possesses an undivided part of the
`entire patent, that joint owner must join all the other co-owners to establish standing. … Absent
`the voluntary joinder of all co-owners of a patent, a co-owner acting alone will lack standing.”);
`see also AntennaSys, Inc. v. AQYR Techs., Inc., 976 F.3d 1374, 1378 (Fed. Cir. 2020) (failure
`to join all-co-owners as plaintiffs impacts a party’s ability to satisfy the statutory prerequisites
`for bringing an infringement suit).
`
`

`

`Case 2:21-cv-00072-JRG Document 25-7 Filed 04/23/21 Page 4 of 29 PageID #: 402
`
`
`
`
`
`
`
`
`
`
`
`
`
`Mark Reiter
`Direct: +1 214.698.3360
`Fax: +1 214.571.2907
`MReiter@gibsondunn.com
`
`
`
`Given that Uber is preparing its response to the Complaint, we would appreciate a response by
`April 9th. We look forward to hearing from you so that we may dispose of this quickly without
`any further effort or expense of either party.
`
`Sincerely,
`
`/s/ Mark Reiter
`
`Mark Reiter
`
`cc:
`
`Samuel F. Baxter
`McKool Smith, P.C.
`104 E. Houston Street, Suite 300
`Marshall, Texas 75670
`
`
`ATTACHMENTS
`
`
`
`
`
`

`

`Case 2:21-cv-00072-JRG Document 25-7 Filed 04/23/21 Page 5 of 29 PageID #: 403
`Case 2:21-cv-00072—JRG Document 25-7 Filed 04/23/21 Page 5 of 29 PageID #: 403
`
`ATTACHMENT A
`
`ATTACHMENT A
`
`

`

`Case 2:21-cv-00072-JRG Document 25-7 Filed 04/23/21 Page 6 of 29 PageID #: 404
`Case 2:21-cv-OOO72-JRe
`
`Contact
`
`www.linkedin.com/in/rusrice
`
` ÿ
`

`ÿ
`!

 ÿ"ÿÿ 
`


` ÿÿ# 
`



ÿ$


` ÿ%


`&
`'ÿ

ÿ
` 

ÿ(ÿ 
` ÿ(

ÿ
` ÿ

  &)
`(
`

)ÿ



)ÿ


`

ÿ

*


` ÿ ÿ

`

&+ÿ
` ÿ
` )ÿÿ 

`(
`
` ÿ

ÿÿ



ÿ 

ÿ

ÿ  ÿ


`

)ÿ(
`

ÿ)
` ÿ 


` ÿ

ÿ 

ÿ 

ÿ"ÿ

ÿÿ 

ÿ"ÿ ÿ



`ÿ



ÿ  ÿ

ÿ 

ÿ"ÿ

ÿ &ÿÿ
`ÿÿ ÿ


`


` ÿ



ÿ
`ÿ

*


`



ÿÿ 
`

`

" ÿ,ÿ-ÿ

" ÿ

*
`ÿ ÿÿ"

ÿ

ÿ.
` 
`/


` ÿ
`
`

/ÿ
` ÿ

,



)ÿ



)ÿ

`)ÿ
`

ÿ 
` ÿ% )ÿÿ

ÿ

" &ÿ

ÿ
` ,
`.

ÿ"

`


`


` ÿ

ÿÿ0

ÿ12ÿ
`.
` ÿ
`

  
`

ÿÿ'

ÿ

ÿ

ÿ

ÿ&

ÿ
`  

3ÿ%4)ÿ
` *)ÿ5)
`6(





)ÿ 77)ÿ$ 8)ÿ " *5" 6
`( )ÿ$



)
` )ÿ &)ÿ9 )ÿ: )ÿ:

&ÿ

,

ÿ  ÿ


`


`
`
` ÿ"ÿ

)ÿ&

ÿ


` %
`



)ÿ

ÿ$


`)ÿ%
`

` 
`


` )ÿ)ÿ6 ( )ÿ)ÿ ;)ÿ 77)ÿ9

)ÿ " ÿ4

(
`


`

)ÿ
`


`

)ÿ<%)ÿ=)ÿ$,



)ÿ9=ÿ8)
`4
` ÿ%.

)ÿ8
`ÿ)ÿ )ÿ$
`

ÿ


` )ÿ$
`">ÿ
` 

 
`

?
`

ÿ"ÿ%

ÿ! )ÿ!0)ÿ ÿ!
`

+ÿ:@)ÿ#ÿ#-)
`
`#8)ÿ



)ÿ9


` ÿ ÿ&

ÿ
` )ÿ4

( 
`)
`#  )ÿ)ÿ% )ÿA$)ÿ)ÿA9Bÿ 
`)ÿ%B)ÿ5)ÿ#(
`

)
`% )ÿ

 ,
`

)ÿC)ÿ

 &)ÿ<

ÿ8)ÿ



#)ÿ
`

)
`!$)ÿ#@)ÿ@!@)ÿ%@)ÿ@

"

)ÿ#



)ÿ ÿ%


`
`*


`



`# 
`!

