Gateway Placement Research Articles

Multi-Objective Optimization of Gateway Location Selection in Long-Range Wide Area Networks: A Tradeoff Analysis between System Costs and Bitrate Maximization

LoRaWANs play a critical role in various applications such as smart farming, industrial IoT, and smart cities. The strategic placement of gateways significantly influences network performance optimization. This study presents a comprehensive analysis of the tradeoffs between system costs and bitrate maximization for selecting optimal gateway locations in LoRaWANs. To address this challenge, a rigorous mathematical model is formulated to incorporate essential factors and constraints related to gateway selection. Furthermore, we propose an innovative metaheuristic algorithm known as the M-VaNSAS algorithm, which effectively explores the solution space and identifies favorable gateway locations. The Pareto front and TOPSIS methods are employed to evaluate and rank the generated solutions, providing a robust assessment framework. Our research findings highlight the suitability of a network model comprising 144 gateways tailored for the Ubon Ratchathani province. Among the evaluated algorithms, the M-VaNSAS method demonstrates exceptional efficiency in gateway location selection, outperforming the PSO, DE, and GA methods.

Single gateway placement in wireless mesh networks

Single gateway placement in wireless mesh networks

Developing an Intelligent Decision Support System for large-scale smart grid communication network planning

The placement of routers and gateways in wireless communication networks for Smart Grid Advanced Metering Infrastructure (AMI) is a complex problem often addressed in the literature through heuristics, clustering, or linear programming approaches. In large-scale scenarios, the complexity is directly related to the region’s number of smart meters and poles. The terrain profile can introduce signal quality degradation between a smart meter and the routers and gateways, further complicating the problem. This study presents the AIDA-ML method, representing a preliminary step toward developing an Intelligent Decision Support System (IDSS) for an effective positioning strategy. AIDA-ML incorporates a feature engineering-based strategy and utilizes machine learning algorithms to learn from the results computed by a heuristic method called AIDA. The heuristic approach is too time-consuming, relying on external resources like numerous terrain profile API calls and a deep understanding of wireless communication loss models. To implement a machine learning-based and more straightforward approach, a feature engineering process is employed to capture the operational characteristics and results of the analytical method while requiring less processing time. Through experiments conducted with real-world data from 26 cities in the state of Paraná, Brazil, comprising 466,237 smart meters and 352,867 poles, the results obtained using machine learning algorithms suggest that AIDA-ML can ensure the connection coverage of smart meters while meeting the same minimum requirements established for the analytical method. Moreover, AIDA-ML offers the advantage of reducing the processing time by 87.60% and by 96.86% the overall search space size compared to the heuristic approach.

OPTIMAL BLUETOOTH LOW ENERGY (BLE) SYSTEM DEPLOYMENT STRATEGY PRIOR TO SYSTEM APPLICATION ON THE CONSTRUCTION SITE

The application of Bluetooth Low Energy (BLE) systems for labour tracking on construction sites is a popular research trend. Strategic system deployment is crucial for ensuring the overall reliability and feasibility of these systems. This study aims to identify the optimal BLE system deployment strategy for tiling work zones in three different renovation sites. The BLE system consists of BLE beacon, BLE gateway, Raspberry Pi (data logger), and MATLAB for data analysis. To ensure optimal placement of the BLE gateway, site visits were conducted to evaluate various conditions, such as power supply availability, signal blockage by structures, and potential disruption to the tiling work. In addition, the beacon transmission (Tx) levels were adjusted to enhance the detection accuracy of the system. The findings show that the optimum beacon Tx powers at sites A, B, and C are -12dBm (86.3% accuracy), -16dBm (94.6% accuracy), and -16dBm (91.1% accuracy), respectively. These findings will be adopted in future research on these sites. The study contributes to the understanding of optimal BLE system deployment strategies in construction sites, which can improve labour tracking accuracy and overall project management.

A load-balanced algorithm for Internet Gateway placement in Backbone Wireless Mesh Networks

