Geometric spanners for wireless ad hoc networks

Alzoubi, Khaled M.; Li, X.-Y.; Wang, Y.; Wan, Peng‐Jun

doi:10.1109/tpds.2003.1195412

Cited by 203 publications

(193 citation statements)

References 27 publications

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“…The following lemma shows that the number of neighboring clusterheads is bounded by a constant. A similar lemma has been proved in [2]. We include our proof for completeness.…”

Section: Performance Analysissupporting

confidence: 60%

Virtual Backbone Construction in MANETs Using Adjustable Transmission Ranges

Dai

2006

IEEE Trans. on Mobile Comput.

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Recently, the use of a virtual backbone in various applications in mobile ad hoc networks (MANETs) has become popular. These applications include topology management, point and area coverage, and routing protocol design. In a MANET, one challenging issue is to construct a virtual backbone in a distributed and localized way while balancing several conflicting objectives: small approximation ratio, fast convergence, and low computation cost. Many existing distributed and localized algorithms select a virtual backbone without resorting to global or geographical information. However, these algorithms incur a high computation cost in a dense network. In this paper, we propose a distributed solution based on reducing the density of the network using two mechanisms: clustering and adjustable transmission range. By using adjustable transmission range, we also achieve another objective, energy-efficient design, as a by-product. As an application, we show an efficient broadcast scheme where nodes (and only * This work was supported in part by NSF grants CCR 0329741, CNS 0434533, CNS 0422762, and EIA 0130806. 1 nodes) in a virtual backbone are used to forward the broadcast message. The virtual backbone is constructed using Wu and Li's marking process [37] and the proposed density reduction process. The application of the density reduction process to other localized algorithms is also discussed. The efficiency of our approach is confirmed through both analytical and simulation study.keywords: Adjustable transmission range, broadcasting, clustering, connected dominating set (CDS), energy efficiency, mobile ad hoc networks (MANETs).

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“…The following lemma shows that the number of neighboring clusterheads is bounded by a constant. A similar lemma has been proved in [2]. We include our proof for completeness.…”

Section: Performance Analysissupporting

confidence: 60%

Virtual Backbone Construction in MANETs Using Adjustable Transmission Ranges

Dai

2006

IEEE Trans. on Mobile Comput.

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“…See [7], [8] for more details. A simple method is to partition the deployment region into grid of size r/ √ 2, select a node (called dominator) from each cell if there is any, and then find nodes (called connectors) to connect every pair of dominators that are at most 3-hops apart.…”

Section: Connected Dominating Setmentioning

confidence: 99%

Complexity of Data Collection, Aggregation, and Selection for Wireless Sensor Networks

Wang

2011

IEEE Trans. Comput.

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Abstract-Processing the gathered information efficiently is a key functionality for wireless sensor networks. In this article, we study the time complexity, message complexity (number of messages used by all nodes), and energy cost complexity (total energy used by all nodes for transmitting messages) of some tasks, such as data collection (collecting raw data of all nodes to a sink), data aggregation (computing the aggregated value of data of all nodes), and queries for a multi-hop wireless sensor network of n nodes. We first present a lower-bound on the complexity for the optimal methods, and then, for most of the tasks studied in this article, we provide an (asymptotically matching) upper-bound on the complexity by presenting efficient distributed algorithms to solve these problems.

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“…• Topology Control Topology control is one of the most important techniques used in wireless ad-hoc and sensor networks for saving energy and eliminating radio interference [17][18] . By adjusting network parameters (e.g., the transmitting range), energy consumption and interference can be effectively reduced; meanwhile some global network properties (e.g., connectivity) can still be well retained.…”

Section: Locationmentioning

confidence: 99%

“…By adjusting network parameters (e.g., the transmitting range), energy consumption and interference can be effectively reduced; meanwhile some global network properties (e.g., connectivity) can still be well retained. Importantly, using location information as a priori knowledge, geometry techniques (e.g., spanner subgraphs and Euclidean minimum spanning trees) can be immediately applied to topology control [17] .…”

Section: Locationmentioning

confidence: 99%

Location, Localization, and Localizability

Liu

Yang

Wang

et al. 2010

J. Comput. Sci. Technol.

267

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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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Geometric spanners for wireless ad hoc networks

Cited by 203 publications

References 27 publications

Virtual Backbone Construction in MANETs Using Adjustable Transmission Ranges

Virtual Backbone Construction in MANETs Using Adjustable Transmission Ranges

Complexity of Data Collection, Aggregation, and Selection for Wireless Sensor Networks

Location, Localization, and Localizability

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