Telecommunications Asset Management Models and Platforms for 5G/6G Networks

Telecommunications Asset Management Models and Platforms for 5G/6G Networks Alexander Goldstein, PhD, Professor, Bonch-Bruevich Telecommunications University, [email protected] Mikail Fenomenov, Bonch-Bruevich Telecommunications University, [email protected] Nikita Petrovsky, Head of Department, RTC Argus, [email protected] David Goldstein, Intern, RTC Argus St.Petersburg, Russia [email protected] Abstract— During the current revolutionary transition of telecommunications toward Beyond 5G networks, asset management throughout the entire life cycle has become a critical task for telecom operators. Two main factors drive this urgency: the radical increase in the diversity of both tangible and intangible assets (especially the latter) in B5G networks and the sharp reduction in the life cycle of these assets. This article analyzes the functionality of asset management systems (AMS), compares several AMS solutions, and presents mathematical models for asset management. Index Terms — business process management, OSS/BSS, NGN and post-NGN, IoT, AMS services, AI, network function virtualization, and Inventory. I. INTRODUCTION Asset management in the telecommunications industry is the systematic management of a telecommunications operator's tangible and intangible assets throughout their entire life cycle. Asset management systems (AMS) allow telecom operators’ administrators to track assets and provide them with information such as the asset manufacturer, inventory ID, installed applications, asset allocation, and maintenance regimens. AMS assists a telecommunications operator in purchasing new equipment and upgrading the software, allocating maintenance costs for each division of the operator company. Assets are understood to mean both physical components of the network (equipment, cables, switches, etc.) and digital and logical resources (IP addresses, licenses, software, licensed frequencies, etc.). The evolution of communications network asset management reflects the path from paper records to intelligent digital twins, where each asset is part of a business process, SLA, and investment cycle. The history of these AMS includes the following stages of development: 1960–1980s — In the era of electromechanical automatic telephone exchanges and copper lines, TfOP operators kept paper and tabular records of cables, rack equipment, and switches. Records were kept in production and maintenance departments using equipment catalogs, inventory books, and schematic diagrams. Asset management functions at this stage were performed manually: write-offs, maintenance, and relocation. 1980–2000s — With the advent of digital automatic telephone exchanges (DX-200, EWSD, S-12, ATSC-90, etc.), more accurate accounting of digital modules, licenses, and software became necessary. Excel spreadsheets and local databases (DB) appeared, in which switches and boards were recorded, and the first maintenance information systems integrated with equipment passports began to be introduced. The need for recording service life, repairs, and upgrades has increased. 2000–2010s — the era of integration with OSS/BSS began. The construction of next-generation NGN (Next Generation Network) multiservice networks requires accounting for optical cables, IP equipment, servers and software, VoIP gateways, and virtualized resources. The OSS systems being implemented (e.g., Cramer, NetCracker, Argus) already include AMS (Asset Management System) functions. The concepts of asset lifecycle management LCM and CMDB have become part of the everyday vocabulary of communications network operators. There is a division into passive (cables, cabinets) and active (equipment, licenses, services) assets. Asset management already encompasses warehouse management, maintenance, and operation of telecommunications equipment, software upgrades, integration with accounting systems, procurement systems, and other financial and ERP systems. 2010–2020s — In the process of further digital transformation and automation, full-fledged asset management platforms are being developed: IBM Maximo, ServiceNow ITAM, Argus-AMS (Russia), SAP EAM, and others. Integration with capital expenditure (CAPEX) planning, risk and failure management, and digital twins (Digital Twins). The implementation of the Configuration Management Database (CMDB) as a single source of reliable data is being completed. Integration with ITIL/ITSM is taking place. Asset Management is being combined with IT Service Management (ITSM), and links with Incident/Problem/Change Management are being improved. There is growing interest in the asset lifecycle, tracking updates, and service life. For multi-service post-NGN public networks with a huge territorial structure, equipment geolocation, remote monitoring, and service level management are becoming particularly important. 