This paper targets energy-efficient scheduling of tasks over multiple processors, where tasks share a common deadline. Distinct from many research results on heuristics-based energy-efficient scheduling, we propose approximation algorithms with different approximation bounds for processors with/without constraints on the maximum processor speed, where no task migration is allowed. When there is no constraint on processor speeds, we propose an approximation algorithm for two-processor scheduling to provide trade-offs among the specified error, the running time, the approximation ratio, and the memory space complexity. An ap