Decentralized algorithms are becoming ever more prevalent in almost all real-world applications that are either data intensive, computation intensive or both. This thesis presents a few decentralized solutions for large-scale (i) data dissemination, (ii) graph partitioning, and (iii) data disambiguation. All these solutions are based on gossip, a light weight peer-to-peer data exchange protocol, and thus, appropriate for execution in a distributed environment. For efficient data dissemination, we make use of the publish/subscribe communication model and provide two distributed solutions, one for topicbased and one for content-based subscriptions, named Vitis and Vinifera respectively. These systems propagate large quantities of data to i...
Gossiping and broadcasting are two problems of information dissemination. In gossiping, every point ...
This paper analyzes the adoption of unstructured P2P overlay networks to build publish-subscribe sys...
none1noThis paper analyzes a class of dissemination algorithms for the discovery of distributed cont...
Community detection, also named as graph clustering, is essential to various graph analysis applicat...
Information dissemination is a fundamental problem in parallel and distributed computing. In its sim...
International audienceGossip-based protocols are now acknowledged as a sound basis to implement coll...
In this position paper we argue for exploiting the synergy between gossip-based algorithms and struc...
Abstract. This paper presents a locality-based dissemination graph algorithm for scalable reliable b...
Abstract—In this paper, we consider the clustering of very large datasets distributed over a network...
Gossip-based communication protocols are appealing in large-scale distributed applications such as i...
Gossip-based communication protocols are appealing in large-scale distributed applications such as i...
Extracting knowledge by performing computations on graphs is becoming increasingly challenging as gr...
Graph partitioning is an essential task for scalable data management and analysis. The current parti...
We consider the problem of clustering graph nodes over large-scale dynamic graphs, such as citation ...
Abstract Identifying clusters is an important aspect of analyzing large datasets. Clustering algorit...
Gossiping and broadcasting are two problems of information dissemination. In gossiping, every point ...
This paper analyzes the adoption of unstructured P2P overlay networks to build publish-subscribe sys...
none1noThis paper analyzes a class of dissemination algorithms for the discovery of distributed cont...
Community detection, also named as graph clustering, is essential to various graph analysis applicat...
Information dissemination is a fundamental problem in parallel and distributed computing. In its sim...
International audienceGossip-based protocols are now acknowledged as a sound basis to implement coll...
In this position paper we argue for exploiting the synergy between gossip-based algorithms and struc...
Abstract. This paper presents a locality-based dissemination graph algorithm for scalable reliable b...
Abstract—In this paper, we consider the clustering of very large datasets distributed over a network...
Gossip-based communication protocols are appealing in large-scale distributed applications such as i...
Gossip-based communication protocols are appealing in large-scale distributed applications such as i...
Extracting knowledge by performing computations on graphs is becoming increasingly challenging as gr...
Graph partitioning is an essential task for scalable data management and analysis. The current parti...
We consider the problem of clustering graph nodes over large-scale dynamic graphs, such as citation ...
Abstract Identifying clusters is an important aspect of analyzing large datasets. Clustering algorit...
Gossiping and broadcasting are two problems of information dissemination. In gossiping, every point ...
This paper analyzes the adoption of unstructured P2P overlay networks to build publish-subscribe sys...
none1noThis paper analyzes a class of dissemination algorithms for the discovery of distributed cont...