Scalable Graph Algorithms and Applications
A special issue of Algorithms (ISSN 1999-4893).
Deadline for manuscript submissions: closed (30 June 2021) | Viewed by 7987
Special Issue Editors
Interests: scalable algorithms; machine learning; combinatorial optimization; graph algorithms; algorithm engineering
Interests: algorithm engineering; graph algorithms; discrete optimization
Interests: theoretical computer science; combinatorial optimization; algorithm engineering; geometric and graph algorithms
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
We invite you to submit your latest research in the area of scalable graph algorithms to the Special Issue, “Scalable Graph Algorithms and Applications”. We solicit high-quality papers to address both algorithm design and algorithm engineering issues related to the processing of large graphs. We consider scalability in a broad sense: (i) for near linear-time graph algorithms such as those related to traversal and shortest-paths, scalability refers to algorithms that address issues of cache-efficiency, I/O-efficiency, GPU parallelism, shared memory parallelism, and distributed algorithms; (ii) for polynomial-time graph algorithms such as those related to matching, flow and centrality computation, scalability refers to the exact and approximate algorithms that scale to millions of nodes and edges; (iii) For NP-hard graph problems such as those related to subgraph pattern matching, scalability refers to the design and engineering of heuristics that are capable of dealing with graphs that have thousands of nodes and tens of thousands of edges. We also invite submissions related to applications of scalable graph algorithms in areas such as social network analysis, navigation systems and sustainable transportation, querying and mining knowledge graphs, semantic web, recommendation systems, financial and economic networks, network epidemic models, bioinformatics, and earth sciences applications.
Dr. Deepak Ajwani
Guest Editor
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Algorithms is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- Cache-efficient graph algorithms
- I/O-efficient graph algorithms
- Shared-memory multicore graph algorithms
- Distributed memory graph algorithms
- Graph algorithms for GPUs
- Streaming graph algorithms
- Randomized graph algorithms
- Approximate graph algorithms
- Dynamic graph algorithms
- Algorithms for large-scale network analytics
- Scalable graph mining
- Efficient heuristics for NP-hard graph problems
- Models for real-world graphs
- Generation of large graph instances
- Simulations involving large graphs
- Applications of large graphs in social network analysis, navigation systems and sustainable transportation, querying and mining knowledge graphs, etc.
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