The internet data traffic is tripling every two years due to the exponential growth in the number of routers. Routers implement the packet classification methodology by determining the flow of the packet, based on various rule checking mechanisms that are performed on the packet headers. However, the memory components like TCAMs used by these various rules are very expensive and power hungry. Henceforth, the current IP Lookup algorithms implemented in hardware are even though able to achieve multi-gigabit speeds, yet suffer with great memory overhead. To overcome this limitation, we propose a packet classification methodology that comprises of MicroCuckoo-hash technique, to route packets. This approach alleviates the memory requirements significantly, by completely eliminating the need for TCAM cells. Cuckoo hash is used to achieve very high speed, hardware accelerated table lookups and also are economical compared to TCAMs. The proposed IP Lookup algorithm is implemented as a simulation-based hardware/software model. This model is developed, tested and synthesized using Vivado HLS tool. / Master of Science