Systematic Survey of Evolving Clustering Paradigms in the Edge-Cloud Continuum
Mobile & Cloud Computing Laboratory
This thesis aims to provide a comprehensive and methodical examination of clustering algorithms within the realm of distributed systems and the evolving edge-cloud computing paradigm. As distributed systems become more intricate and the interplay between edge devices and cloud infrastructures deepens, effective data clustering becomes paramount to achieve optimized performance and data management. The investigation will assess the efficacy, scalability, and adaptability of existing clustering methodologies in these computing environments. Moreover, it will shed light on the unique challenges posed by the fusion of edge and cloud computing, seeking innovative strategies to enhance clustering efficiency. Ultimately, this research endeavor aspires to not only bridge the current knowledge gaps but also provide direction for future advancements in clustering techniques tailored to distributed systems and the edge-cloud continuum.
Graduation Theses defence year
Spoken language (s)
Requirements for candidates
Application of contact
Chinmaya Kumar Dehury