 ÿ"ÿÿ 
`


` 
`%
` ÿ-2DEÿ,ÿ@



ÿ-ÿ&


`5



ÿ



ÿ%


`ÿÿ
`
` Fÿ
` ÿ"ÿ
`

)ÿ" ÿ

ÿ ÿ(ÿ

ÿ"

ÿ 
`

)
`=%ÿ 
`

)ÿ 
`


` ÿ$ 

)ÿ ÿ &ÿ


`@

ÿDÿ"ÿG
`
`Rus Rice
`
`Head of SaaS Engineering at JumpCloud
`
`Summaw
`
`I'm super passionate about solving problems in technology,
`
`business, people, service execution and delivery; in particular, I love
`
`building teams that create large scale cloud services, mobile apps,
`
`and uncovering the latent value of the vast volume of data generated
`
`to create long term value for the company.
`
`I am an engineering leader with experience across multiple
`
`successful start-ups (2 successful exits and a few more amazing
`
`"learning opportunities") in e-commerce, aerospace, media, and
`
`telecom domains. Also, I have successfully led mid-sized software
`
`engineering teams at Fortune 50 organizations.
`
`Technologies that I've used over the years include: AWS, Linux, Go,
`
`Kubernetes, C++, MongoDB, lnflux/Grafana/Kibana, Memcache,
`
`Datadog, Loggly, Nomad, Vault, Very Large-scale Cloud Services
`
`(millions of users), System Design/Architecture, Dev Metrics, Agile
`
`Engineering, Scrum, Kanban, TDD, C#, C++, .Net, RESTful Web
`
`Services, microservices, SOA, SQL, Map-Reduce, NoSQL DBs,
`
`Windows Azure, Big Data, R, Machine learning, Microsoft’s internal
`
`equivalent of Apache Hadoop, HDFS, and Hive; VolP, Java (J2EE,
`
`EJB, Servlets), Networking and Systems programming, Weblogic,
`
`JRun, Tomcat, Ant, UML, STL, UNIX (Solaris, AlX, SGI), Jbuilder,
`
`ACE, Real-time, SS7, Telephony, Oracle DB, TogetherJ, Eclipse,
`
`HTML, JSP, PHP, LDAP, Perforce, Jmeter, and Apache.
`
`Expenence
`
`JumpCloud
`
`Head of SaaS Engineering
`
`April 2019 - Present (2 years)
`
`I am hiring! Looking for architects, front end and back end Software Engineers,
`
`QA Engineers, Engineering Managers, among many others.
`
`Page 1 of 4
`
`(Linkedln)
`
`Top Skills
`
`Cloud Computing
`
`Leadership Development
`
`  
`
` 

` 
` 
`

`
` 

 
`ÿ
` 
`  ÿ 
` 
`




`ÿ






` 
`


` ÿ




`
`
`Engineering Leadership
`
`ÿ
`
`ÿ
`
`

`

`ÿ
`
`ÿ
`
`
`
`people, and the majority of our Seattle engineering office across source ingest,
`
`ÿ
`  
`

 
`


`
`

ÿ
`ÿ 
` 
`

ÿ
`

ÿÿ
`
` ÿ !"ÿ#ÿ$ ÿ !%ÿ&'ÿ(ÿÿ

 )
`*ÿÿ$
`+ÿ ÿÿ$,ÿ  ÿ

-ÿÿ ÿ- 
` ÿ
`

ÿ.

