In-Network Computing for App-Centric Micro-Services
draft-sarathchandra-coin-appcentres-01
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| Authors | Chathura Sarathchandra , Dirk Trossen , Michael Boniface | ||
| Last updated | 2019-10-30 (Latest revision 2019-05-02) | ||
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draft-sarathchandra-coin-appcentres-01
COIN C. Sarathchandra
INTERNET-DRAFT D. Trossen
Intended Status: Informational InterDigital Europe, Ltd.
Expires: May 2, 2020 M. Boniface
University of Southampton
October 30, 2019
In-Network Computing for App-Centric Micro-Services
draft-sarathchandra-coin-appcentres-01
Abstract
The application-centric deployment of 'Internet' services has
increased over the past ten years with many million applications
providing user-centric services, executed on increasingly more
powerful smartphones that are supported by Internet-based cloud
services in distributed data centres, the latter mainly provided by
large scale players such as Google, Amazon and alike. This draft
outlines a vision of evolving those data centres towards executing
app-centric micro-services; we dub this evolved data centre as an
AppCentre. Complemented with the proliferation of such AppCentres at
the edge of the network, they will allow for such micro-services to
be distributed across many places of execution, including mobile
terminals themselves, while specific micro-service chains equal
today's applications in existing smartphones. We outline the key
enabling technologies that needs to be provided for such evolution to
be realized, including references to ongoing IETF work in some
areas.
Status of this Memo
This Internet-Draft is submitted to IETF in full conformance with the
provisions of BCP 78 and BCP 79.
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The list of current Internet-Drafts can be accessed at
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http://www.ietf.org/1id-abstracts.html
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http://www.ietf.org/shadow.html
Copyright and License Notice
Copyright (c) 2019 IETF Trust and the persons identified as the
document authors. All rights reserved.
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Table of Contents
1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . 3
2 Terminology . . . . . . . . . . . . . . . . . . . . . . . . . . 4
3. Use Cases . . . . . . . . . . . . . . . . . . . . . . . . . . 4
3.1 Mobile Application Function Offloading . . . . . . . . . . . 4
3.2 Collaborative Gaming . . . . . . . . . . . . . . . . . . . 6
4 Enabling Technologies . . . . . . . . . . . . . . . . . . . . . 6
4.1 Application Packaging . . . . . . . . . . . . . . . . . . . 6
4.2 Service Deployment . . . . . . . . . . . . . . . . . . . . 7
4.3 Service Routing . . . . . . . . . . . . . . . . . . . . . . 8
4.4 Service Pinning . . . . . . . . . . . . . . . . . . . . . . 9
4.5 State Synchronisation . . . . . . . . . . . . . . . . . . . 9
5 Security Considerations . . . . . . . . . . . . . . . . . . . . 9
6 IANA Considerations . . . . . . . . . . . . . . . . . . . . . . 9
7 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . 9
8 References . . . . . . . . . . . . . . . . . . . . . . . . . . 10
8.1 Normative References . . . . . . . . . . . . . . . . . . . 10
8.2 Informative References . . . . . . . . . . . . . . . . . . 10
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . . 11
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1 Introduction
With the increasing dominance of smartphones and application markets,
the end-user experiences today have been increasingly centered around
the applications and the ecosystems that smartphone platforms create.
The experience of the 'Internet' has changed from 'accessing a web
site through a web browser' to 'installing and running an application
on a smartphone'. This app-centric model has changed the way services
are being delivered not only for end-users, but also for business-to-
consumer (B2C) and business-to-business (B2B) relationships.
Designing and engineering applications is largely done statically at
design time, such that achieving significant performance improvements
thereafter has become a challenge (especially, at runtime in response
to changing demands and resources). Applications today come
prepackaged putting them at disadvantage for improving efficiency due
to the monolithic nature of the application packaging. Decomposing
application functions into micro-services [MSERVICE1] [MSERVICE2]
allows applications to be packaged dynamically at run-time taking
varying application requirements and constraints into consideration.
Interpreting an application as a chain of micro-services, allows the
application structure, functionality, and performance to be adapted
dynamically at runtime in consideration of tradeoffs between quality
of experience, quality of service and cost.