2020-2030s — With the transition to 5G/6G networks and the use of cloud/fog technologies, the Internet of Things (IoT) and Artificial Intelligence (AI) in Asset Management systems, asset management now includes virtual network functions ISSN 2305-7254________________________________________PROCEEDING OF THE 38TH CONFERENCE OF FRUCT ASSOCIATION ---------------------------------------------------------------------------- 359 ---------------------------------------------------------------------------- (VNF), containerized components (Kubernetes), SaaS licenses, etc. In this regard, ML models are now used in AMS for wear prediction, integration with IoT sensors, and cloud AMS services. This allows you to manage remote node resources, predict failures based on telemetry, and automatically plan maintenance. New features of AMS include virtualization, intellectualization, and digital twins, as well as integration with AI/ML, predictive maintenance, and automatic optimization systems. Expansion to virtualized NFV/SDN infrastructure and cloud resources (up to Kubernetes nodes) is underway. The use of digital twins involves representing an asset as a digital entity with telemetry, status, and metadata. II. AMS ARCHITECTURE It is crucial to distinguish AMS systems from traditional NRI (Network Resource Inventory) technical accounting, which is designed to store information about relevant accounting objects (including their parameters, connections, etc.). Unlike NRI, AMS systems focus on managing the lifecycle of virtually any tangible and intangible assets of a telecommunications company, including asset movement accounting, support for replenishment order management, and support for development projects (e.g., construction of the Operator's infrastructure for 5 G generations). Asset Management should also be distinguished from warehouse accounting functionality, which does not allow assets to be used in network management processes. Thus, the Asset Management system manages the lifecycle of telecommunications equipment and software, as well as IT systems—recording purchases, commissioning, maintenance, upgrades, and write-offs, integration with OSS/ERP/CRM—transferring data to related systems: logistics, billing, procurement, reporting, and analytics — asset valuation, depreciation, SLA monitoring, security, and compliance — regulatory compliance and asset access control. With this in mind, the approximate structure of an AMS is shown in Fig. 1. According to this structure, an AMS has the following groups of business functions: ꞏResource strategy & planning – automates the processes of planning resource purchases and their consumption; ꞏResource capability delivery – provides the business with the required resources; ꞏResource Lifecycle Management – records all possible statuses and locations of inventory items; ꞏResource Catalog Management – ensures that the inventory catalog is kept up to date; ꞏSpares and Warehouse Inventory Management – automates the management of inventory at the enterprise. Fig. 1. Asset Management System Structure To expand on the typical AMS structure shown in Fig. 1, Table I summarizes the characteristics of the five most popular AMS systems. Before proceeding, we would like to note that the information has been gathered from public sources and our experience working with colleagues from operating companies, and is not intended to be definitive. Nevertheless, we will provide our reasoning for the table below. The reasons for our choice are as follows: ꞏIBM Maximo - a powerful, world-class EAM platform; integrates well with telecom environments, especially in CAPEX-intensive projects (pillars, data centers, base stations); has reliable support for TOR, SLA, and mobile interfaces. ꞏArgus AMS – a Russian localized solution with maintenance support, integration with OSS/BSS, management accounting of material and IT assets; support for regulatory documentation; suitable for the telecom realities of Russia and the CIS. ꞏServiceNow ITAM – suitable for operators with a strong IT infrastructure; deep integration with ITSM and CMDB, advanced SAM module, flexible cloud deployment; used by many Tier-1 CSPs. ꞏBMC Helix Discovery – implements auto-discovery of IT and network assets; used in multi-cloud environments, suitable for infrastructure automation, especially in IP/MPLS and virtualized networks. Let's take a closer look at the functionality of these AMSs, which perform the functions of asset balance accounting, asset lifecycle status, history of changes in their properties, as well as warehouse and inventory accounting, IT asset accounting and management, organization of a communication network object inventory database for use in related processes, and analytical reporting in telecommunications companies. The AMS system allows you to solve the following tasks: ISSN 2305-7254________________________________________PROCEEDING OF THE 38TH CONFERENCE OF FRUCT ASSOCIATION ---------------------------------------------------------------------------- 