ÿ/
` 

ÿ ÿ ÿ 

(ÿ

ÿ

ÿÿÿ


`ÿ
`

ÿ


`ÿ
`-
`  0ÿ
`

ÿ . ÿ  ÿ

ÿ, 

ÿ

ÿ   
` ÿ ÿ  ÿ
`



ÿ ÿÿ.(ÿÿ
`


`
`ÿ ÿ
`

ÿ 


`ÿ
`
`$,ÿÿÿ
`

 #. ÿ #

# ÿ  ÿ 

`ÿ



ÿ

ÿ,ÿ,
`102ÿ,ÿÿ
` ÿ ÿ3ÿ
`

ÿ4

ÿ- ÿ0.ÿ
`5


`



ÿ
`.ÿ
`

ÿ  ,ÿ.ÿ 
`6ÿ

.ÿ
`(
` ÿ ÿ

ÿ$,ÿ  ÿ(

ÿ
`ÿ ÿ

7ÿ(

ÿ
`

ÿ


` 

ÿ

,  ÿÿÿ  ÿ,
`ÿ$,ÿ ÿ ÿ
`

0
`
`

ÿ ÿ
` ÿ  ÿ (
`
`




`! ÿ(ÿ8ÿ

 
`
` ÿ

-ÿÿÿ&ÿ
`

)
`
` ÿ %ÿ#ÿ
` ÿ !"ÿ&2ÿ(ÿ!ÿ

 )
`9

 ÿ:$
`; ÿ ÿ/# 

ÿ6( ÿ ÿ4



ÿ,
`ÿ ,ÿ ÿÿ ÿ 
` 

,  ÿ3

+ÿ
`



ÿ 



`

ÿ
`


`ÿ


`ÿ ÿ  ÿ 

`ÿ


`.

 ÿ
`

 ÿ ÿ.ÿ6( ÿ 


`ÿ; ÿ 

 ÿ ÿ

,
`ÿ 0ÿ

ÿ

ÿÿ ,ÿ ÿ
` 
`ÿ ÿ,(ÿ

ÿ , 
` ,

<ÿ

- ÿ ÿ

ÿ ÿ
` 
`ÿ 


`ÿ0
`

ÿ ÿ.
`ÿ 
`
`ÿ ÿ5(ÿ ÿÿ, ÿ

ÿ

ÿ.
` # (ÿ
`


`ÿ ÿ 
`

ÿ 
`

ÿÿ
`$ÿ /ÿ#ÿ
` ÿ %ÿ&'ÿ(ÿ8ÿ

 )
`9

 ÿ:$
`=ÿ (ÿ3!ÿ ÿ3ÿ 


`ÿ ÿ&8#!/ÿ 

ÿ( 
`(ÿ
` )ÿ ,


` 
` ÿÿ( ÿ.ÿ (
`ÿ( ÿ-

6ÿ( 
`
`

`

ÿ  

ÿ
`

 ÿ,
`ÿ ÿ
`

 ÿ3

+ÿ
`

 ÿ 


`
`ÿÿ

ÿ1
`
`Case 2:21-cv-00072-JRG Document 25-7 Filed 04/23/21 Page 7 of 29 PageID #: 405
`Case 2:21-cv-00072-JRe
`
`https://jumpcloud.com/careers/
`
`No agencies, please.
`
`iStreamPlanet
`
`Senior Director Of Engineering
`
`March 2016 - April 2019 (3 years 2 months)
`
`I lead all Aventus media software engineering teams, which comprise about 50
`
`switching/mixing, transcoding, publishing, media origin, video on demand,
`
`digital rights management, control plane, site reliability engineering, escalation
`
`engineering, and core product infrastructure.
`
`Aventus is a cloud-based end-to-end media processing solution for live events,
`
`24x7 live linear channels, and VOD content. Complete with flexible acquisition
`
`options, scalable transcoding, adaptive bitrate packaging, robust security,
`
`and ad opportunities, Aventus helps you scale and monetize your content for
`
`millions. Provided as a managed sen/ice, Aventus simplifies the complexities
`
`of the changing media industry.
`
`Microsoft
`
`10 years 8 months
`
`Principal Software Eng Manager (Engineering Director)
`
`March 2009 - March 2016 (7 years 1 month)
`
`Led the 25-person Skype Media Control Services dev and test teams that
`
`provided VolP control protocols, conferencing logic and media processing for
`
`both consumer and business Skype products. Led, mentored and motivated
`
`a mix of front line dev managers, architects, and very senior individual
`
`developers; owned end to end architecture, project execution, instilled best
`
`engineering practices, ensured quality and ran DevOps support to enable
`
`single/multi-party conferences and application sharing.
`
`Senior Engineering Manager
`
`August 2005 - March 2009 (3 years 8 months)
`
`Built many V1 and V2 product teams (8-15 people typically each) developing
`
`machine learning systems, big data/analytics systems, networking systems,
`
`location determination cloud services, and consumer VolP cloud products.
`
`Page 2 of 4
`
`