Interpreting any resource rich networked computing (and storage)
capability not just as a pico or micro-data centre, but as an
application-centric execution data centre (AppCentre), allows
distributed execution of micro-services. These micro-services may
then be deployed on the most appropriate AppCentre (edge/fog/cloud
resources) to satisfy requirements under varying constraints. In
addition, the high degree of distribution of application and data
partitions, and compute resources offered by the execution
environment decentralizes control between multiple cooperating
parties (multi-technology, multi-domain, multi-ownership
environments).
The emergence of AppCentreS will democratise infrastructure and
service provision to anyone with compute resources, while app-centric
computing provides a truly pervasive user experience. Moreover, this
will lead to new forms of application interactions and experiences
based on cooperative AppCentreS (pico-micro and large cloud data
centres), in which applications are being designed, (micro-services)
dynamically composed and executed.
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2 Terminology
The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT",
"SHOULD", "SHOULD NOT", "RECOMMENDED", "MAY", and "OPTIONAL" in this
document are to be interpreted as described in RFC 2119 [RFC2119].
3. Use Cases
3.1 Mobile Application Function Offloading
The App-centric model increases the ubiquity of computing elements
available for execution of application functions. Most functions can
be categorised into any of three, "receiving", "processing" and
"displaying" function groups. Partitioning an application into micro-
services allows for denoting the application as a sequence of
receiving->processing->displaying, for a flexible composition and
distributed execution. Any device may realize one or more of the
micro-services of an application and expose them to the execution
environment. When the micro-service sequence is executed on a single
device, the outcome is what you see today as applications running on
mobile devices. However, if any of the three functions are terminated
on the device (e.g., for optimising the experience), the execution of
the rest of the functions may be moved to other suitable devices
which have exposed the corresponding micro-services to the
environment. The result of the latter is flexible mobile function
offloading, for possible reduction of power consumption (e.g.,
offloading CPU intensive process functions to a remote server) or for
improved device capabilities (e.g., moving display functions to a
nearby smart TV).
The above scenario can be exemplified in an immersive gaming
application, where a single user plays a game using a VR headset. The
headset hosts functions that "display" frames to the user, as well as
the functions for VR content processing and frame rendering combining
with input data received from sensors in the VR headset. Once this
application is partitioned into micro-services and deployed in an
app-centric execution environment, only the "display" micro-service
is left in the headset, while the compute intensive real-time VR
content processing micro-services can be offloaded to a nearby
resource rich home PC, for a better execution (faster and possibly
higher resolution generation).
Figure 1 shows one realisation of the above scenario, where a 'DPR
app' running on a mobile device (containing the partitioned
Display(D), Process(P) and Receive(R) micro services) over an SDN
network. The packaged applications are made available through a
localised 'playstore server'. The application installation is
realized as a 'service deployment' process (Section 4.2.), combining
the local app installation with a distributed micro-service
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deployment (and orchestration) on most suitable AppCentreS
('processing server').
+----------+
Mobile |Processing|
+---------+ | Server |
| App | +----------+
| +-----+ | |
| |D|P|R| | +--+
| +-----+ | |SR| Internet
| +-----+ | +--+ /
| | SR | | | /
| +-----+ | +----------+ +------+
+---------+ /|SDN Switch|_____|Border|
\ +-------+ / +----------+ | SR |
\| 5GAN |/ | +------+
+-------+ |
|
+----------+
+---------+ /|SDN Switch|
| +-----+ | +-------+ / +----------+
| | SR | | /|WIFI AP|/ \
| +-----+ | / +-------+ +--+
|+-------+|/ |SR|
||Display|| /+--+
|| || +---------+
|+-------+| |Playstore|
+---------+ | Server |
TV +---------+
Figure 1: Application Function Offloading Example
Such localized deployment could, for instance, be provided by a
visiting site, such as a hotel or a theme park. Once the 'processing'
micro-service is terminated on the mobile device, the 'service
routing' (SR) elements in the network (Section 4.3.) route requests
to the previously deployed 'processing' micro-service running on the
'processing server' AppCentre over an existing SDN network.
