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

2. Wireless Networking Is Important But... Peak bandwidth is physically limited for any given frequency band Further exploitation in diversity (e.g., multipath and fine-grained beamforming gains) is getting increasingly difficult Gap in meeting application demands is growing 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. That is, approximate input and results can be tolerated. For example: – Sensor data processing – Big data analysis – Probability distribution estimation – Multimedia 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 of Approximate Networking Use approximate network node hardware and protocols, and traffic-reducing networks Allow efficient, inexpensive and scalable networks, and nanoscale post-CMOS implementations which are inherently less deterministic Enable new security means. E.g., integrated encryption and compression, that is, compressing phenomena (population distributions) encrypted in secret distortion distributions, rather than insesure compression followed by encryption Can exploit theory in network coding and compressive sensing (e.g., any received linear combinations of packets are useful)

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