Performance Comparison of Data Reduction Techniques for Wireless Multimedia Sensor Network Applications

Abstract

With the increased use of smart phones, Wireless Multimedia Sensor Networks (WMSNs) will have opportunities to deploy such devices in several contexts for data collection and processing. While smart phones come with richer resources and can do complex processing, their battery is still limited. Background subtraction (BS) and compression techniques are common data reduction schemes, which have been used for camera sensors to reduce energy consumption in WMSNs. In this paper, we investigate the performance of various BS algorithms and compression techniques in terms of computation and communication energy, time, and quality. We have picked five different BS algorithms and two compression techniques and implemented them in an Android platform. Considering the fact that these BS algorithms will be run within the context of WMSNs where the data is subject to packet losses and errors, we also investigated the performance in terms of packet loss ratio in the network under various packet sizes. The experiment results indicated that the most energy-efficient BS algorithm could also provide the best quality in terms of the foreground detected. The results also indicate that data reduction techniques including BS algorithms and compression techniques can provide significant energy savings in terms of transmission energy costs.

Adaptive Real-Time Routing Protocol for (m,k)-Firm in Industrial Wireless Multimedia Sensor Networks

“…There are some research work to enhance the performance of WMSN. At first, Sarisaray-Bolukand and Akkaya [17] presented how to utilize background subtraction and compression techniques to reduce data. They analyzed the previous work in the aspects of computation and communication energy, time, and quality and provide quantitative experimental results for packet loss on the Android platform.…”

A Review of Data Gathering Algorithms for Real-Time Processing in Internet of Things Environment

“…A performance assessment of information reduction techniques for IoT based WSN Multimedia applications has been provided in [40]. In this article, the authors study the performance of various BS algorithms and compression techniques in computing and communication energy, time, and quality.…”

Energy-efficient secured data reduction technique using image difference function in wireless video sensor networks

“…Different techniques have been proposed in the litterature to reduce energy consumption in Wireless Sensor Networks: Data Redundancy techniques [4][5][6][7][8][9][10], Data aggregation [8], Backround subtraction [11], Geometrical criteria [12][13][14], Physical and Network layers approaches [15,16] and Scheduling [4,[17][18][19][20]. Data redundancy has been considered in several research work for energy reduction.…”

“…In order to reduce the energy consumption on the sensor node level, Akkaya et al in [11] adopted the background subtraction (BS) and compression techniques as common data reduction schemes.…”

“…12 The Decrypted Frame Figures 10,11,12 show the validity of the security algorithm and how the frame can be retreived on the coordinator using the decryption algorithm.…”