Any app-centric execution environment MUST provide means for
dynamically choosing the best possible micro-service sequence (i.e.,
chaining of micro-services) for a given application experience. Any
solution SHOULD also provide methods for choosing and/or deploying
the best possible instances of micro-services in the app-centric
execution environment, for service routing, and for pinning the
resources to the corresponding micro-services.
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3.2 Collaborative Gaming
There has been a recent shift from applications that provide single-
user experiences, such as the ones described in the previous section
to collaborative/cooperative experiences such as multi-user gaming
and mixed/virtual reality. The latter leads to increasing amounts of
interaction where input (e.g., gesture, gaze, touch, movement) and
output (e.g., visual display, sound, and actuation) needs to be
processed within strict timing constraints and synchronized to ensure
temporal and spatial consistency with local and distant users. App-
centric design allows functions with high data and process coupling
to be modularised, deployed and executed, such that the subset of
micro-services is cooperatively executed towards optimising multi-
user experiences.
The same example in previous section can be envisaged from a multi-
player gaming scenario. Here the micro-services that need to be
executed cooperatively are executed in a localised and synchronised
manner for player coordination and synchronizing interaction and
state between collaborating players.
Any app-centric execution environment MUST provide means for real-
time synchronization and consistency of distributed application
states.
4 Enabling Technologies
4.1 Application Packaging
Applications often consist of one or more sub-elements (e.g., audio,
visual, hepatic elements) which are 'packaged' together, resulting in
the final installable software artifact. Conventionally, application
developers perform the packaging process at design time, by packaging
a set of software components as a (often single) monolithic software
package, for satisfying a set of predefined application
requirements.
Decomposing micro-services of an application, and then executing them
on peer execution points in AppCentreS (e.g., on an app-centric
serverless runtime [SRVLESS]) can be done with design-time planning.
Micro-service decomposition process involves, defining clear
boundaries of the micro-service (e.g., using wrapper classes for
handling input/output requests), which could be done by the
application developer at design-time (e.g., through Android app
packaging by including, as part of the asset directory, a service
orchestration template [TOSCA] that describes the decomposed micro-
services). Likewise, the peer execution points could be 'known' to
the application (e.g., using well-known and fixed peer execution
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points on AppCentreS) and incorporated with the micro-services by the
developer at design-time.
Existing programming frameworks address decomposition and execution
of applications centering around other aspects such as concurrency
[ERLANG]. For decomposing at runtime, application elements can be
profiled using various techniques such as dynamic program analysis or
dwarf application benchmarks. The local profiler information can be
combined with the profiler information of other devices in the
network for improved accuracy. The output of such a profiler process
can then be used to identify smaller constituting sub-components of
the application in forms of pico-services, their interdependencies
and data flow (e.g., using caller/callee information, instruction
usage). Due to the complex nature of resulting application structure
and therefore its increased overhead, in most cases, it may not be
optimal to decompose applications at the pico level. Therefore, one
may cluster pico-services into micro-services with common
characteristics, enabling a meaningful (e.g., clustering pico-
services with same resource dependency) and a performant
decomposition of applications. Characteristics of micro-services can
be defined as a set of concepts using an ontology language, which can
then be used for clustering similar pico-services into micro-
services. Micro-services may then be partitioned along their
identified borders. Moreover, mechanisms for governance, discovery
and offloading can be employed for 'unknown' peer execution points on
AppCentreS with distributed loci of control.
Therefore, with this app-centric model, application packaging can be
done at runtime by constructing micro-service chains for satisfying
requirements of experiences (e.g., interaction requirements), under
varying constraints (e.g., temporal consistency between multiple
players within a shared AR/VR world)[SCOMPOSE]. Such packaging
includes mechanisms for selecting the best possible micro-services
for a given experience at runtime in the multi-X environment. These
run-time packaging operations may continuously discover the 'unknown'
and adapt towards an optimal experience. Such decision mechanisms
handle the variability, volatility and scarcity within this multi-X
framework.
4.2 Service Deployment
The service function chains, constituting each individual
application, will need deployment mechanisms in a true multi-X
(multi-user, multi-infrastructure, multi-domain) environment
[SDEPLOY1][SDEPLOY2]. Most importantly, application installation and
orchestration processes are married into one, as a set of procedures
governed by device owners directly or with delegated authority.
