TiNA

Sharaf, Mohamed A.; Beaver, Jonathan; Labrinidis, Alexandros; Chrysanthis, Panos K.

doi:10.1145/940935.940937

Cited by 36 publications

(1 citation statement)

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“…At the same time, on application layer, we can use search technique of distributed database to filter collected data step by step. The typical algorithm includes TAG [6], TINA [7] , Medians and beyond [8], etc. Besides, there is a model driving fusion that uses some model to describe and fuse data.…”

Section: Introductionmentioning

confidence: 99%

A Secure Data Fusion Algorithm Based on Behavior Trust in Wireless Sensor Networks

Zhu¹,

Ming-zheng²,

Xu³

et al. 2008

2008 4th International Conference on Wireless Communications, Networking and Mobile Computing

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Secure data fusion is an important application of wireless sensor network. Previous works are implemented by authentication among neighboring sensors. Considering that in many cases, data fusion event is both spatially and temporally correlated, this paper proposes a distributed and localized secure data fusion algorithm based on behavior trust. The security and reliability of the algorithm are implemented by statistical hypothesis test for matching the reading sequence of sensors and statistical characters of the data fusion event. The simulation results show the validity of the algorithm. Keywords wireless sensor network; data fusion; behavior trust; security INTRODUCTIONAn important character of wireless sensor network is that a set of sensor nodes with limited function complete a great perceptive assignment concurrently. Due to the sensor network nodes have limited battery energy, disposal ability, storage capability and communication bandwidth, they are influenced by environment greatly. We should use the nodes' ability of local calculation and storage ability to dispose data, get rid of redundant information, reduce transmission quantity and dispose information fusion. [1][2][3] In wireless sensor networks, the functions of data fusion are mostly showed on saving energy, improving data collection efficiency, enhancing data accuracy and getting synthesis information, etc. Data package fusion mostly combines with routing protocol on network layer. The typical algorithm includes Data funneling [4], AIDA[5] and so on. At the same time, on application layer, we can use search technique of distributed database to filter collected data step by step. The typical algorithm includes TAG [6], TINA[7] , Medians and beyond[8], etc. Besides, there is a model driving fusion that uses some model to describe and fuse data. The typical algorithm includes Wavelet neural -networks [9], Kalman filtering[10], Probabilistic model [11]and so on.Be different from traditional multi-sensor data fusion, sensor networks' character decides the complexity in researching data fusion. An important thing to achieve data fusion in wireless sensor network is to make sure security and credibility during data fusion. Presently, previous data fusion algorithms in sensor networks mainly use the methods based on encryption and authentication to achieve security, they can not dispose data fusion's insecure problems resulted from false behaviors as it said [12]. In recent years, networks' trust research has become a hotspot [13]. Networks' trust technology is a new secure method which adds behavior trust based on the previous networks' secure technology, intensifies dynamic disposal on network states, provides strategy basic for implementing intelligent self-adapted networks' security and service quality control.

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Section: Introductionmentioning

confidence: 99%

A Secure Data Fusion Algorithm Based on Behavior Trust in Wireless Sensor Networks

Zhu¹,

Ming-zheng²,

Xu³

et al. 2008

2008 4th International Conference on Wireless Communications, Networking and Mobile Computing

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MAX–MIN aggregation in wireless sensor networks: mechanism and modeling

Deng

et al. 2012

Wireless Communications

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In‐network aggregation is crucial in the design of a wireless sensor network (WSN) due to the potential redundancy in the data collected by sensors. Based on the characteristics of sensor data and the requirements of WSN applications, data can be aggregated by using different functions. MAX—MIN aggregation is one such aggregation function that works to extract the maximum and minimum readings among all the sensors in the network or the sensors in a concerned region. MAX—MIN aggregation is a critical operation in many WSN applications. In this paper, we propose an effective mechanism for MAX—MIN aggregation in a WSN, which is called Sensor MAX—MIN Aggregation (SMMA). SMMA aggregates data in an energy‐efficient manner and outputs the accurate aggregate result. We build an analytical model to analyze the performance of SMMA as well as to optimize its parameter settings. Simulation results are used to validate our models and also evaluate the performance of SMMA. Copyright © 2010 John Wiley & Sons, Ltd.

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RAPS: a precision‐adaptive protocol towards improved data fidelity in wireless sensor networks

Deng

Zhang

Jiao

et al. 2012

Wireless Communications

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Achieving high data quality and efficient network resource utilization is two major design objectives of wireless sensor networks (WSNs). However, these two objectives are often conflictive. By allowing sensors to report sampled data at high rates, fine-grained data quality can be obtained. However, the limited resources of a WSN make it difficult to support very high traffic rate. Therefore, the capability of adaptively adjusting sensor nodes' traffic-generating rates on the basis of the availability of network resources and application requirements is critical. This issue has attracted much attention recently, and some work has been carried out.To achieve high data quality and improved utilization of network resources, in this paper, we propose rate-based adaptive precision setting (RAPS) protocol, which works in a way that each sensor can adaptively adjust its traffic-generating rate on the basis of the current network resources availability and application requirements. RAPS introduces the following two key factors into its design: application's precision requirement and packet arrival rate. Analytical and simulation results show that RAPS can achieve improved data quality while reducing packet delivery latency.

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TiNA

Cited by 36 publications

References 0 publications

A Secure Data Fusion Algorithm Based on Behavior Trust in Wireless Sensor Networks

A Secure Data Fusion Algorithm Based on Behavior Trust in Wireless Sensor Networks

MAX–MIN aggregation in wireless sensor networks: mechanism and modeling

RAPS: a precision‐adaptive protocol towards improved data fidelity in wireless sensor networks

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