Implementation of Greedy and Simulated Annealing Algorithms for Wireless Access Point Placement

Puspitasari, Nila Feby; Fatta, Hanif Al; Wibowo, Ferry Wahyu

doi:10.1109/aims.2015.35

Cited by 8 publications

(5 citation statements)

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“…UWB anchors placement has been optimized with genetic algorithms and a Gaussian process based residual model [1]. It has also been noted that the exact placement of these beacons greatly affects their performance and it is difficult to analytically determine their range measurements at a given location [1], [2]. Wi-Fi access point optimization has also been considered using line of site and non-line of site models, using non-convex optimization [2].…”

Section: Background / Related Workmentioning

confidence: 99%

“…It has also been noted that the exact placement of these beacons greatly affects their performance and it is difficult to analytically determine their range measurements at a given location [1], [2]. Wi-Fi access point optimization has also been considered using line of site and non-line of site models, using non-convex optimization [2]. Base station placement for cellular mobile communication systems is investigated, in which global coverage [3] or demand coverage [4] are common objectives.…”

Section: Background / Related Workmentioning

confidence: 99%

“…Let L d (x) : X → R be the desired light intensity and L u (x) : X → R be the unknown light intensity at each position x ∈ X . 2 Let L s (x, s; O) : X × R 3N → R be the light intensity at position x generated by light sources configured by the robot with configuration s, conditioned on obstacles. The light intensity with the light source configuration s is given by L(x, s; O) = L u (x) + L s (x, s; O) for each x ∈ X .…”

Section: Notation and Formulationmentioning

confidence: 99%

See 2 more Smart Citations

On-line AUV Survey Planning for Finding Safe Vessel Paths through Hazardous Environments

Denniston

Krogstad

Kemna

et al. 2018

2018 IEEE/OES Autonomous Underwater Vehicle Workshop (AUV)

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Autonomous underwater vehicles (AUVs) are robotic platforms that are commonly used to map the sea floor, for example for benthic surveys or for naval mine countermeasures (MCM) operations. AUVs create an acoustic image of the survey area, such that objects on the seabed can be identified and, in the case of MCM, mines can be found and disposed of. The common method for creating such seabed maps is to run a lawnmower survey, which is a standard method in coverage path planning. We are interested in exploring alternate techniques for surveying areas of interest, in order to reduce mission time or assess feasible actions, such as finding a safe path through a hazardous region. In this paper, we use Gaussian Process regression to build models of seabed complexity data, obtained through lawnmower surveys. We evaluate several commonly used kernels to assess their modeling performance, which includes modeling discontinuities in the data. Our results show that an additive Matérn kernel is most suitable for modeling seabed complexity data. On top of the GP model, we use adaptations of two standard path planning methods, A* and RRT*, to find safe paths for marine vessels through the modeled areas. We evaluate the planned paths and also run a vehicle dynamics simulator to assess potential performance by a marine vessel.

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Section: Background / Related Workmentioning

confidence: 99%

Section: Background / Related Workmentioning

confidence: 99%

Section: Notation and Formulationmentioning

confidence: 99%

See 1 more Smart Citation

On-line AUV Survey Planning for Finding Safe Vessel Paths through Hazardous Environments

Denniston

Krogstad

Kemna

et al. 2018

2018 IEEE/OES Autonomous Underwater Vehicle Workshop (AUV)

View full text Add to dashboard Cite

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“…Hence, determining the best location for Access Point (AP) devices based on the calculation of length and optimizing for AP deployment because the access point is the main part of the network and its location plays a major role in improving network performance as well as optimizing coverage for various environments. In context, several algorithms and simulation scenarios have been presented by researchers in various recent researches to predict the AP device coverage area based on the local position [5]. Data transmission and receiving will be very important to measure and analyse signal strength values using various appropriate parameters to obtain good coverage areas.…”

