An Efficient Algorithms For Wireless Network Using Cloud Computing
Abstract
An algorithm that can decide vertical handofffor mobile users armed with current multi-mode mobile devices to communicate continuously in the NGWN. It integrates the edge values of deep parameters, which are considered as the necessary metrics in the decisionmaking process used to select the optimal target network.To tackle this research goal, we used the concept of artificial intelligence & machine learning along with computing speed in cloud computing to plan a suitable algorithm for the transfer of origination that can take care of data vagueness and uncertainty and deal with multiple vertical parameters of origination, such as network context, mobile terminal conditions, power r Specifically, we analyzed the interesting case: vertical handoff decision between mobile WiMAXand WiFi<E access networks. Implementing the proposed handoff decision algorithm provides a network selection mechanism to help mobile users select the best wireless access network among all available wireless access systems, that is, one that always offers users the best coupling services. Simulation tests indicate increase in experiential network efficiency by avoiding redundant handover. In the everpresent environment, most Handover decision process creates a ping pong effect produced by the inefficiency of network handover metrics that do not think through the required enduser achievements.As equated to numerous existing algorithms; our algorithm matches the expected fluctuations in network efficiency and favors mobile users without wasting network resources. It reduces transmission time And preventable handoff, which reduces the ping pong effect and improves user satisfaction.
