Computing in Network Research Group P. Liu
Internet-Draft H. Yao
Intended status: Informational L. Geng
Expires: May 5, 2021 China Mobile
November 1, 2020
Differential Computing Resource Reservation
draft-liu-coin-differential-reservation-01
Abstract
Computing in the network may require the embedded computing
capability in the network device, such as gateway, switch, etc, and
there might be so much distributed computing task in the network.
Some new applications like AR/VR, motion control put forward higher
demand of network than before, and AI is also considered to be used
in the app and network. In order to satisfy the demands, it needs to
guarantee both the bandwidth resource and the computing resource
which is linked by the network.
Requirements Language
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].
Status of This Memo
This Internet-Draft is submitted in full conformance with the
provisions of BCP 78 and BCP 79.
Internet-Drafts are working documents of the Internet Engineering
Task Force (IETF). Note that other groups may also distribute
working documents as Internet-Drafts. The list of current Internet-
Drafts is at https://datatracker.ietf.org/drafts/current/.
Internet-Drafts are draft documents valid for a maximum of six months
and may be updated, replaced, or obsoleted by other documents at any
time. It is inappropriate to use Internet-Drafts as reference
material or to cite them other than as "work in progress."
This Internet-Draft will expire on May 5, 2021.
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Table of Contents
1. Overview . . . . . . . . . . . . . . . . . . . . . . . . . . 2
2. Serial Distributed Computing Model . . . . . . . . . . . . . 3
3. Problems of Existing Protocol . . . . . . . . . . . . . . . . 4
4. Reference Method . . . . . . . . . . . . . . . . . . . . . . 5
4.1. Distributed Resource Reservation . . . . . . . . . . . . 5
4.2. Centralized Resource Reservation . . . . . . . . . . . . 6
4.2.1. PCEP . . . . . . . . . . . . . . . . . . . . . . . . 7
4.2.2. Netconf/Yang . . . . . . . . . . . . . . . . . . . . 7
5. Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . 8
6. Security Considerations . . . . . . . . . . . . . . . . . . . 8
7. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 8
8. Normative References . . . . . . . . . . . . . . . . . . . . 8
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 9
1. Overview
From cloud computing to edge computing, computing power is
distributed and extends to customers. In the future network and
computing integration system, computing power will be distributed in
all nodes as ubiquitous endogenous resources. The user's request can
be satisfied by calling the nearest node resource, which is no longer
limited to a specific node.
The basic topology abstraction of traditional Internet architecture
is the end-to-end model: the network is in the middle, the computing
is in the periphery, and the host realizes the logical virtual full
connection through the network. In the trend of network and
computing convergence, computing resource may be embedded in the
network. From the perspective of completing users' computing tasks,
embedded resources are no longer peer-to-peer relationship, but need
to consider the different distances and network conditions.
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There are two kinds of ideas of the convergence, One is from the
perspective of the network, to realize the perception of computing
resources based on the network, so as to perform routing, scheduling,
etc. The other is from the perspective of the data center, to
realize the perception of network status based on the data center,
and apply the scheduling of microservices and other architectures to
a wide range network.
Some researching on computing and network convergence has been
carried out in standardization organizations, including many network
architectures proposed by operators. However, no matter who is the
subject of perception, it is to provide better services, so the
network and computing will develop in a more refined direction.
Based on the perspective of network aware computing resources, this
draft analyzes the problems of resource reservation in the trend of
network and computing convergence, and put forwards the corresponding
reference schemes.
The reservation of traditional network resources is same in an end-
to-end path, which means the reserved bandwidth resources will not
change from the client to the server, but computing is different.
Distributed computing will bring different computing power, and
different resources need to be reserved for different nodes. For
example, AI algorithm now has a model of step-by-step iteration at
multiple nodes. The previous iteration will affect the next
calculation results, and the computing resources required for each
iteration are not the same. From the perspective of network
standard, we hope to regard computing resources as the dimensions to
measure network performance, such as the same bandwidth, path, etc.,
while the traditional technologies of resource reservation have not
considered the reservation of computing resources, and have not
considered the differentiated resource reservation model.
2. Serial Distributed Computing Model
In the model of computing in the network, the computing resource may
be distributed in multiple nodes. A task may be divided into several
parts to be executed by multiple nodes, including serial distribution
and parallel distribution. Parallel distribution can reserve
resources separately. However, in the serial computing model, the
calculation process of serial distribution algorithm is sequential,
and the results of the previous calculation need to be used in the
later calculation, so it will bring the following two
characteristics:
Different computing nodes on the same path need different reserved
computing resources.
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The bandwidth resources to be reserved maybe different after the
previous calculations in the same path.
A typical example is the artificial intelligence algorithm, which
involves the multi-layer convolution iterative process and can be
completed by multiple computing device in serial. As shown in the
figure, 20%, 30% and 50% tasks are calculated on network device 1, 3
and server respectively, and the calculation results of device 1 will
affect the subsequent calculation of device 3 and server. Then,
Network device 1, 3 and server need to reserve corresponding
computing resources respectively.
Since devices 1 and 3 calculated, the traffic will change after
passing through devices 1 and 3, so the bandwidth resources to be
reserved are different.
+------+ +--------+
|Client| ->| Server |
+------+ \ +--------+ +--------+ +--------+ / +--------+
\->|network | |network | |network |->/ 50% of
|device 1|-->|device 2|-->|device 3| computing
+--------+ +--------+ +--------+ tasks
20% of 30% of
computing computing
tasks tasks
Serial distributed computing model
3. Problems of Existing Protocol
Existing resource reservation protocols work on different layers of
network, such as Resource ReSerVation Protocol(RSVP) and Path
Computation Element Protocol (PCEP) . RSVP is a traditional protocol,
which only focuses on how to initiate the reservation of resources,
not the establishment of path. Later, RSVP-TE protocol was developed
for MPLS. PCEP was designed to separate the path calculation and
path establishment functions of RSVP-TE firstly, which means that the
path calculation part before resource reservation can be realized.
