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Exploring Opportunities in Approximate Networking: Challenges and Innovations in Wireless Systems

The panel discusses the significant opportunities in approximate networking, particularly within wireless systems. As applications increasingly demand higher bandwidth, it's crucial to find solutions that respect Shannon's capacity theorem while bridging the gap in performance. The panel highlights potential applications such as sensor data processing, big data analysis, machine learning, and object recognition, where approximate networking can be beneficial. By leveraging new hardware and protocols, networks can be made more efficient and robust, enhancing security and performance.

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Exploring Opportunities in Approximate Networking: Challenges and Innovations in Wireless Systems

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  1. Approximate Networking H. T. Kung Harvard University Panel 1 on “What Are the Biggest Opportunities in Networking Problem?” NITRD Workshop on Complex Engineered NetworksWashington, DCSeptember 20-21, 2012

  2. Wireless Networking Is ImportantBut ... • Peak bandwidth is physically limited for any given frequency band • Further exploitation in diversity (e.g., multipath and fine-grained beamforming) is getting increasingly difficult • Gap in meeting application demands is growing • Thus we need to find ways to fill the gap without violating Shannon's capacity theorem

  3. Fortunately, There Are Opportunities • Many applications don’t need networks for exact packet delivery, for example: • Sensor data processing • Big data analysis • Probability distribution estimation • Image/vision object recognition and tracking • Machine learning • Biologically inspired systems • For these applications, approximate networking may be sufficient: • Deliver fraction of packets • Deliver approximate packets • Deliver combined packets

  4. Advantages • We can use approximate network node hardware and protocols, and traffic-reducing networks • This allows efficient network implementation and robust network management • Moreover, this enables new security means, e.g., integrated encryption and compression using secret distortion distribution keys rather than compression followed by encryption • Theory in network coding and compressive sensing can be exploited

  5. Summary • We have argued that approximate networking, especially for wireless networking, is a good opportunity for future networking

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