Heterogeneous resource allocation with latency guarantee for computing power network

Computing Power Network (CPN) is a new paradigm that integrates communication, computing, and storage resources to provide services for tasks. However, tasks composed of non-independent subtasks have a preference for the resources required at each stage, which increases the difficulty of heterogeneous resource allocation and reduces the latency performance of CPN services. Motivated by this, this paper jointly optimizes the full-service cycle of tasks, including transmission, task partitioning, and offloading. First, the transmission bandwidth is dynamically configured based on delay sensitivity of tasks. Second, with the real-time information from edge resource clusters and state resource clusters in the network, the optimal partitioning for a computation task is derived. Third, personalized resource allocation schemes are customized for computation and storage tasks respectively. Finally, the impact of resource parameter configuration on the latency violation probability of CPN is revealed. Moreover, compared with the benchmark schemes, our proposed scheme reduces the network latency violation probability by up to 1.17 × in the same network setting.