PCE L. M. Contreras Internet-Draft Telefonica Intended status: Informational F. Agraz Expires: 7 January 2027 S. Spadaro Universitat Politecnica de Catalunya Q. Xiong ZTE Corporation 6 July 2026 Path Computation Based on Precision Availability Metrics draft-contreras-pce-pam-07 Abstract This document extends PCEP to support Precision Availability Metrics (PAM) [RFC9544] for path computation. The optimization objectives for PAM computations are encoded using the Objective Function (OF) object defined in [RFC5541], allowing PCCs to specify precise optimization criteria for services with SLO requirements. And a PCE can report the statistical characterization associated with a computed path. 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 7 January 2027. Copyright Notice Copyright (c) 2026 IETF Trust and the persons identified as the document authors. All rights reserved. This document is subject to BCP 78 and the IETF Trust's Legal Provisions Relating to IETF Documents (https://trustee.ietf.org/ license-info) in effect on the date of publication of this document. Contreras, et al. Expires 7 January 2027 [Page 1] Internet-Draft PAM-based PCE July 2026 Please review these documents carefully, as they describe your rights and restrictions with respect to this document. Code Components extracted from this document must include Revised BSD License text as described in Section 4.e of the Trust Legal Provisions and are provided without warranty as described in the Revised BSD License. Table of Contents 1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 2 2. Terminology . . . . . . . . . . . . . . . . . . . . . . . . . 3 3. Rationale of the usage of PAM for path calculation . . . . . 3 3.1. Dynamic behavior of performance parameters . . . . . . . 3 3.2. Applicability . . . . . . . . . . . . . . . . . . . . . . 4 3.3. Usage of collected metrics . . . . . . . . . . . . . . . 4 3.4. Calculation or selection of the path . . . . . . . . . . 6 4. PAM Objective Functions . . . . . . . . . . . . . . . . . . . 7 4.1. PAM Compliance Objective Function . . . . . . . . . . . . 8 4.2. Minimum Violated Intervals Objective Function . . . . . . 9 4.3. Minimum Severe Violated Intervals Objective Function . . 10 4.4. Interaction with Path Constraints . . . . . . . . . . . . 11 5. PAM report TLV . . . . . . . . . . . . . . . . . . . . . . . 11 6. Security and operational considerations . . . . . . . . . . . 12 6.1. Security considerations . . . . . . . . . . . . . . . . . 12 6.2. Operational considerations . . . . . . . . . . . . . . . 12 7. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 12 7.1. New PCE Objective Function Codes . . . . . . . . . . . . 12 7.2. PCEP TLV . . . . . . . . . . . . . . . . . . . . . . . . 13 8. Informative References . . . . . . . . . . . . . . . . . . . 13 Appendix A. Path Histogram Composition . . . . . . . . . . . . . 15 A.1. Additive Metrics . . . . . . . . . . . . . . . . . . . . 15 A.2. Multiplicative Metrics . . . . . . . . . . . . . . . . . 15 A.3. Maximization / Minimization Metrics (Bottleneck Metrics) . . . . . . . . . . . . . . . . . . . . . . . . 15 Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . 16 Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 16 1. Introduction Some network services, such as Network Slices [RFC9543] and Deterministic Networking [RFC8578] [RFC8655], express their performance requirements using Service Level Objectives (SLOs). At the time of calculating a path by the PCE, the METRIC object [RFC5440] serves for the purposes of indicating either the metric that MUST be optimized by the path computation algorithm, or a bound on the path cost that MUST NOT be exceeded for the path to be considered as acceptable. The value of the metric refers to the instantaneous observed behavior of that parameter, without a notion Contreras, et al. Expires 7 January 2027 [Page 2] Internet-Draft PAM-based PCE July 2026 of behavior along the preceding time. This cannot be sufficient for certain networking services which require to experience stable behavior along the time according to their SLOs. Precision Availability Metrics (PAM) [RFC9544] introduce statistical performance attributes, including Violated Intervals (VI), Severe Violated Intervals (SVI), Violated Interval Ratio (VIR), and Severely Violated Interval Ratio (SVIR). These metrics describe the historical or probabilistic behavior of a path across observation intervals, rather than its instantaneous state. This document extends PCEP to support PAM-based path computation. It defines: * PAM-specific Objective Functions (OFs), encoded using the OF object defined in [RFC5541], to instruct the PCE on how to rank and select paths based on statistical SLO compliance. * PAM Report TLVs, used by the PCE to convey the statistical characterization of the computed path to the Path Computation Client (PCC). 