Section: Introductionmentioning

confidence: 99%

Implementation Mixed Wireless Network with Lower Number of Wi-Fi Routers for Optimal Coverage

et al. 2021

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With the development of various wireless communication networks, Wi-Fi Router positioning and deployment systems have become widely popular in recent years to improve coverage in various environments. In this paper, we present an appropriate mechanism for defining the deployment of Wi-Fi Routers to improve coverage in the Oxford Languages Institute (OLI) environment. In addition, the institute's environment was simulated using the Wireless InSite (WI) Package. In this work, two types of Wi-Fi Routers are used. The first is the TP-Link, while the second is the Rocket. These two devices operate at 2.4 and 5 GHz frequencies. There are two objectives in this work. The first aim is to determine the best location to cover the simulated scene environment in a better way. The second aim is to compare Wi-Fi Routers to find out which Wi-Fi Router is better and find out how many Wi-Fi Routers we need to cover the institute's environment. The comparison between Wi-Fi Routers was based on basic parameters to measure the performance of wireless networks, the most important of which are Coverage Rate (CR) Percentage, Signal Quality Rate (SQR), and Received Power Rate (RPR). According to the results that were shown on the Graphical User Interface (GUI) using MATLAB Software. We noticed that the CR, SQR, and RPR of the Rocket are 83.9080%, 97.0082%, and -35.2337 dBm respectively, and these results are better than the results provided by the TP-Link, as it gave the CR, SQR, and RPR are 32.1839%, 77.8690%, and -58.1685 dBm, respectively. Finally, we conclude that CR using the Rocket is good and we need one device to cover the institute’s environment. While CR using the TP-Link is bad and we need five devices to reach the coverage provided by the Rocket because the Rocket has high transmitted power and gain capacity.

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“…Hence, the coverage area of AP devices would be obtained based on the length calculation and optimizing the AP deployment. In context, a combination of algorithm and simulated annealing has been presented by researchers in [4] to predict the coverage area of the AP device based on localized position. Wi-Fi works based on the standards of IEEE 802.11, where it has been selected two unlicensed frequency bands of 2.4 GHz and 5 GHz to be related to any Wi-Fi-based devices [5].…”

Section: Introductionmentioning

confidence: 99%

Optimal Coverage Area with Lower Number of Access Point

Zaal¹,

Mosleh²,

Abbas³

et al. 2020

Proceedings of the Proceedings of the 1st International Multi-Disciplinary Conference Theme: Sustainable Development and Smart

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With the rapid development in the field of communication networks, an indoor positioning system (IPs) has become extremely popular in recent years. In this paper, we compute the access points (AP's) localization to get the best coverage of the building that takes as a case study and administration of the network. The most interesting researcher topics were computing the Received Signal Strength (RSS) measurement and path loss of the signal. RSS and path loss measurement obtained from different received points distributed in different places of the building. The objective of this technique provides an overview of the available outputs of a standard Wi-Fi signal, which is the RSS from each Access Point. So, it is possible to get a list of the received power coming from all the APs covering the area where the received points are distributed in different locations. The results to determine the best direction at each received point was achieved using Wireless Insite. The methodology is applied over two steps, these are data collecting phase, and localization phase. The case study is implemented simulation results using 3D-Ray Tracing approach based wireless InSite software. This software is a suite of ray-tracing models and high-fidelity EM solvers for the analysis of site-specific radio wave propagation and wireless communication system. The aims of this paper finding the best result of the access points that coverage and transmit a signal to most received points to obtain the lowest cost of the localization method for indoor communication application.

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Implementation of Greedy and Simulated Annealing Algorithms for Wireless Access Point Placement

Cited by 8 publications

References 8 publications

On-line AUV Survey Planning for Finding Safe Vessel Paths through Hazardous Environments

On-line AUV Survey Planning for Finding Safe Vessel Paths through Hazardous Environments

Implementation Mixed Wireless Network with Lower Number of Wi-Fi Routers for Optimal Coverage

Optimal Coverage Area with Lower Number of Access Point

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