Internet DRAFT - draft-iab-iotsi-workshop
draft-iab-iotsi-workshop
Network Working Group J. Jimenez
Internet-Draft Ericsson
Intended status: Informational H. Tschofenig
Expires: January 3, 2019 Arm Ltd.
D. Thaler
Microsoft
July 02, 2018
Report from the Internet of Things (IoT) Semantic Interoperability
(IOTSI) Workshop 2016
draft-iab-iotsi-workshop-02
Abstract
This document provides a summary of the 'Workshop on Internet of
Things (IoT) Semantic Interoperability (IOTSI)', which took place in
Santa Clara, California, on March 17-18, 2016. The main goal of the
workshop was to foster a discussion on the different approaches used
by companies and Standards Developing Organizations (SDOs) to
accomplish interoperability at the application layer. This report
summarizes the discussions, and lists recommendations to the
standards community. The views and positions in this report are
those of the workshop participants and do not necessarily reflect
those of the authors and the Internet Architecture Board (IAB), which
organized the workshop.
Status of This Memo
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provisions of BCP 78 and BCP 79.
Internet-Drafts are working documents of the Internet Engineering
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Internet-Drafts are draft documents valid for a maximum of six months
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material or to cite them other than as "work in progress."
This Internet-Draft will expire on January 3, 2019.
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Copyright Notice
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Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 2
2. Terminology . . . . . . . . . . . . . . . . . . . . . . . . . 4
3. What Problems to Solve . . . . . . . . . . . . . . . . . . . 4
4. Translation . . . . . . . . . . . . . . . . . . . . . . . . . 7
5. Dealing with change . . . . . . . . . . . . . . . . . . . . . 9
6. Security Considerations . . . . . . . . . . . . . . . . . . . 10
7. Collaboration . . . . . . . . . . . . . . . . . . . . . . . . 11
8. Acknowledgements . . . . . . . . . . . . . . . . . . . . . . 11
9. Appendix A: Program Committee . . . . . . . . . . . . . . . . 11
10. Appendix B: Accepted Position Papers . . . . . . . . . . . . 11
11. Appendix C: List of Participants . . . . . . . . . . . . . . 14
12. Informative References . . . . . . . . . . . . . . . . . . . 16
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 17
1. Introduction
The Internet Architecture Board (IAB) holds occasional workshops
designed to consider long-term issues and strategies for the
Internet, and to suggest future directions for the Internet
architecture. The investigated topics often require coordinated
efforts of many organizations and industry bodies to improve an
identified problem. One of the targets of the workshops is to
establish communication between relevant organizations, especially
when the topics are out of the scope for the Internet Engineering
Task Force (IETF). This long-term planning function of the IAB is
complementary to the ongoing engineering efforts performed by working
groups of the IETF.
With the expansion of the Internet of Things (IoT), interoperability
becomes more and more important. Standards Developing Organizations
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(SDOs) have done a tremendous amount of work to standardize new
protocols, and to profile existing protocols.
At the application layer and at the level of solution frameworks,
interoperability is not yet mature. Particularly, the work on data
formats (in the form of data models and information models) has not
seen the same level of consistency throughout SDOs.
One common problem is the lack of an encoding-independent
standardization of the information, the so-called information model.
Another problem is the strong relationship with the underlying
communication architecture, such as a Remote Procedure Call (RPC)
style design or a RESTful design. Furthermore, groups develop
solutions that are very similar on the surface but differ slightly in
their standardized outcome, leading to interoperability problems.
Finally, some groups favor different encodings for use with various
application layer protocols.
Thus, the IAB decided to organize a workshop to reach out to relevant
stakeholders to explore the state-of-the-art and to identify
commonality and gaps [IOTSIAG][IOTSIWS]. In particular, the IAB was
interested to learn about the following aspects:
o What is the state of the art in data and information models? What
should an information model look like?
o What is the role of formal languages, such as schema languages, in
describing information and data models?
o What is the role of metadata, which is attached to data to make it
self-describing?
o How can we achieve interoperability when different organizations,
companies and individuals develop extensions?
o What is the experience with interworking various data models
developed from different groups, or with data models that evolved
over time?
o What functionality should online repositories for sharing schemas
have?
o How can existing data models be mapped against each other to offer
interworking?
o Is there room for harmonization, or are the use cases of different
groups and organizations so unique that there is no possibility
for cooperation?