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 [RFC2119]. In addition, the terms defined in [RFC9544] are also used in this document. 3. Rationale of the usage of PAM for path calculation 3.1. Dynamic behavior of performance parameters [RFC9544] introduced the concept of intervals for measuring the behavior of measurable performance parameters against some predefined thresholds. Those intervals consider a given time window. Thus, it is possible to define a Violated Interval (VI) as the time interval during which at least one of the performance parameters presents degradation respect to a predefined optimal level threshold. Similarly, when the threshold is defined as critical, the degradation of the performance parameter in a time window generates a Severe Violated Interval (SVI). Taking into account the VIs and SVIs it is feasible to generate availability metrics showing some degree of historic behavior in the form of the following ratios: Contreras, et al. Expires 7 January 2027 [Page 3] Internet-Draft PAM-based PCE July 2026 * Violated Interval Ratio (VIR), defined as the ratio of the summed numbers of VIs and SVIs to the total number of time unit intervals along a predefined availability period. * Severely Violated Interval Ratio (SVIR), defined as the ratio of SVIs to the total number of time unit intervals along a predefined availability period. At the time of provisioning a networking service which requires stable SLOs along the time, it is important to ensure that the selected path has shown such stable behavior in the past. Despite the fact that the past behavior is not a guarantee of future behavior, it can be presumed that those paths with lower VIR and SVIR will better satisfy the SLOs of the intended networking service. Alternatively, PAM can be used by the path computation entity for fine-grained path computation. Then PAM are useful criteria for calculating and selecting paths. 3.2. Applicability Three situations of applicability of precision metrics can be identified: * The provision of a path according to the desired behavior along the time. In this scenario different segments of a potential path could be monitored before the path is created. The path calculation can take into consideration the measured characteristics of the segments forming that path for decision. * The selection of a path according to its long-run characteristics. In this scenario, an existing path being monitored along the time can be selected if its behavior is compliant with the long-run behavior expected by the customer. * The triggering of corrective actions for a selected path. It could be the case that a selected path suffers degradation. The precision metrics can assist on the identification of such potential problems, e.g, raising incidents or anomalies to operational groups, as described in [I-D.ietf-nmop-network-incident-yang]. 3.3. Usage of collected metrics The Traffic Engineering Database (TED) defined in [RFC4655] could be considered as the component providing the precision metrics of interest. Contreras, et al. Expires 7 January 2027 [Page 4] Internet-Draft PAM-based PCE July 2026 The TED stores information related to the network topology, including nodes, links, link attributes (e.g., bandwidth, delay), and any constraints relevant for traffic engineering. It is dynamically updated with information received via routing protocols (e.g., OSPF- TE, IS-IS-TE), ensuring the PCE has up-to-date knowledge of the network status and behavior. It is also possible to define policies like administrative group (coloring), to be used in constraint-based path computation. In order to support precision metrics, the TED could be extended to support e.g. time-series storage and processing capabilities (e.g., to derive histograms from them, as described for instance in Appendix A). The metrics could be gathered from in-band telemetry, active probing mechanisms, or streaming telemetry via standardized interfaces, as complementary information sources to the information received from routing protocols. Assuming that capability, the PCE queries the TED for compliance with precision constraints. - Topology Path computation request - Single value metrics based on PAM metrics - Precision metrics +-------------+ +-------------+ +-------------+ | Path | | Path | | Traffic | | Computation |<------->| Computation |<------->| Engineering | | Client | | Element | | Database | +-------------+ +-------------+ +-------------+ ^ | v +-------------+ | Data | | Sources | +-------------+ - Link state info - Active Probes - Streaming telemetry - In-band OAM - etc Figure 1: Usage of precision metrics stored in TED The implementation of the TED and its support to the collection, processing and generation of the precision metrics is out of scope of this document. Similarly, the mechanisms used to collect telemetry and build the statistical characterisation are outside