The placement of Internet Gateways (IGWs) is crucial in designing Backbone Wireless Mesh Networks (BWMNs) as it establishes the connection between the BWMN and the wired backbone. Efficient placement ensures high-bandwidth network coverage and utilization of the BWMN architecture. Despite considerable research efforts devoted to the IGW placement problem in WMNs, further research is still needed to tackle IGW reduction, improve Quality of Service (QoS), and achieve load balancing among IGWs and Wireless Mesh Routers (WMRs). In this paper, we propose a Load-balanced Algorithm for IGW placement in BWMN to achieve high-bandwidth network coverage while satisfying QoS constraints. The algorithm distributes WMRs among IGWs based on their location and computation degree, considering the load balance between IGWs and WMRs in each cluster. Experimental results demonstrate that our algorithm outperforms existing algorithms in terms of the number of IGWs placed in various scenarios. Our algorithm achieves an impressive reduction of more than 20% in the number of IGWs required in small typologies, and the improvement further escalates in larger topologies. To accomplish this, we utilize the innovative IGW Reallocation() algorithm, which accurately calculates the load ratio for each WMR within each cluster, facilitating the selection of the most suitable WMR to be designated as the new IGW. Additionally, our algorithm effectively addresses traffic load balancing for both IGWs and the entire network system by skillfully leveraging the relay links and delay hops present within WMRs forming the clusters. The outcomes of our research conclusively demonstrate that our Load-balanced Algorithm significantly enhances IGW placement efficiency, network coverage, and traffic load balancing, leading to improved performance, scalability, and a noteworthy contribution to the design and optimization of BWMNs.

HEURISTIC GATEWAY PLACEMENT FOR MINIMAL TRANSMISSION POWER & COLLISION PROBABILITY IN AN INTERNET OF THINGS LOW POWER WIDE AREA NETWORK (HGPMTPIoT-LPWAN)

A variety of long-range (LoRa), low-power, and low bit-rate wireless network technologies have been made possible by the Internet of Things' (IoT) rapid growth. As a radio technology for the implementation of numerous Internet of Things applications, the LoRa low-power wide area network (LPWAN) has gained prominence. LoRa is frequently used in conjunction with the Long-Range Wide Area Network Media Access Control (LoRaWAN MAC) protocol and functions in the Industrial, Scientific, and Medical (ISM) bands, which are unlicensed. As a result of receiving a wide variety of different message sizes from diverse applications, LoRa networks experience scalability issues when the number of end nodes connected to one network is more than the shared number of channels. This results in collisions and packet loss. In this paper, heuristic gateway placement for minimal transmission power & collision probability in an internet of things low power wide area network (HGPMTPIOT-LPWAN) is proposed to increase network efficiency, and improve overall performance by measuring collision probability, which in turn can help to reduce the need for retransmissions and packet drop rate. The things network simulator is used to measure the collisions and packet drop rate. An improved performance for HGPMTPIOT as against the efficient graph-based gateway placement (EGBGP) for large-scale LoRaWAN deployments is achieved for packet drop rate by 6%. Likewise, the simulation results show improvements in terms of decreasing the collision probability for 20 to 60 nodes by 20%.

Efficient graph-based gateway placement for large-scale LoRaWAN deployments

Low Power Wide Area Networks with Long Range Wide Area Networks (LoRaWANs) as one of their most prominent representatives are promising solutions for future Internet of Things deployments. The technology is characterized by low energy requirements leading to long battery lifetimes. However, the drawbacks are limited throughput rates and the unreliable nature of the LoRa technology. Specifically its random channel access approach leads to significant message collisions and thus, data loss in larger deployments. From a network planning point of view, the reduction of potentially colliding messages at the frequency bands in combination with limiting the transmission duration of messages is a promising approach. For that reason, we present a novel graph-based gateway placement approach. We show that our approach performs similar to state-of-the-art related work in the worst case and reduces the required number of gateways by up to 40% while reducing the collision probability by up to 70%. Furthermore, we overcome the challenge of scalability of our approach when placing gateways in very large networks. By splitting the problem into smaller problem instances by pre-clustering, we can solve arbitrarily large instances efficiently without a significant increase in number of required gateways in real networks.

LoRaWAN Gateway Placement in Smart Agriculture: An Analysis of Clustering Algorithms and Performance Metrics

The use of Wireless Sensor Networks (WSN) in smart agriculture has emerged in recent years. LoRaWAN (Long Range Wide Area Networks) is widely recognized as one of the most suitable technologies for this application, due to its capacity to transmit data over long distances while consuming little energy. Determining the number and location of gateways (GWs) in a production setting is one of the most challenging tasks of planning and building this type of network. Various solutions to the LoRaWAN gateway placement problem have been proposed in the literature, utilizing clustering algorithms; however, few works have compared the performance of various strategies. Considering all these facts, this paper proposes a strategy for planning the number and localization of LoRaWAN GWs, to cover a vast agricultural region. Four clustering algorithms were used to deploy the network GWs: K-Means and its three versions: Minibatch K-Means; Bisecting K-Means; and Fuzzy c-Means (FCM). As performance metrics, uplink delivery rate (ULDR) and energy consumption were used, to provide subsidies for the network designer and the client, with which to choose the best setup. A stochastic energy model was used to evaluate power consumption. Simulations were performed, considering two scenarios: Scenario 1 with lower-medium concurrence, and Scenario 2 with higher-medium concurrence. The simulations showed that the use of more than two GWs in Scenario 1 did not lead to significant improvements in ULDR and energy consumption, whereas, in Scenario 2, the suggested number of GWs was between 11 and 15. The results showed that for Scenario 1, the FCM algorithm was superior to all alternatives, regarding the ULDR and mean energy consumption, while the K-Means algorithm was superior with respect to maximum energy consumption. In relation to Scenario 2, K-Means caused the best ULDR and mean consumption, while FCM produced the lowest maximum consumption.

