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Grid technology is popular in science and business computing environment, with workflow the flexibility and applicability of the grid system can be greatly enhanced. Cost-effective scheduling of grid workflow applications represented by DAG (directed acyclic graph)is an essential and complex problem. In general such problem is NP-hard. In this paper, a novel heuristics, DSL (deadline segment leveling) is proposed. Considering its parallel and synchronization properties, the grid workflow application is divided into segments, and each segment is partitioned into groups further using a segment leveling method. The floating time is prorated to each group to enlarge group duration. In term of control dependencies between tasks, time interval for each task is determined. Experimental results shows DSL can achieve considerable performance improvement than MCP (minimal critical path) and other leveling-based heuristics.