`

`ÿ
`
`ÿ
`
`
`
`delivery activities for the entire company, spanning cloud service development,
`
`ÿ
`  
`
`ÿ   
`ÿÿÿÿÿÿÿÿ !"
`#ÿ$%ÿ
`&ÿÿ!%''ÿ 'ÿ(  !ÿ(ÿ'(ÿ''ÿ  ÿ(%'!) ÿ(
`(' %ÿ %  ÿ*!ÿÿ ÿ! )+ÿ) ÿ'!(ÿ% ÿ(%'!) +
` ,&+ÿ(ÿ(! (ÿ))'  !ÿ(%'!) -
`.')(ÿ%ÿ) 'ÿ*(  ÿ'ÿ!+ÿ(ÿ% 'ÿ %!'%(ÿ ÿ '
`(ÿ( ' ÿ( ÿ!ÿ/   !-
`$%'!)(ÿ!ÿ0ÿ! ÿ1ÿ% 2ÿ('(ÿ 3!ÿ1 
`!%ÿ -
`#ÿÿ'ÿ  ÿ ÿ) ÿÿ ÿ ÿ !)ÿ(ÿÿ ''ÿ 
` ÿÿ4&-
`  ÿÿ/ (ÿ1ÿ&!*ÿ(  ÿ5 !'ÿ ÿ-
`,)%
`  )'ÿ&!*ÿ  67 'ÿ8(
`
`ÿÿÿ9ÿ"
`:!'(+ÿ,
`5ÿÿÿ 'ÿ  ÿ'(ÿ!*ÿ,)%;ÿ!* !'ÿ$%'!) 
`&% ÿ!)ÿ(ÿ ÿ ÿ! ÿ!*ÿ!' !ÿ!(
`((ÿ! )ÿ8:&ÿ)!(ÿ!ÿ ÿ ÿ) * ÿ(-
`& '&!*
`& !ÿ&!*ÿ  
`<<ÿÿÿÿ"
`:!'(+ÿ,
`& '&!*ÿ!)ÿÿ!ÿ!*ÿÿ) !ÿ!*ÿ8! !ÿ:(ÿ&% ÿ(
`5ÿ3! (ÿÿ!ÿ!*ÿÿ'ÿ )'!ÿ09"-ÿ5ÿ(%'!)(ÿ!*ÿ*!ÿ!
`= 'ÿ))'  !ÿ> !ÿ(ÿ1ÿÿÿ !1 'ÿ!ÿ'! !
`))'  !-ÿ
`& '&!*ÿÿ/ (ÿ1ÿ,)%ÿ& ÿ ÿ-
`!3& !ÿ&!*ÿ  67 'ÿ8(
`<<?ÿÿ<<ÿÿ"
`:!'(+ÿ,
`ÿÿ!*ÿ9
`
`Case 2:21-cv-00072-JRG Document 25-7 Filed 04/23/21 Page 8 of 29 PageID #: 406
`Case 2:21-cv-00072-JRe
`
`QwikCart®
`
`VP Engineering
`
`August 2011 - March 2015 (3 years 8 months)
`
`Set the overall technical direction and led all engineering development and
`
`iOS, and Android application development.
`
`Helped venture capital fundraising early on, and heavily involved in technical
`
`due diligence during our acquisition.
`
`Developed core C# ecommerce web services; delegated major subsystems
`
`over time.
`
`Grew the lean engineering team spanning 1 site in Europe and 2 smaller sites
`
`in the USA.
`
`QwikCart was acquired by Software Paradigms International in 2015.
`
`Openwave
`
`Principal Software Engineer/Technical Lead
`
`2001 - 2005 (4 years)
`
`l was the technical engineering lead of Openwave's Professional Development
`
`Services group charged with creating custom software solutions around
`
`standard company LBS products to meet carrier specific needs.
`
`SignalSoft
`
`Senior Software Engineer
`
`1998 - 2001 (3 years)
`
`SignalSoft Corp was one of the pioneers of Location Based Sen/ices and
`
`I joined as one of the early employees (#40). I developed software for our
`
`Wireless Application Framework reused by 5 key mobile network location
`
`applications.
`
`SignalSoft was acquired by Openwave Systems in 2001.
`
`Ae rojet
`
`Senior Software Engineer/Technical Lead
`
`1997 - 1998 (1 year)
`
`Page 3 of 4
`
`

`

`Case 2:21-cv-00072-JRG Document 25-7 Filed 04/23/21 Page 9 of 29 PageID #: 407
`Case 2:21-cv-OOO72-JRe
`
`l was the technical development lead for ground station communication
`
`software on the Space Based Infrared System program co-developed with
`
`Lockheed Martin.
`
`Ultra Electronics, Advanced Tactical Systems
`
`Software Engineer
`
`1993 - 1997 (4 years)
`
`I joined APC (now Ultra Electronics ATS) as one of the early employees (#14)
`
`for the all major US armed services. My work spanned both hardware and
`
`ÿ
` ÿ ÿÿ 
` 

ÿ 


`ÿ

 ÿÿ
` ÿ
`ÿ 
` 
`
` ÿ
`ÿÿ ÿ ÿ
` ÿÿÿ  

 ÿ 
`  ÿ
`
`

ÿ

 
`  ÿ! 
`  ÿ"  

ÿ
`
` ÿ
`
`
`#$$%ÿÿ#$$&ÿ'(ÿ)
` ÿ*
` ÿ!+,ÿ'
` ÿ

ÿ

 
` ÿ!")ÿÿ
`ÿÿÿ

ÿ

ÿ'-#()
`
` ÿ ÿ
`.

