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@article{199742,
        author = {S.Shobana},
        title = {Deep Learning Driven Task Offloading for Energy Efficient Ad Hoc Mobile Cloudlets},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {11},
        pages = {13340-13344},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=199742},
        abstract = {Mobile cloud computing (MCC), an emerging paradigm for mobile services, builds on the convergence of cloud computing and the rapid evolution of mobile applications. However, resource-constrained mobile devices struggle to fully leverage these capabilities. Cloudlets offer an effective intermediate processing layer between mobile devices and remote clouds, addressing key limitations such as latency and energy consumption. This study proposes a novel hybrid offloading algorithm based on deep learning to optimize mobile cloudlet provisioning. Experimental results demonstrate that the approach significantly reduces average execution time and minimizes energy consumption on mobile devices.},
        keywords = {Cloudlets, Deep learning, Energy optimization, Hybrid offloading algorithm, Mobile Cloud Computing (MCC).},
        month = {April},
        }