Energy Efficient Image Compression and Transmission in WSN

Energy Efficient Image Compression and Transmission in WSN

Wajeeha Aslam (National University of Sciences and Technology (NUST), Pakistan), Muazzam A. Khan (National University of Sciences and Technology (NUST), Pakistan), M. Usman Akram (National University of Sciences and Technology (NUST), Pakistan), Nazar Abbas Saqib (National University of Sciences and Technology (NUST), Pakistan) and Seungmin Rho (Sungkyul University, South Korea)
DOI: 10.4018/978-1-4666-9941-0.ch004
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Wireless sensor networks are greatly habituated in widespread applications but still yet step behind human intelligence and vision. The main reason is constraints of processing, energy consumptions and communication of image data over the sensor nodes. Wireless sensor network is a cooperative network of nodes called motes. Image compression and transmission over a wide ranged sensor network is an emerging challenge with respect to battery, life time constraints. It reduces communication latency and makes sensor network efficient with respect to energy consumption. In this paper we will have an analysis and comparative look on different image compression techniques in order to reduce computational load, memory requirements and enhance coding speed and image quality. Along with compression, different transmission methods will be discussed and analyzed with respect to energy consumption for better performance in wireless sensor networks.
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1. Introduction

Wireless sensor network (WSN) comprises dozens to several thousands of inexpensive, resource constrained and autonomous devices called sensor nodes. Nodes are interlinked with the high energy base stations also called sinks shown in Fig 1. All of the data is transmitted, aggregated and filtered at sinks. Typically a sensor node is small device having low power battery, microcontroller, and sensor, and transceiver, hardware architecture as depicted in Fig 2. Low cost and low complexity of nature demands lead to compromise on transmission rate, reliability, efficiency and power consumption. Although WSN is widely used in military, civilian, emergency and different environmental situations, yet now it’s a challenge for us to transmit human sensed data like image through wireless network with low power consumption within available bandwidth.

Figure 1.

Sensor networks

Figure 2.

Sensor node’s hardware architecture

In distributed network a single node has not enough computational power to compress large amount of data that’s why computation of compression is divided among nodes evenly. Conservation of energy in sensor network is directly proportional to the number of bits transmitted. In this paper work we will analyze and compare different image compression and transmission techniques regarding energy efficient in wireless sensor network.

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