ÿÿ 

ÿ,( ÿ

 
`ÿ
` ÿ  

ÿ 


`ÿ 


`ÿÿ

ÿ*ÿÿ ÿ ÿÿ ÿ
`
` ÿ.ÿ ÿ
`
` ÿ


`  
`
`"ÿ
`ÿÿ"/ÿÿ!
`
` 

ÿÿ 
`  ÿ,ÿ 
` 
`
`
`ÿÿ,

 ÿ


`ÿÿ
`
`
` ÿ
`
`
`ÿ
`
`
`
`and was responsible to develop C4l applications and tactical datalink protocols
`
`ÿ
`
`ÿ
`
`
`
`software layers.
`
`Education
`
`The University of Texas at Austin
`
`Bachelors of Science, Computer Science
`
`University of Colorado Boulder
`
`Masters of Engineering, Engineering Management
`
`Page 4 of 4
`
`+ÿ(ÿÿ(
`
`

`

`Case 2:21-cv-00072-JRG Document 25-7 Filed 04/23/21 Page 10 of 29 PageID #: 408
`Case 2:21-cv-00072—JRG Document 25-7 Filed 04/23/21 Page 10 of 29 PageID #: 408
`
`ATTACHMENT B
`
`ATTACHMENT B
`
`

`

`Case 2:21-cv-00072-JRG Document 25-7 Filed 04/23/21 Page 11 of 29 PageID #: 409
`
`US008618984B2
`
`(12) United States Patent
`Lin et al.
`
`(10) Patent No.:
`(45) Date of Patent:
`
`US 8,618,984 B2
`Dec. 31, 2013
`
`(54) SELECTING BEACONS FOR LOCATION
`NFERENCE
`
`(75) Inventors: Jyh-Han Lin, Mercer Island, WA (US);
`Lon-Chan Chu, Redmond, WA (US);
`Aravind Krishnamachari Seshadri,
`Redmond, WA (US); Prasanta Ghosal
`s
`...
`s
`RNR S.Schifteels Anup
`s
`s
`s
`Kashinath Pachlag, Bothell, WA (US)
`
`(73) Assignee: Msion Corporation, Redmond, WA
`US
`
`(*) Notice:
`
`Subject to any disclaimer, the term of this
`patent is extended or adjusted under 35
`U.S.C. 154(b) by 323 days.
`
`7/2008 Houri
`7,397,424 B2
`1/2009 Morgan et al. ............. 455,456.5
`7,474,897 B2 *
`8, 2009 Taschereau
`7,577,244 B2
`7,750,848 B2 * 7/2010 Normarket al. ......... 342,357.25
`2004/0203904 A1* 10, 2004 Gwon et al. ............... 455,456.1
`2007/0001867 A1* 1/2007 Rowe et al. .............. 340,825.49
`2007/0210961 A1
`9/2007 Romijn
`2008/017.6583 A1* 7/2008 Brachet et al. ............. 455,456.3
`2008/0238767 A1 10, 2008 Zhou
`2008/0252511 A1 10, 2008 Jacotot
`2008/0280624 A1 1 1/2008 Wrappe
`2010, 0013704 A1
`1/2010 Coutel et al. ............. 342,357.04
`
`OTHER PUBLICATIONS
`Olson et al., “Robust Range-Only Beacon Localization.” IEEE AUV,
`2004.
`
`Continued
`(Continued)
`
`(21) Appl. No.: 12/727,901
`(22) Filed:
`Mar 19, 2010
`(65)
`Prior Publication Data
`
`Sep. 22, 2011
`
`(2010.01)
`
`US 2011 FO227791 A1
`(51) Int. Cl.
`GOIS 5/02
`(52) U.S. Cl
`CPC
`
`G0IS 5/0252 (2013.01); G0IS5/0278
`• us
`(2013.01)
`
`- - - - - - - - - - - - -
`
`58 F. fo - - - - - ificati- - - - - -s - - - - - - - h- - - - - - 342/451: 342/464
`(58) is:
`assification s386. 450, 451, 463,464
`S
`licati - - - - - file? - - - - -
`1
`s
`hhi s
`s
`ee application file for complete search history.
`References Cited
`
`(56)
`
`U.S. PATENT DOCUMENTS
`
`Primary Examiner — Gregory C Issing
`
`ABSTRACT
`
`57
`(57)
`Location inference using selected beacons. Data is received
`representing a set of beacons observed by a computing
`device. The beacons are located withina first geographic area.
`geograp
`A Subset (e.g., a clique) of the beacons is selected based on a
`coverage area of each of the beacons, where each of the
`beacons in the selected subset has a coverage area that over
`laps with the coverage area of each of the other beacons in the
`selected Subset. Using known or estimated positions of the
`beacons, a second geographic area is defined based on the
`selected subset of beacons and the beacon reference data and
`the coverage areas associated therewith. The second geo
`graphic area, Smaller than the first geographic area, represents
`an aroproximate location of the computing device. In some
`pp
`pulung
`embodiments, the computing device is calculated to be within
`the second geographic area with 95% probability.
`
`5,936,572 A *
`6,776,334 B1
`
`8, 1999 Loomis et al. ........... 342.357.29
`8/2004 Garg
`
`20 Claims, 5 Drawing Sheets
`
`ISEE C1C3, W1
`AND W3. FIND
`MYPOSITION?
`
`INFER USERS
`POSITION
`RATIVETO
`C1 C3, W1 AND
`W3
`
`
`
`POSITIONING
`SYSTEM
`
`