However, apart from extending towards multi-X environments, the
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process also needs to cater for changes in the environment, caused,
e.g., by movement of users, new pervasive sensors/actuators, and
changes to available infrastructure resources. Methods to deploy
service functions as executable code into chosen service execution
points, supporting the various endpoint realizations (e.g., device
stacks, COTS stacks, etc.), and service function endpoint realization
through utilizing existing and emerging virtualisation techniques.
A combination of application installation procedure and orchestrated
service deployment can be achieved by utilizing the application
packaging with integrated service deployment templates described in
Section 4.1 such that the application installation procedure on the
installing device is being extended to not only install the local
application package but also extract the service deployment template
for orchestrating with the localized infrastructure, using, for
instance, REST APIs for submitting the template to the orchestrator.
4.3 Service Routing
Service routing within a combined compute and network infrastructure
that will enable true end-to-end experiences across distributed
application execution points provisioned on distant cloud, edge and
device-centric resources (e.g., using ICN/name-based routing
methods), is a key aspect of app-centric micro-service execution.
Once the micro-services are packaged and deployed in such highly
distributed micro-data centres, the routing mechanisms will ensure
efficient information exchange (e.g., for satisfying application
requirements) between corresponding micro-services within the multi-X
execution environment.
Routing becomes a problem of routing the micro-service requests, not
just packets, as done through IP. Traditionally, the combination of
the Domain Naming Service (DNS) and IP routing has been used for this
purpose. However, the advent of virtualisation with use cases such as
those outlined above have made it challenging to further rely on the
DNS. This is mainly down to the long delay in updating DNS entries to
'point' to the right micro-service instances. If one was to use the
DNS, would be updating the DNS entries at a high rate, caused by the
diversity of trigger, e.g., through movement. DNS has not been
designed for such frequent update, rendering it useless for such
highly dynamic applications. With many edge scenarios in the VR/AR
space demanding interactivity and being latency-sensitive, efficient
routing will be key to any solution.
Various ongoing work on service request forwarding [nSFF] with the
service function chaining [RFC7665] framework as well as name-based
routing [ICN5G][ICN4G] address some aspects described above. However,
further extensions to those need to be considered supporting an app-
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centric model.
4.4 Service Pinning
Allocating the right resources to the right micro-services is a
fundamental task when executing micro-services on such highly
distributed app-centric micro-data centres (e.g., resource management
in cloud [CLOUDFED]), particularly in the light of volatile resource
availability as well as concurrent and highly dynamic resource
access. Once the specific set of micro-services of an application has
been identified, during the lifetime of the application, requirements
(e.g., QoS) must be ensured by the execution environment. Therefore,
all micro-data centres and the execution environment will realize
mechanisms for ensuring the utilization of specific resources within
a pool of resources (i.e., resources in all app-centric micro-data
centres), for a specific set of micro-services belonging to one
application, while also ensuring integrity in the wider system.
4.5 State Synchronisation
Given the highly distributed nature of app-centric micro-services,
their state exchange and synchronisation is a very crucial aspect for
ensuring in-application and system wide consistency. Mechanisms that
ensure consistency will ensure that data is synchronised with
different spatial, temporal and relational data within a given time
period.
5 Security Considerations
N/A
6 IANA Considerations
N/A
7 Conclusion
This draft positions the evolution of data centres as one of becoming
execution centres for the app-centric experiences provided today by
smartphones. With the proliferation of data centres closer to the end
user in the form of edge-based micro data centres, we believe that
app-centric experiences will ultimately be executed across those
many, highly distributed execution points that this increasingly rich
edge environment will provide. Although a number of activities are
currently underway to address some of the challenges for realizing
such AppCentre evolution, we believe that the COIN research group
will provide a suitable forum to drive forward the remaining research
and its dissemination into working systems and the necessary
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standardization of key aspects and protocols. Future work on this
draft will focus on contributing its main points to an evolving
research roadmap that we would see as a possible outcome of the COIN
RG.
8 References
8.1 Normative References
[RFC2119] Bradner, S., "Key words for use in RFCs to Indicate
Requirement Levels", BCP 14, RFC 2119, DOI
10.17487/RFC2119, March 1997, <https://www.rfc-
editor.org/info/rfc2119>.
