Computation Resource Allocation Using NOMA Technique

There have been many clients using cloud computing in recent years, ranging from small businesses to large corporations. The tremendous amount of information and resources that cloud organizations must handle has created challenges. Managing resources inefficiently can lead to poor performance in cloud computing. Diverse stakeholders need resources allocated equally to meet their needs without sacrificing the company's financial success or user satisfaction. If the assets are not available on the list, a customer's request cannot be withheld indefinitely. To make IoT devices more energy-efficient, we utilize nonorthogonal multiple access (NOMA) technology to handle vast amounts of data. IoT devices have been designed to achieve maximum energy efficiency while allowing for maximum tolerable delay requirements by formulating a joint resource allocation problem that considers both intracell and intercell interference. We partitioned the problem of resource allocation for radio and computing to start addressing this interactable mixed-integer nonconvex problem. Further divisions of this radio resource allocation are Subchannel allocation, which can be addressed using a matching technique, and power allocation, which uses a sequential convex programming algorithm. With the use of the knapsack algorithm, computation resource allocation can be obtained. we mainly focus on minimizing the delay and increase the energy efficiency. The simulation results demonstrate the effectiveness of the suggested NOMA technique.