A survey on communication and data management issues in mobile sensor networks

Zhu, Chunsheng; Shu, Lei; Hara, Takahiro; Wang, Lei; Nishio, Shojiro; Yang, Laurence T.

doi:10.1002/wcm.1219

Cited by 135 publications

(75 citation statements)

References 66 publications

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“…Data collection and management, transmission scheduling of the collected data, routing, and localization are major challenges in these networks. Di Francesco et al [27] survey data collection schemes in WSNs with MEs, while Zhu et al [28] survey communication and data management issues in mobile WSNs. Anastasi et al [29] investigate data delivery to one or multiple MEs in the context of sparsely deployed sensor nodes.…”

Section: Related Workmentioning

confidence: 99%

Optimizing event coverage in theme parks

Solmaz

Turgut

2014

Wireless Netw

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Abstract-Theme parks can be modeled as geographical areas where large crowds of people move among different attractions. The operators of a theme park are interested in quickly and efficiently handling events occurring at various locations in the park. We propose a model which deploys a wireless network with mobile sinks to facilitate event coverage. The event coverage problem can be divided into two sub-problems: the static problem of mobile sink positioning and the dynamic problem of event handling decisions of the mobile sinks. For the mobile sink positioning problem we propose two strategies: crowd density based probability estimation (CDPE) and hot-spot based probability estimation (HSPE). For the event handling decision problem, we propose an approach which represents movement opportunities in the park as a graph with dynamically changing weights, and searches for the shortest path in this dynamic graph. The proposed approaches are simulated on scenarios which model the movement of the visitors using two sophisticated human mobility models.

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Section: Related Workmentioning

confidence: 99%

Optimizing event coverage in theme parks

Solmaz

Turgut

2014

Wireless Netw

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“…The process of sensor node location is to identify the position of the node to be located (known as the unknown node) according to a certain positioning mechanism by using a few known location beacon nodes (also known as anchor nodes) [8]. Therefore, after the unknown node is correctly positioned, it can locate the specific location of the event that the sensor node monitors.…”

Section: Introductionmentioning

confidence: 99%

An Algorithm of Mobile Robot Node Location Based on Wireless Sensor Network

2017

Int. J. Onl. Eng.

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Abstract-In the wireless sensor network, there is a consistent one-to-one match between the information collected by the node and the location of the node. Therefore, it attempts to determine the location of unknown nodes for wireless sensor networks. At present, there are many kinds of node localization methods. Because of the distance error, hardware level, application environment and application costs and other factors, the positioning accuracy of various node positioning methods is not in complete accord. The objective function is established and algorithm simulation experiments are carried out to make a mobile ronot node localization. The experimnettal results showed that the proposed algorithm can achieve higher localization precision in fewer nodes. In addition, the localization algorithm was compared with the classical localization algorithm. In conclusion, it is verified that the localization algorithm proposed in this paper has higher localization accuracy than the traditional classical localization algorithm when the number of nodes is larger than a certain number.

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“…However, when sensor nodes are concentrated in one zone, transmission of event packets to the BS can fail. Mobile Wireless Sensor Networks (MWSNs) are used to solve these problems [2]. The MWSNs is a special WSN in which the sensor nodes can move.…”

Section: Introductionmentioning

confidence: 99%

Improving the Energy Efficiency of Fog Computing-Based System for Selective Forwarding Detection in Mobile Wireless Sensor Networks Using Multipath Route

Chung

2017

ijarcs

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Selective forwarding attacks in mobile wireless sensor networks are difficult to detect because they selectively delete packets. Such attacks are more dangerous than selective forwarding attacks in wireless sensor networks because it is difficult to detect a selective forwarding attack that occurs on sensor nodes with high mobility. In order to detect such attacks, a fog computing-based selective forwarding attack detection technique has been proposed. However, in the ad hoc on-demand distance vector (AODV) routing scheme using a single path, all packets are dropped until a selective forwarding attack is detected. In addition, energy consumption for path re-setting is significant because sensor nodes move frequently. To solve this problem, we propose a selective forwarding attack detection method using an ad hoc on-demand multipath distance vector (AOMDV) routing technique. The proposed scheme increases the packet transmission probability to the BS and increases the energy efficiency of the sensor network. Experiments with the proposed method show that the energy efficiency of the sensor network is improved by about 10%.

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A survey on communication and data management issues in mobile sensor networks

Cited by 135 publications

References 66 publications

Optimizing event coverage in theme parks

Optimizing event coverage in theme parks

An Algorithm of Mobile Robot Node Location Based on Wireless Sensor Network

Improving the Energy Efficiency of Fog Computing-Based System for Selective Forwarding Detection in Mobile Wireless Sensor Networks Using Multipath Route

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