Many existing scheduling approaches in cloud data centers try to consolidate Virtual Machines (VMs) by VM live migration technique to minimize the number of Physical Machines (PMs) and hence minimize the energy consumption, however, it introduces high migration overhead; furthermore, the cost factor that leads to high payment cost for cloud users is usually not taken into account. Aiming at energy reduction for cloud providers and payment saving for cloud users, as well as guaranteeing the deadline of user tasks, a heuristic task scheduling algorithm called Energy and Deadline-Aware with Non-Migration Scheduling (EDA-NMS) was proposed. The execution of the tasks that have loose deadlines was postponed to avoid waking up new PMs and migration overhead, thus reducing the energy consumption. The results of extensive experiments show that compared with Proactive and Reactive Scheduling (PRS) algorithm, by selecting a smart VM combination scheme, EDA-NMS can reduce the static energy consumption and ensure the lowest payment with meeting the deadline requirement for key user tasks.