Design of an Adaptive Architecture for Energy Efficient Wireless Image Communication

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• 作者：Clark N. Taylor ; Debashis Panigrahi ; Sujit Dey
• 刊名：Lecture Notes in Computer Science
• 出版年：2002
• 出版时间：2002
• 年：2002
• 卷：2268
• 期：1
• 页码：506-508
• 全文大小：273.7 KB
• 参考文献：
• 作者单位：
• 刊物类别：Computer Science
• 刊物主题：Artificial Intelligence and Robotics
  Computer Communication Networks
  Software Engineering
  Data Encryption
  Database Management
  Computation by Abstract Devices
  Algorithm Analysis and Problem Complexity
  
• 出版者：Springer Berlin / Heidelberg
• ISSN：1611-3349

文摘

With the projected significant growth in mobile internet and multimedia services, there is a strong demand for next-generation wireless appliances capable of image communication. However, wireless image communication faces significant bottlenecks including high energy and bandwidth consumption. Past studies have shown that the bottlenecks to wireless image communication can be overcome by developing adaptive image compression algorithms and dynamically adapting them to current channel conditions and service requirements [1],[2]. In this paper, we present the design of an adaptive hardware/software architecture that enables adaptive wireless image communication. Through intelligent co-design of the proposed architecture and algorithms, we achieve an architecture which enables not only power and performance efficient implementation, but also fast and efficient run-time adaptation of image compression parameters. To achieve efficient image compression and run-time adaptation, we characterized the adaptation needs of an adaptive image compression algorithm in terms of parameters, and implemented an adaptive hardware/software architecture capable of executing JPEG image compression with different parameters. We present experimental results demonstrating that the proposed architecture enables low overhead adaptation to current wireless conditions and requirements while implementing a low cost (energy and performance) implementation of adaptive image compression algorithms.