Joint Device Association, Resource Allocation, and Computation Offloading in Ultradense Multidevice and Multitask IoT Networks

With the emergence of more and more applications of Internet of Things (IoT) mobile devices (IMDs), a contradiction between mobile energy demand and limited battery capacity becomes increasingly prominent. In addition, in ultradense IoT networks, the ultradensely deployed small base stations (SBSs) will consume a large amount of energy. To reduce the network-wide energy consumption and prolong the standby time of IMDs and SBSs, under the proportional computation resource allocation and devices' latency constraints, we jointly perform the device association, computation offloading, and resource allocation to minimize the network-wide energy consumption for ultradense multidevice and multitask IoT networks. To further balance the network loads and fully utilize the computation resources, we take account of multistep computation offloading. Considering that the finally formulated problem is in a nonlinear and mixed-integer form, we develop an improved hierarchical adaptive search (IHAS) algorithm to find its solution. Then, we give the convergence, computational complexity, and parallel implementation analyses for such an algorithm. By comparing with other algorithms, we can easily find that such an algorithm can greatly reduce the network-wide energy consumption under devices' latency constraints.