Content Placement (CP) problem in Cloud-based Content Delivery Networks(CCDNs) leverage resource elasticity to build cost effective CDNs thatguarantee QoS. In this paper, we present our novel CP model, which optimallyplaces content on surrogates in the cloud, to achieve (a) minimum cost ofleasing storage and bandwidth resources for data coming into and going out ofthe cloud zones and regions, (b) guarantee Service Level Agreement (SLA), and(c) minimize degree of QoS violations. The CP problem is NP-Hard, hence wedesign a unique push-based heuristic, called Weighted Social Network Analysis(W-SNA) for CCDN providers. W-SNA is based on Betweeness Centrality (BC) fromSNA and prioritizes surrogates based on their relationship to the othervertices in the network graph. To achieve our unique objectives, we furtherprioritize surrogates based on weights derived from storage cost and contentrequests. We compare our heuristic to current state of the art Greedy Site (GS)and purely Social Network Analysis (SNA) heuristics, which are relevant to ourwork. 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 itskind, which is timely and gives a fundamental pre-allocation scheme for futureonline and dynamic resource provision for CCDNs.
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