the scope of this document. Contreras, et al. Expires 7 January 2027 [Page 5] Internet-Draft PAM-based PCE July 2026 3.4. Calculation or selection of the path For a given metric, i.e. metric X, it is defined a frequency of values per bin for such a metric (e.g., if the metric refers to latency, a way of expressing it could be to consider the latency below 20 ms the 90% of the time, and below 25 ms the 99% of the time). Thus, the calculation or selection of a path for such a metric X will consist on the comparison of the frequency of the metric values per bin, so that the intended path behaves equal or better than such described behavior. For that purpose, the statistical behavior of the path is characterized e.g. as described in Appendix A. When selecting a path, the PCE evaluates candidate paths according to the following procedure: 1. Retrieve PAM information associated with links and path segments. 2. Build the end-to-end statistical characterization of each candidate path. 3. Apply mandatory PAM constraints to eliminate infeasible paths and rank feasible ones. 4. Apply PAM objective functions across the remaining feasible candidate paths. 5. Select the path maximizing the objective function value and report back the statistical characterization associated with the selected path by means of a PAM Report TLV.. Contreras, et al. Expires 7 January 2027 [Page 6] Internet-Draft PAM-based PCE July 2026 +---------------------+ | Candidate Paths | +----------+----------+ | v +---------------------+ | PAM Constraints | | Evaluation | +----------+----------+ | Feasible Paths | v +---------------------+ | PAM Objective | | Function | +----------+----------+ | v +---------------------+ | Selected Path | +---------------------+ Figure 2: Process The construction of end-to-end statistical distributions derived from the per-link observations is implementation dependent and outside the scope of this document. The resulting end-to-end distribution SHALL be represented using the PAM TLVs defined by this document. 4. PAM Objective Functions The Path Computation Element (PCE) can use Precision Availability Metrics (PAM) in two different ways during path computation. First, PAM information can be used as a path constraint. In this mode, candidate paths that do not satisfy the requested PAM characteristics are discarded during the path computation process. Second, PAM information can be used as an optimization criterion. In this case, multiple candidate paths can satisfy the requested PAM constraints and the PCE uses one or more PAM-related objective functions to identify the preferred path among the feasible alternatives. The specific algorithms used by a PCE implementation are outside the scope of this document. This section defines PAM objective functions that extend the OF object defined in [RFC5541]. These objective functions enable PAM- aware path computation and selection. Contreras, et al. Expires 7 January 2027 [Page 7] Internet-Draft PAM-based PCE July 2026 4.1. PAM Compliance Objective Function The PAM Compliance Objective Function aims at selecting the candidate path whose statistical behavior exhibits the highest level of compliance with the requested Service Level Objective (SLO). When multiple feasible paths are available, the PCE evaluates the statistical characterization associated with each path and selects the one providing the highest degree of compliance with the requested PAM profile. The method used to determine the level of compliance is implementation-specific. This objective function is particularly useful when the PCC requests a specific statistical distribution describing the expected service behavior over a given observation interval. The description of the new objective function is as follows. * Objective Function Code: TBD1 * Name: PAM Compliance (PAM-COMP) * Description: Selects the candidate path with highest compliance to requested PAM characteristics. The PCE evaluates statistical distributions and selects the path providing optimal alignment with requested SLO profiles. The objective function is formulated using the following terminology: * A network comprises a set of N links {Li, (i=1...N)}. * A path P is a list of K links {Lpi,(i=1...K)}. * Metric of link L is denoted M(L). This can be any metric such as path delay, path delay variation, or path loss as per [RFC8233]. * For a given metric X, the requested PAM profile is denoted R_X. R_X is composed of a set of bins {Bj, (j=1...B)} and the corresponding requested frequency values {rj, (j=1...B)}. Each pair (Bj, rj) describes the expected statistical behavior of the metric over the observation interval. For example, for a delay metric, a bin may indicate that the path delay is expected to be below a given threshold for at least a specified fraction of the observation interval. Contreras, et al. Expires 7 January 2027 [Page 8] Internet-Draft PAM-based