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o How can organizations better work together to increase awareness
and information sharing?
2. Terminology
The first roadblock to interoperability at the level of data models
is the lack of a common vocabulary to start the discussion.
[RFC3444] provides a starting point by separating conceptual models
for designers, or "information models", from concrete detailed
definitions for implementers, or "data models". There are concepts
that are undefined in that RFC and elsewhere, such as the interaction
with the resources of an endpoint, or "interaction model". Therefore
the three "main" common models that were identified were:
Information Model
An information model defines an environment at the highest level
of abstraction and expresses the desired functionality.
Information models can be defined informally (e.g., in plain
English) or more formally (e.g., UML, Entity-Relationship
Diagrams, etc.). Implementation details are hidden.
Data Model
A data model defines concrete data representations at a lower
level of abstraction, including implementation and protocol-
specific details. Some examples are: SNMP Management Information
Base (MIB) modules, W3C Thing Description (TD) Things, YANG
models, LWM2M Schemas, OCF Schemas, and so on.
Interaction Model
An interaction model defines how data is accessed and retrieved
from the endpoints, being therefore tied to the specific
communication pattern that the system has (e.g., REST methods,
Publish/Subscribe operations, or RPC calls).
Another identified terminology issue is the semantic meaning overload
that some terms have. The meaning can vary depending on the context
in which the term is used. Some examples of such terms are:
semantics, models, encoding, serialization format, media types or
encoding types. Due to time constraints, no concrete terminology was
agreed upon, but work will continue within each organization to
create various terminology documents. The participants agreed to set
up a github repository [IOTSIGIT] for sharing information.
3. What Problems to Solve
The participants agreed that there is not simply a single problem to
be solved, but rather a range. During the workshop the following
problems were discussed:
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o Formal Languages for Documentation Purposes
To simplify review and publication, SDOs need formal descriptions of
their data and interaction models. Several of them use a tabular
representation found in the specification itself, but use a formal
language as an alternative way of describing objects and resources
for formal purposes. Some examples of formal language use are as
follows.
The Open Mobile Alliance (OMA), now OMA SpecWorks, used an XML schema
[LWM2M-Schema] to describe their object and resource definitions.
The XML files of standardized objects are available for download at
[OMNA].
The Bluetooth SIG defined Generic Attributes (GATT) services and
characteristics for use with Bluetooth Smart/Low Energy. The
services and characteristics are shown in a tabular form on the
Bluetooth SIG website at [SIG], and are also defined as XML instance
documents.
The Open Connectivity Foundation (OCF) uses JSON Schemas to formally
define data models, and RAML to define interaction models. The
standard files are available online at OneIoTa.org.
The AllSeen Alliance uses AllJoyn Introspection XML to define data
and interaction models in the same formal language, tailored for RPC-
style interaction. The standard files are available online on the
AllSeen Alliance web site, but both standard and vendor-defined model
files can be obtained by directly querying a device for them at
runtime.
The World-Wide Web Consortium (W3C) uses the Resource Description
Framework (RDF) to define data and interaction models using a format
tailored for the web.
The Internet Engineering Task Force (IETF) uses YANG to define data
and interaction models. Other SDOs may use various other formats.
o Formal Languages for Code Generation
Code generation tools that use formal data and information modelling
languages are needed by developers. For example, the AllSeen Visual
Studio Plugin [AllSeen-Plugin] offers a wizard to generate code based
on the formal description of the data model. Another example of a
data modelling language that can be used for code generation is YANG.
A popular tool to help with code generation of YANG modules is pyang
[PYANG]. An example of a tool that can do code generation for
multiple ecosystems is OpenDOF [OpenDOF]. Use cases discussed for
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code generation included easing development of server-side device
functionality, clients, and compliance tests.
o Debugging Support
Debugging tools are needed that implement generic object browsers,
which use standard data models and/or retrieve formal language
descriptions from the devices themselves. As one example, the NRF
Bluetooth Smart sniffer from Nordic Semiconductor [nRF-Sniffer] can
be used to display services and characteristics defined by the
Bluetooth SIG. As another example, AllJoyn Explorer
[AllJoynExplorer] can be used to browse and interact with any
resource exposed by an AllJoyn device, including both standard and
vendor-defined data models, by retrieving the formal descriptions
from the device at runtime.
o Translation
The working assumption is that devices need to have a common data
model with a priori knowledge of data types and actions. However
that would imply that each consortium/organization will try to define
their own, causing a major interoperability problem, if not a
completely intractable one given the amount of variations,
extensions, compositions or versioning changes that will happen on a
per data model basis.
