Receiver-oriented design of Bloom filters for data-centric routing

  • Authors:
  • Deke Guo;Yuan He;Panlong Yang

  • Affiliations:
  • Key Laboratory of C4 ISR Technology, National University of Defense Technology, Changsha Hunan 410073, China;Department of Computer Science and Engineering, Hong Kong University of Science and Technology, Hong Kong, China;Institute of Communication Engineering, P.L.A University of Science and Technology, Nanjing Jiangsu 210000, China

  • Venue:
  • Computer Networks: The International Journal of Computer and Telecommunications Networking
  • Year:
  • 2010

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Abstract

Bloom filter (BF) is a space-efficient data structure that represents a large set of items and supports efficient membership queries. It has been widely proposed to employ Bloom filters in the routing entries so as to facilitate data-centric routing in network applications. The existing designs of Bloom filters, however, cannot effectively support in-network queries. Given a query for a data item at a node in the network, the noise in unrelated routing entries very likely equals to the useful information of the item in the right routing entries. Consequently, the majority of queries are routed towards many wrong nodes besides those destinations, wasting large quantities of network traffic. To address this issue, we classified the existing designs as CUBF (Cumulative Bloom filters) and ABF (Aggregated Bloom filters), and then evaluate their performance in routing queries under the noisy environments. Based on the evaluation results, we propose a receiver-oriented design of Bloom filters to sufficiently restrict the probability of a wrong routing decision. Moreover, we significantly decrease the delay of a routing decision in the case of CUBF by using the bit slice approach, and reduce the transmission size of each BF in the case of ABF by using the compression approach. Both the theoretical analysis and experimental results demonstrate that our receiver-oriented design of Bloom filters apparently outperforms the existing approaches in terms of the success probability of routing and network traffic cost.