Therefore, RSVP and PCEP can be used together or separately.
However, thoes protocols have some problem when meets the computing
tasks:
First, they do not consider the computing attribute, also can't carry
the value of reserved computing resource.
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Second, The reserved value of bandwidth resource along the path is
unchanged.
It should be noted that we only analyzes the resource reservation
protocol in the network field. For the resource reservation of
microservice architecture, there may be problems of applying the
microservice architecture in the operator network, so it will not be
analyzed for the time being.
4. Reference Method
This section provides distributed and centralized resource
reservation reference scheme based on the existing protocol of
network. It should be noted that for serial distributed computing,
we assume that the application side implements the following
functions:
The number of steps are involved in the calculation.
The computing proportion of calculation required at each node.
For bandwidth changes after each step of calculation, if this item
cannot be implemented, the same bandwidth resources will be reserved
by default.
4.1. Distributed Resource Reservation
Distributed resource reservation can be implemented by extending RSVP
or RSVP-TE protocol. The server receives the client's service
request, calculating the resource reservation strategy and return it.
The process is as follows:
1. The client sends the service request, carrying the service
requirements and the collected resource status of each node on the
path. They will be collected and added to the information that
carried by the service request.
2. The server receives the client's service request, then generates
the resource reservation strategy for target nodes on the path based
on the the service requirements and the resource status of each node,
and return the resource reservation strategy to each target node
along the path to reserve the resource.
The resource status at least includes the computing resource status
such as the catergery of chip, algorithm, etc. It can also includes
the network resource status such as bandwidth, delay, etc.
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The resource reservation strategy at least includes the computing
resource reservation information of target nodes, which is as
follows:
1. Determine the serial distributed computing subtasks and computing
resources required by each computing subtask based on the service
request.
2. Select the target nodes for each computing subtask and generate
the computing resources reservation information to inform each target
node to reserve resource based on the computing resource status of
each node and the computing resources required by each computing
subtask.
Moreover, if the bandwidth change after each subtask can be
calculated, the resource reservation strategy can also carrying the
bandwidth resources reservation information.
It can be realized by defining new object of RSVP or RSVP-TE to
reserve different resources in each target nodes. The object can be
customized and extended with variable length. For example,
redefining a new class num as 30, carries the following message body:
[L = 0, IPv4, 64, IP address1, bandwidth 1, computing resource 1]
[L = 0, IPv4, 64, IP address2, bandwidth 2, computing resource 2]
[L = 0, IPv4, 64, IP address3, bandwidth 3, computing resource 3]
[L = 0, IPv4, 64, IP address4, bandwidth 4, computing resource 4]
......
It should be noted that the extended object can not only carry the
collected resources status of each node in the PATH message, but also
return the resource reservation strategy in the RESV message.
4.2. Centralized Resource Reservation
Centralized resource reservation can be realized by the network
manager. The manager receives the service request, calculates the
network and computing resources needed, and initiates resource
reservation configuration for the target nodes along the path.The
process is as follows:
The client sends a service request to the network manager.
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Network manager selects the path according to the service request and
get the resource status of each node on the path.
Network manager generates the resource reservation strategy based on
the client's service request and resource status of each node.
Network manager sends resource reservation strategy to target nodes
to reserve the resource.
The resource status at least includes the computing resource status.
The resource reservation strategy at least includes the computing
resource reservation information of each target node. Which are the
same with chapter 4.1.
If at least one node in the selected path does not meet the resource
reservation requirements, it is necessary to re-select at least one
node in the path and get the resource status of the re-selected node
until the path meets the requirements of the resource reservation
strategy.
4.2.1. PCEP
By adding calculation force resource reservation field to resource
reservation object in PECP message, each calculation force flow has a
dynamic resource range based on the minimum reserved resource.
+---------+---------+-----------+----------+--------+
| Object | Label | Reserverd |Interface | In/ |
| Type | ID | Bandwidth |IP Address| Out |
+---------+---------+-----------+----------+--------+
PCEP extension
4.2.2. Netconf/Yang
It can also send resource reservation configuration to the target
nodes by netconf and defining the Yang structure. The reference Yang
module is as follows.
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module: rs-computing-network
+--rw rs-computing-network
+--rw added-device[id]
| +--rw service id string
| +--rw user id string
| +--rw bandwitdh mbps
| +--rw computing resource tbd
+--rw deleted-device[id]
Yang Module
5. Conclusion
The draft proposes a method of differential reservation of computing
power and bandwidth resources based on the network protocol. Because
the traditional network does not include computing power, the
reservation of network resources is the same on the path. This
scheme can accurately reserve computing power and network resources
for the serial distributed computing services. It also present the
reference methods to realize different resource reservation.Of
course, there may be more and more appropriate methods to achieve the
computing and network resource reservation, which may require more
analysis and discussion.
6. Security Considerations
TBD.
7. IANA Considerations
TBD.
8. 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>.
[RFC5440] Vasseur, JP., Ed. and JL. Le Roux, Ed., "Path Computation
Element (PCE) Communication Protocol (PCEP)", RFC 5440,
DOI 10.17487/RFC5440, March 2009,
<https://www.rfc-editor.org/info/rfc5440>.
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Authors' Addresses
Peng Liu
China Mobile
Beijing 100053
China
Email: liupengyjy@chinamobile.com
Huijuan Yao
China Mobile
Beijing 100053
China
Email: yaohuijuan@chinamobile.com
Liang Geng
China Mobile
Beijing 100053
China
Email: gengliang@chinamobile.com
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