Another potential approach is to have a minimal ammount of
information on the device to allow for a runtime binding to a
specific model, the objective being to require as little prior
knowledge as possible.
Moreover, gateways, bridges and other similar devices need to
dynamically translate (or map) one data model to another one.
Complexity will increase as there are also multiple protocols and
schemas that make interoperability harder to achieve.
o Runtime Discovery
Runtime discovery allows IoT devices to exchange metadata about the
data, potentially along with the data exchanged itself. In some
cases the metadata not only describes data but also the interaction
model as well. An example of such an approach has been shown with
HATEOAS [HATEOAS]. Another example is that all AllJoyn devices
support such runtime discovery using a protocol mechanism called
"introspection", where the metadata is queried from the device itself
[AllSeen].
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There are various models, whether deployed or possible, for such
discovery. The metadata might be extracted from a specification, or
looked up on a cloud repository (e.g., OneIoTa for OCF models), or
looked up via a vendor's site, or obtained from the device itself
(such as in the AllJoyn case). The relevant metadata might be
obtained from the same place, or different pieces might be obtained
from different places, such as separately obtaining information such
as (a) syntax information, (b) end-user descriptions in a desired
language, and (c) developer-specific comments for implementers.
4. Translation
In an ideal world where organizations and companies cooperate and
agree on a single data model standard, there is no need for gateways
that translate from one data model to the other one. However, this
is far from reality today, and there are many proprietary data models
in addition to the already standardized ones. As a consequence,
gateways are needed to translate between data models. This leads to
(n^2)-n combinations, in the worst case.
There are analogies with gateways back in the 1980s that were used to
translate between network layer protocols. Eventually IP took over,
providing the necessary end-to-end interoperability at the network
layer. Unfortunately, the introduction of gateways leads to the loss
of expressiveness due to the translation between data models. The
functionality of IP was so valuable in the market that advanced
features of other networking protocols became less attractive and
were not used anymore.
Participants discussed an alternative which they called a 'red star',
shown in Figure 1, where data models are translated to a common data
model shown in the middle. This reduces the number of translations
that are needed down to 2n (in the best case). The problem, of
course, is that everyone wants their own data model to be the red
star in the center.
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+-----+ +-----+
| | | |
| | -- -- | |
| | -- -- | |
+-----+ -- -- +-----+
-- ---
-- --
-- --
-- --
--- -- A -- ---
/ \ ___/ \___ / \
| | ---------------', .'--------------- | |
\ / /. ^ .\ \ /
--- /' '\ ---
-- --
-- --
-- --
-- --
-- --
/\ -- -- /\
/ \ -- -- / \
/ \ / \
/ \ / \
/--------\ /--------\
Figure 1: The 'Red Star' in Data/Information Models.
While the workshop itself was not a suitable forum to discuss the
design of such translation in detail, several questions were raised:
o Do we need a "red star" that does everything or could we design
something that offers a more restricted functionality?
o How do we handle loss of data and loss of functionality?
o Should data be translated between data models or data models be
translated?
o How can interaction models be translated? They need to be dealt
with in addition to the data models.
o Many (if not all) data and interaction models have some bizarre
functionality that cannot be translated easily. How can those be
handled?
o What limitations are we going to accept in these translations?
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The participants also addressed the question of when translation
should be done. Two use cases were discussed:
a) Design time: a translation between data model descriptions, such
as translating a YANG model to a RAML/JSON model, can be performed
once, during design time. A single information model might be mapped
to a number of different data models.
b) Run time: Runtime translation of values in two standard data
models can only be algorithmically done when the data model on one
side is algorithmically derived from the data model on the other
side. This was called a "derived model". It was discussed that the
availability of runtime discovery can aid in semantic translation,
such as when a vendor-specific data model on one side of a protocol
bridge is resolved and the translator can algorithmically derive the
semantically-equivalent vendor-specific data model on the other side
of a protocol bridge, as discussed in [BridgeTaxonomy].
The participants agreed that algorithm translation will generally
require custom code, whenever one is translating to anything other
than a derived model.
