Jia Yu

Computer Networks and Communications · Journal of Grid Computing · 2005–2006

A researcher in the Science corpus: 4 papers; trusts 30 researchers and is trusted by 12 researchers here, as inferred from the citation graph.

Subfields

Whom Jia Yu trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

  1. Rajkumar Buyya
  2. Ian T Foster
  3. Wil M.P. van der Aalst
  4. David Abramson
  5. Carl Kesselman
  6. Jan Mendling
  7. Ewa Deelman
  8. Todd Tannenbaum
  9. Jonathan Giddy
  10. Albert Y. Zomaya

Who trusts Jia Yu overall

  1. Ming Mao
  2. Mala Kalra
  3. Zhangjun Wu
  4. Rajkumar Buyya
  5. Marty A. Humphrey
  6. Sarbjeet Singh
  7. Jie Li
  8. Xiao Liu
  9. Ewa Deelman
  10. Zhiwei Ni

Papers from Jia Yu's perspective

Ordered by how strongly the researchers Jia Yu trusts endorse each paper. Same corpus, a different order for every researcher.

  1. Grid information services for distributed resource sharing (Proceedings 10th IEEE International Symposium on High Performance Distributed Computing)
  2. The Anatomy of the Grid: Enabling Scalable Virtual Organizations (The international journal of high performance computing applications)
  3. Nimrod/G: an architecture for a resource management and scheduling system in a global computational grid (Proceedings Fourth International Conference/Exhibition on High Performance Computing in the Asia-Pacific Region)
  4. The GRID: Blueprint for a New Computing Infrastructure (Parallel Distributed Comput. Pract.)
  5. Giggle: A Framework for Constructing Scalable Replica Location Services (International Conference on Software Composition)
  6. Genetic Algorithms in Search Optimization and Machine Learning
  7. High performance parametric modeling with Nimrod/G: killer application for the global grid? (Proceedings, International Parallel and Distributed Processing Symposium (IPDPS))
  8. The Physiology of the Grid An Open Grid Services Architecture for Distributed Systems Integration
  9. The data grid: Towards an architecture for the distributed management and analysis of large scientific datasets
  10. A and V

Their papers