`

`Case 2:21-cv-00072-JRG Document 25-7 Filed 04/23/21 Page 12 of 29 PageID #: 410
`
`US 8,618,984 B2
`Page 2
`
`(56)
`
`References Cited
`
`OTHER PUBLICATIONS
`
`Meneses, et al., “Enhancing the Location-Context through Inference
`over Positioning Data'. Retrieved at{<http://ubicomp.algoritimi.
`uminho.pt/csmu? proc/meneses-135.pdf>>, Jun. 2006, pp. 10.
`Sinha, et al., “A Beacon Selection Algorithm for Bounded Error
`Location Estimation in Ad Hoc Networks'. Retrieved at <<http://
`ieeexplore.ieee.org/stamp? stamp.jsp?arnumber 4127348&isnum
`ber=4127326>, Mar. 5-7, 2007, pp. 6.
`
`Lieckfeldt, et al. An Algorithm for Distributed Beacon Selection,
`Retrieved at<http://ieeexplore.ieee.org/stamp? stamp.jsp?arnum
`ber=4517414&isnumber=45.17341>>, Sixth Annual IEEE Interna
`tional Conference on Pervasive Computing and Communications,
`Mar. 17-21, 2008, pp. 318-323.
`Bahl, et al., “RADAR: An In-Building RF-based User Location and
`Tracking System”. Retrieved at{<http://www.cs.indiana.edu/~con
`nelly/Docs/radar.pdf>>, 2000, pp. 10.
`
`* cited by examiner
`
`

`

`Case 2:21-cv-00072-JRG Document 25-7 Filed 04/23/21 Page 13 of 29 PageID #: 411
`
`U.S. Patent
`
`Dec. 31, 2013
`
`Sheet 1 of 5
`
`US 8,618,984 B2
`
`
`
`
`5) NINOILISOd
`
`VNE
`LSÅS
`
`CINV
`INA’S
`O’IOCINI—.
`"9MA
`CIN\/
`9 MW?NOI
`LISOd XIN
`
`I "5ÐI
`
`ZO
`
`

`

`Case 2:21-cv-00072-JRG Document 25-7 Filed 04/23/21 Page 14 of 29 PageID #: 412
`
`U.S. Patent
`
`Dec. 31, 2013
`
`Sheet 2 of 5
`
`US 8,618,984 B2
`
`
`
`Z '5ÐI
`
`

`

`Case 2:21-cv-00072-JRG Document 25-7 Filed 04/23/21 Page 15 of 29 PageID #: 413314
`n
`e
`1e
`aP12/
`s
`C
`GR.J.D
`7.52
`f
`C
`g
`
`o2wDm
`
`emm2u1,
`
`t3
`
`B5MM03dammFS
`
`
`
` OtOn0.mwa1P2.2SeCaU
`
`0S5U
`
`g9aa8P196a28
`
`..2#Bmm
`
`
`
`
`
`<._.<n_mozmmmu—mmzoo/Em
`
`
`
`<mm<>mO_>_m=>_
`
`E”mUH>mQ
`
`
`
`
`
`memmmuoE63mg05::on
`
`momSmm.UHn—
`
`
`
`
`
`2%._.m_mmm__n__._.2m_n__zoo/Em
`
`
`
`._.Zm_zon__>_oomo<n_m_m_._.z_
`
`
`
`._.Zm_zon__>_oomm._..__u_
`
`
`
`._.Zm_zon__>_ooMDOZQ
`
`
`
`._.Zm_zOn__>_Oomozmmmn—Z
`
`
`
`
`
`<mm<mo<mm>8EEmEEEEQzoo/mm.
`
`ES.
`
`2%mUH>mQ
`
`
`
`
`
`

