Article ID Journal Published Year Pages File Type
6883063 Computer Networks 2014 42 Pages PDF
Abstract
Recent studies on the practice of shaping subscribers' traffic by Internet service providers (ISPs) give a new insight into the actual performance of broadband access networks at a packet level. Unlike metro and backbone networks, however, access networks directly interface with end-users, so it is important to base the study and design of access networks on the behaviors of and the actual performance perceived by end-users. In this paper we study the effect of ISP traffic shaping using traffic models based on user behaviors and application/session-layer metrics providing quantifiable measures of user-perceived performance for HTTP, FTP, and streaming video traffic. To compare the user-perceived performance of shaped traffic flows with those of unshaped ones in an integrated way, we use a multivariate non-inferiority testing procedure. We first investigate the effect of the token generation rate and the token bucket size of a token bucket filter (TBF) on user-perceived performance at a subscriber level with a single subscriber. Then we investigate their effect at an access level where shaped traffic flows from multiple subscribers interact with one another in a common shared access network. The simulation results show that for a given token generation rate, a larger token bucket - i.e., up to 100 MB and 1 GB for access line rates of 100 Mbit/s and 1 Gbit/s, respectively - provides better user-perceived performance at both subscriber and access levels. It is also shown that the loose burst control resulting from the large token bucket - again up to 100 MB for access line rate of 100 Mbit/s - does not negatively affect user-perceived performance with multiple subscribers even in the presence of non-conformant subscribers; with a much larger token bucket (e.g., size of 10 GB), however, the negative effect of non-conformant subscribers on the user-perceived performance of conformant subscribers becomes clearly visible because the impact of token bucket size and that of token generation rate are virtually indistinguishable in this case.
Related Topics
Physical Sciences and Engineering Computer Science Computer Networks and Communications
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