INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Special Issue | Volume XIV, Issue XIII, October 2025
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Topology Optimization for Low-Power-Wide-Area Networks
(LPWANs) within Internet of Things (IOT)
Padmaja D Kadam*, Sonali P Lohar
Department of Computer Science, Dr. D. Y. Patil, Arts, Commerce & Science College, Pimpri, Pune-18, Maharashtra,
India
DOI: https://doi.org/10.51583/IJLTEMAS.2025.1413SP001
Received: 26 June 2025; Accepted: 02 July 2025; Published: 22 October 2025
Abstract: Low-Power Wide-Area Networks (LPWANs) have emerged as a critical enabler for large-scale Internet of Things
(IoT) deployments due to their long-range communication capabilities and low energy consumption. However, achieving optimal
performance in LPWAN-based IoT systems requires careful network topology design to balance energy efficiency, coverage,
scalability, and reliability. This paper investigates topology optimization strategies tailored for LPWANs, focusing on
technologies such as LoRaWAN, NB-IoT, and Sigfox. We propose a multi-objective optimization framework that considers node
placement, gateway density, data traffic patterns, and energy constraints. By applying both simulation and analytical modeling,
we showcase notable enhancements in network longevity, delay performance, and packet delivery efficiency. Our results provide
practical guidelines for deploying scalable and sustainable LPWAN topologies in diverse IoT applications, ranging from smart
cities to remote environmental monitoring.
Keywords: Internet of Things, Low-Powered Wide Area Network, Long Range, Long Range WAN.
I. Introduction
The rapid expansion of the Internet of Things (IoT) has driven the need for efficient and scalable communication technologies
capable of connecting billions of devices across vast geographical areas. Devices that interact using technologies such as RFID
tags, sensors, actuators, and mobile phones collaborate to complete specific tasks. The Internet of Things (IoT) comprises three
key aspects: "Things oriented," focusing on the physical objects involved; "Internet oriented," which supports connectivity among
different components; and "Semantic oriented," which manages and interprets the data being exchanged. traffic of communicating
devices within IoT networks Low-Power Wide-Area Networks (LPWANs) have emerged as a leading solution to meet these
demands due to their ability to support long-range communication with minimal energy consumption. Technologies such as
LoRaWAN, NB-IoT, and Sigfox have become increasingly popular for enabling large-scale IoT deployments in various domains,
including smart cities, agriculture, industrial monitoring, and environmental sensing.
Despite their advantages, designing effective LPWAN topologies presents significant challenges. Network performance is heavily
influenced by factors such as node placement, gateway density, traffic patterns, and energy constraints. Improper topology design
can lead to reduced network lifetime, increased latency, and poor data reliability, which hinder the scalability and sustainability of
IoT applications.
Recent developments in IoT communication have paved the way for Low-Power Wide-Area Networks (LPWANs), which are
wireless protocol standards designed specifically for IoT platforms. Low cost, low power consumption, and wide coverage that
connect multiple heterogeneous devices within a continuous network [14]. Studies have shown that LPWAN technologies exhibit
different levels of performance in terms of energy consumption, communication range, coverage area, and latency. LPWAN is a
technology triggered within the IoT that is characterized by low-power operating devices, less expensive network devices, and
wider coverage.
This paper focuses on topology optimization strategies tailored specifically for LPWANs, aiming to balance the trade-offs
between energy efficiency, coverage, scalability, and reliability. By leveraging multi-objective optimization techniques and
combining simulation with analytical modeling, we seek to provide actionable insights and design guidelines that facilitate the
deployment of robust and efficient LPWAN infrastructures.
II. Motivation of The Study
Power-efficient conservation and a wide range triggered the evolution of LPWAN technology within IoT.
The rapid rise in the number of end devices has increased network density, leading to higher energy consumption and a decline in
the energy efficiency of LPWAN technologies. Proper allocation of Spreading Factor (SF) values plays a vital role in optimizing
energy usage in LoRaWAN systems, highlighting the need for further research into more effective assignment methods. The rapid
growth of the Internet of Things (IoT) has led to the deployment of billions of connected devices, many of which operate in
environments with limited energy, bandwidth, and computational resources. Low-Power Wide-Area Networks (LPWANs) have
emerged as a critical enabler for long-range, energy-efficient communication in such scenarios. Technologies such as LoRaWAN,
Sigfox, and NB-IoT are widely adopted due to their ability to support massive IoT deployments with minimal power
consumption.
INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,
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ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Special Issue | Volume XIV, Issue XIII, October 2025
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Optimizing the topology of LPWANs offers a promising solution to enhance network efficiency, coverage, scalability, and energy
conservation. By intelligently organizing the layout and connectivity of nodes, topology optimization can significantly improve
data delivery, extend network lifetime, and ensure reliable communication. Despite its importance, there remains a gap in
practical, adaptive, and scalable topology optimization strategies tailored specifically for LPWAN constraints and IoT application
requirements.
