Wireless Multimedia Sensor Networks on Reconfigurable Hardware: Information Reduction Techniques

Traditional wireless sensor networks (WSNs) capture scalar data such as temperature, vibration, pressure, or humidity. Motivated by the success of WSNs and also with the emergence of new technology in the form of low-cost image sensors, researchers have proposed combining image and audio sensors with WSNs to form wireless multimedia sensor networks (WMSNs). This introduces practical and research challenges, because multimedia sensors, particularly image sensors, generate huge amounts of data to be processed and distributed within the network, while sensor nodes have restricted battery power and hardware resources.This book describes how reconfigurable hardware technologies such as field-programmable gate arrays (FPGAs) offer cost-effective, flexible platforms for implementing WMSNs, with a main focus on developing efficient algorithms and architectures for information reduction, including event detection, event compression, and multicamera processing for hardware implementations. The authors include a comprehensive review of wireless multimedia sensor networks, a complete specification of a very low-complexity, low-memory FPGA WMSN node processor, and several case studies that illustrate information reduction algorithms for visual event compression, detection, and fusion.The book will be of interest to academic researchers, R&D engineers, and computer science and engineering graduate students engaged with signal and video processing, computer vision, embedded systems, and sensor networks

Low-complexity, low-area computer architectures for cryptographic application in resource constrained environments

RCE (Resource Constrained Environment) is known for its stringent hardware design requirements. With the rise of Internet of Things (IoT), low-complexity and low-area designs are becoming prominent in the face of complex security threats. Two low-complexity, low-area cryptographic processors based on the ultimate reduced instruction set computer (URISC) are created to provide security features for wireless visual sensor networks (WVSN) by using field-programmable gate array (FPGA) based visual processors typically used in RCEs. The first processor is the Two Instruction Set Computer (TISC) running the Skipjack cipher. To improve security, a Compact Instruction Set Architecture (CISA) processor running the full AES with modified S-Box was created. The modified S-Box achieved a gate count reduction of 23% with no functional compromise compared to Boyar’s. Using the Spartan-3L XC3S1500L-4-FG320 FPGA, the implementation of the TISC occupies 71 slices and 1 block RAM. The TISC achieved a throughput of 46.38 kbps at a stable 24MHz clock. The CISA which occupies 157 slices and 1 block RAM, achieved a throughput of 119.3 kbps at a stable 24MHz clock. The CISA processor is demonstrated in two main applications, the first in a multilevel, multi cipher architecture (MMA) with two modes of operation, (1) by selecting cipher programs (primitives) and sharing crypto-blocks, (2) by using simple authentication, key renewal schemes, and showing perceptual improvements over direct AES on images. The second application demonstrates the use of the CISA processor as part of a selective encryption architecture (SEA) in combination with the millions instructions per second set partitioning in hierarchical trees (MIPS SPIHT) visual processor. The SEA is implemented on a Celoxica RC203 Vertex XC2V3000 FPGA occupying 6251 slices and a visual sensor is used to capture real world images. Four images frames were captured from a camera sensor, compressed, selectively encrypted, and sent over to a PC environment for decryption. The final design emulates a working visual sensor, from on node processing and encryption to back-end data processing on a server computer

Low-complexity, low-area computer architectures for cryptographic application in resource constrained environments

RCE (Resource Constrained Environment) is known for its stringent hardware design requirements. With the rise of Internet of Things (IoT), low-complexity and low-area designs are becoming prominent in the face of complex security threats. Two low-complexity, low-area cryptographic processors based on the ultimate reduced instruction set computer (URISC) are created to provide security features for wireless visual sensor networks (WVSN) by using field-programmable gate array (FPGA) based visual processors typically used in RCEs. The first processor is the Two Instruction Set Computer (TISC) running the Skipjack cipher. To improve security, a Compact Instruction Set Architecture (CISA) processor running the full AES with modified S-Box was created. The modified S-Box achieved a gate count reduction of 23% with no functional compromise compared to Boyar’s. Using the Spartan-3L XC3S1500L-4-FG320 FPGA, the implementation of the TISC occupies 71 slices and 1 block RAM. The TISC achieved a throughput of 46.38 kbps at a stable 24MHz clock. The CISA which occupies 157 slices and 1 block RAM, achieved a throughput of 119.3 kbps at a stable 24MHz clock. The CISA processor is demonstrated in two main applications, the first in a multilevel, multi cipher architecture (MMA) with two modes of operation, (1) by selecting cipher programs (primitives) and sharing crypto-blocks, (2) by using simple authentication, key renewal schemes, and showing perceptual improvements over direct AES on images. The second application demonstrates the use of the CISA processor as part of a selective encryption architecture (SEA) in combination with the millions instructions per second set partitioning in hierarchical trees (MIPS SPIHT) visual processor. The SEA is implemented on a Celoxica RC203 Vertex XC2V3000 FPGA occupying 6251 slices and a visual sensor is used to capture real world images. Four images frames were captured from a camera sensor, compressed, selectively encrypted, and sent over to a PC environment for decryption. The final design emulates a working visual sensor, from on node processing and encryption to back-end data processing on a server computer