Participants concluded that it is typically easier to translate data
between systems that follow the same communication architecture.
5. Dealing with change
A large part of the workshop was dedicated to the evolution of
devices and server-side applications. Interactions between devices
and services and how their relationship evolves over time is
complicated by their respective different interaction models.
The workshop participants discussed various approaches to deal with
change. In the most basic case, a developer might use a description
of an API and implement the protocol steps. Sometimes the data or
information model can be used to generate code stubs. Subsequent
changes to an API require changes on the clients to upgrade to the
new version, which requires some development of new code to satisfy
the needs of the new API.
These interactions could be made machine-understandable in the first
place, enabling for changes to happen at runtime. In that scenario,
a machine client could discover the possible interactions with a
service, adapting to changes as they occur without specific code
being developed to adapt to them.
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The challenge seems to be to code the human-readable specification
into a machine-readable format. Machine-readable languages require a
shared vocabulary to give meaning to the tags.
These types of interactions are often based on the REST architectural
style. Its principle is that a device or endpoint only needs a
single entry point with a host providing descriptions of the API in-
band by means of web links and forms.
By defining IoT-specific relation types, it is possible to drive
interactions through links instead of hardcoding URIs into a RESTful
client, thus making the system flexible enough for later changes.
The definition of the basic hypermedia formats for IoT is still work
in progress. However, some of the existing mechanisms can be reused,
such as resource discovery, forms, or links.
6. Security Considerations
There were two types of security considerations discussed: use of
formal data models for security configuration, and security of data
and data models in general.
It was observed that the security assumptions and configuration, or
"security model", varies by ecosystem today, making the job of a
translator difficult. For example, the types of security principals
(e.g., user vs. device vs. application), the use of access control
lists (ACLs) vs. capabilities, and what types of policies can be
expressed, all vary by ecosystem. As a result, the security model
architecture generally dictates where translation can be done.
One approach discussed was whether two endpoints might be able to use
some overlay security model, across a translator between two
ecosystems, which only works if the two endpoints agree on a common
data model for their communication. Another approach discussed was
simply having a translator act as a trusted intermediary, which
allows the translator to be able to translate between different data
models.
One suggestion discussed was potentially adding metadata into either
the formal data model language, or accompanying the data values over
the wire, tagging the data with privacy levels. However, sometimes
even the privacy level of information might itself be sensitive.
Still, it was observed that being able to dynamically learn security
requirements might help provide better UIs and translators.
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7. Collaboration
The participants discussed how best to share information among their
various organizations. One discussion was around having joint
meetings. One current challenge reported was that organizations were
not aware of when and where each others' meetings were scheduled, and
sharing such information could help organizations better collocate
meetings. To facilitate this exchange, the participants agreed to
add links to their respective meeting schedules from a common page in
the IOTSI repository [IOTSIGIT].
Another challenge reported was that organizations did not know how to
find each others' published data models, and sharing such information
could better facilitate reuse of the same information model. To
facilitate this exchange, this participants discussed whether a
common repository might be used by multiple organizations. The OCF's
OneIoTa repository was discussed as one possibility but it was
reported that its terms of use at the time of the workshop prevented
this. The OCF agreed to take this back and look at updating the
terms of use to allow other organizations to use it too, as the
restriction was not the intent. Schema.org was discussed as another
possibility. In the meantime, the participants agreed to add links
to their respective repositories from a common page in the IOTSI
repository [IOTSIGIT].
It was also agreed that the iotsi@iab.org mailing list would remain
open and available for sharing information between all relevant
organizations.
8. Acknowledgements
We would like to thank all paper authors and participants for their
contributions, and Ericsson for hosting the workshop.
9. Appendix A: Program Committee
This workshop was organized by the following individuals: Jari Arkko,
Ralph Droms, Jaime Jimenez, Michael Koster, Dave Thaler, and Hannes
Tschofenig.
