



GREEN                                                       M. A. Jadoon
Internet-Draft                                              S. Robitzsch
Intended status: Standards Track                     InterDigital Europe
Expires: 8 January 2026                                      7 July 2025


       A YANG Data Model for Reporting Utilization Scores in ISAC
                 draft-jadoon-green-isac-utilization-00

Abstract

   This document defines a basic YANG data model to report sensing
   measurements utilization score (US) in Integrated Sensing and
   Communication (ISAC) systems.  The score quantifies the resource
   impact of different sensing measurements, including compute, memory,
   storage, energy, and latency.  The model supports per-measurement
   telemetry reporting.

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   This Internet-Draft will expire on 8 January 2026.

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   provided without warranty as described in the Revised BSD License.



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Table of Contents

   1.  Introduction  . . . . . . . . . . . . . . . . . . . . . . . .   2
   2.  Model Scope . . . . . . . . . . . . . . . . . . . . . . . . .   2
   3.  Tree Diagram  . . . . . . . . . . . . . . . . . . . . . . . .   2
   4.  YANG Module . . . . . . . . . . . . . . . . . . . . . . . . .   3
     4.1.  JSON Encoding Example . . . . . . . . . . . . . . . . . .   4
   5.  Security Considerations . . . . . . . . . . . . . . . . . . .   5
   6.  IANA Considerations . . . . . . . . . . . . . . . . . . . . .   5
   7.  Acknowledgements  . . . . . . . . . . . . . . . . . . . . . .   5
   8.  Normative References  . . . . . . . . . . . . . . . . . . . .   5
   Authors' Addresses  . . . . . . . . . . . . . . . . . . . . . . .   6

1.  Introduction

   ISAC introduces a paradigm where network nodes perform both
   communication and sensing tasks.  Several use cases and their
   requirements for ISAC have been defined in 3GPP [TR22.837] and
   ETSI[GR-ISC001].  A sensing task involves measurements of parameters
   such as Doppler, angle of arrival (AoA), and radar cross section
   (RCS), micro-doppler, range/delay [Jadoon2025] etc., each consumes
   varying amounts of system resources such as memory, energy, storage.

   To enable energy-efficient orchestration, it is important to measure
   and report the utilization impact of each measurement for a sensing
   task.  This draft proposes a YANG data model that allows ISAC-enabled
   devices to report an SMUS per sensing task, computed from weighted
   metrics such as CPU usage, memory, energy draw, storage load, and
   latency.

2.  Model Scope

   The model is intended for systems that support ISAC and want to
   participate in energy-aware operations.

3.  Tree Diagram















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   module: ietf-isac-utilization
     +--ro sensing-utilization
        +--ro function-score* [function]
           +--ro function                   sensing-function
           +--ro score-components
           |  +--ro compute-score?         decimal64
           |  +--ro memory-score?          decimal64
           |  +--ro energy-score?          decimal64
           |  +--ro storage-score?         decimal64
           |  +--ro latency-score?         decimal64
           +--ro weights
           |  +--ro compute-weight?        decimal64
           |  +--ro memory-weight?         decimal64
           |  +--ro energy-weight?         decimal64
           |  +--ro storage-weight?        decimal64
           |  +--ro latency-weight?        decimal64
           +--ro total-utilization-score?  uint8

4.  YANG Module

module ietf-isac-utilization {
     yang-version 1.1;
     namespace "urn:ietf:params:xml:ns:yang:ietf-isac-utilization";
     prefix isac-util;

     organization "InterDigital Europe";
     contact "Muhammad Awais Jadoon <muhammad.awaisjadoon@interdigital.com>";

     description
        "YANG data model for reporting ISAC sensing resource utilization scores.";

     revision "2025-06-28" {
       description "Initial version.";
     }

     typedef sensing-function {
       type enumeration {
         enum delay {
           description "Time delay measurement representing target range.";
         }
             enum doppler {
           description "Doppler shift measurement representing target velocity.";
         }
         enum micro-doppler {
           description "Micro-Doppler analysis for fine-grained motion of target.";
         }
         enum aoa {
           description "Angle of Arrival estimation.";



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         }
         enum rcs {
           description "Radar Cross Section estimation.";
         }
       }
       description "Enumerates supported sensing measurement functions within ISAC systems.";
     }

     container sensing-utilization {
       config false;

       list function-score {
         key "function";
         leaf function {
           type sensing-function;
         }

         container score-components {
           leaf compute-score { type decimal64 { fraction-digits 2; } units "%"; }
           leaf memory-score { type decimal64 { fraction-digits 2; } units "%"; }
           leaf energy-score { type decimal64 { fraction-digits 2; } units "%"; }
           leaf storage-score { type decimal64 { fraction-digits 2; } units "%"; }
           leaf latency-score { type decimal64 { fraction-digits 2; } units "%"; }
         }

         container weights {
           leaf compute-weight { type decimal64 { fraction-digits 2; } units "ratio"; }
           leaf memory-weight { type decimal64 { fraction-digits 2; }  units "ratio"; }
           leaf energy-weight { type decimal64 { fraction-digits 2; }  units "ratio"; }
           leaf storage-weight { type decimal64 { fraction-digits 2; }  units "ratio"; }
           leaf latency-weight { type decimal64 { fraction-digits 2; }  units "ratio"; }
         }

         leaf total-utilization-score {
           type uint8;
           description "Composite score (0–100) aggregating all measurements.";
         }
       }
     }
   }

   Note: The sensing measurement types defined in this document (e.g.,
   Delay, Doppler, micro-Doppler, AoA, RCS) is not exhaustive.  The YANG
   model is extensible, and additional sensing measurments may be
   incorporated as the standards develop.

4.1.  JSON Encoding Example




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   {
     "ietf-isac-utilization:sensing-utilization": {
       "function-score": [
         {
           "function": "micro-doppler",
           "score-components": {
             "compute-score": 82.0,
             "memory-score": 60.0,
             "energy-score": 75.0,
             "storage-score": 50.0,
             "latency-score": 45.0
           },
           "weights": {
             "compute-weight": 0.3,
             "memory-weight": 0.2,
             "energy-weight": 0.3,
             "storage-weight": 0.1,
             "latency-weight": 0.1
           },
           "total-utilization-score": 70
         }
       ]
     }
   }

5.  Security Considerations

   TBD

6.  IANA Considerations

   TBD

7.  Acknowledgements

   This work has received funding from the Smart Networks and Services
   Joint Undertaking (SNS JU) under the European Union's Horizon Europe
   research and innovation programme under Grant Agreement No 101192521
   (MultiX).

8.  Normative References

   [GR-ISC001]
              ETSI, "Integrated Sensing And Communications (ISAC); Use
              Cases and Deployment Scenarios", ETSI GR ISC001 V1.1.1 ,
              2025.





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   [Jadoon2025]
              Jadoon, M. A., Robitzsch, S., and F. Conceição, "Dynamic
              and Resource-Efficient ISAC Operations in Sensing-Enabled
              6G Systems", Accepted, to appear in IEEE ICC 2025 , 2025.

   [TR22.837] 3GPP, "Study on Integrated Sensing and Communication
              (ISAC)", 3GPP TR 22.837 V19.4.0 , 2024.

Authors' Addresses

   Muhammad Awais Jadoon
   InterDigital Europe
   United Kingdom
   Email: muhammad.awaisjadoon@interdigital.com


   Sebastian Robitzsch
   InterDigital Europe
   United Kingdom
   Email: Sebastian.Robitzsch@InterDigital.com































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