Currently, the increasing rate of routing lookups in Internet routers, the large number of prefixes and also the transition from IPV4 to IPV6, have caused Internet designers to propose new lookup algorithms and try to reduce the memory cost and the prefix search and update procedures times. Recently, some new algorithms are proposed trying to store the prefixes in a balanced tree to reduce the worst case prefix search and update times. These algorithms improve the search and update times compared to previous range based trees. In this paper it is shown that there is no need to treat the prefixes as ranges. It is only required to compare them like scalar values using a predefined rule. The method "Scalar Prefix Search" which is presented here, is built on this concept and combining it with the proposed store and search methods, interprets each prefix as a number without any encoding, the need to convert it to the prefix end points or to use the Trie based algorithms whose performance completely depends on IP address length. This method can be applied to many different tree structures. It is implemented using the Binary Search Tree and some other balanced trees such as RB-tree, AVL-tree and B-tree for both IPV4 and IPV6 prefixes. Comparison results show better lookup and update performance or superior storage requirements for Scalar Prefix Search in both average and worst cases, against current solutions like PIBT [1] and LPFST [2].

SUMMARYRecently, we have proposed a new prefix lookup algorithm which would use the prefixes as scalar numbers. This algorithm could be applied to different tree structures such as Binary Search Tree and some other balanced trees like RB-tree, AVL-tree and B-tree with minor modifications in the search, insert and/or delete procedures to make them capable of finding the prefixes of an incoming string e.g. an IP address. As a result, the search procedure complexity would be O(log n) where n is the number of prefixes stored in the tree. More important, the search complexity would not depend on the address length w i.e. 32 for IPv4 and 128 for IPv6. Here, it is assumed that interface to memory is wide enough to access the prefix and some simple operations like comparison can be done in O(1) even for the word length w. Moreover, insertion and deletion procedures of this algorithm are much simpler and faster than its competitors. In what follows, we report the software implementation results of this algorithm and compare it with other solutions for both IPv4 and IPv6. It also reports on a simple hardware implementation of the algorithm for IPv4. Comparison results show better lookup and update performances or superior storage requirements for Scalar Prefix Search in both average and worst cases.

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