Recent studies in Profit-driven Resource Allocation in Cloud Computing focus on maximizing the revenue and profitability of cloud service providers while maintaining efficient resource utilization and service quality. Researchers have proposed intelligent frameworks that integrate workload prediction, dynamic pricing, and optimization models such as game theory, reinforcement learning, and metaheuristics to balance user satisfaction and provider profit. These approaches adaptively allocate resources based on demand trends, energy efficiency, and cost-benefit ratios, ensuring economic sustainability alongside performance goals. By emphasizing profit optimization rather than solely cost reduction, modern solutions enable cloud providers to achieve greater financial efficiency, scalability, and competitiveness across multi-cloud, edge, and IoT-based environments.