10. Appendix B: Accepted Position Papers
o Jari Arkko, "Gadgets and Protocols Come and Go, Data Is Forever"
o Carsten Bormann, "Noise in specifications hurts"
o Benoit Claise, "YANG as the Data Modelling Language in the IoT
space"
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o Robert Cragie, "The ZigBee Cluster Library over IP"
o Dee Denteneer, Michael Verschoor, Teresa Zotti, "Fairhair:
interoperable IoT services for major Building Automation and
Lighting Control ecosystems"
o Universal Devices, "Object Oriented Approach to IoT
Interoperability"
o Bryant Eastham, "Interoperability and the OpenDOF Project"
o Stephen Farrell, Alissa Cooper, "It's Often True: Security's
Ignored (IOTSI) - and Privacy too"
o Christian Groves, Lui Yan, ang Weiwei, "Overview of IoT semantics
landscape"
o Ted Hardie, "Loci of Interoperability for the Internet of Things"
o Russ Housley, "Vehicle-to-Vehicle and Vehicle-to-Infrastructure
Communications"
o Jaime Jimenez, Michael Koster, Hannes Tschofenig, "IPSO Smart
Objects"
o David Jones, IOTDB - "Interoperability Through Semantic
Metastandards"
o Sebastian Kaebisch, Darko Anicic, "Thing Description as Enabler of
Semantic Interoperability on the Web of Things"
o Achilleas Kemos, "Alliance for Internet of Things Innovation
Semantic Interoperability Release 2.0, AIOTI WG03 - IoT
Standardisation"
o Ari Keraenen, Cullen Jennings, "SenML: simple building block for
IoT semantic interoperability"
o Dongmyoung Kim, Yunchul Choi, Yonggeun Hong, "Research on Unified
Data Model and Framework to Support Interoperability between IoT
Applications"
o Michael Koster, "Model-Based Hypertext Language"
o Matthias Kovatsch, Yassin N. Hassan, Klaus Hartke, "Semantic
Interoperability Requires self describing Interaction Models"
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o Kai Kreuzer, "A Pragmatic Approach to Interoperability in the
Internet of Things"
o Barry Leiba, "Position Paper"
o Marcello Lioy, "AllJoyn"
o Kerry Lynn, Laird Dornin, "Modeling RESTful APIs with JSON Hyper-
Schema"
o Erik Nordmark, "Thoughts on IoT Semantic Interoperability: Scope
of security issues"
o Open Geospatial Consortium, "OGC SensorThings API: Communicating
"Where" in the Web of Things"
o Jean Paoli, Taqi Jaffri, "IoT Information Model Interoperability:
An Open, Crowd-Sourced Approach in Three Parallel Parti"
o Joaquin Prado, "OMA Lightweight M2M Resource Model"
o Dave Raggett, Soumya Kanti Datta, "Input paper for IAB Semantic
Interoperability Workshop"
o Pete Rai, Stephen Tallamy, "Semantic Overlays Over Immutable Data
to Facilitate Time and Context Specific Interoperability"
o Jasper Roes, Laura Daniele, "Towards semantic interoperability in
the IoT using the Smart Appliances REFerence ontology (SAREF) and
its extensions"
o Max Senges, "Submission for IAB IoT Sematic Interoperability
workshop"
o Bill Silverajan, Mert Ocak, Jaime Jimenez, "Implementation
Experiences of Semantic Interoperability for RESTful Gateway
Management"
o Ned Smith, Jeff Sedayao, Claire Vishik, "Key Semantic
Interoperability Gaps in the Internet-of-Things Meta-Models"
o Robert Sparks and Ben Campbell, "Considerations for certain IoT
based services"
o J. Clarke Stevens, "Open Connectivity Foundation oneIoTa Tool"
o J. Clarke Stevens, Piper Merriam, "Derived Models for
Interoperability Between IoT Ecosystems"
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o Ravi Subramaniam, "Semantic Interoperability in Open Connectivity
Foundation (OCF) - formerly Open Interconnect Consortium (OIC)""
o Andrew Sullivan, "Position paper for IOTSI workshop"
o Darshak Thakore, "IoT Security in the context of Semantic
Interoperability"