This study is motivated by the need to bridge that gap—by developing and evaluating topology optimization methods that align
with the unique characteristics and limitations of LPWAN-based IoT systems. Such advancements are vital to support the
sustainable growth of IoT infrastructures across diverse sectors such as smart cities, agriculture, logistics, and environmental
monitoring.
1.2 Aim and Objectives of the Study
The aim of this study is to develop and evaluate topology optimization strategies for Low-Power Wide-Area Networks
(LPWANs) within Internet of Things (IoT) environments to enhance network performance, improve energy efficiency, and
support scalable and reliable device connectivity.
The objectives are to:
I.To analyzes existing LPWAN topologies used in IoT systems and identify their limitations in terms of energy efficiency,
coverage, and scalability.
II.To investigates the impact of network density and device distribution on LPWAN performance, particularly in terms of power
consumption and data transmission reliability.
1.3 Significance of the Study
The continued growth of nodes in the IoT domain, as a result of cost efficiency, power efficiency, and wider network coverage,
leading to its high popularity and acceptance in some parts of the world, has led to data traffic generation. Thus, this requires
complex computation for the manipulation of IoT devices communicating within its domain efficient allocation of spreading
factors can help minimize network traffic and reduce energy consumption in IoT environments.
1.4 Scope and Limitation of the Study
The study will focus on Long Range (LoRa), which is a proprietary LoRaWAN protocol used across the IoT domain, specifically
in LPWAN. LoRa-enabled devices are known for their affordability, efficient energy usage, and extensive communication range.
LoRa is a physical layer based on chirp spread spectrum modulation techniques that use wireless communication technology.
Related Work
To address the energy efficiency of IoT devices, considers the optimization of network traffic management for energy power-
saving management in computer networks using a centralized control framework and a hierarchical control framework on both-
sized networks. The Media Access Control protocol is another technique that describes the rules of sending frames across the IoT
network.
I.developed a universal framework to model wireless network device energy usage at the system level ii. Conducted an
investigation into the existing literature on the application of the Internet of Things in energy systems in general, and smart grids
in particular.
iii. Conducted an experiment on the spatial and temporal correlation of the generated traffic in wireless sensor networks (WSNs).
The growing deployment of Low-Power Wide-Area Networks (LPWANs) in Internet of Things (IoT) applications has prompted
extensive research aimed at improving network performance, particularly through topology optimization. LPWAN technologies
such as LoRaWAN, NB-IoT, and Sigfox are designed for long-range, low-power communication; however, their effectiveness
can be significantly influenced by the underlying network topology.
Topology Control and Optimization: Several studies have focused on optimizing LPWAN topologies to enhance energy
efficiency, reduce latency, and improve overall network reliability. For example, clustering methods have been widely used to
organize nodes into energy-efficient groups. These approaches help to reduce the distance between communicating nodes and the
gateway, minimizing power usage and extending network lifespan. Some researchers have also explored gateway placement
optimization, where the strategic positioning of gateways leads to better coverage and reduced transmission loss.
Spreading Factor Allocation in LoRaWAN: In LoRa-based networks, the spreading factor (SF) plays a key role in determining
communication range, data rate, and time on air.
Energy-Aware Protocols: Energy consumption is a primary concern in LPWAN-enabled IoT systems. Researchers have
proposed various energy-aware protocols and algorithms, such as Adaptive Data Rate (ADR), to adjust transmission parameters
dynamically.
INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,
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ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Special Issue | Volume XIV, Issue XIII, October 2025
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Scalability and Interference Management: The scalability of LPWANs has also been studied, particularly in dense IoT
deployments. Interference and packet collision become more prominent as the number of devices increases.
Machine Learning and Intelligent Topologies: More recently, machine learning and artificial intelligence have been applied to
predict optimal topologies and resource allocation in real-time.
III. Methodology Research Methodology
This section includes the extended analysis of the IoT network that is considered in this research work in order to simulate the IoT
network using LoRaWAN protocol within an IoT domain and a detailed explanation of the parameters adopted, along with the
model of how the Optimized Low-Power Wide Area Network is going to be implemented using suitable tools. The methodology
integrates simulation, mathematical modeling, and algorithmic optimization to achieve efficient, scalable, and energy-conscious
network designs.
Framework of the Research
The research framework was formulated based on the proposed objectives of the research work. The proposed methodology
describes how spreading factor allocation to various end nodes was implemented using the network simulator MATLAB to
simulate the IoT network based on the LoRaWAN protocol and to allocate spreading factors to end devices across the IoT
network. It provides a structured approach to investigate and optimize network topology in LPWANs for IoT applications. It
integrates theoretical models, simulation tools, and algorithmic optimization within a clear problem-solution-outcome pathway.
