Path computation in a network is dependent on the network’s processes and resource usage pattern. While distributed traffic control methods improve the scalability of a system, their topology and link state conditions may influence the sub-optimal path computation. Herein, we present Pathfinder, an application-aware distributed path computation model. The proposed model framework can improve path computation functions through software-defined network controls. In the paper, we first analyse the key issues in distributed path computation functions and then present Pathfinder’s system architecture, followed by its design principles and orchestration environment. Furthermore, we evaluate our system’s performance by comparing it with FreeFlow and Prune-Dijk techniques. Our results demonstrate that Pathfinder outperforms these two techniques and delivers significant improvement in the system’s resource utilisation behaviour.

Hai Jin, Aaqif Afzaal Abbasi, Song Wu (2016). Pathfinder: Application-Aware Distributed Path Computation in Clouds. INTERNATIONAL JOURNAL OF PARALLEL PROGRAMMING.

Pathfinder: Application-Aware Distributed Path Computation in Clouds

Aaqif Afzaal Abbasi
;
2016-01-01

Abstract

Path computation in a network is dependent on the network’s processes and resource usage pattern. While distributed traffic control methods improve the scalability of a system, their topology and link state conditions may influence the sub-optimal path computation. Herein, we present Pathfinder, an application-aware distributed path computation model. The proposed model framework can improve path computation functions through software-defined network controls. In the paper, we first analyse the key issues in distributed path computation functions and then present Pathfinder’s system architecture, followed by its design principles and orchestration environment. Furthermore, we evaluate our system’s performance by comparing it with FreeFlow and Prune-Dijk techniques. Our results demonstrate that Pathfinder outperforms these two techniques and delivers significant improvement in the system’s resource utilisation behaviour.
2016
Hai Jin, Aaqif Afzaal Abbasi, Song Wu (2016). Pathfinder: Application-Aware Distributed Path Computation in Clouds. INTERNATIONAL JOURNAL OF PARALLEL PROGRAMMING.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10447/641604
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