Graph partitioning is a theoretical subject with applications in many areas, principally:
numerical analysis, programs mapping onto parallel architectures, image segmentation …

This authoritative handbook reveals the connections between bioinspired techniques and
the development of solutions to problems that arise in diverse problem domains. It provides …

In this paper we generalize and improve the multiscale organization of graphs by
introducing a new measure that quantifies the “closeness” between two nodes. The …

Graphs are used for modeling a large spectrum of data from the web, to social connections
between individuals, to concept maps and ontologies. As the number and complexities of …

Given a graph and an integer k, the goal of the graph partitioning problem is to find a
partition of the vertex set in k classes, while minimizing the number of cut edges, and …

Graph partitioning is a well-known optimization problem of great interest in theoretical and
applied studies. Since the 1990s, many multilevel schemes have been introduced as a …

Graph processing has become an integral part of big data analytics. With the ever increasing
size of the graphs, one needs to partition them into smaller clusters, which can be managed …

Balanced graph partitioning is an NP-complete problem with a wide range of applications.
These applications include many large-scale distributed problems, including the optimal …

Many real-world engineering problems can be expressed in terms of partial differential
equations and solved by using the finite-element method, which is usually parallelised, ie …

Applying ICT devices to WDS makes it possible to introduce also the new concept of Smart
WAter Network (SWAN), as a key Smart City subsystem, improving the traditional …