Advanced network services, such as firewalls, policy-based routing, and virtual private networks, must rely on routers to classify packets into different flows based on packet headers and predefined filter tables. When multiple filters are overlapped, conflicts may occur, leading to ambiguity in the packet classification. Conflict detection ensures the correctness of packet classification and has received considerable attention in recent years. However, most conflict-detection algorithms are implemented on a conventional central processing unit (CPU). Compared with a CPU, a graphics processing unit (GPU) exhibits higher computing power with parallel computing, hence accelerates the execution speed of conflict detection. In this study, we employed a GPU to develop two efficient algorithms for parallel conflict detection: the general parallel conflict-detection algorithm (the GPCDA) and the enhanced parallel conflict-detection algorithm (the EPCDA). In the GPCDA, we demonstrate how to perform conflict detection through parallel execution on GPU cores. While in the EPCDA, we analyze the critical procedure in conflict detection as to reduce the number of matches required for each filter. In addition, the EPCDA adopts a workload balance method to enable load balancing of GPU execution threads, thereby significantly improving performance. The simulation results show that with the 100 K filter database, the GPCDA and the EPCDA execute conflict detection 2.8 to 13.9 and 9.4 to 33.7 times faster, respectively, than the CPU-based algorithm.

To support advanced network services, Internet routers must perform packet classification based on a set of rules called packet filters. If two or more filters overlap, a filter conflict will occur and lead to ambiguity in packet classification. Further, it may affect network security or even the correctness of packet routing. Hence, it is necessary to detect conflicts to avoid the above problems. In recent years, many conflict detection algorithms have been proposed, but most of them detect conflicts for only prefix fields (i.e., source/destination IP address fields) of filters. For greater practicality, conflict detection must include non-prefix fields such as source/destination IP port fields and the protocol field. In this study, we propose an efficient conflict detection algorithm for five-dimensional filters, which include both prefix and non-prefix fields. In the proposed algorithm, a tiny lookup table is created for quickly filtering out a large portion of non-conflicting filter pairs, thereby reducing the overall conflict detection time. Experimental results show that our algorithm reduces the detection time by 10% to 28% compared with other conflict detection algorithms for 20 K filter databases. More importantly, our algorithm can be used to extend any existing conflict detection algorithms for two-dimensional filters to support fast conflict detection for five-dimensional filters.