A directionality based location discovery scheme for wireless sensor networks

Nasipuri, Asis; Li, Kai

doi:10.1145/570738.570754

Cited by 269 publications

(147 citation statements)

References 16 publications

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“…A straightforward localization technique, involving three rotating reference beacons at the boundary of a sensor network providing localization for all interior nodes, is described in [32]. A more detailed description of AoA-based triangulation techniques is provided in [33].…”

Section: Angle Measurementmentioning

confidence: 99%

Location, Localization, and Localizability

Liu

Yang

Wang

et al. 2010

J. Comput. Sci. Technol.

263

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Location-aware technology spawns numerous unforeseen pervasive applications in a wide range of living, production, commence, and public services. This article provides an overview of the location, localization, and localizability issues of wireless ad-hoc and sensor networks. Making data geographically meaningful, location information is essential for many applications, and it deeply aids a number of network functions, such as network routing, topology control, coverage, boundary detection, clustering, etc. We investigate a large body of existing localization approaches with focuses on error control and network localizability, the two rising aspects that attract significant research interests in recent years. Error control aims to alleviate the negative impact of noisy ranging measurement and the error accumulation effect during cooperative localization process. Network localizability provides theoretical analysis on the performance of localization approaches, providing guidance on network configuration and adjustment. We emphasize the basic principles of localization to understand the state-of-the-art and to address directions of future research in the new and largely open areas of location-aware technologies.Keywords location-based services (LBS), localization, error control, localizability, wireless ad-hoc and sensor networks LocationThe proliferation of wireless and mobile devices has fostered the demand for context-aware applications, in which location is viewed as one of the most significant contexts. For example, pervasive medical care is designed to accurately record and manage patient movements [1][2] ; smart space enables the interaction between physical space and human activities [3][4] ; modern logistics has major concerns on goods transportation, inventory, and warehousing [5][6] ; environmental monitoring networks sense air, water, and soil quality and detect the source of pollutants in real time [7][8][9][10][11] ; and mobile peer-to-peer computing encourages content sharing and contributing among mobile hosts in the vicinity [12][13] . In brief, location-based service (LBS) is a key enabling technology of these applications and widely exists in nowadays wireless communication networks from the short-range Bluetooth to the long-range telecommunication networks, as illustrated in Fig.1.Recent technological advances have enabled the development of low-cost, low-power, and multifunctional sensor devices. These nodes are autonomous devices with integrated sensing, processing, and communication capabilities. With the rapid development of wireless sensor networks (WSNs), location information becomes critically essential and indispensable. The overwhelming reason is that WSNs are fundamentally intended to provide information on spatial-temporal characteristics of the physical world; hence, it is important to associate sensed data with locations, making data geographically meaningful. For example, a number of applications, such as object tracking and environment monitoring, inherently rely on loc...

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Section: Angle Measurementmentioning

confidence: 99%

Location, Localization, and Localizability

Liu

Yang

Wang

et al. 2010

J. Comput. Sci. Technol.

263

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“…Indeed, as discussed earlier, all the current localization schemes are vulnerable, since they were not developed to handle malicious attacks. Almost all of the range-based localization schemes and some range-free schemes (e.g., [4], [28]- [30], [33], [34]) eventually reduce localization to a Minimum Mean Square Estimation (MMSE) problem. Though this is effective to reduce the impact of measurement errors that occur during localization, an adversary can still introduce arbitrarily large location errors by compromising a single anchor node and having the compromised anchor node declaring a false location.…”

Section: Impacts Of the Attacksmentioning

confidence: 99%

LAD: Localization anomaly detection for wireless sensor networks

Fang

Ningi

2006

Journal of Parallel and Distributed Computing

134

130

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Abstract-In wireless sensor networks (WSNs), sensors' locations play a critical role in many applications. Having a GPS receiver on every sensor node is costly. In the past, a number of location discovery (localization) schemes have been proposed. Most of these schemes share a common feature: they use some special nodes, called beacon nodes, which are assumed to know their own locations (e.g., through GPS receivers or manual configuration). Other sensors discover their locations based on the reference information provided by these beacon nodes.Most of the beacon-based localization schemes assume a benign environment, where all beacon nodes are supposed to provide correct reference information. However, when the sensor networks are deployed in a hostile environment, where beacon nodes can be compromised, such an assumption does not hold anymore.In this paper, we propose a general scheme to detect localization anomalies that are caused by adversaries. Our scheme is independent from the localization schemes. We formulate the problem as an anomaly intrusion detection problem, and we propose a number of ways to detect localization anomalies. We have conducted simulations to evaluate the performance of our scheme, including the false positive rates, the detection rates, and the resilience to node compromises.

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“…Many practical distributed algorithms for localization in space (e.g., [1,7,14,16,20,21]) and time (e.g., [5,8,13,23,24]) are based on a few common structural elements. In this section we point out these structural elements and discuss various concrete instances of these elements found in existing algorithms.…”

Section: Distributed Algorithms For Localization In Spacetimementioning

confidence: 99%

Towards a unified view on space and time in sensor networks

Römer

Mattern

2005

Computer Communications

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In wireless sensor networks, many applications rely on the ability of sensor nodes to estimate their physical location and time with respect to a common reference scale. This necessity is reflected by the development of a significant number of algorithms for localization and time synchronization for sensor networks in the recent past. However, research on location estimation on the one hand and on time synchronization on the other hand has been largely separated. Despite this, models, requirements, techniques, and algorithms of the two domains are rather similar and in some respects closely related. The purpose of this paper is to make this affinity explicit, with the hope of stimulating a mutual fertilization and enabling a better understanding of both domains.

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A directionality based location discovery scheme for wireless sensor networks

Cited by 269 publications

References 16 publications

Location, Localization, and Localizability

Location, Localization, and Localizability

LAD: Localization anomaly detection for wireless sensor networks

Towards a unified view on space and time in sensor networks

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