Recent research in Volunteer Computing explores how distributed, user-contributed resources can be efficiently utilized to support large-scale and data-intensive computations across cloud, edge, and IoT environments. Studies focus on enhancing reliability, scalability, and security within volunteer-based infrastructures through clustering, task scheduling, and confidentiality mechanisms. Reinforcement learning and intelligent scheduling algorithms are being applied to manage dynamic resource availability and optimize workflow execution in heterogeneous volunteer systems. Researchers are also examining integration with edge and fog computing to improve QoS for latency-sensitive applications, while addressing challenges such as trust management, incentive mechanisms, and energy efficiency, making volunteer computing a vital component of sustainable and decentralized cloud ecosystems.