Analysis of user demand patterns and locality for YouTube traffic

Abstract

Video content, of which YouTube is a major part, constitutes a large share of residential Internet traffic. In this paper, we analyse the user demand patterns for YouTube in two metropolitan access networks with more than 1 million requests over three consecutive weeks in the first network and more than 600,000 requests over four consecutive weeks in the second network. In particular we examine the existence of “local interest communities”, i.e. the extent to which users living closer to each other tend to request the same content to a higher degree, and it is found that this applies to (i) the two networks themselves; (ii) regions within these networks (iii) households with regions and (iv) terminals within households. We also find that different types of access devices (PCs and handhelds) tend to form similar interest communities. It is also found that repeats are (i) “self-generating” in the sense that the more times a clip has been played, the higher the probability of playing it again, (ii) “long-lasting” in the sense that repeats can occur even after several days and (iii) “semiregular” in the sense that replays have a noticeable tendency to occur with relatively constant intervals. The implications of these findings are that the benefits from large groups of users in terms of caching gain may be exaggerated, since users are different depending on where they live and what equipment they use, and that high gains can be achieved in relatively small groups or even for individual users thanks to their relatively predictable behaviour.