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Abstract
Packet classification is a crucial function in computer networks that involves identifying packets based on specific criteria, such as source and destination IP addresses, protocol type, and port numbers. Various packet classification techniques have been proposed over the years, each with its own strengths and weaknesses. In this paper, we provide a brief overview of packet classification techniques used in computer networks, including decision-tree-based algorithms, bit-vector-based algorithms, hash-based algorithms, and others. We compare and contrast these algorithms based on their performance characteristics, complexity, and scalability. Finally, we discuss future directions for research in packet classification and conclude with a summary of the key takeaways
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