`

`Case 2:21-cv-00072-JRG Document 25-7 Filed 04/23/21 Page 16 of 29 PageID #: 414
`
`U.S. Patent
`
`Dec. 31, 2013
`
`Sheet 4 of 5
`
`US 8,618,984 B2
`
`FIG. 4
`
`
`
`
`
`RECEIVE BEACONNO
`FINGERPRINT FROM
`MOBILEDEVICE
`
`404
`
`406
`
`4.08
`
`410
`
`REMOVE OUTLYING BEACONS
`
`SELECT CLIQUE OF BEACONS
`
`INFER GEOGRAPHICAREA OF
`MOBILE DEVICE BASED ON
`SELECTED BEACONS
`
`PROVIDE THE INFERRED
`GEOGRAPHICAREA TO THE
`MOBILE DEVICE AS THE
`APPROXIMATE LOCATION OF THE
`MOBILE DEVICE
`
`

`

`Case 2:21-cv-00072-JRG Document 25-7 Filed 04/23/21 Page 17 of 29 PageID #: 415
`
`U.S. Patent
`
`Dec. 31, 2013
`
`Sheet 5 of 5
`
`US 8,618,984 B2
`
`FIG.5
`
`
`
`

`

`Case 2:21-cv-00072-JRG Document 25-7 Filed 04/23/21 Page 18 of 29 PageID #: 416
`
`1.
`SELECTING BEACONS FOR LOCATION
`NFERENCE
`
`US 8,618,984 B2
`
`BACKGROUND
`
`Some existing positioning systems such as global position
`ing systems (GPS) determine the location of devices using
`satellites. Other systems such as collaborative positioning
`systems determine the location of the devices based on
`crowd-sourced data. The crowd-sourced data typically
`includes a list of beacons observed at a particular location
`along with identification of the particular location as obtained
`by mobile devices such as laptops, netbooks, and cellular
`telephones. The positions of the beacons are then used to
`estimate the location of devices (e.g., those lacking GPS
`capability or coverage) that request position information
`based on an observed list of beacons. The complexity and
`accuracy of the estimations depend in part on which beacons
`are selected for the estimations.
`
`10
`
`15
`
`SUMMARY
`
`Embodiments of the disclosure enable the selection of
`beacons from which to infer a location of a computing device.
`A computing device observes a set of beacons within a first
`geographic area. Data representing the set of beacons is
`received from the computing device. A subset of the beacons
`is selected based on a coverage area of each of the beacons
`such that each of the beacons in the selected subset has a
`coverage area that overlaps with the coverage area of each of
`the other beacons in the selected Subset. A second geographic
`area, Smaller than the first geographic area, is defined based
`on the selected Subset of beacons, beacon reference data, and
`the coverage areas to estimate the location of the computing
`device.
`This Summary is provided to introduce a selection of con
`cepts in a simplified form that are further described below in
`the Detailed Description. This Summary is not intended to
`identify key features or essential features of the claimed sub
`ject matter, nor is it intended to be used as an aid in determin
`ing the scope of the claimed Subject matter.
`
`25
`
`30
`
`35
`
`40
`
`BRIEF DESCRIPTION OF THE DRAWINGS
`
`FIG. 1 is an exemplary block diagram illustrating a posi
`tioning system inferring a location of a mobile device based
`on a beacon fingerprint provided by the mobile device.
`FIG.2 is an exemplary block diagram illustrating receipt of
`a beacon fingerprint from a mobile computing device and
`calculation of a location for the mobile computing device
`based on the beacon fingerprint.
`FIG. 3 is an exemplary block diagram illustrating a com
`puting device selecting beacons from which to infera location
`of another device.
`FIG. 4 is an exemplary flow chart illustrating location
`inference based on selected beacons.
`FIG. 5 is an exemplary block diagram illustrating a beacon
`fingerprint having a maximally complete clique.
`Corresponding reference characters indicate correspond
`ing parts throughout the drawings.
`
`45
`
`50
`
`55
`
`60
`
`DETAILED DESCRIPTION
`
`Referring to the figures, embodiments of the disclosure
`enable selection of beacons from which to infer a location of
`a computing device. The beacons are selected based on their
`relationship to neighboring beacons. In some embodiments,
`
`65
`
`2
`the computing device detects a set of beacons b1, b, . . . .
`b}. Knowing the estimated positions and coverage areas of
`each of the beacons, aspects of the disclosure determine the
`Smallest circle Such that the location of the computing device
`is within the circle with 95% probability. The calculated
`location of the computing device is provided to the computing
`device.
`Referring again to FIG. 1, an exemplary block diagram
`illustrates the positioning system 106 inferring a location of a
`mobile device 102 based on a beacon fingerprint provided by
`the mobile device 102. The mobile device 102 (e.g., a mobile
