Real-Time Databases Techniques in Wireless Sensor Networks

Chagas, Luana Dantas; Lima, Eduardo Pereira; Neto, Pedro Fernandes Ribeiro

doi:10.1109/icns.2010.32

Cited by 8 publications

(5 citation statements)

References 3 publications

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“…This method chooses the path to that node .Which has lower energy and it enhances the energy level and speed of the data transmission. Chagas et al [9] the work was done in this paper was on the basis of energy consumption during the data storage and to correct the problems that occurs during the transmission of data only in the online system. The technique was need in this paper was distribution of the data that means divided the data in small amounts at the storage time.…”

Section: Related Workmentioning

confidence: 99%

Energy Efficient Data Aggregation in Wireless Sensor Networks using Mobile Sink Node

Bansal,

Bathla

2019

IJEAT

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The wireless sensor networks consist of numerous small nodes which are also called as energy resource-constrained sensor nodes. The communication of these nodes can be done in a various way. There is also the processing of signal tasks which is done through the various computational resources provided by the networks. The energy of the sensor nodes gets consumed when transmit the data or receive data from the network. To reduce energy consumption of the network various techniques has been proposed which are known as clustering techniques. In the proposed work the mobile sink is deployed in the network which reduces overhead in the network. Experimental results shows that the proposed work outperforms the existing one in terms of reduced energy consumption of the network, increased throughput of the network, reduced delay in the network.

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Section: Related Workmentioning

confidence: 99%

Energy Efficient Data Aggregation in Wireless Sensor Networks using Mobile Sink Node

Bansal,

Bathla

2019

IJEAT

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“…The RTStream offers periodic responses in real time without interrupting the query instance execution, but it is unable to provide the latest result of the incoming data stream because of the incoming data stream reported to next query instance. Authors in [Chagas et al 2010] have presented a real-time database technique (RTDT) that uses SQL-like language. The RTDT employs in-network processing for energy efficiency.…”

Section: Network Layermentioning

confidence: 99%

QoS in Body Area Networks

Razzaque

Hira²,

Dira

2017

ACM Trans. Sen. Netw.

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Body Area Networks (BANs) are becoming increasingly popular and have shown great potential in realtime monitoring of the human body. With the promise of being cost effective, unobtrusive, and facilitating continuous monitoring, BANs have attracted a wide range of monitoring applications, including medical and healthcare, sports, and rehabilitation systems. Most of these applications are real-time and life-critical, and require a strict guarantee of Quality of Service (QoS), in terms of timeliness, reliability, etc. Recently, there have been a number of proposals describing diverse approaches or frameworks to achieve QoS in BANs (i.e., for different layers or tiers, different protocols). This survey put these individual efforts into perspective and presents a more holistic view of the area. In this regard, this article identifies a set of QoS requirements for BANs applications and shows how these requirements are linked in a 3-tier BAN system, and presents a comprehensive review of the existing proposals against those requirements. In addition, open research issues, challenges, and future research directions in achieving these QoS in BANs are highlighted.

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“…Therefore, we face an urgent need to reduce the amount and frequency of data transmissions, especially in underwater circumstances. Some studies on data storage sought to reduce redundant data conveyance by allowing users to selectively acquire data by querying the network [ 15 ]. One of the two major approaches to data storage in sensor networks is the “warehouse” approach, in which all sensor data is collected into a large, central database from which users can acquire their data of interest [ 15 ].…”

Section: Introductionmentioning

confidence: 99%

“…Some studies on data storage sought to reduce redundant data conveyance by allowing users to selectively acquire data by querying the network [ 15 ]. One of the two major approaches to data storage in sensor networks is the “warehouse” approach, in which all sensor data is collected into a large, central database from which users can acquire their data of interest [ 15 ]. Another approach is the distributed approach, in which each distributed devices such as sensor nodes can act like a database and users query each node for data [ 16 ].…”

Section: Introductionmentioning

confidence: 99%

A Query Result Merging Scheme for Providing Energy Efficiency in Underwater Sensor Networks

Park

2011

Sensors

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Underwater sensor networks are emerging as a promising distributed data management system for various applications in underwater environments, despite their limited accessibility and restricted energy capacity. With the aid of recent developments in ubiquitous data computing, an increasing number of users are expected to overcome low accessibility by applying queries to underwater sensor networks. However, when multiple users send queries to an underwater sensor network in a disorganized manner, it may incur lethal energy waste and problematic network traffic. The current query management mechanisms cannot effectively deal with this matter due to their limited applicability and unrealistic assumptions. In this paper, a novel query management scheme involving query result merging is proposed for underwater sensor networks. The mechanism is based on a relational database model and is adjusted to the practical restrictions affecting underwater communication environments. Network simulations will prove that the scheme becomes more efficient with a greater number of queries and a smaller period range.

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Real-Time Databases Techniques in Wireless Sensor Networks

Cited by 8 publications

References 3 publications

Energy Efficient Data Aggregation in Wireless Sensor Networks using Mobile Sink Node

Energy Efficient Data Aggregation in Wireless Sensor Networks using Mobile Sink Node

QoS in Body Area Networks

A Query Result Merging Scheme for Providing Energy Efficiency in Underwater Sensor Networks

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