Y. Tock, N. Naaman, A. Harpaz, and G. Gershinsky (Israel)
Multicasting algorithms, multicast mapping, data dissemi
nation, receiver interest, hierarchical clustering, optimiza
A large-scale data dissemination application is character
ized by a large number of information ﬂows and infor
mation consumers. Consumers are interested in different,
yet overlapping, subsets of the ﬂows. Multicast is used to
deliver subsets of the ﬂows to subsets of the consumers.
Since multicast groups are a limited resource, each con
sumer must ﬁlter out a large number of unneeded ﬂows.
We alleviate the end-node ﬁltering load by using hierarchi
cal clustering of ﬂows to transport-layer sessions, and clus
tering of sessions to network-layer multicast groups. This
scheme allows for hierarchical ﬁltering of ﬂows at the re
ceivers. We formulate a cost function that models and em
phasizes the ﬁltering process, and propose algorithms for
the solution of the hierarchical mapping problem. Perfor
mance evaluation indicates a signiﬁcant reduction of end
node ﬁltering cost compared to a non-hierarchic approach.