Modern embedded processors provide hardware support for cache locking, a mechanism used to facilitate the WCET (Worst-Case Execution Time) calculation of a task. We investigate the problem of integrating task scheduling and cache locking for a set of pre-emptible tasks with individual release times and deadlines on a multicore processor with two level caches. We propose a novel integrated approach that schedules the task set and allocates the locked cache contents of each task to the local caches (L1 caches) and the level two cache (L2 cache). Our approach consists of three major components, the task scheduler, the L1 cache allocator, and the L2 cache allocator. The task scheduler aims at minimizing the number of task preemptions. The L1 cache allocator converts the interference graph of all the tasks scheduled on each core into a DAG by considering the preemptions between tasks and allocates L1 cache space to each task. The L2 cache allocator converts the interference graph of all the tasks into a DAG by using a k-longest-path based graph orientation algorithm and allocates L2 cache space to each task. Both cache allocators significantly improve the utilization of all the caches due to the efficient use of the interference graphs of tasks. We have implemented our approach and compared it with the extended version of the preemption tree-based approach and the static analysis approach without cache locking by using a set of benchmarks from the MRTC benchmark suite and SNU real-time benchmarks. Compared to the extended version of the preemption tree-based approach, the maximum WCRT (Worst Case Response Time) improvement of our approach is 15%. Compared to the static analysis approach, the maximum WCRT improvement of our approach is 37%.