Abstract
Disaster evacuation assigns bulk endangered data to geographically distributed datacenters out of disaster zone within acceptable duration. However, previous works overlooked the bandwidth allocation proportion problem and multi-path routing problem for multiple concurrent evacuation transfers (especially with shared links). Therefore they could not guarantee full utilization of network transmission capability in disaster evacuation. In this paper, with flexible traffic scheduling in the Software Defined Network scenarios, we propose a new optimal bandwidth proportion allocation strategy for concurrent evacuation transfers. To maximize disaster evacuation capability, we formulate the bandwidth allocation problem as a new Bandwidth-Proportion-Constrained Multi-Commodity Flow (BPC-MCF) problem. To obtain optimal solution for practical networks of large scale, we propose a Bandwidth-Proportion-Aware Ant Colony Optimization (BPA-ACO) algorithm to achieve maximum evacuation flow matching data amount proportion of concurrent evacuation transfers. We introduce available evacuation capability, bandwidth proportion offset and link sharing degree to guide optimal solution searching. We adjust bandwidth proportion by rearranging flows in shared links and alternate paths. Through extensive simulations we demonstrate that our algorithm has better performance with less total evacuation time and higher network utilization.
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Acknowledgment
The study is supported by the National Natural Science Foundation of China (NSFC No. 61672323), the Natural Science Foundation of Shandong Province (Grant No. ZR2015FM008, BS2015DX003), and the Fundamental Research Funds of Shandong University (Grant No. 2017JC043).
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Li, X., Wang, H., Yi, S., Yao, X., Zhu, F., Zhai, L. (2017). Optimizing Concurrent Evacuation Transfers for Geo-Distributed Datacenters in SDN. In: Ibrahim, S., Choo, KK., Yan, Z., Pedrycz, W. (eds) Algorithms and Architectures for Parallel Processing. ICA3PP 2017. Lecture Notes in Computer Science(), vol 10393. Springer, Cham. https://doi.org/10.1007/978-3-319-65482-9_7
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DOI: https://doi.org/10.1007/978-3-319-65482-9_7
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