A Partial Store-and-Forward Scheduling Method for Inter-Datacenter Bulk Data Transfers

Abstract

Temporarily storing delay-tolerant data at peak hours and forwarding the data at off-peak hours, i.e., performing Store-and-Forward (SnF) using datacenter storage, can mitigate peak-hour congestion and exploit off-peak-hour bandwidth in inter-datacenter networks. Most prior studies considered a case where all nodes along their routing paths provided SnF options for the scheduling decision making. Intuitively, their solutions maximize the scheduling flexibility. However, the computational complexity of their solutions increases exponentially with the hop count. Meanwhile, SnF operations are generally performed on a portion of nodes rather than every node along the path. Thus, the considered case seems to be unnecessary in practice. In this paper, our studies reveal that desirable performance can be attained by involving a portion of nodes rather than all nodes along the path in the decision making. Thus, we propose a partial SnF scheduling method, which involves a portion of nodes in scheduling and introduces a network abstraction based on the involved nodes. Simulations demonstrate that the proposed method has lower complexity while achieving high performance.