NoG - Nagging on Grids

NoG is a problem solving environment for distributed combinatorial optimization using the nagging technique. Nagging is a distributed search paradigm originally devised by Dr. Alberto Maria Segre based on the NICE (Network Infrastructure to Support Combinatorial Search). Grid computing represents different resource models and constraints from the NICE. To make nagging work on Grids, NoG creates novel overlay middleware models to manage Grid resource and distributed task communication. In the NoG, we also aim to further understand the nature of nagging and extend nagging techniques to a broader context in which distributed combinatorial optimization methods can scale well to large-scale distributed systems. Currently, a TSP problem is used as a case study.

People: Yan Liu, Shaowen Wang, Alberto Maria Segre