Sensor network localisation based on sorted RSSI quantisation

ArticleinInternational Journal of Ad Hoc and Ubiquitous Computing 1(4):222-229 · January 2006with5 Reads
DOI: 10.1504/IJAHUC.2006.010503 · Source: DBLP
Abstract
Range estimation is essential in many sensor network localisation algorithms. Although wireless sensor systems usually have available received signal strength indication (RSSI) readings, this information has not been effectively used in the existing localisation algorithms. In this paper, we present a novel approach to localisation of sensors in an ad hoc sensor network based on a sorted RSSI quantisation algorithm. This algorithm can improve the range estimation accuracy when distance information is not available or too erroneous. The range level used in the quantisation process can be determined by each node, using an adaptive quantisation scheme. The new algorithm can be implemented in a distributed way and achieves significant improvement over existing range-free algorithms. The performance advantage for various sensor networks is shown, with experimental results from our extensive simulation with a realistic radio model.
    • "he possibility of using the location and time information to determine the movement speed of mobile nodes. They have used the Green Peak Technologies WSN evaluation kit and Ti Location Engine to perform their tests. Authors conclude that the single difference between the two systems is the algorithms used for filtering the raw location information. Li et al. (2006) present an algorithm that takes into consideration the value of the RSSI to locate the sensors in an ad hoc sensor network. The proposal uses adaptive quantisation scheme for each node to determine the range level used in the quantisation process. As results show, this algorithm improves the range estimation accuracy when distance infor"
    Full-text · Dataset · Apr 2014 · International Journal of Ad Hoc and Ubiquitous Computing
    • "he possibility of using the location and time information to determine the movement speed of mobile nodes. They have used the Green Peak Technologies WSN evaluation kit and Ti Location Engine to perform their tests. Authors conclude that the single difference between the two systems is the algorithms used for filtering the raw location information. Li et al. (2006) present an algorithm that takes into consideration the value of the RSSI to locate the sensors in an ad hoc sensor network. The proposal uses adaptive quantisation scheme for each node to determine the range level used in the quantisation process. As results show, this algorithm improves the range estimation accuracy when distance infor"
    [Show abstract] [Hide abstract] ABSTRACT: Wireless signals present particular behaviour in indoor environments. Walls, roofs and floors generate reflections and refractions that conduce to constructive and destructive interferences due to the multipath effect. In this paper, we perform an analytical study based on the signal strength generated by an access point (AP) inside a building. The evolution of the signal strength allows us to move away the sensors from the AP without reducing the signal level and link quality. We study the IEEE 802.11 technology. These results are compared with the theoretical distribution channels to know what should be followed to avoid interferences. Finally, taking as a reference the measures provided, we develop a method for estimating indoor signal strength that will help us determine the best position for wireless sensors. Our method will allow saving 15% of sensors. The reduction in the number of sensors provides us economic and energy savings, allowing us to prolong the network lifetime.
    Full-text · Article · Jan 2014
    • "centroid scheme [19] and APIT [4]. Range quantization methods like DV-Hop [5] and DHL [6] associate each 1-hop connection with an estimated distance, while others apply RSSI quantization [20]. These schemes also use multilateration techniques but rely on measures like hop count to estimate distances to anchor nodes. "
    Full-text · Chapter · Dec 2010 · International Journal of Ad Hoc and Ubiquitous Computing
Show more

  • undefined · undefined
  • undefined · undefined
  • undefined · undefined