The Computing-Aware Routing Architecture in Computing-Aware Traffic Steering
draft-peng-cats-car-architecture-00

cats                                                             T. Peng
Internet-Draft                                                     Y. Ma
Intended status: Informational               Beijing Jiaotong University
Expires: 20 August 2024                                 17 February 2024

  The Computing-Aware Routing Architecture in Computing-Aware Traffic
                                Steering
                  draft-peng-cats-car-architecture-00

Abstract

   This document proposes a compute-aware routing (CAR) architecture for
   Computing-Aware Traffic Steering (CATS), designed to support routing
   systems with compute resource awareness and provide a standardized
   approach for network devices and services.

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   This Internet-Draft will expire on 20 August 2024.

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Table of Contents

   1.  Introduction  . . . . . . . . . . . . . . . . . . . . . . . .   2
   2.  The Computing-Aware Routing Headers (CARH)  . . . . . . . . .   2
   3.  Computing-Aware Info (CAI)  . . . . . . . . . . . . . . . . .   3
   4.  Advanced Info . . . . . . . . . . . . . . . . . . . . . . . .   5
     4.1.  0xF0 - Composite Performance Score (CPS)  . . . . . . . .   5
     4.2.  0xF1 - Network Quality Index (NQI)  . . . . . . . . . . .   5
   5.  Security Considerations . . . . . . . . . . . . . . . . . . .   6
   6.  IANA Considerations . . . . . . . . . . . . . . . . . . . . .   6
   Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . .   6
   Authors' Addresses  . . . . . . . . . . . . . . . . . . . . . . .   6

1.  Introduction

   With the continuous increase of computing resources and the
   popularity of distributed computing, how to fully utilize these
   dispersed computing resources to provide better services has become
   an important challenge.  To address this challenge, Computing-Aware
   Traffic Steering (CATS) has been proposed.

   CATS requires the network to be able to perceive information about
   computing resources and select appropriate service instances based on
   the joint indicators of computing and the network, thereby achieving
   dynamic control of network traffic.  In the implementation of CATS, a
   key task is to design a message format that can transmit computing
   resource information.

   Therefore, the Computing-Aware Routing (CAR) message format is
   proposed.

   The CAR is a flexible and powerful message transmission method
   designed to support computing resource-aware routing systems.

2.  The Computing-Aware Routing Headers (CARH)

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    0                   1                   2                   3
    0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1
   +-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+
   |Version|     Time to Live      |            Length             |
   +-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+
   |                                                               |
   |                       Timestamp (64 bits)                     |
   |                                                               |
   +-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+
   |  CAI Type[0]  |                 CAI Value[0]                  |
   +-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+
   |                              ...                              |
   +-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+
   |  CAI Type[n]  |                 CAI Value[n]                  |
   +-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+

   The CARH contains the following fields:

   *  Version Number (4-bit): The version number indicates the CARH
      format version.

   *  Time to Live (8-bit): Time to Live indicates the effective time of
      the resource information represented by CARH.

   *  Length (16-bit): Length of the CARH.

   *  Timestamp (64-bit): Timestamp for perceiving resource information.

   *  CAI Type (8-bit): Computing-Aware Info Type (CAI Type) represents
      a type of computing resource and the order of magnitude
      corresponding to the specific value of that type of resource.
      This section corresponds one-to-one with the CAI Value.

   *  CAI Value (24-bit): Computing-Aware Info Value (CAI Value)
      represents the specific value of the resource identified by the
      CAI Type.

3.  Computing-Aware Info (CAI)

   In order to comprehensively evaluate the computing power in the
   network, CARH needs to introduce a series of dynamic performance
   indicators to capture real-time changes in computing resources.

   These indicators need to cover key performance parameters of network
   devices during operation, such as CPU Utilization, CPU Frequency, CPU
   Cores, Memory Utilization, Memory Frequency, Storage Utilization, GPU
   Memory, GPU Utilization, etc.

