EABF: Energy efficient self-adaptive Bloom filter for network packet processing

Future Internet requires re-thinking of network infrastructure towards the balance between computing capacities and energy sustainable techniques. As one of computing intensive components, Bloom filters are widely used for network packet processing. In this paper, an energy efficient self-adaptive Bloom filter, EABF, is devoted to a balance of power and performance especially for high performance networks. The basic idea is to give the Bloom Filter the capability to adjust the number of active hash functions according to the current workload automatically. This adaption depends on its control policies. Three policies are presented and compared. We also give the method to implement EABF in hardware for higher performance. It is presented in a two-stage platform based on FPGA where Stage 1 is always active and Stage 2, a secondary stage, is only active when necessary. The platform can also be extended to multi-stages. A control circuit is designed for flexibly changing working stage and reducing both dynamic and static power consumption. Analysis and experiments show that our dynamic two-stage EABF can achieve almost the best power savings as that of the fixed schemes; unlike the fixed schemes that might have much longer latency, EABF maintains nearly 1 clock cycle latency as that of a regular Bloom filter.