The main challenge of problem lies in the perception of Cognitive Radio technology is to discover licensed empty spectrum pattern. The efficient model is needed for allocation among licensed and unlicensed users in wireless spectrum to improve the extraction rate and collision rate. To discover the spectrum hole in spectrum paging bands, stirred by FP mining technique proposed an efficient enumeration approach, namely Constraint Based Frequent Periodic Pattern Mining (CBFPP). The proposed algorithm uses TRIE-like data structure with data mining constraints. CBFPP algorithm predicts periodic spectrum occupancy holes in the paging bands. It is shown that CBFPP has a high prediction accuracy with reasonable time complexity. Experiment with synthetic and real data validate higher prediction accuracy and with reasonable time complexities. The unlicensed user utilizes the predicted spectrum pattern in spectrum usage of channel without significant interference to licensed users.
Traditional methodologies for routing in media streaming is challenging because packets are not retransmitted when there is loss or corruption of packets. Thus throughput, packet loss rate or delay is not guaranteed. Providing multipath for every transmission helps in meeting efficient
load balancing metrics. Software defined networking (SDN) approach is used to configure the network topology and increase the network performance and monitoring. Controller act as a centralized management device which monitors the overlay network. It reacts to network failures/changes by administering
alternate routing instructions to the overlay nodes. The overlay network enhances different load balancing metrics. Dijkstra’s algorithm is used to solve the routing problem for find the shortest path. The proposed scheme is using an AOMDV multipath on-demand routing protocol which dynamically
finds multipath. It experimentally evaluates performance metrics like end-to-end delay, throughput using AOMDV is compared with AODV.
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