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   In CARH, use Computing-Aware Info (CAI) to carry these key
   performance parameters.

   Computing-Aware Info (CAI) consists of two parts: Computing-Aware
   Info Type (CAI Type) and Computing-Aware Info Value (CAI Value).

   Use the CAI Type field to represent the type of resource being
   carried, and use the CAI Value field to represent the numerical value
   and order of magnitude corresponding to the resource being carried.

   Here are some definitions of the CAI Type field.

   *  0x01 - CPU Utilization: Indicates the percentage of time the CPU
      processor is executing tasks.  The calculation formula is the used
      CPU time divided by the total CPU time.

   *  0x02 - CPU Frequency: Refers to the number of instructions
      executed by the CPU per second, usually in hertz (Hz).

   *  0x03 - CPU Cores: Represents the number of physical cores in the
      CPU processor.  Multi-core processors can execute multiple tasks
      simultaneously.

   *  0x04 - Memory Utilization: Indicates the percentage of system
      memory in use.  The calculation formula uses memory divided by
      total memory.

   *  0x05 - Memory Frequency: Refers to the clock speed of RAM,
      indicating the amount of data that the memory module can transfer
      per second.

   *  0x06 - Storage Utilization: Indicates the percentage of storage
      capacity being used in the storage system.  The calculation
      formula uses storage divided by total storage capacity.

   *  0x07 - GPU Memory: Refers to the memory on the graphics processing
      unit (GPU) used to store data required for graphics and computing
      tasks.

   *  0x08 - GPU Utilization: Indicates the percentage of time the GPU
      processor is performing tasks.  The calculation formula is the
      used GPU time divided by the total GPU time.

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4.  Advanced Info

   Dynamic performance indicators can only serve as basic information
   transmitted in CARH.  In fact, based on performance indicator
   information, some advanced performance indicators can be established
   according to specific network scenarios.  Advanced info is also a
   supplementary definition of CAI Type.

4.1.  0xF0 - Composite Performance Score (CPS)

   From the perspective of computing power, a computing power weight
   allocation mechanism can be introduced to assign appropriate weights
   to different computing power factors.

   This mechanism gives appropriate weights to different computing power
   factors to more accurately reflect their relative importance when
   calculating comprehensive performance indicators.

   For example, in some scenarios, CPU utilization may be more critical,
   while memory usage may be more important in other scenarios.  This
   can be customized by network administrators according to specific
   needs, or adjusted through CATS intelligent algorithms for Self-
   Adaptation.

   Therefore, a comprehensive scoring model can be proposed to take into
   account various computing power factors and generate a comprehensive
   score.

   This score can be a standardized value that reflects the overall
   computing power status of the system.  The formulation of a
   comprehensive scoring model can combine Data Analysis and network
   topology features.

4.2.  0xF1 - Network Quality Index (NQI)

   From the perspective of network status, a network quality measurement
   mechanism can be introduced to evaluate network quality.

   Network Quality Index (NQI) takes into account several important
   performance indicators in the network, including latency, packet loss
   rate, bandwidth utilization, etc.

   The goal of NQI is to provide a single metric to measure the overall
   quality of the network, so that network administrators and system
   operators can more easily understand the performance of the network
   and take corresponding measures to optimize the network.

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   The definition of NQI is based on the weighted average of a series of
   network performance indicators.  Each performance indicator is
   assigned a weight, which reflects the relative importance of each
   indicator to network quality.  Then, by multiplying the values of
   each indicator with its corresponding weight and adding all weighted
   values, a comprehensive score, namely NQI, is obtained.

5.  Security Considerations

   TBD.

6.  IANA Considerations

   This document has no IANA actions.

Acknowledgments

   TODO acknowledge.

Authors' Addresses

   Tianhao Peng
   Beijing Jiaotong University
   Email: th.peng@bjtu.edu.cn

   Yuyin Ma
   Beijing Jiaotong University
   Email: mayuyin@bjtu.edu.cn

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