A Graph Drawing Approach to Sensor Network Localization

Nawaz, Syed Junaid; Jha, Sanjay

doi:10.1109/mobhoc.2007.4428610

Cited by 10 publications

(8 citation statements)

References 31 publications

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“…The use of graph drawing to address the problem of localization for nodes without GPS devices has been shown to be effective in other work on sensor localization [22].…”

Section: B Using Fr To Seed the Gamentioning

confidence: 99%

“…Kamada-Kawai utilises spring force [15], whereas Fruchterman-Reingold uses an opposed force-directed algorithm [16]. In [17], Nawaz et al detail an anchor-free localisation mechanism that utilises a modified graph-drawing algorithm. The approach is based on the Kamada-Kawai graph drawing algorithm [15], utilising a sensor equipped with range-finding devices.…”

Section: B Localisationmentioning

confidence: 99%

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Position-Relative Identities in the Internet of Things: An Evolutionary GHT Approach

Attwood

Lamb

Abuelma'atti

2014

IEEE Internet Things J.

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The Internet of Things (IoT) will result in the deployment of many billions of wireless embedded systems creating interactive pervasive environments. It is envisaged that devices will cooperate to provide greater system knowledge than the sum of its parts. In an emergency situation, the flow of data across the Internet of Things may be disrupted, giving rise to a requirement for machine-to-machine interaction within the remaining ubiquitous environment. Geographic Hash Tables (GHTs) provide an efficient mechanism to support fault-tolerant rendezvous communication between devices. However, current approaches either rely on devices being equipped with a GPS or being manually assigned an identity. This is unrealistic when the majority of these systems will be located inside buildings and will be too numerous to expect manual configuration. Additionally when using GHT as a distributed data store, imbalance in the topology can lead to storage and routing overhead. This causes unfair work load, exhausting limited power supplies as well as causing poor data redundancy. To deal with these issues we propose an approach that balances graph-based layout identity assignment, through the application of multi fitness genetic algorithms. Our experiments show through simulation that our multi fitness evolution technique improves on the initial graph-based layout, providing devices with improved balance and reachability metrics. Index Terms-data centric storage, evolutionary computing and genetic algorithms, information dispersal, load balancing, Wireless sensor networks

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“…The use of graph drawing to address the problem of localization for nodes without GPS devices has been shown to be effective in other work on sensor localization [22].…”

Section: B Using Fr To Seed the Gamentioning

confidence: 99%

Section: B Localisationmentioning

confidence: 99%

Position-Relative Identities in the Internet of Things: An Evolutionary GHT Approach

Attwood

Lamb

Abuelma'atti

2014

IEEE Internet Things J.

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“…In this paper, we focus not on these aesthetic criteria but on visualizing the structure of a conveyor system as accurately as possible. Drawing the physical structure of a network as a graph is an approach mainly used in the area of sensor networks [18,25] and molecular structures [1]; however, to the best of our knowledge, it has never been applied to conveyor systems. Eades and Wormald proposed in [12] that to draw a graph with edges being straight lines that do not cross each other and with the same as well as different distances between all nodes is an NP-hard problem.…”

Section: Introductionmentioning

confidence: 99%

Data-driven graph drawing techniques with applications for conveyor systems

et al. 2020

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The visualization of conveyor systems in the sense of a connected graph is a challenging problem. Starting from communication data provided by the IT system, graph drawing techniques are applied to generate an appealing layout of the conveyor system. From a mathematical point of view, the key idea is to use the concept of stress majorization to minimize a stress function over the positions of the nodes in the graph. Different to the already existing literature, we have to take care of special features inspired by the real-world problems.

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“…Monte Carlo Localization (Dellaert et al, 1999), Convex Optimization (Doherty et al, 2001), Iterative Multi-lateration (Tay et al, 2006) and MDS (Costa et al, 2006) are the most popular of localization algorithms. Graph drawing is an interesting anchor-free network localization technique that yields a local or relative map of the nodes positions based on the network possibility problem (Nawaz and Jha, 2007), but are usually centralized and computationally expensive.…”

Section: Introductionmentioning

confidence: 99%

A Fast Multidimensional Scaling Filter for Vehicular Cooperative Positioning

et al. 2012

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Vehicular communication technologies are becoming staples of modern societies. This paper proposes a new positioning algorithm for vehicular networks. The algorithm is a non-classic Multi-Dimensional Scaling Filter (MDSF) that builds on a novel and computationally effective Multi-Dimensional Scaling (MDS) solution covariance estimation technique and also a Maximum Likelihood (ML) filter. In general a major drawback of the non-classic MDS is the high computational cost because of its iterative nature. It is shown that a special blend between vehicular Map-Matching (MM) and MDSF considerably reduces the number of iterations and the convergence time, making the MDSF a suitable algorithm for vehicular network positioning. The performance of MDSF is compared with that of an Extended Kalman Filter (EKF) together with the Cramar Rao Lower Bound (CRLB). It is shown through simulation that for all types of traffic conditions MDSF performs better than EKF and closer to CRLB than EKF. It is also shown that both MDSF and EKF algorithms are robust to typical Global Positioning System (GPS) outages in deep urban canyons. CRLB also proves that Cooperative Positioning (CP) in general has the ability to bridge short GPS outages.K E Y WO R D S 1. Vehicular Positioning. 2. Cooperative Positioning. 3. DRSC. 4. Map-Matching. I N T R O D U C T I O N . Dedicated Short Range Communication (DSRC) is a 75 MHz communication medium between 5·85GHz and 5·925 GHz. DSRC standards and technology form a platform for vehicle-to-vehicle and vehicle-toinfrastructure communications. This communication platform will enable Vehicular Adhoc NETworks (VANET) through which many Intelligent Transport Systems (ITS) applications can become realities, including safety-related applications, driver assistance, and traffic assignment (traffic control) systems. Safety applications transmit information about unforeseeable (by the driver) and potentially dangerous collisions or events (Boukerche et al., 2008). Driver assistance systems include speed management for avoiding traffic jams, automated highway entering or coordination of

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A Graph Drawing Approach to Sensor Network Localization

Cited by 10 publications

References 31 publications

Position-Relative Identities in the Internet of Things: An Evolutionary GHT Approach

Position-Relative Identities in the Internet of Things: An Evolutionary GHT Approach

Data-driven graph drawing techniques with applications for conveyor systems

A Fast Multidimensional Scaling Filter for Vehicular Cooperative Positioning

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