Resilience enhancement scheme for gateway placement in space information networks

Space information networks provide users with network services anytime and anywhere through satellites and gateways. Gateways are the main part of the terrestrial facilities of the space information networks, and their placement poses an important issue that will significantly affect the network performance. At the same time, the low security of gateways makes them vulnerable to cyber attacks, increasing the end-to-end delay of users. Therefore, it is critical to place gateways in suitable locations to maintain the availability of communications in malicious scenarios. Accordingly, this paper introduces resilience into the gateway placement problem for the first time, considering a scenario involving malicious users, a low earth orbit satellite constellation, and terrestrial networks with limited communications. Malicious users may launch simultaneous distributed denial of service attacks against arbitrary gateways. An optimization model is proposed to simultaneously optimize the average network delay in normal services and potentially malicious scenarios. In order to improve the solution efficiency of the gateway layout, an improved cuckoo search algorithm is proposed, and the comparison results show that its performance is better than the existing algorithms. The results of the case study show that the proposed optimization model can significantly enhance the ability of the space information networks to absorb malicious attacks. When 90% of the gateways are attacked, the end-to-end delay of users can be reduced by up to 82%.

Optimizing Broadband Access and Network Design in Wireless Mesh Networks using Multi-Objective Particle Swarm Optimization

Wireless Mesh Networks (WMNs) are becoming increasingly recognized as a promising solution for delivering broadband internet access, owing to their versatility, rapid deployment capabilities, and self-configuring characteristics. This work focuses on optimizing the gateway placement problem in WMNs taking into account objectives like minimizing the number of gateways, reducing hop count, and minimizing the path delay. We employ Multi-Objective Particle Swarm Optimization (MOPSO) to simultaneously optimize these objectives and find an optimal gateway placement. The results demonstrate its superiority over traditional Particle Swarm Optimization (PSO) in finding better solutions with conflicting objectives. The work provides a practical and effective approach to optimizing broadband access, network design, and gateway placement in WMNs, contributing to the advancement of wireless communication technology.

Optimal Gateway Placement for Minimizing Intersatellite Link Usage in LEO Megaconstellation Networks

Megaconstellation networks, represented by Starlink and OneWeb, have become a promising solution for the wide-area Internet of Things (IoT). IoT messages collected by the satellite can be routed to the ground gateway via multiple intersatellite link (ISL) relays and then access the ground network. Compared to traditional constellations, megaconstellations with massive satellites require more ISL relays that are greatly affected by the number and location of ground gateways. In this article, we focus on the ISL usage for connecting satellites and gateways and propose a novel method with low computation cost to evaluate the ISL usage metric. Then, we formulate a mixed-integer optimization model for the gateway site optimization (GSO) problem with minimizing the overall ISL usage, which is then simplified through model transformation. An IBD-PSO algorithm is proposed to solve the transformed GSO problem. Based on the Starlink constellation, simulation results have verified the proposed method by comparisons with previous studies. We further investigate how the gateway placement is affected by the gateway number and traffic demand pattern. The relations between gateway placement and ISL hop count of different satellites are also studied.

Traffic-aware gateway placement and queue management in flying networks

Unmanned Aerial Vehicles (UAVs) have emerged as adequate platforms to carry communications nodes, including Wi-Fi Access Points and cellular Base Stations. This has led to the concept of flying networks composed of UAVs as a flexible and agile solution to provide on-demand wireless connectivity anytime, anywhere. However, state of the art works have been focused on optimizing the placement of the access network providing connectivity to ground users, overlooking the backhaul network design. In order to improve the overall Quality of Service (QoS) offered to ground users, the placement of Flying Gateways (FGWs) and the size of the queues configured in the UAVs need to be carefully defined to meet strict performance requirements. The main contribution of this article is a traffic-aware gateway placement and queue management (GPQM) algorithm for flying networks. GPQM takes advantage of knowing in advance the positions of the UAVs and their traffic demand to determine the FGW position and the queue size of the UAVs, in order to maximize the aggregate throughput and provide stochastic delay guarantees. GPQM is evaluated by means of ns-3 simulations, considering a realistic wireless channel model. The results demonstrate significant gains in the QoS offered when GPQM is used.

