113 citations · 601 across the 32 of their papers we have counts for
32 papers
Clustered Edge Intelligence: Beyond Just Convergence of Edge Computing and AI
Chinmaya Kumar Dehury, Boris Sedlak, Alaa Saleh +4
We are moving from an information age to the age of intelligence. A decade, or possibly less than that, data will not be the gold anymore rather the derived intelligence out of the…
Fog Computing and Large Language Models: A vision for mutual beneficiaries
Satish Narayana Srirama
Fog computing utilizes proximal computational resources for sensor data processing and actuation, and addresses the latency, network load, and privacy issues of cloud-centric Inter…
Cloud-native and Distributed Systems for Efficient and Scalable Large Language Models -- A Research Agenda
Minxian Xu, Jingfeng Wu, Shengye Song +16
The rapid rise of Large Language Models (LLMs) has revolutionized various artificial intelligence (AI) applications, from natural language processing to code generation. However, t…
Evaluating the impact of code smell refactoring on the energy consumption of Android applications
Hina Anwar, Dietmar Pfahl, Satish N. Srirama
Energy consumption of mobile apps is a domain that is receiving a lot of attention from researchers. Recent studies indicate that the energy consumption of mobile devices could be…
StatuScale: Status-aware and Elastic Scaling Strategy for Microservice Applications
Linfeng Wen, Minxian Xu, Sukhpal Singh Gill +4
Microservice architecture has transformed traditional monolithic applications into lightweight components. Scaling these lightweight microservices is more efficient than scaling se…
Distributed Edge Analytics in Edge-Fog-Cloud Continuum
Satish Narayana Srirama
To address the increased latency, network load and compromised privacy issues associated with the Cloud-centric IoT applications, fog computing has emerged. Fog computing utilizes…