### Abstract

Balanced graph partitioning is a well known NP-complete problem with a wide range of applications. These applications include many large-scale distributed problems including the optimal storage of large sets of graph-structured data over several hosts-A key problem in today's Cloud infrastructure. However, in very large-scale distributed scenarios, state-of-the-Art algorithms are not directly applicable, because they typically involve frequent global operations over the entire graph. In this paper, we propose a fully distributed algorithm, called JA-BE-JA, that uses local search and simulated annealing techniques for graph partitioning. The algorithm is massively parallel: there is no central coordination, each node is processed independently, and only the direct neighbors of the node, and a small subset of random nodes in the graph need to be known locally. Strict synchronization is not required. These features allow JA-BE-JA to be easily adapted to any distributed graph-processing system from data centers to fully distributed networks. We perform a thorough experimental analysis, which shows that the minimal edge-cut value achieved by JA-BE-JA is comparable to state-of-the-Art centralized algorithms such as METIS. In particular, on large social networks JA-BEJA outperforms METIS, which makes JA-BE-JA-A bottom-up, self-organizing algorithm-A highly competitive practical solution for graph partitioning.

Original language | English |
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Title of host publication | International Conference on Self-Adaptive and Self-Organizing Systems, SASO |

Pages | 51-60 |

Number of pages | 10 |

DOIs | |

Publication status | Published - 2013 |

Event | 2013 IEEE 7th International Conference on Self-Adaptive and Self-Organizing Systems, SASO 2013 - Philadelphia, PA, United States Duration: Sep 9 2013 → Sep 13 2013 |

### Other

Other | 2013 IEEE 7th International Conference on Self-Adaptive and Self-Organizing Systems, SASO 2013 |
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Country | United States |

City | Philadelphia, PA |

Period | 9/9/13 → 9/13/13 |

### Fingerprint

### Keywords

- distributed algorithm
- graph partitioning
- load balancing
- simulated annealing

### ASJC Scopus subject areas

- Computer Networks and Communications
- Information Systems
- Control and Systems Engineering

### Cite this

*International Conference on Self-Adaptive and Self-Organizing Systems, SASO*(pp. 51-60). [6676492] https://doi.org/10.1109/SASO.2013.13

**JA-BE-JA : A distributed algorithm for balanced graph Partitioning.** / Rahimian, Fatemeh; Payberah, Amir H.; Girdzijauskas, Sarunas; Jelasity, M.; Haridi, Seif.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

*International Conference on Self-Adaptive and Self-Organizing Systems, SASO.*, 6676492, pp. 51-60, 2013 IEEE 7th International Conference on Self-Adaptive and Self-Organizing Systems, SASO 2013, Philadelphia, PA, United States, 9/9/13. https://doi.org/10.1109/SASO.2013.13

}

TY - GEN

T1 - JA-BE-JA

T2 - A distributed algorithm for balanced graph Partitioning

AU - Rahimian, Fatemeh

AU - Payberah, Amir H.

AU - Girdzijauskas, Sarunas

AU - Jelasity, M.

AU - Haridi, Seif

PY - 2013

Y1 - 2013

N2 - Balanced graph partitioning is a well known NP-complete problem with a wide range of applications. These applications include many large-scale distributed problems including the optimal storage of large sets of graph-structured data over several hosts-A key problem in today's Cloud infrastructure. However, in very large-scale distributed scenarios, state-of-the-Art algorithms are not directly applicable, because they typically involve frequent global operations over the entire graph. In this paper, we propose a fully distributed algorithm, called JA-BE-JA, that uses local search and simulated annealing techniques for graph partitioning. The algorithm is massively parallel: there is no central coordination, each node is processed independently, and only the direct neighbors of the node, and a small subset of random nodes in the graph need to be known locally. Strict synchronization is not required. These features allow JA-BE-JA to be easily adapted to any distributed graph-processing system from data centers to fully distributed networks. We perform a thorough experimental analysis, which shows that the minimal edge-cut value achieved by JA-BE-JA is comparable to state-of-the-Art centralized algorithms such as METIS. In particular, on large social networks JA-BEJA outperforms METIS, which makes JA-BE-JA-A bottom-up, self-organizing algorithm-A highly competitive practical solution for graph partitioning.

AB - Balanced graph partitioning is a well known NP-complete problem with a wide range of applications. These applications include many large-scale distributed problems including the optimal storage of large sets of graph-structured data over several hosts-A key problem in today's Cloud infrastructure. However, in very large-scale distributed scenarios, state-of-the-Art algorithms are not directly applicable, because they typically involve frequent global operations over the entire graph. In this paper, we propose a fully distributed algorithm, called JA-BE-JA, that uses local search and simulated annealing techniques for graph partitioning. The algorithm is massively parallel: there is no central coordination, each node is processed independently, and only the direct neighbors of the node, and a small subset of random nodes in the graph need to be known locally. Strict synchronization is not required. These features allow JA-BE-JA to be easily adapted to any distributed graph-processing system from data centers to fully distributed networks. We perform a thorough experimental analysis, which shows that the minimal edge-cut value achieved by JA-BE-JA is comparable to state-of-the-Art centralized algorithms such as METIS. In particular, on large social networks JA-BEJA outperforms METIS, which makes JA-BE-JA-A bottom-up, self-organizing algorithm-A highly competitive practical solution for graph partitioning.

KW - distributed algorithm

KW - graph partitioning

KW - load balancing

KW - simulated annealing

UR - http://www.scopus.com/inward/record.url?scp=84893207551&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84893207551&partnerID=8YFLogxK

U2 - 10.1109/SASO.2013.13

DO - 10.1109/SASO.2013.13

M3 - Conference contribution

AN - SCOPUS:84893207551

SN - 9780769551296

SP - 51

EP - 60

BT - International Conference on Self-Adaptive and Self-Organizing Systems, SASO

ER -