Localization in Wireless Sensor Networks with Known Coordinate Database

Fang, Zhen; Zhao, Zhan; Cui, Xunxue; Geng, Daoqu; Du, Lidong; Pang, Cheng

doi:10.1155/2010/901283

Cited by 19 publications

(14 citation statements)

References 4 publications

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“…e use of the GPS technology is not an energy-e cient method to know the location of the sensor nodes [22,23]; therefore, there are some e cient geometric methods to localize the nodes using some anchor nodes having known locations in the network. e most used methods are hyperbole method, trilateration, and triangulation [24,25]. e determination of the distance between the nodes will be given by the following techniques: angle of arrival (AOA) [26], received signal strength indication (RSSI) [27], and time of arrival (TOA) [28].…”

Section: Localization Of the Sensor Nodesmentioning

confidence: 99%

Routing and Clustering of Sensor Nodes in the Honeycomb Architecture

Amine

Bouragba

Ouzzif

2019

Journal of Computer Networks and Communications

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Energy is the most valuable resource in wireless sensor networks; this resource is limited and much in demand during routing and communication between sensor nodes. Hierarchy structuring of the network into clusters allows reducing the energy consumption by using small distance transmissions within clusters in a multihop manner. In this article, we choose to use a hybrid routing protocol named Efficient Honeycomb Clustering Algorithm (EHCA), which is at the same time hierarchical and geographical protocol by using honeycomb clustering. This kind of clustering guarantees the balancing of the energy consumption through changing in each round the location of the cluster head, which is in a given vertex of the honeycomb cluster. The combination of geographical and hierarchical routing with the use of honeycomb clustering has proved its efficiency; the performances of our protocol outperform the existing protocols in terms of the number of nodes alive, the latency of data delivery, and the percentage of successful data delivery to the sinks. The simulations testify the superiority of our protocol against the existing geographical and hierarchical protocols.

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Section: Localization Of the Sensor Nodesmentioning

confidence: 99%

Routing and Clustering of Sensor Nodes in the Honeycomb Architecture

Amine

Bouragba

Ouzzif

2019

Journal of Computer Networks and Communications

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“…The sink is located at the center of monitoring area. We suppose that the sink has all the required information about SNs, such as location coordinates, either by using localization algorithms [35][36][37][38] or GPS device; also, all SNs have the same amount of energy.…”

Section: Network Modelmentioning

confidence: 99%

Multi-mobile agent itinerary planning-based energy and fault aware data aggregation in wireless sensor networks

Fissaoui

Beni‐Hssane

Saadi

2018

J Wireless Com Network

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Mobile agent (MA)-based wireless sensor networks present a good alternative to the traditional client/server paradigm. Instead of sending the data gathered by each node to the sink as in client/server, MAs migrate to the sensor nodes (SNs) to collect data, thus reducing energy consumption and bandwidth usage. For MAs, to migrate among SNs, an itinerary should be planned before the migration. Many approaches have been proposed to solve the problem of itinerary planning for MAs, but all of these approaches are based on the assumption that MAs visit all SNs. This assumption, however, is inefficient because of the increasing size of the MAs after visiting each node. Also, in case of node(s) failure, as it is often the case in WSNs, the MAs may not be able to migrate among SNs. None of the proposed approaches takes into consideration the problem of fault tolerance. In this paper, we propose multi-mobile agent itinerary planning-based energy and fault aware data aggregation in wireless sensor networks (MAEF) to plan itineraries for MAs. This can be achieved by grouping nodes in clusters and planning itineraries efficiently among cluster heads (CHs) only. What is more, an alternative itinerary is planned in case of node(s) failure. The simulation result clearly shows that our novel approach performs better than the existing ones.

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“…The sink sends out requests to the nodes in order to obtain their coordinates and the remaining energy of each sensor in the sensing area. The sensor nodes are aware of their location using trilateration and triangulation techniques [9,10,11] and no GPS receiver is required for every sensor since the GPS system is costly. The signal reception is energy consuming and may not function where physical obstacle exist.…”

Section: Set Up Phasementioning

confidence: 99%