360 ---------------------------------------------------------------------------- • Create a unified, centralized system for operational accounting of resources, organized by location and purpose (e.g., operation, storage, maintenance, repair, etc.), in terms of their operational characteristics. • Accounting for resources broken down by budgeting sources and investment programs, by resource type, according to a category catalog, by operational and consumer characteristics (new/used, illiquid), material characteristics, indicating the direction of use of materials (e.g., for repairs, construction, ongoing operation, etc.) • Ensure and support resource movement processes from the formation of needs to decommissioning by ensuring that each movement operation is recorded in relation to the responsible user, each movement operation has a clearly defined type, each movement operation contains information about the assets being changed (affected), the possibility of using and connecting electronic signature means to confirm the execution of operations is provided, timely operational information is provided to interested parties, and automated notification of related information systems about changes made is provided. • Control the current composition and consumption of resources, with the possibility of forming a reserve fund for emergency situations, and reduce the costs of purchasing both tangible and intangible resources within the organization. This is achieved by displaying the current status of balances at a given moment in time, identifying unclaimed balances and idle materials, forecasting consumption, and taking preventive measures (initiating pre-purchases). • Generate analytical reports thanks to a flexible classification structure and a flexible resource classification mechanism. These tools enable you to quickly search for/select the required analogue, followed by an analysis of the resources available to operate. To perform this task, the user only needs to create a filter by specifying the required characteristics. Based on the results, the system will analyze availability and, if necessary, automatically generate an order to move the found resources, reserving them for task completion (to prevent the found resources from being removed). Reporting tools are provided with the following capabilities: generating reports on the current status of balances at a given location, generating reports on changes in the status of assets (balance, characteristics), and generating reports based on data from multiple sources (information systems). Thus, AMS serves as a kind of central hub for managing the company's assets and connects the various departments of the enterprise. The AMS system can act as a master system for operator asset data and build asset management algorithms within the existing IT landscape. Such a system enables the easy identification of any purchased and assigned asset, the tracking of current inventory levels, and the maintenance of the required level of non-depletable balances to enhance service delivery speed, which is crucial for B5G networks. III. M ATHEMATICAL MODELS OF AMS Now let's move on to the most interesting part of the article – the analysis of mathematical models used in asset management systems in telecommunications. These models enable you to optimize asset management, maintenance, depreciation, and investment decisions. By analogy with the comparative analysis of AMS, we will present these models in Table II. Fig. 2. Asset Management Lifecycle The systems mentioned above use the models listed in Table I. For example, IBM Maximo utilizes predictive analytics (Predictive Maintenance) and an Asset Health Index, while ARGUS AMS employs reliability and maintenance planning models, as well as scheduled maintenance. ServiceNow ITAM leverages ML and CMDB links for risk assessment and replacement. TABLE I Model Purpose Formulas / Ideas Asset Life Cycle Model (LCM) Assessment of the value, condition, and service life of an asset V(t) = 𝑉𝑒 — exponential depreciation Optimal maintenance model (Preventive Maintenance) Determination of optimal maintenance intervals C(t) = 𝐶  󰇛𝑡󰇜𝐶 where 𝐶— maintenance intervals, 𝐶 — failure costs Reliability Models Calculation of failure probability and mean time between failures R(t) = 𝑒  , where λ — шы failure rate Markov asset state models Transitions between states: operational → partially operational → inoperative Матрицы переходов: P=[𝑝], where 𝑝 — is the probability of transition from state i to j ISSN 2305-7254________________________________________PROCEEDING OF THE 38TH CONFERENCE OF FRUCT ASSOCIATION ---------------------------------------------------------------------------- 361 ---------------------------------------------------------------------------- Model Purpose Formulas / Ideas Asset Value Index / Risk Matrix Determining asset maintenance priorities based on value and failure risk Matrices