PCE July 2026 * The statistical characterization of metric X for a candidate path P is denoted H_X(P). H_X(P) is composed of the same set of bins {Bj, (j=1...B)} and the corresponding observed, estimated, or derived frequency values {pj(P), (j=1...B)} for the candidate path. * For each bin Bj, the compliance of path P with respect to the requested PAM profile R_X is denoted c_j(P,R_X). The definition of c_j(P,R_X) depends on the semantics of the metric and on whether lower or higher values are preferable. For metrics where lower values are preferable, such as delay, a path is considered more compliant when the frequency of values not exceeding the requested bin threshold is greater than or equal to the requested frequency. For metrics where higher values are preferable, the comparison is applied in the opposite direction. * The overall PAM compliance of a path P with respect to the requested PAM profile R_X is denoted C(P,R_X), where C(P,R_X) = min { c_j(P,R_X), j=1...B }. This formulation captures the weakest compliance level across all the requested bins and therefore favors paths whose statistical behavior is aligned with the complete requested PAM profile, rather than with only a subset of the requested bins. * The PAM-COMP OF is to find a path P such that C(P,R_X) is maximized among the feasible candidate paths through Maximize C(P,R_X), subject to the path constraints applicable to the computation. * A path P is fully compliant with the requested PAM profile R_X when all the requested bin-level conditions are satisfied. When more than one fully compliant path exists, the PCE SHOULD prefer the path with the highest value of C(P,R_X). When no candidate path can fully satisfy the requested PAM profile and the PAM profile is used as a desirable optimization criterion rather than as a mandatory constraint, the PCE MAY select the path with the highest value of C(P,R_X) and SHOULD report the resulting statistical characterization using the PAM Report TLV. 4.2. Minimum Violated Intervals Objective Function The Minimum Violated Intervals (Min-VI) Objective Function aims at selecting the path exhibiting the lowest occurrence of Violated Intervals (VI). When several candidate paths satisfy the requested constraints, the PCE SHOULD prefer the path associated with the lowest VI occurrence. This objective function favors paths presenting fewer periods of performance degradation with respect to the requested service objectives. Contreras, et al. Expires 7 January 2027 [Page 9] Internet-Draft PAM-based PCE July 2026 The description of the new objective function is as follows: * Objective Function Code: TBD2 * Name: Minimum Violated Intervals (MIN-VI) * Description: Selects the path with lowest Violated Interval (VI) occurrence, minimizing periods of performance degradation relative to SLO thresholds. The objective function is formulated using the following terminology: * A network comprises a set of N links {Li, (i=1...N)}. * A path P is a list of K links {Lpi,(i=1...K)}. * Violated Interval on link L is denoted VI(L) * The Violated Intervals of a path P is denoted VI(P), where VI(P) = Max {VI(Lpi), (i=1...K)}. * The Min-VI OF is to find a path P such that ( Max { VI(Lpi), i=1...K } ) is minimized. 4.3. Minimum Severe Violated Intervals Objective Function The Minimum Severe Violated Intervals (Min-SVI) Objective Function aims at selecting the path exhibiting the lowest occurrence of Severe Violated Intervals (SVI). When several candidate paths satisfy the requested constraints, the PCE SHOULD prefer the path associated with the lowest SVI occurrence. This objective function is particularly relevant for services where severe service degradation events must be minimized. The description of the new objective function is as follows: * Objective Function Code: TBD3 * Name: Minimum Severe Violated Intervals (MIN-SVI) * Description: Selects the path with lowest Severe Violated Interval (SVI) occurrence, minimizing severe degradation events. The objective function is formulated using the following terminology: * A network comprises a set of N links {Li, (i=1...N)}. * A path P is a list of K links {Lpi,(i=1...K)}. Contreras, et al. Expires 7 January 2027 [Page 10] Internet-Draft PAM-based PCE July 2026 * Severe Violated Interval on link L is denoted SVI(L) * The Severe Violated Intervals of a path P is denoted SVI(P), where SVI(P) = Max {SVI(Lpi), (i=1...K)}. * The Min-SVI OF is to find a path P such that ( Max { SVI(Lpi), i=1...K } ) is minimized. 4.4. Interaction with Path Constraints A PCC MAY request PAM information to be treated as a mandatory constraint or as a desirable optimization criterion. Thus, when PAM information is expressed as a mandatory constraint, candidate paths not satisfying the requested PAM requirements SHALL be excluded from the solution set. On the other hand, when PAM information is expressed as a desirable criterion, candidate paths not satisfying the requested PAM requirements MAY still be considered by the PCE. In such cases, PAM objective functions can be used to identify the most suitable path among the available alternatives. Potential mechanisms used to compare statistical distributions and determine the preferred candidate path are outside the scope of this document. 