Mobile ad-hoc wireless sensor networks

Abstract

The biggest disadvantage that Mobile Ad-Hoc Wireless Sensor Networks have is the localization of individual node i.e. each node's position relative to each other in the network. In this research paper we intend to do research on various solutions like Calibree, a novel localization algorithm that does not require off-line calibration [1], Directional Localization where each node must have an idea of its neighboring node [2] and radio-beacon based approach to location called, Place lab [3]. Using Global Positioning System for locating any node is not only expensive when used on larger scale but impractical too when used in enclosed spaces. To rectify such problems, in this paper we have done a research on various algorithms for directional node localization in GPS free wireless networks. [1]

Keywords

Localization, mobility, sensor networks

Localization Algorithm

The core localization algorithm works on well-defined rounds. Each round essentially consists of three steps:

  1. Measure distances between neighbors
  2. Move nodes
  3. Exchange distance values for that round as validation for movement [2]

Project Bibliography:

Varshavsky, Alex. Pankratov, Denis. Krumm, John. Lara, Eyal. Calibration-free Localization

using Relative Distance Estimations. Sydney, Australia: Springer-Verlag, Berlin, Heidelberg, May 2008. Print.

Most of the existing localization algorithms, such as centroid or finger- printing, compute the location of a mobile device based on measurements of signal strengths from radio base stations.

Unfortunately, these algorithms require tedious and expensive off-line calibration in the target deployment area before they can be used for localization.

In this paper, we present Calibree, a novel localization algorithm that does not require off-line calibration. The algorithm starts by computing relative distances between pairs of mobile phones based on signatures of their radio environment. It then combines these distances with the known locations of a small number of GPS-equipped phones to estimate absolute locations of all phones, effectively spreading location measurements from phones with GPS to those without. Also, when no phones report their absolute locations, Calibree algorithm can be used to estimate relative distances between phones.

Akcan, Hseyin. Kriakov, Vassil. Brnnimann, Herv. Delis, Alex. GPS-Free Node Localization in

Mobile Wireless Sensor Networks. Chicago, Illinois, USA: ACM, 2006. Print.

The main contribution of this work is that it presents a solution to the problem of directional localization in GPS free sensor networks with mobile nodes. Provides directional neighbor localization in a network-wide coordinate system Works under fairly large motion and distance measurement errors

Unaffected by the speed of nodes Works for any network size supports a stable network in mobility problems.

This paper also explains the GPS free Localization algorithm which is based on three important steps: Measure distances between neighbors, Move nodes and Exchange distance values for that round as validation for movement.

Meguerdichian, Seapahn. Slijepcevic, Sasa. Karayan, Vahag. Potkonjak, Miodrag. Localized

Algorithms in Wireless Ad-hoc Networks: Location Discovery and Sensor Exposure. Long Beach, USA: ACM, October 2001. Print.

Localized algorithms are the special type of distributed algorithms in which only the subset of nodes in the WASN (Wireless Ad-hoc Sensor Networks) participate in sensing, computation and communication. In this paper there is going to be a localized algorithm which will be used to solve optimization problems in wireless ad-hoc networks which has some important components. The idea is going to be in a way like, requesting and processing data locally and only the nodes which are likely to contribute for rapid formation of the solution will be involved.

This algorithm will enable two types of optimizations and then it will be applied to two fundamental problems in sensor networks which are location discovery and exposure-based coverage. Moreover, its effectiveness will be demonstrated in some examples.

LaMarca, Anthony. Chawathe, Yatil. Consolvo, Sunny. Hightower, Jeffrey. Smith, Ian. Scott,

James. Sohn, Tim. Howard, James. Hughes, Jeff. Potter, Fred. Tabert, Jason. Powledge,

Pauline. Borriello, Gaetano. Schilit, Bill. Place Lab: Device Positioning using Radio Beacons in the Wild. Munich, Germany: Springer Berlin / Heidelberg, May 2005. Print.

The major task in mobile computing is the awareness of location i.e. nodes. This paper represents radio beacon-based approach to location, called Place Lab, that can overcome the lack of ubiquity and high-cost found in existing location sensing approaches. Using Place Lab, commodity laptops, PDAs and cell phones we can locate their position by listening for the cell IDs of fixed radio beacons, such as wireless access points, and referencing the beacons' positions in a cached database.

In this paper there we will present an experimental result which will show that the 802.11 and GSM beacons are enough pervasive in the greater Seattle area to achieve 20-30 meter median accuracy with nearly full 100% coverage.

REFRENCES

  1. Varshavsky, Alex. Pankratov, Denis. Krumm, John. Lara, Eyal.Calibration-free Localization using Relative Distance Estimations.Sydney, Australia: Springer-Verlag, Berlin, Heidelberg, May2008.
  2. Akcan, Hseyin. Kriakov, Vassil. Brnnimann, Herv. Delis, Alex.GPS-Free Node Localization in Mobile Wireless Sensor Networks.Chicago, Illinois, USA: ACM, 2006.
  3. LaMarca, Anthony. Chawathe, Yatil. Consolvo, Sunny. Hightower, Jeffrey. Smith, Ian. Scott, James. Sohn, Tim. Howard, James. Hughes, Jeff. Potter, Fred. Tabert, Jason. Powledge, Pauline. Borriello, Gaetano. Schilit, Bill.Place Lab: Device Positioning using Radio Beacons in the Wild.Munich, Germany: Springer Berlin / Heidelberg, May 2005.
  4. Meguerdichian, Seapahn. Slijepcevic, Sasa. Karayan, Vahag. Potkonjak, Miodrag.Localized Algorithms in Wireless Ad-hoc Networks: Location Discovery and Sensor Exposure.Long Beach, USA: ACM, October 2001.

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