with axes “Criticality” × “State” → color zones (green, yellow, red) CAPEX/ OPEXmodels Distribution of investments between asset maintenance and replacement 𝑁𝑃𝑉1  С𝐹 󰇛1𝑟󰇜   where С𝐹 — is the cash flow Wear and tear prediction models (ML) Predicting time to failure based on historical data Models: linear regression, Random Forest, XGBoost by parameters: age, conditions, etc. Here is an example of optimizing the maintenance schedule. We need to find the interval 𝜏опт at which the sum of the cost of regular maintenance 𝐶 and the expected cost of failure  󰇛е󰇜 𝐶 is minimal, i.e., find the minimum min C(t) = 𝐶  󰇛𝑡󰇜 𝐶. Let the initial cost of the asset — the Session Border Controller (SBC) — be 100,000 conventional units. Let's calculate this example using the key formulas in Table 2 — cost, reliability, optimal maintenance interval, and NPV of the project. The values of cost V(t) and reliability R(t) are calculated over a 10-year period. The graph illustrates the rate at which the asset depreciates at a 7% annual rate. The calculations allow us to evaluate the effectiveness of maintenance and the economics of asset operation. Fig. 2. Change in asset value SBC According to the exponential depreciation model in Fig. 2, the asset value V(t) decreases over time. After just five years, the asset loses about 30–35% of its value, and by year 10, almost half of it. The reliability model shows that the probability of failure-free operation decreases exponentially. After 10 years, reliability is less than 60%. This is important when planning maintenance and replacement. R(t) = 𝑒  , λ=0.05 1NPV (Net Present Value) is a financial indicator that assesses the profitability of an investment project, taking into account the time value of money. In other words, NPV shows how much “today's” money an investment will bring, taking into account inflation and other factors affecting the value of money over time. A model that minimizes the total costs of maintenance and failure repair is calculated for a given cost of prevention (€ 1,500) and the cost of failure (€ 25,000). The optimal interval was found to be 0.5 years, with an average annual cost of 1,625 euros. C(t) = 𝐶  󰇛𝑡󰇜 𝐶 = 1,625 euros The total discounted income from the asset's operation over 5 years, taking into account income from its use and maintenance costs, amounted to approximately € 90,955 at a discount rate of 10%. This shows that the asset is economically efficient with the right maintenance strategy. 𝑁𝑃𝑉  ∑С  󰇛󰇜   = 90,955 This example clearly illustrates that regular and optimally planned maintenance allows you to: reduce risks and costs, maintain high reliability, maximize the financial return from the operation of a telecommunications asset, which is particularly relevant for telecommunications operators, where equipment costs are high and downtime is critical. CONCLUSION In the context of the transformation of 5G/B5G network operators, asset management is becoming not just an accounting tool but a key element of strategic planning, operational efficiency, and financial stability. Historically, AMS systems have evolved from paper inventories and simple equipment accounting to intelligent digital platforms integrated with OSS/BSS, ITSM, ERP, and geoinformation systems. Modern AMS platforms (e.g., IBM Maximo, Argus-AMS, SAP EAM, ServiceNow ITAM) provide the ability to not only track the location, technical condition, and value of assets, but also: – calculate maintenance and replacement plans based on reliability and economic models, – integrate with digital twins and IoT sensor networks, – analyze asset lifecycles using predictive analytics and machine learning, – make informed investment decisions (CAPEX/OPEX) based on NPV, TCO, and failure risk assessments. These mathematical models enable telecom operators to minimize costs, extend asset lifetimes, enhance infrastructure reliability, and ultimately improve customer service quality. The implementation of modern asset management practices in the telecommunications industry enables a shift from reactive to proactive asset management, which is ISSN 2305-7254________________________________________PROCEEDING OF THE 38TH CONFERENCE OF FRUCT ASSOCIATION ---------------------------------------------------------------------------- 362 ---------------------------------------------------------------------------- especially important in the era of 5G/6G networks, edge infrastructure, and network function virtualization. REFERENCES [1] Goldstein, B. Goldstein. Information and Communication Management. // St. Petersburg: BHV-Petersburg, 2025. – 200 p. [2] TM Forum – Asset Management in the Age of 5G — white paper, 2022 [3] K. E. Samuilov, A. V. Chukarin, N. V. Yarkina. Business Processes and Information Technology in the Management of a Modern Information and Communications Company. Moscow: Alpina Publishers, 2015. 512 p. [4] John Woodhouse. 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