Green cloud computing is the latest research trend where various approaches are introduced to minimize the energy consumptions and carbon footprint produced by computers. Further, the pay-per-use pricing model used in the cloud system helps to achieve economy of scale. Noticeably, many real-time applications that demand both temporal and functional correctness are moving to the cloud. It becomes a challenging task for a cloud service provider to ensure real-time response while minimizing computation energy and execution cost. In this regard, task scheduling plays a key role in achieving a performance improvement of the system with several constraints. In this paper, we proposed a multi-constraint scheduling algorithm, namely MCSA for the real-time task in the virtualized cloud environment. First, we assign a score value to a VM based on computation energy and execution cost. Then, MCSA use this scoring value to choose the appropriate VM for a task. We analyzed the proposed MCSA algorithm through extensive simulations and experiments. We consider Guarantee Ratio, Average Execution Cost, and Average Energy Consumption under various scenarios to show the effectiveness of MCSA over some existing schemes.