Towards Line-Speed and Accurate On-line Popularity Monitoring on NDN Routers

Abstract—NDN enables routers to cache received contents for future requests to reduce upstream traffic. To this end, various caching policies are proposed, typically based on some notion of content popularity, e.g., LFU. But these policies simply assume the availability of content popularity information without elaborating how that information is obtained and maintained in routers. Towards line-speed and accurate on-line popularity monitoring on NDN routers, we propose a Bloom filter-based method to continuously capture content popularity with efficient usage of memory. In this method, multiple Bloom filters are employed and each one is responsible for a particular range of popularity. Content objects whose popularities fall into a Bloom filter’s range will be inserted into that Bloom filter. Meanwhile, a sliding window monitoring scheme is proposed to implement more frequent and real-time update of the popularities. Moreover, we put forward three optimization schemes to further speed up the monitoring operations. Using a real trace stored in off-chip memory as input and setting the monitoring time window to 30 min, this method achieves a monitoring speed of 20.92 million objects per second (M/s) with multiple threads. This speed is equivalent to 16.74 Gbps throughput assuming the content length is 100 Bytes in average, but only consumes around 32 MB memory. By simulating the environment on the line card using a real-time generated synthetic trace, this method even reaches a speed of 251.07 M/s (equivalent to 200.86 Gbps) because the trace is fetched from high speed on-chip memory, rather than the off-chip DRAMs. Furthermore, both theoretical and experimental analyses elucidate very low relative error of this method. At last, a real trace-driven comparison shows that LFU policy achieves higher hit rate than LRU with much less unnecessary cache replacements