o Dave Thaler, "IoT Bridge Taxonomy"
o Dave Thaler, S"ummary of AllSeen Alliance Work Relevant to
Semantic Interoperability"
o Mark Underwood, Michael Gruninger, Leo Obrst, Ken Baclawski, Mike
Bennett, Gary Berg-Cross, Torsten Hahmann, Ram Sriram, "Internet
of Things: Toward Smart Networked Systems and Societies"
o Peter van der Stok, Andy Bierman, "YANG-Based Constrained
Management Interface (CoMI)"
11. Appendix C: List of Participants
o Andy Bierman, YumaWorks
o Carsten Bormann, Uni Bremen/TZI
o Ben Campbell, Oracle
o Benoit Claise, Cisco
o Alissa Cooper, Cisco
o Robert Cragie, ARM Limited
o Laura Daniele, TNO
o Bryant Eastham, OpenDOF
o Christian Groves, Huawei
o Ted Hardie, Google
o Yonggeun Hong, ETRI
o Russ Housley, Vigil Security
o David Janes, IOTDB
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o Jaime Jimenez, Ericsson
o Shailendra Karody, Catalina Labs
o Ari Keraenen, Ericsson
o Michael Koster, SmartThings
o Matthias Kovatsch, Siemens
o Kai Kreuzer, Deutsche Telekom
o Barry Leiba, Huawei
o Steve Liang, Uni Calgary
o Marcello Lioy, Qualcomm
o Kerry Lynn, Verizon
o Mayan Mathen, Catalina Labs
o Erik Nordmark, Arista
o Jean Paoli, Microsoft
o Joaquin Prado, OMA
o Dave Raggett, W3C
o Max Senges, Google
o Ned Smith, Intel
o Robert Sparks, Oracle
o Ram Sriram, NIST
o Clarke Stevens
o Ram Subramanian, Intel
o Andrew Sullivan, DIN
o Darshak Thakore, CableLabs
o Dave Thaler, Microsoft
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o Hannes Tschofenig, ARM Limited
o Michael Verschoor, Philips Lighting
12. Informative References
[AllJoynExplorer]
Microsoft, "AllJoyn Explorer", 2016.
[AllSeen] Thaler, D., "Summary of AllSeen Alliance Work Relevant to
Semantic Interoperability", 2016, <https://www.iab.org/wp-
content/IAB-uploads/2016/03/AllSeen-summary-IOTSI.pdf>.
[AllSeen-Plugin]
Rockwell, B., "Using the AllJoyn Studio Extension", 2016.
[BridgeTaxonomy]
Thaler, D., "IoT Bridge Taxonomy", 2016,
<https://www.iab.org/wp-content/IAB-uploads/2016/03/
DThaler-IOTSI.pdf>.
[HATEOAS] Kovatsch, M., "Semantic Interoperability Requires Self-
describing Interaction Models - HATEOAS for the Internet
of Things", Proceedings of the IoT Semantic
Interoperability Workshop 2016, 2016,
<https://www.iab.org/wp-content/IAB-uploads/2016/03/2016-
IAB-HATEOAS.pdf>.
[IOTSIAG] IAB, "IoT Workshop for Semantic Interoperability (IOTSI) -
Agenda and Slides", 2016,
<https://www.iab.org/activities/workshops/iotsi/agenda/>.
[IOTSIGIT]
IOTSI, "Github Collaborative Repository", 2016,
<https://github.com/iotsi/iotsi>.
[IOTSIWS] IAB, "IoT Workshop for Semantic Interoperability (IOTSI)
2016 - Main Page and Position Papers", 2016,
<https://www.iab.org/activities/workshops/iotsi/>.
[LWM2M-Schema]
OMA, "OMA LWM2M XML Schema", 2018.
[nRF-Sniffer]
Nordic Semiconductor, "nRF Sniffer - Smart/Bluetooth low
energy packet sniffer", 2016.
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[OMNA] OMA, "OMNA Lightweight M2M (LWM2M) Object & Resource
Registry", 2018.
[OpenDOF] OpenDOF, "The OpenDOF Project", 2015,
<https://opendof.org>.
[PYANG] Bjorklund, M., "An extensible YANG validator and converter
in python", 2016.
[RFC3444] Pras, A. and J. Schoenwaelder, "On the Difference between
Information Models and Data Models", RFC 3444,
DOI 10.17487/RFC3444, January 2003, <https://www.rfc-
editor.org/info/rfc3444>.
[SIG] Bluetooth SIG, "GATT Specifications", 2018,
<https://www.bluetooth.com/specifications/gatt>.
Authors' Addresses
Jaime Jimenez
Ericsson
Email: jaime.jimenez@ericsson.com
Hannes Tschofenig
Arm Ltd.
Email: hannes.tschofenig@arm.com
Dave Thaler
Microsoft
Email: dthaler@microsoft.com
Jimenez, et al. Expires January 3, 2019 [Page 17]