1. Research Inputs
i. Theoretical Foundation
Principles of LPWAN communication (e.g., LoRaWAN, Sigfox, NB-IoT)
IoT system architecture and data flow
ii. Technical Requirements
Device capabilities (battery life, transmission power)
Network coverage area
iii. Environmental Parameters
Node distribution (uniform/random/clustered)
Propagation models (urban, suburban, rural)
2. Research Processes
Step 1: Problem Identification and Modeling
Identify core challenges in LPWAN topology (e.g., energy inefficiency, poor scalability)
Step 2: Algorithm Selection and Development
Choose appropriate optimization techniques: o Heuristic/met heuristic (GA, PSO, ACO)
MILP / constraint-based models
Develop or adapt algorithms to:
Optimize gateway placement
Cluster IoT devices effectively
Determine optimal routing paths
Step 3: Simulation and Implementation
Step 4: Performance Evaluation
Measure performance using key metrics:
Energy consumption
Network lifetime
3. Research Outputs
i. Optimized Topology Designs
INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,
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ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Special Issue | Volume XIV, Issue XIII, October 2025
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Network layout with enhanced energy efficiency and coverage
Adaptive algorithms for node clustering and routing
ii. Evaluation Results
Comparative analysis of optimized vs. non-optimized topologies
Performance across varying node densities and network scales
iii. Design Guidelines
Recommendations for LPWAN deployments in different environments
Trade-offs between energy, coverage, and cost
iv. Outcome and Contributions
Scientific Contribution: New or improved optimization algorithms tailored for LPWAN topologies in IoT.
Practical Application: Deployable guidelines for real-world LPWAN planning (e.g., smart agriculture, environmental
monitoring).
Scalability: Framework adaptable to varying network sizes and topologies.
Internet of Things (IoT) Architecture
Many scholars have varied opinions about the number of levels in IoT technology design. It also states that architectural design
must be programmed according to the requirements of IoT technologies to receive accurate data from IoT applications. Therefore,
selecting appropriate hardware and software is necessary when using the IoT application type. have mentioned that IoT
architecture has four layers as follows: application, information processing, network infrastructure, and sensing. The IoT
architecture describes the layered structure that enables the collection, processing, transmission, and utilization of data from
connected devices.
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Perception Layer (Sensing Layer)
Function: Responsible for collecting physical data from the environment.
Components: Sensors (e.g., temperature, humidity, motion)
Actuators
RFID tags
Cameras
Role:
Identifies objects and gathers data
Converts analog signals to digital
Network Layer (Transmission Layer)
Function: Transfers the collected data from perception layer to data centers or cloud platforms.
Technologies Used:
LPWAN (LoRaWAN, Sigfox, NB-IoT)
Wi-Fi / Bluetooth
4G/5G cellular networks
Ethernet
Role:
Handles data routing and transmission
Provides secure communication protocols
Information Processing Layer
The service processing layer, located above the network infrastructure layer, is responsible for managing and coordinating
services to meet the specific needs and preferences of users. Information analytics, security management, process modeling, and
device management are among the main.
Application Layer
The application layer integrates apps and offers ways for users and applications to communicate with one another. Support sub
layers are frequently built for unique requirements like edge/fog computing and cloud computing.
Parameters for the Implementation of the Proposed Model
i. Network Deployment Parameters
ii. Device and Energy Parameters
iii. Communication Parameters
iv. Optimization Model Parameters
IV. Summary
IoT technology is increasingly embedded in daily life, influencing how people interact with devices and their environment. To
support the billions of Internet connected devices and the data they produce, Low-Powered Wide Area Networks (LPWANs)
have been introduced. LPWANs are capable of providing reliable connectivity even in low-density areas and with devices
consuming low amounts of energy. The research focused on three key approaches: developing an energy consumption model for
LoRaWAN, simulating an IoT wireless sensor network, and implementing spreading factor allocation across the network Particle
Swarm Optimization (PSO) is utilized to enhance the battery efficiency of IoT devices operating within LPWANs.
V. Conclusion
In LPWAN systems, managing battery power consumption is crucial, making it essential to implement effective spreading factor
strategies that ensure optimal allocation to end devices from the gateway, thereby minimizing network traffic.
This study used particle swarm optimization algorithms for effective allocation and yielded better results. This study highlights
the importance of topology optimization in addressing these challenges. By strategically organizing the network structure and
INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Special Issue | Volume XIV, Issue XIII, October 2025
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efficiently allocating spreading factors to end devices, it is possible to significantly reduce power consumption, improve data
transmission reliability, and enhance overall network performance. Techniques such as adaptive clustering, gateway placement
and dynamic spreading factor assignment are essential to achieving these goals.
Furthermore, incorporating intelligent algorithms and context-aware strategies into LPWAN topology design can lead to more
responsive and sustainable IoT deployments. As the demand for large-scale IoT systems continues to grow, optimizing LPWAN
topology will play a vital role in ensuring the longevity and effectiveness of these networks.
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