Overhearing-Based Data Transmission Reduction for Periodical Data Gathering in Wireless Sensor Networks

Iima, Yuuki; Kanzaki, Akimitsu; Hara, Takahiro; Nishio, Shojiro

doi:10.1109/cisis.2009.42

Cited by 21 publications

(20 citation statements)

References 6 publications

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“…The data sink broadcasts one estimated value toward each broadcast group, and all nodes in the same broadcast group receive the same estimated value. To estimate the observed values of nodes, we can use methods proposed in conventional studies such as [4].…”

Section: Bandc Methodsmentioning

confidence: 99%

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A Broadcast-Based Data Gathering Method Considering Energy Consumption for Sensor Networks

Kitajima

Yoshihisa

Ogawa

et al. 2009

2009 Tenth International Conference on Mobile Data Management: Systems, Services and Middleware

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In recent years, there has been an increasing interest in sensor networks, in which sensor nodes such as temperature or humidity sensors communicate with each other for environmental monitoring and so on. In sensor networks, it is important to reduce the energy consumption, since sensor nodes have limits in battery. Most researches achieve this by reducing sensor amount of transmitted data. However, there is a problem that the amount of transmitted data become large and their energy consumption becomes high when there are a lot of nodes in the sensing area. To solve the problem, we previously proposed a data gathering method. In this method, the data sink estimates the data value of nodes, broadcasts the estimated values, and then, sensor nodes whose observed values are largely different from the estimated values send the data. However, this method has a problem that it cannot sufficiently reduce the energy consumption. In this paper, we propose a new broadcastbased data gathering method. In this method, the data sink reduces the nodes which send their observed values when the reliability of gathered values by the data sink is high.

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Section: Bandc Methodsmentioning

confidence: 99%

“…Since observed values tend to have certain spatial and temporal correlations, we can estimate the data values in many cases [4]. Based on this fact, we proposed a data collection method where the data sink estimates sensor data and broadcasts the estimated values [5].…”

Section: Introductionmentioning

confidence: 99%

A Broadcast-Based Data Gathering Method Considering Energy Consumption for Sensor Networks

Kitajima

Yoshihisa

Ogawa

et al. 2009

2009 Tenth International Conference on Mobile Data Management: Systems, Services and Middleware

Self Cite

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“…In addition, since WAVE is a broadcast-based communication mechanism, sensor data are forwarded to the sink node in multi-paths, which generally consumes more energy in comparison with single-path forwarding. B. ODAS [6] 1) Assumptions of ODAS: We next briefly introduce our data aggregation mechanism. In ODAS, TDMA is assumed as the MAC protocol.…”

Section: A Wave [2]mentioning

confidence: 99%

“…Many data aggregation mechanisms have been proposed [3][4][5]; however, these proposals require message exchanges in order to share information. We have proposed an overhearing-based data aggregation mechanism that, unlike previous proposals, utilizes spatial interpolation (ODAS) [6]. In ODAS, each sensor node overhears messages and determines the redundancy of its sensor data by using sensor data overheard from neighbor nodes.…”

Section: Introductionmentioning

confidence: 98%

Autonomous data gathering mechanism with transmission reduction for wireless sensor networks

Taniguchi

Kanzaki

Wakamiya

et al. 2011

2011 International Conference on Communications, Computing and Control Applications (CCCA)

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In this paper, we propose an autonomous and energy-efficient data gathering mechanism with transmission reduction for wireless sensor networks (WSNs). In our proposed mechanism, sensor nodes schedule their message transmission timing in a self-organizing manner such that they can gather sensor data over a whole WSN and transmit that data to a sink node while switching between a sleep state and an active state. In addition, each sensor node determines the redundancy of its sensor data according to overheard messages so that only necessary sensor data are gathered and transmitted to the sink node. Our proposed mechanism does not require additional control messages and enables both data traffic and control traffic to be drastically reduced. Through simulation experiments, we confirmed that the number of message transmissions can be reduced by up to 77% with our proposed mechanism compared to a conventional mechanism.

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“…The first approach is used when the goal of the sensor network application is to estimate an event from the sensor field with a certain reliability at a sink node [4–6]. In this approach, only some of the nodes transmit their sensed information to the sink node.…”

Section: Introductionmentioning

confidence: 99%

Energy‐Efficient Data Gathering Scheme Based on Broadcast Transmissions in Wireless Sensor Networks

Lee

2013

The Scientific World Journal

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Improving energy efficiency is the most important challenge in wireless sensor networks. Because sensing information is correlated in many sensor network applications, some previous works have proposed ideas that reduce the energy consumption of the network by exploiting the spatial correlation between sensed information. In this paper, we propose a distributed data compression framework that exploits the broadcasting characteristic of the wireless medium to improve energy efficiency. We analyze the performance of the proposed framework numerically and compare it with the performance of previous works using simulation. The proposed scheme performs better when the sensing information is correlated.

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Overhearing-Based Data Transmission Reduction for Periodical Data Gathering in Wireless Sensor Networks

Cited by 21 publications

References 6 publications

A Broadcast-Based Data Gathering Method Considering Energy Consumption for Sensor Networks

A Broadcast-Based Data Gathering Method Considering Energy Consumption for Sensor Networks

Autonomous data gathering mechanism with transmission reduction for wireless sensor networks

Energy‐Efficient Data Gathering Scheme Based on Broadcast Transmissions in Wireless Sensor Networks

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