Bandwidth turbulence control based on flow community structure in the Internet

Abstract

Bursty flows vary rapidly in short period of time, and cause fierce bandwidth turbulence in the Internet. In this letter, we model the flow bandwidth turbulence process by constructing a flow interaction network (FIN network), with nodes representing flows and edges denoting bandwidth interactions among them. To restrain the bandwidth turbulence in FIN networks, an immune control strategy based on flow community structure is proposed. Flows in community boundary positions are immunized to cut off the inter-community turbulence spreading. By applying this control strategy in the first- and the second-level flow communities separately, 97.2% flows can effectively avoid bandwidth variations by immunizing 21% flows, and the average bandwidth variation degree reaches near zero. To achieve a similar result, about 70%–90% immune flows are needed with targeted control strategy based on flow degrees and random control strategy. Moreover, simulation results showed that the control effect of the proposed strategy improves significantly if the immune flow number is relatively smaller in each control step.

Dynamic behavior analysis of an internet flow interaction model under cascading failures

“…A small initial shock, such as a flow burst or the breakdown of an internet router can trigger cascading failure. Understanding the response of internet flow to the occurrence of failure is essential, because it directly affects the quality of internet service [27,28]. The number of internet flows is enormous, and its relationship with network components (routers and links) is complicated; thus, analyzing flow behavior is extremely difficult.…”