Methodology for LoRa Gateway Placement Based on Bio-Inspired Algorithmsfor a Smart Campus in Wooded Area

The Internet of Things (IoT) device scenario has several emerging technologies. Among them, Low-Power Wide-Area Networks (LPWANs) have proven to be efficient connections for smart devices. These devices communicate through gateways that exchange points with the central server. This study proposes an empirical and statistical methodology based on measurements carried out in a typical scenario of Amazonian cities composed of forests and buildings on the Campus of the Federal University of Pará (UFPA) to apply an adjustment to the coefficients in the UFPA propagation model. Furthermore, an Evolutionary Particle Swarm Optimization (EPSO) metaheuristic with multi-objective optimization was applied to maximize the coverage area and minimize the number of gateways to assist in the planning of a LoRa network. The results of simulations using the Monte Carlo method show that the EPSO-based gateway placement optimization methodology can be used to plan future LPWAN networks. As reception sensitivity is a decisive factor in the coverage area, with −108 dBm, the optimal solution determined the use of three gateways to cover the smart campus area.

Gateway Placement in Integrated Satellite–Terrestrial Networks: Supporting Communications and Internet of Remote Things

Low Earth orbit (LEO) satellite constellations have become a promising architecture to integrate with terrestrial networks for facilitating communications and Internet of Remote Things (IoRT) services through gateways. Nevertheless, different gateway locations may have various channel conditions and service demands due to differentiated atmospheric conditions, populations, and number of terminal devices required by IoRT services in different areas. Besides, the gateway placement scheme further affects the service coverage performance and the access performance of the network to service demands. Therefore, gateway placement plays a pivotal role in improving network capabilities in the integrated system of LEO satellites and terrestrial networks (ISoLS-TNs). Motivated by the aforementioned facts, in this article, we first formulate the gateway placement problem in ISoLS-TNs as a multiobjective optimization problem to maximize the total revenue of service data demand within coverage while minimizing the average access distance and the number of deployed gateways. In order to enhance network resource utilization and assure local information confidentiality, a distributed resource allocation (DRA) mechanism based on the alternating direction method of multipliers (ADMMs) algorithm is designed to calculate the total revenue of service data demand within coverage. Furthermore, we propose a genetic-based gateway placement algorithm with the ADMM for DRA. Finally, through massive simulations based on real data, we validate the effectiveness of the proposed algorithm in improving resource utilization and coverage performance of the network. In addition, the results also bring lights on the relationship between service data demand distribution and gateway location preference.

Hybrid PLC and LoRaWAN Smart Metering Networks: Modeling and Optimization

The evolution toward the so-called smart grid (SG) needs to be supported by robust and cost-efficient advanced metering infrastructure. This article focuses on technology selection and gateway placement in hybrid SGs, wherein each smart meter (SM) is equipped with either a power line communication or a long-range wide area network protocol node to connect to its serving gateway. The latter is endowed with both technologies. In particular, we introduce an analytical framework to characterize the performance–cost tradeoffs using a multicriteria optimization approach. For each technology, a set of performance objective functions (i.e., sum-rate and max–min) has been derived based on the ergodic capacity, whereas the cost is represented by SG hardware expenses. Then, the nondominated sorting genetic algorithm-II has been exploited using an appropriate chromosome structure to provide the suitable access technology for each SM along with the optimal number and the placement of the serving GWs. Extensive numerical simulations have shown that hybrid solutions provide a good interplay between performance and investment costs, spurring the need to redefine the conventional SG designs traditionally operating in single communication technologies.

Carbon Footprint vs Energy Optimization in IoT Network Deployments

We are witnessing the full integration of the Internet of Things (IoT) into many social and economic sectors. Part of this unprecedented growth is due to the emergence of new communication technologies such as Low Power Wide Area Networks (LPWAN), which have been the catalyst for previously unfeasible smart applications. Efforts to optimize energy consumption in these types of networks have been necessary to extend their lifetime. However, not much attention has been paid to the study and optimization of the carbon footprints (CF) of these network deployments. In general, it has always been understood that minimizing energy consumption should also minimize the carbon footprint. In this work, the carbon footprint of a generic IoT network that uses renewable energy sources and communicates via LoRa is explored, and an optimization framework is proposed. We have found that minimizing energy consumption and the carbon footprint are two different things. In fact, we show that it is not possible to minimize the carbon footprint without greater energy consumption, and vice versa. This is due to the placement of gateways in the network. Our findings could be extrapolated to other networks with similar topologies. These results suggest that a fresh perspective on the optimization of IoT networks is needed to seriously consider environmental sustainability criteria that has been ignored up to now.

