Enhanced Adaptive Cuckoo filter searching technique for Approximate Membership Data Structure (AMDS) in network layer.

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Mrs.G.Indumathi, Dr.B.S.E.Zoraida


 In large data center, virtual machines are connected dynamically and data are moved between the physical machines and the virtual machines. With this environment, the Network Layer transfers the packets to the Transport Layer. To improve the security and to increase the speed of the packet transmission in the network layer, packet-filtering is carried out by firewalls based on the decision of routers namely Network addresses, Ports or Protocols. Earlier packet filtering techniques are IP data-gram, Queuing and Scheduling. In order to overcome the limitation in security mechanisms in the above filtering techniques, hashing algorithms are used for analyzing the elements in the packets that are stored in the Hash tables. The hashing algorithms are used in Quotient filter, Bloom filter, Cuckoo filter and Adaptive Cuckoo Filter (ACF). AMDS is termed as An Approximate Membership Data Structures were used to store the fingerprints in cuckoo hash tables. In this paper an attempt is made to improve the searching strategy in Cuckoo filter. Spring constant factor and Leivy Flight theorem is introduced in the searching strategy for best solution identification path. A suit of benchmark functions are employed to verify the performance of network with respect to time, speed and the memory space in the packets transmission. The performance of the Enhanced searching strategy gives better result when compared to ACF.

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