The 24th IEEE/ACM International Symposium on Cluster, Cloud, and Internet Computing (CCGrid 2024) is a leading forum for disseminating and discussing research activities and results on a broad range of topics in distributed systems, ranging from computing Clusters to widely distributed clouds and emerging Internet computing paradigms, such as fog/edge computing for Internet of Things (IoT)/big data applications. The conference features keynotes, technical presentations, posters, workshops, and the SCALE challenge featuring live demonstrations. We solicit original contributions in all aspects of distributed systems and applications in the context of cluster, cloud, and Internet computing environments. Specific topics of interest include but are not limited to the following research tracks:

• Track 1: Hardware Systems and Networking: Sustainable and green computing; architecture, networking of data centers; virtualized hardware (GPUs, tensor processing units, FPGAs); RISC V / Open hardware architectures, etc.
• Track 2: Software Systems and Platforms: Service-oriented architectures; utility computing models; IaaS, PaaS, SaaS; programming models and runtime systems; resource management and scheduling; and energy-efficient software.
• Track 3: Machine Learning (ML) for Systems and Systems for ML: Techniques, platforms, and systems for supporting machine learning and artificial intelligence applications; use of ML/AI applications to enhance the performance of cluster, cloud and Internet-computing systems; ML/AI techniques for workload prediction; application scheduling, resource placement, resilience in cluster, cloud and Internet-computing systems.
• Track 4: Future Compute Continuum and Seamless Ecosystems: Internet computing frontiers; future Internet; osmotic computing; cloud-economics; post- and Non-Von Neumann computing; quantum computing.
• Track 5: Applications and Workflows: Data science; machine learning and artificial intelligence applications; cyber-physical systems; e-Health; Internet of Things (IoT)-enabled smart systems and applications; workflows.
• Track 6: Performance Monitoring, Modeling, Analysis, and Benchmarking: Performance models; monitoring and evaluation tools; analysis of system/application performance; performance benchmarking; visualization for system or application performance; cloud performance; edge performance; and cloud-native performance tools.
• Track 7: Distributed and Parallel Storage Systems: storage and memory stack architecture; distributed and parallel storage; HW/SW co-design for storage systems; NVM storage; cloud storage; edge storage; storage- and memory-as-a-service; file and data management; key-value stores; CDNs; data privacy, integrity, and regulation; resilience of service attacks.
• Track 8: Education about Cluster, Cloud and Internet Computing: curriculum, didactics, and technology developments for cluster, cloud, and Internet-scale computing; virtual laboratory; teaching parallel and distributed systems; teaching performance; teaching cloud, cluster, and Internet-scale technologies; sharing digital learning objects; sharing lab experiments; reproducing educational experiments; teaching methodology in cluster, cloud and Internet computing.