`telephone) detects or observes one or more beacons including
`cellular towers (or sector if directional antennas are
`employed) and wireless fidelity (Wi-Fi) access points or other
`wireless access points (WAPs).
`The beacons detected by the mobile device 102 at a given
`point in time represent the beacon fingerprint. The beacon
`fingerprint may also include other attributes of the detection
`Such as signal strength. While aspects of the disclosure may
`be described with reference to beacons implementing proto
`cols such as the 802.11 family of protocols, embodiments of
`the disclosure are operable with any beacon for wireless
`communication. In the example of FIG. 1, the mobile device
`102 detects the presence of beacons C1, C3, W1, and W3.
`The mobile device 102 provides the detected beacon fin
`gerprint to the positioning system 106 via a network 104. The
`network 104 includes a wireless cellular network in some
`embodiments, but other types of networks such as Wi-Fi and
`those providing Internet access are contemplated in other
`embodiments.
`The positioning system 106 stores, or has access to, data
`describing the approximate location of one or more of the
`beacons. The data is referred to as beacon reference data 314
`and describes, for example, the longitude, latitude, and/or
`altitude of the beacons. In some embodiments, the beacon
`reference data 314 is stored in a beacon store 212. Using the
`approximate location of at least one of the beacons in the
`detected beacon fingerprint, the positioning system 106 oper
`ates to infer the location of the mobile device 102 relative to
`the detected beacon fingerprint, as described herein. The
`inferred location is provided to the mobile device 102.
`Referring next to FIG. 2, an exemplary block diagram
`illustrates receipt of a beacon fingerprint from a mobile com
`puting device and calculation of a location for the mobile
`computing device based on the beacon fingerprint. The sys
`tem illustrated in FIG. 2 represents an example of a location
`inference system or positioning system in accordance with
`aspects of the disclosure. However, other systems, elements,
`and configurations are contemplated and within the scope of
`embodiments of the disclosure.
`The inference engine 214 receives a beacon fingerprint
`from devices such as the mobile device 204. The inference
`engine 214 accesses the beacon reference data 314 stored in
`the beacon store and predicts the location of observation
`associated with the unresolved beacon fingerprint. The pre
`dicted location is provided to the mobile device 204. The
`operation of the inference engine 214 is next described with
`reference to FIG. 3.
`Referring next to FIG. 3, exemplary block diagram illus
`trates a computing device 304 selecting beacons from a bea
`con fingerprint and calculating a location of another device
`based on the selected beacons. In some embodiments, the
`computing device 304 is associated with the positioning sys
`tem 106. For example, the computing device 304 represents
`the inference engine 214.
`The computing device 304 receives data from one or more
`of the devices 302, such as device #1 through device iiM, via
`
`

`

`Case 2:21-cv-00072-JRG Document 25-7 Filed 04/23/21 Page 19 of 29 PageID #: 417
`
`US 8,618,984 B2
`
`3
`a network 306. The devices 302 include, for example, mobile
`computing devices such as mobile device 102. However, the
`devices 302 may include any device executing instructions
`(e.g., application programs) to provide data. The data
`includes beacon fingerprints.
`In some embodiments, the devices 302 include portable
`computing devices such as laptops, netbooks, gaming
`devices, and/or portable media players. Further, each of the
`devices 302 may represent a group of processing units or
`other computing devices.
`Exemplary networks 306 include wired and/or wireless
`networks, and may represent local area networks or global
`networks such as the Internet. In embodiments in which the
`network 306 includes wireless networks, the computing
`device 304 and the devices 302 may be enabled with technol
`ogy such as BLUETOOTH brand wireless communication
`services (secured or unsecured), radio frequency identifica
`tion (RFID), Wi-Fi such as peer-to-peer Wi-Fi, ZIGBEE
`brand wireless communication services, near field communi
`cation (NFC), and other technologies that enable short-range
`or long-range wireless communication.
`The computing device 304 has at least one processor 308
`and one or more computer-readable media Such as a memory
`area 310. The processor 308 includes any quantity of process
`ing units, and is pr