Distance Aware Gateway Placement Optimization for Machine-to-Machine (M2M) Communication in IoT Network

In the research field, network performance for different smart applications plays an important role in the IoT network. Several factors, such as packet delay, network throughput, energy consumption, heterogeneity, proper gateway placement and load balancing, have a greater impact on network performance. In this article, two factors, such as optimal gateway placement and energy consumption, are investigated in order to improve the performance of the IoT network. Various methods are used to find the lo-cation of the Coordinating Devices (CDs) and to place constraint gateways in such a way that all CDs within the network should be covered by at least one gateway in order to allow the dissemination of data within the net-work. All of these CDs in the wireless network send their data to their near-by gateway based on Euclidean distance optimization. Euclidean distance performance is better than linear data transmission. During data transmission, nodes are unable to transmit data due to obstacles encountered in the path to the destination which result in a minimal energy efficiency improvement. Our proposed system solves the issue of gateway location optimization based on different distance-based approaches called Euclidean Distance (ED) and Manhattan Distance (MD) used in the wireless network to achieve the objective of reducing energy consumption.

Gateway Placement Optimization in LEO Satellite Networks Based on Traffic Estimation

Using satellite constellations to provide global Internet access services has recently drawn increasing attention. A low-Earth orbit (LEO) satellite network with multiple satellites provides global coverage, low latency, and operates independently, by which it effectively complements terrestrial IP networks. Satellite gateways are located on the ground and can serve as data exchange points between satellite networks and the Internet. As the placement scheme can affect network performance, finding appropriate sites for gateways constitutes a fundamental problem. This paper proposes a gateway placement optimization (GPO) method for LEO satellite networks in order to solve this problem by modeling it as a combination optimization problem. We aim to identify the best gateway locations that can balance traffic loads while using as few gateways as possible. The constraints to be satisfied concern the physical links between gateways and satellites: specifically, link interference, satellite bandwidth, and number of satellite antennas. We use a gravity model to estimate the traffic matrix from/to gateways and satellites, then we adopt and modify the discrete particle swarm optimization (PSO) algorithm to solve this problem. Finally, we apply the GPO method to numerical tests on real satellite constellations. The results indicate that our method performs well and effectively.

Gateway placement and traffic load simulation in sensor networks

AbstractBecause of the wide variety of possible application fields and the spread of smart devices, the research of wireless sensor networks has become an increasingly important area in the last decade. During the design of these networks, several important aspects have to be considered, for example the lifetime of the network, expected battery usage, or robustness of the installed system. In this paper a simulation environment is introduced that enables the testing of different information spreading methods on the network and provides suggestions for gateway placements with different objectives.

LoRa Network Planning and Deployment: A Terrestrial Navigation Application

Long Range (LoRa) is a popular low power wide area network (LPWAN) technology which operates in the Industrial, Scientific and Medical (ISM) frequency band transmitting information over ranges in excess of 20 km and 5 km in rural and urban landscapes respectively. This is of significance in applications where LoRa may be used as a terrestrial navigation system, or in any wireless sensor network (WSN) applications. A key system performance parameter for network planning and coverage prediction in ranging applications is the horizontal dilution of precision (HDOP). HDOP, is dependent on transmitter geometry and can amplify the position errors depending on how the transmitters are placed with respect to one another. Despite the importance of HDOP, there is no prescribed transmitter or gateway placement technique in the literature that has been combined with HDOP to obtain good position fixes within the coverage area. We propose a gateway placement technique called imaginary triangular tessellation technique to be used in conjunction with HDOP. The HDOP performance of our proposed technique is compared against three other placement techniques, namely naive, Deluany and random placement for the same number of gateways using the total average HDOP score of the area where a method has been deployed, as well as statistical significance and effect size as tests. The goal of our experiment is to find a placement technique that results in a better HDOP score (values between 0 and 1) in most parts of the coverage area. The HDOP scores for the random, Delauny, naive and our proposed technique are 30%, 50% 47% and 70% respectively for 8 gateways. The results also suggest that at least 8 LoRa gateways are needed to service our chosen geographical area of 2500 hectares or 6175 federation football fields. The results demonstrate that our proposed method can be used to set up and plan a LoRa network for use in scenarios such as tracking of animals, vehicles and navigation.