In the past decade cluster computing platforms have been widely applied to support a variety of scientific and commercial applications, many of which are parallel in nature. However, scheduling parallel applications on large scale clusters is technically challenging due to significant communication latencies and high energy consumption. As such, shortening schedule length and conserving energy consumption are two major concerns in designing economical and environmentally friendly clusters. In this paper, we propose an energy-efficient scheduling algorithm (TDVAS) using the dynamic voltage scaling technique to provide significant energy savings for clusters. The TDVAS algorithm aims at judiciously leveraging processor idle times to lower processor voltages (i.e., the dynamic voltage scaling technique or DVS), thereby reducing energy consumption experienced by parallel applications running on clusters. Reducing processor voltages, however, can inevitably lead to increased execution time...