Self-* and Algorithmic aspects of
Networked Distributed Systems

The SANDS (Self-* and Algorithmic aspects of Networked Distributed Systems) research group, led by Asst. Prof. Anwitaman Datta, is a small distributed grouping of people at NTU Singapore working on large-scale distributed systems. Some of our members come from the Parallel and Distributed Computing Center (PDCC) while others come from the Center for Advanced Information Systems (CAIS).

We believe that the 21st century knowledge based society will continue to be driven by large-scale networked distributed systems which are self-organizing and adaptive to their environment, and will be strongly coupled to the social bonds and activities it facilitates and serves. We are interested in large-scale networked distributed information systems like peer-to-peer systems and social & collaboration networks, self-organization and algorithmic issues of these systems and networks and their scalability, resilience, adaptivity, security and performance under dynamic and wide-spectrum of environments. Specifically, our works span the following aspects:

Systems research

Our primary focus is to design and deploy scalable distributed and peer-to-peer information systems. We are particularly interested in data management, reliability and security issues in such systems.

Algorithms

Our systems research is driven by the study and use of distributed and nature inspired algorithms, including randomized, epidemic and swarm ones.

Self-* properties

In order to build scalable and robust decentralized systems, it is essential to understand (or algorithmically design) emergent phenomena like self-organization, stabilization, healing and optimization. We use analytical models and large-scale simulations to identify (or exploit) networked distributed systems' structural properties, time-evolution, causal and cyclic (feedback) relations.

Social networks and informatics

The internet has over the decades changed the way the society interacts and works. The boundaries of the society and the web have turned further amorphous with the advent of Web 2.0 sites and online social networking services. Sociological studies are thus an essential ingredient in understanding modern networked distributed systems. Our work in this realm include social network mining, trust and reputation mechanisms, collaboration communities, information propagation and visualization techniques for semantic social networks.