5. PAM report TLV The PAM Report TLV is used by a PCE to report the statistical characterization associated with a computed path. This TLV allows a PCC to understand the Precision Availability Metrics (PAM) information that has been used during path computation and path selection. Such information can be particularly useful when the requested PAM profile has been expressed as a desirable objective rather than as a mandatory constraint.The PAM Report TLV MAY be included in PCRep messages and other PCEP messages carrying path computation results. The PAM Report TLV contains the statistical characterization associated with the selected path and MAY include: * The performance metric being described (e.g., one-way delay, round-trip delay, jitter, packet loss). * The observation interval used for deriving the statistical characterization. * The kind of statistical distribution associated with the selected path. Contreras, et al. Expires 7 January 2027 [Page 11] Internet-Draft PAM-based PCE July 2026 * The distribution representation, including the set of bins or intervals used to characterize the metric values. The encoding of specific statistical distributions and the representation of bins are outside the scope of this document. * The corresponding PAM indicators, such as Violated Intervals (VI) and Severe Violated Intervals (SVI), as defined in [RFC9544]. When the requested PAM profile cannot be satisfied exactly, the PAM Report TLV provides visibility about the statistical characteristics of the path actually selected by the PCE. Moreover, when PAM information is requested as a desirable optimization criterion, the PCE MAY select a path whose statistical characterization differs from the one requested by the PCC. In such case, the PCE SHOULD include a PAM Report TLV allowing the PCC to know (and evaluate) the characteristics of the selected path. 6. Security and operational considerations 6.1. Security considerations Same security and operational considerations as described in [RFC5440] apply also in this document. Other security considerations will be addressed in future versions of the document. 6.2. Operational considerations The work with precision metrics can impose stringent requirements in terms of collection, processing and assessment of metrics of interest. Such capabilities are expected to be supported by external systems, such as the TED, with the role of the PCE being limited to the work with processed information (e.g., histograms) so to assess that the precision metric used as constraint is compliant with the expectation of the PCC. Such external supportive systems are out of scope of this document. 7. IANA Considerations 7.1. New PCE Objective Function Codes IANA is requested to assign the following values in the "Objective Function" subregistry within the "Path Computation Element Protocol (PCEP) Numbers" registry: Contreras, et al. Expires 7 January 2027 [Page 12] Internet-Draft PAM-based PCE July 2026 +-----------+--------------------------------------------+--------------+ |Code Point | Name | Reference | +-----------+--------------------------------------------+--------------+ | TBD1 | PAM Compliance (PAM-COMP) | This document| | TBD2 | Minimum Violated Intervals (MIN-VI) | This document| | TBD3 | Minimum Severe Violated Intervals (MIN-SVI)| This document| +--------------+-----------------------------------------+--------------+ 7.2. PCEP TLV IANA is requested to assign the following values in the "PCEP TLV Type Indicators" subregistry within the "Path Computation Element Protocol (PCEP) Numbers" registry: +----------+--------------------------------+--------------+ |TLV Type | Name | Reference | +----------+--------------------------------+--------------+ | TBD4 | PAM Report | This document| +----------+--------------------------------+--------------+ 8. Informative References [I-D.ietf-nmop-network-incident-yang] Hu, T., Contreras, L. M., Wu, Q., Davis, N., and C. Feng, "A YANG Data Model for Network Incident Management", Work in Progress, Internet-Draft, draft-ietf-nmop-network- incident-yang-10, 6 July 2026, . [IANA_METRIC_Object] "METRIC Object T Field", n.d., . [IEEE.754.2019] "754-2019 - IEEE Standard for Floating-Point Arithmetic", 22 July 2019, . [RFC2119] Bradner, S., "Key words for use in RFCs to Indicate Requirement Levels", BCP 14, RFC 2119, DOI 10.17487/RFC2119, March 1997, . Contreras, et al. Expires 7 January 2027 [Page 13] Internet-Draft PAM-based PCE July 2026 [RFC4655] Farrel, A., Vasseur, J.