Add to ORKGSignal compression is an important tool for reducing the communication costs and increasing the lifetime of wireless sensor network deployments. In this paper, we overview and classify an array of proposed compression methods, with an emphasis on illustrating the differences between the various approaches
A novel compression algorithm based on the principle of Adaptive Huffman Code is proposed in the pap...
AbstractUnlike classical wired networks and wireless sensor networks, WMSN differs from their predec...
Abstract: As a newly proposed theory, compressive sensing (CS) is commonly used in signal processing...
The major challenge in designing wireless sensor networks (WSNs) is to resolve the limitation of ene...
Abstract—Data compression is an art used to reduce the number of bits required to transmit the data ...
Data gathering, either for event recognition or for monitoring applications is the primary intention...
Abstract- Wireless sensor network consists of many tiny disposable low power devices called nodes, w...
Energy consumption has risen to be a bottleneck in wireless sensor networks. This is caused by the c...
Power saving is a critical issue in wireless sensor networks (WSNs) since sensor nodes are powered b...
Power saving is a critical issue in wireless sensor networks (WSNs) since sensor nodes are powered b...
Wireless sensor networks possess significant limitations in storage, bandwidth, and power. This has ...
Data compression techniques have extensive applications in power-constrained digital communication s...
Despite the large body of theoretical research available on compression algorithms for wireless sens...
Energy consumption is one of the most critical issues in wireless sensor network (WSN). For a sensor...
Abstract—Wireless sensor networks (WSNs) open a new research field for pervasive computing and conte...
A novel compression algorithm based on the principle of Adaptive Huffman Code is proposed in the pap...
AbstractUnlike classical wired networks and wireless sensor networks, WMSN differs from their predec...
Abstract: As a newly proposed theory, compressive sensing (CS) is commonly used in signal processing...
The major challenge in designing wireless sensor networks (WSNs) is to resolve the limitation of ene...
Abstract—Data compression is an art used to reduce the number of bits required to transmit the data ...
Data gathering, either for event recognition or for monitoring applications is the primary intention...
Abstract- Wireless sensor network consists of many tiny disposable low power devices called nodes, w...
Energy consumption has risen to be a bottleneck in wireless sensor networks. This is caused by the c...
Power saving is a critical issue in wireless sensor networks (WSNs) since sensor nodes are powered b...
Power saving is a critical issue in wireless sensor networks (WSNs) since sensor nodes are powered b...
Wireless sensor networks possess significant limitations in storage, bandwidth, and power. This has ...
Data compression techniques have extensive applications in power-constrained digital communication s...
Despite the large body of theoretical research available on compression algorithms for wireless sens...
Energy consumption is one of the most critical issues in wireless sensor network (WSN). For a sensor...
Abstract—Wireless sensor networks (WSNs) open a new research field for pervasive computing and conte...
A novel compression algorithm based on the principle of Adaptive Huffman Code is proposed in the pap...
AbstractUnlike classical wired networks and wireless sensor networks, WMSN differs from their predec...
Abstract: As a newly proposed theory, compressive sensing (CS) is commonly used in signal processing...