A QoS-Based Wireless Multimedia Sensor Cluster Protocol

Díaz, J.R.; Lloret, Jaime; Jiménez, Jose M.; Rodrigues, Joel J. P. C.

doi:10.1155/2014/480372

Cited by 15 publications

(20 citation statements)

References 27 publications

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“…The number of hops for a given packet is calculated according to the required QoS as the end‐to‐end delay and depending on the industrial monitoring applications and others industrial applications. Authors of Diaz et al 25 propose a QoS‐based multimedia wireless sensor cluster protocol. They consider the QoS parameters such as bandwidth, delay, jitter, and packet loss.…”

Section: Related Workmentioning

confidence: 99%

“…The propagation conditions are homogeneous, which ever part of the network is being considered. This has two consequences: The selection of a log normal shadowing‐type propagation model 1031 to model the variability of propagation conditions in the deployment environment across the whole network. The unique parameters of this model, the attenuation factor, and the sigma will therefore be constants for a given network and environment. The physical layer considered in this paper is the 802.15.4 25 layer. In this standard, the receiver moves abruptly from the collision state to the capture state.…”

Section: Network Modelmentioning

confidence: 99%

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Interference‐aware clustering approach improving QoS for linear WSNs using a token‐based MAC protocol

Ndoye

Diallo

Hakem

et al. 2020

Int J Communication

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Summary Wireless sensor networks (WSNs) have received a lot of attention from both academia and industry due to the increasing need for ubiquitous computing for monitoring applications, the continuous advances in miniaturization of electronic devices, and the ultra‐low‐power wireless technologies. These innovations in technology have driven the curiosity to use sensor networks in a new kind of applications such as road track or railway monitoring, border monitoring, oil and gas, or even water pipeline monitoring. Due to the underlying linear topology of these applications, a new type of network, called a linear sensor network (LSN), has emerged. Because of the specific characteristics of this application and the resource constraints of sensors, some of the major challenges faced in LSNs are to reduce end‐to‐end delays, to maximize the packet delivery ratio to a sink, and an even distribution of the load between nodes. To achieve these objectives, it is necessary to control node‐to‐node packet traffic conditions and to manage radio interference created by simultaneously active nodes. This paper addresses these challenges and proposes a new method of clustering LSNs that reduces or controls radio interference risks in order to satisfy these objectives, application needs, and the resource limitations of sensor nodes in the best possible way. This method is applied for LSNs using a token‐passing mechanism to access the medium. The performance evaluation is conducted by using a realistic propagation model in the analytical evaluation and also a NS‐2 simulation process.

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Section: Related Workmentioning

confidence: 99%

Section: Network Modelmentioning

confidence: 99%

Interference‐aware clustering approach improving QoS for linear WSNs using a token‐based MAC protocol

Ndoye

Diallo

Hakem

et al. 2020

Int J Communication

Self Cite

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“…For algorithms based on multimedia streaming data, in WMSNs, multimedia clustering protocols use the quality of service (QoS) parameters [14]. The requirements of QoS differ based on to the multimedia applications type.…”

Section: Literature Reviewmentioning

confidence: 99%

“…The requirements of QoS differ based on to the multimedia applications type. QoS has several metrics such as jitter, delay, bandwidth, reliability [15] and packet loss [14]. A lot of multimedia applications are time critical, they require to be managed with a limited time.…”

Section: Literature Reviewmentioning

confidence: 99%

Improving K-Means Algorithm by Grid-Density Clustering for Distributed WSN Data Stream

Alghamdi¹,

Abdullah²

2018

ijacsa

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At recent years, Wireless Sensor Networks (WSNs) had a widespread range of applications in many fields related to military surveillance, monitoring health, observing habitat and so on. WSNs contain individual nodes that interact with the environment by sensing and processing physical parameters. Sometimes, sensor nodes generate a big amount of sequential tuple-oriented and small data that is called Data Streams. Data streams usually are huge data that arrive online, flowing rapidly in a very high speed, unlimited and can't be controlled orderly during arrival. Due to WSN limitations, some challenges are faced and need to be solved. Extending network lifetime and reducing energy consumption are main challenges that could be solved by Data Mining techniques. Clustering is a common data mining technique that effectively organizes WSNs structure. It has proven its efficiency on network performance by extending network lifetime and saving energy of sensor nodes. This paper develops a grid-density clustering algorithm that enhances clustering in WSNs by combining grid and density techniques. The algorithm helps to face limitations found in WSNs that carry data streams. Grid-density algorithm is proposed based on the well-Known K-Means clustering algorithm to enhance it. By using Matlab, the grid-density clustering algorithm is compared with K-Means algorithm. The simulation results prove that the grid-density algorithm outperforms K-Means by 15% in network lifetime and by 13% in energy consumption.

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“…But in these services the Quality of Service (QoS) must be guaranteed [6] [7] in order to provide a good experience at the end user side [8].…”

Section: Introductionmentioning

confidence: 99%

Ad hoc Network for Emergency Rescue System based on Unmanned Aerial Vehicles

Cambra

Sendra

Lloret

et al. 2016

NPA

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Intelligent Unmanned Aerial Vehicles (UAVs) on emergency rescue are widely used to detect injured mountaineers in inaccessible areas. These systems should satisfy several features. It is important to know the georeference of the injured mountaineers. It is also important to have real-time images of the area where people have suffered the accident. In this paper, we present the development of a UAV integrated within a wireless ad hoc network and the communication protocol that is able to transfer data between several UAV's and the Smartphones carried by the mountaineers. This paper also shows how ad hoc networks extend the wireless coverage for emergency situations in critical areas without GSM cellular coverage. After developing our system, we have focused our effort on demonstrating the correct operation of our UAV and its network performance when the system is used to track someone within a zone. Experimental results show the big potential of this kind of networks working in hostile environments such as big mountains, ravines and river canyons without GSM signal communication.

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A QoS-Based Wireless Multimedia Sensor Cluster Protocol

Cited by 15 publications

References 27 publications

Interference‐aware clustering approach improving QoS for linear WSNs using a token‐based MAC protocol

Interference‐aware clustering approach improving QoS for linear WSNs using a token‐based MAC protocol

Improving K-Means Algorithm by Grid-Density Clustering for Distributed WSN Data Stream

Ad hoc Network for Emergency Rescue System based on Unmanned Aerial Vehicles

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