  Content Placement (CP) problem in Cloud-based Content Delivery Networks
(CCDNs) leverage resource elasticity to build cost effective CDNs that
guarantee QoS. In this paper, we present our novel CP model, which optimally
places content on surrogates in the cloud, to achieve (a) minimum cost of
leasing storage and bandwidth resources for data coming into and going out of
the cloud zones and regions, (b) guarantee Service Level Agreement (SLA), and
(c) minimize degree of QoS violations. The CP problem is NP-Hard, hence we
design a unique push-based heuristic, called Weighted Social Network Analysis
(W-SNA) for CCDN providers. W-SNA is based on Betweeness Centrality (BC) from
SNA and prioritizes surrogates based on their relationship to the other
vertices in the network graph. To achieve our unique objectives, we further
prioritize surrogates based on weights derived from storage cost and content
requests. We compare our heuristic to current state of the art Greedy Site (GS)
and purely Social Network Analysis (SNA) heuristics, which are relevant to our
work. We show that W-SNA outperforms GS and SNA in minimizing cost and QoS.
Moreover, W-SNA guarantees SLA but also minimizes the degree of QoS violations.
To the best of our knowledge, this is the first model and heuristic of its
kind, which is timely and gives a fundamental pre-allocation scheme for future
online and dynamic resource provision for CCDNs.
