A Multi-Sensor RSS Spatial Sensing-Based Robust Stochastic Optimization Algorithm for Enhanced Wireless Tethering
The reliability of wireless communication in a network of mobile wireless robot nodes depends on the received radio signal strength (RSS). When the robot nodes are deployed in hostile environments with ionizing radiations (such as in some scientific facilities), there is a possibility that some elec...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2014-12-01
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| Series: | Sensors |
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| Online Access: | http://www.mdpi.com/1424-8220/14/12/23970 |
| _version_ | 1798025951165022208 |
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| author | Ramviyas Parasuraman Thomas Fabry Luca Molinari Keith Kershaw Mario Di Castro Alessandro Masi Manuel Ferre |
| author_facet | Ramviyas Parasuraman Thomas Fabry Luca Molinari Keith Kershaw Mario Di Castro Alessandro Masi Manuel Ferre |
| author_sort | Ramviyas Parasuraman |
| collection | DOAJ |
| description | The reliability of wireless communication in a network of mobile wireless robot nodes depends on the received radio signal strength (RSS). When the robot nodes are deployed in hostile environments with ionizing radiations (such as in some scientific facilities), there is a possibility that some electronic components may fail randomly (due to radiation effects), which causes problems in wireless connectivity. The objective of this paper is to maximize robot mission capabilities by maximizing the wireless network capacity and to reduce the risk of communication failure. Thus, in this paper, we consider a multi-node wireless tethering structure called the “server-relay-client” framework that uses (multiple) relay nodes in between a server and a client node. We propose a robust stochastic optimization (RSO) algorithm using a multi-sensor-based RSS sampling method at the relay nodes to efficiently improve and balance the RSS between the source and client nodes to improve the network capacity and to provide redundant networking abilities. We use pre-processing techniques, such as exponential moving averaging and spatial averaging filters on the RSS data for smoothing. We apply a receiver spatial diversity concept and employ a position controller on the relay node using a stochastic gradient ascent method for self-positioning the relay node to achieve the RSS balancing task. The effectiveness of the proposed solution is validated by extensive simulations and field experiments in CERN facilities. For the field trials, we used a youBot mobile robot platform as the relay node, and two stand-alone Raspberry Pi computers as the client and server nodes. The algorithm has been proven to be robust to noise in the radio signals and to work effectively even under non-line-of-sight conditions. |
| first_indexed | 2024-04-11T18:27:13Z |
| format | Article |
| id | doaj.art-18fba8b128df4bfb8755468409231826 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-11T18:27:13Z |
| publishDate | 2014-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-18fba8b128df4bfb87554684092318262022-12-22T04:09:34ZengMDPI AGSensors1424-82202014-12-011412239702400310.3390/s141223970s141223970A Multi-Sensor RSS Spatial Sensing-Based Robust Stochastic Optimization Algorithm for Enhanced Wireless TetheringRamviyas Parasuraman0Thomas Fabry1Luca Molinari2Keith Kershaw3Mario Di Castro4Alessandro Masi5Manuel Ferre6European Organization for Nuclear Research (CERN), Geneva 1211, SwitzerlandEuropean Organization for Nuclear Research (CERN), Geneva 1211, SwitzerlandEuropean Organization for Nuclear Research (CERN), Geneva 1211, SwitzerlandEuropean Organization for Nuclear Research (CERN), Geneva 1211, SwitzerlandEuropean Organization for Nuclear Research (CERN), Geneva 1211, SwitzerlandEuropean Organization for Nuclear Research (CERN), Geneva 1211, SwitzerlandCAR UPM-CSIC, Universidad Politécnica de Madrid, Madrid 28006, SpainThe reliability of wireless communication in a network of mobile wireless robot nodes depends on the received radio signal strength (RSS). When the robot nodes are deployed in hostile environments with ionizing radiations (such as in some scientific facilities), there is a possibility that some electronic components may fail randomly (due to radiation effects), which causes problems in wireless connectivity. The objective of this paper is to maximize robot mission capabilities by maximizing the wireless network capacity and to reduce the risk of communication failure. Thus, in this paper, we consider a multi-node wireless tethering structure called the “server-relay-client” framework that uses (multiple) relay nodes in between a server and a client node. We propose a robust stochastic optimization (RSO) algorithm using a multi-sensor-based RSS sampling method at the relay nodes to efficiently improve and balance the RSS between the source and client nodes to improve the network capacity and to provide redundant networking abilities. We use pre-processing techniques, such as exponential moving averaging and spatial averaging filters on the RSS data for smoothing. We apply a receiver spatial diversity concept and employ a position controller on the relay node using a stochastic gradient ascent method for self-positioning the relay node to achieve the RSS balancing task. The effectiveness of the proposed solution is validated by extensive simulations and field experiments in CERN facilities. For the field trials, we used a youBot mobile robot platform as the relay node, and two stand-alone Raspberry Pi computers as the client and server nodes. The algorithm has been proven to be robust to noise in the radio signals and to work effectively even under non-line-of-sight conditions.http://www.mdpi.com/1424-8220/14/12/23970wireless tetheringrelaywireless nodesmobile robotsmulti-sensor samplingRSSreceiver spatial sampling |
| spellingShingle | Ramviyas Parasuraman Thomas Fabry Luca Molinari Keith Kershaw Mario Di Castro Alessandro Masi Manuel Ferre A Multi-Sensor RSS Spatial Sensing-Based Robust Stochastic Optimization Algorithm for Enhanced Wireless Tethering Sensors wireless tethering relay wireless nodes mobile robots multi-sensor sampling RSS receiver spatial sampling |
| title | A Multi-Sensor RSS Spatial Sensing-Based Robust Stochastic Optimization Algorithm for Enhanced Wireless Tethering |
| title_full | A Multi-Sensor RSS Spatial Sensing-Based Robust Stochastic Optimization Algorithm for Enhanced Wireless Tethering |
| title_fullStr | A Multi-Sensor RSS Spatial Sensing-Based Robust Stochastic Optimization Algorithm for Enhanced Wireless Tethering |
| title_full_unstemmed | A Multi-Sensor RSS Spatial Sensing-Based Robust Stochastic Optimization Algorithm for Enhanced Wireless Tethering |
| title_short | A Multi-Sensor RSS Spatial Sensing-Based Robust Stochastic Optimization Algorithm for Enhanced Wireless Tethering |
| title_sort | multi sensor rss spatial sensing based robust stochastic optimization algorithm for enhanced wireless tethering |
| topic | wireless tethering relay wireless nodes mobile robots multi-sensor sampling RSS receiver spatial sampling |
| url | http://www.mdpi.com/1424-8220/14/12/23970 |
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