Problem statement: This study is for effective scheduling of grid job s based on economy for space shared resources in Bag of tasks grid. Gr id Computing aims in combining the power of heterogeneous, geographically distributed, multi-do main computational resources to provide high performance or high throughput. Approach: Space shared resources are parallel supercomputers and clusters of workstations that provides a great amou nt of computational power. These resources require jobs to be specified formally in terms of the amoun t of time (tr) and number of processors (p) needed for execution. Bag-of-Tasks (BoT) is an application consists of several uniprocessor and independent tasks that have no inter-task communications or tas k-dependencies. BoT is highly suitable for executio n in grids. It is capable of tolerating network delay s or faults and does not require formal job submiss ion. The Explicit allocation strategy assigns the formal job parameters (p, tr) to the job requests, minimi zing the overhead on the grid users to provide a formal job specification. This strategy uses adaptive heur istics to determine the parameters based on certain heuris tics, in order to improve throughput. In the propos ed system, explicit allocation strategy combined with Deadline and Budget Constraint (DBC) Cost Time optimization algorithm performs effective schedulin g of the jobs based on the user's quality of servic e (QoS) requirements such as deadline, budget and optimization strategy. Results: The cost-time optimization scheduling allocates the cheapest reso urces to ensure that the deadline can be met and computation is minimized. In case if there are two resources with the same cost, scheduling is done in any affordable resource so that the job gets execut ed as early as possible. Conclusion: The performance of this scheme against the existing system is evalu ated using cost factor (C factor ) and speed up ratio (T speedup ) and this scheme is more effective than the existi ng system.