-P., and J. Ash, "A Path Computation Element (PCE)-Based Architecture", RFC 4655, DOI 10.17487/RFC4655, August 2006, . [RFC5440] Vasseur, JP., Ed. and JL. Le Roux, Ed., "Path Computation Element (PCE) Communication Protocol (PCEP)", RFC 5440, DOI 10.17487/RFC5440, March 2009, . [RFC5541] Le Roux, JL., Vasseur, JP., and Y. Lee, "Encoding of Objective Functions in the Path Computation Element Communication Protocol (PCEP)", RFC 5541, DOI 10.17487/RFC5541, June 2009, . [RFC8233] Dhody, D., Wu, Q., Manral, V., Ali, Z., and K. Kumaki, "Extensions to the Path Computation Element Communication Protocol (PCEP) to Compute Service-Aware Label Switched Paths (LSPs)", RFC 8233, DOI 10.17487/RFC8233, September 2017, . [RFC8578] Grossman, E., Ed., "Deterministic Networking Use Cases", RFC 8578, DOI 10.17487/RFC8578, May 2019, . [RFC8655] Finn, N., Thubert, P., Varga, B., and J. Farkas, "Deterministic Networking Architecture", RFC 8655, DOI 10.17487/RFC8655, October 2019, . [RFC9543] Farrel, A., Ed., Drake, J., Ed., Rokui, R., Homma, S., Makhijani, K., Contreras, L., and J. Tantsura, "A Framework for Network Slices in Networks Built from IETF Technologies", RFC 9543, DOI 10.17487/RFC9543, March 2024, . [RFC9544] Mirsky, G., Halpern, J., Min, X., Clemm, A., Strassner, J., and J. François, "Precision Availability Metrics (PAMs) for Services Governed by Service Level Objectives (SLOs)", RFC 9544, DOI 10.17487/RFC9544, March 2024, . Contreras, et al. Expires 7 January 2027 [Page 14] Internet-Draft PAM-based PCE July 2026 Appendix A. Path Histogram Composition In order to obtain the statistical distribution of a metric over a complete path from the corresponding distributions of its constituent segments (e.g., hops) it is necessary to consider the class of the metric under evaluation, i.e., if the metric is additive, multiplicative, or maximal/minimal. A.1. Additive Metrics Additive metrics are those that sum along the path, such as delay or IGP cost [RFC4655], [RFC8233]. To generate a path histogram from segment histograms, the total path value can be obtained by summing the individual segment values along a period, and then forming the histogram. Alternatively, considering that a histogram is divided into discrete bins representing value ranges, it is possible to perform a bin-by- bin summation. The histogram for the path is then obtained by summing the bin values across the segments. A.2. Multiplicative Metrics Multiplicative metrics, for example link availability or success probability [RFC8233], combine along a path by multiplying segment (e.g., per hop) values. The path histogram can be obtained by combining the segment values and computing the product for each combination. Alternatively, logarithmic transformation can be applied to convert multiplicative aggregation into additive form, enabling reuse of additive histogram composition techniques. In this method, the values of each histogram bin are transformed by taking the logarithm, effectively converting multiplication into addition. The histograms can then be combined by summing the log-transformed bin values across segments, using the values of each bin per segment to calculate the resulting distribution. After aggregating the histograms in the log domain, the path histogram can be transformed back to the original metric domain by applying the exponential function, yielding the final probabilities for the multiplicative path values. A.3. Maximization / Minimization Metrics (Bottleneck Metrics) Bottleneck metrics are defined by taking the maximum or minimum value along the path, such as bandwidth, MTU, etc [RFC4655]. To construct a path histogram, the values of each segment are considered to build the cumulative distribution function (CDF) of the path. Contreras, et al. Expires 7 January 2027 [Page 15] Internet-Draft PAM-based PCE July 2026 Acknowledgements The authors thank Dhruv Dhody, Rakesh Gandhi, Ruediger Geib, Amal Karboubi and Greg Mirsky for the comments received that helped to improve the document. This work has been partially funded by the European Commission Horizon Europe SNS JU PREDICT-6G project (GA 101095890), and the Spanish Ministry of Economic Affairs and Digital Transformation and the European Union NextGenerationEU UNICO 5G I+D "Towards a smart and efficient telecom infrastructure meeting current and future industry needs" (TIMING) project (TSI-063000-2021-145, -148, -149). Authors' Addresses Luis M. Contreras Telefonica Ronda de la Comunicacion, s/n 28050 Madrid Spain Email: luismiguel.contrerasmurillo@telefonica.com URI: http://lmcontreras.com Fernando Agraz Universitat Politecnica de Catalunya 08034 Barcelona Spain Email: fernando.agraz@upc.edu Salvatore Spadaro Universitat Politecnica de Catalunya 08034 Barcelona Spain Email: salvatore.spadaro@upc.edu Quan Xiong ZTE Corporation China Email: xiong.quan@zte.com.cn Contreras, et al. Expires 7 January 2027 [Page 16]