Vehicle-to-Everything (V2X) requires high-speed communication and high-level security. However, as the number of connected devices increases exponentially, communication networks are suffering from huge traffic and various security issues. It is well known that performance and security of network equipment significantly depends on the packet classification algorithm because it is one of the most fundamental packet processing functions. Thus, the algorithm should run fast even with the huge set of packet processing rules. Unfortunately, previous packet classification algorithms have focused on the processing speed only, failing to be scalable with the rule-set size. In this paper, we propose a new packet classification approach balancing classification speed and scalability. It can be applied to most decision tree-based packet classification algorithms such as HyperCuts and EffiCuts. It determines partitioning fields considering the rule duplication explicitly, which makes the algorithm memory-effective. In addition, the proposed approach reduces the decision tree size substantially with the minimal sacrifice of classification performance. As a result, we can attain high-speed packet classification and scalability simultaneously, which is very essential for latest services such as V2X and Internet-of-Things (IoT).

One of the key applications in the 5G system is Vehicle-to-Everything (V2X). Ultra-low delay communication is essential for the safety of users and pedestrians in V2X. However, as sophisticated and various cyberattacks are increasing, it becomes hard to satisfy low delay constraints. To protect networks from such attacks, even single network security equipment provides multiple security functions, resulting in the inevitable additive delay in packet processing. In this paper, we suggest a new packet classification paradigm to resolve this issue. The proposed algorithm integrates multiple policy rule-sets into a single rule-set and classifies incoming packets using the integrated rule-set. Thus, it has a unique feature providing high classification performance regardless of the number of security policies. Through extensive performance evaluations, we confirm that the performance improvement is also increased with the total rule-set number increasing without the significant overhead of memory cost. We expect that it will mitigate the delay issue of existing network equipment for upcoming services such as V2X.

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