[RFC7665] Halpern, J., Ed., and C. Pignataro, Ed., "Service Function
Chaining (SFC) Architecture", RFC 7665, DOI
10.17487/RFC7665, October 2015, <https://www.rfc-
editor.org/info/rfc7665>.
8.2 Informative References
[MSERVICE1] Dragoni, N., Giallorenzo, S., Lafuente, A. L., Mazzara,
M., Montesi, F., Mustafin, R., & Safina, L. (2017).
Microservices: yesterday,today, and tomorrow. In Present
and Ulterior Software Engineering (pp. 195-216). Springer,
Cham.
[MSERVICE2] Balalaie, A., Heydarnoori, A., & Jamshidi, P. (2016).
Microservices architecture enables devops: Migration to a
cloud-native architecture. IEEE Software, 33(3), 42-52.
[SRVLESS] C. Cicconetti, M. Conti and A. Passarella, "An
Architectural Framework for Serverless Edge Computing:
Design and Emulation Tools," 2018 IEEE International
Conference on Cloud Computing Technology and Science
(CloudCom), Nicosia, 2018, pp. 48-55. doi:
10.1109/CloudCom2018.2018.00024
[TOSCA] Topology and Orchestration Specification for Cloud
Applications Version 1.0. 25 November 2013. OASIS
Standard. <http://docs.oasis-
open.org/tosca/TOSCA/v1.0/os/TOSCA-v1.0-os.html>.
[ERLANG] Armstrong, Joe, et al. "Concurrent programming in ERLANG."
(1993).
[SCOMPOSE] M. Hirzel, R. Soule, S. Schneider, B. Gedik, and R. Grimm,
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"A Catalog of Stream Processing Optimizations", ACM
Computing Surveys,46(4):1-34, Mar. 2014
[SDEPLOY1] Lu, H., Shtern, M., Simmons, B., Smit, M., & Litoiu, M.
(2013, June). Pattern-based deployment service for next
generation clouds. In 2013 IEEE Ninth World Congress on
Services (pp. 464-471). IEEE.
[SDEPLOY2] Eilam, T., Elder, M., Konstantinou, A. V., & Snible, E.
(2011, May). Pattern-based composite application
deployment. In 12th IFIP/IEEE International Symposium on
Integrated Network Management (IM 2011) and Workshops (pp.
217-224). IEEE.
[nSFF] Trossen, D., Purkayastha, D., Rahman, A., "Name-Based
Service Function Forwarder (nSFF) component within SFC
framework", <https://datatracker.ietf.org/doc/draft-
trossen-sfc-name-based-sff> (work in progress), April
2019.
[ICN5G] Ravindran, R., Suthar, P., Trossen, D., Wang, C., White,
G., "Enabling ICN in 3GPP's 5G NextGen Core Architecture",
<https://tools.ietf.org/html/draft-ravi-icnrg-5gc-icn-03>
(work in progress), March 2019.
[ICN4G] Suthar, P., Jangam, Ed., Trossen, D., Ravindran, R.,
"Native Deployment of ICN in LTE, 4G Mobile Networks",
<https://tools.ietf.org/html/draft-irtf-icnrg-icn-lte-4g-
03> (work in progress), March 2019.
[CLOUDFED] M. Liaqat, V. Chang, A. Gani, S. Hafizah Ab Hamid, M.
Toseef, U. Shoaib, R. Liaqat Ali, "Federated cloud
resource management: Review and discussion", Elsevier
Journal of Network and Computer Applications, 2017.
Authors' Addresses
Chathura Sarathchandra
InterDigital Europe, Ltd.
64 Great Eastern Street, 1st Floor
London EC2A 3QR
United Kingdom
Email: Chathura.Sarathchandra@InterDigital.com
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Dirk Trossen
InterDigital Europe, Ltd.
64 Great Eastern Street, 1st Floor
London EC2A 3QR
United Kingdom
Email: Dirk.Trossen@InterDigital.com
Michael Boniface
University of Southampton
University Road
Southampton SO17 1BJ
United Kingdom
Email: mjb@it-innovation.soton.ac.uk
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