A Survey on Content Placement Algorithms for Cloud-Based Content Delivery Networks <s> 2) MINING CONTENT <s> In recent years, technical challenges are emerging on how to efficiently distribute the rapid growing user-generated contents (UGCs) with long-tailed nature. To address this issue, we have previously proposed cloud centric media network (CCMN) for cost-efficient UGCs delivery. In this paper, we further study the content placement problem in CCMN. Our objective is to minimize the monetary cost incurred by using cloud resources to orchestrate an elastic and global content delivery network (CDN) service. In particular, this objective is achieved via a two-step method. First, for a single content, we map it into a k-center problem, and find a logarithmic relationship between the mean hop distance from users to contents, and the reciprocal of replica number. Second, for multiple contents, we formulate a convex optimization with storage and bandwidth capacity constraints, which can be solved by our proposed algorithm. Finally, we verify the algorithm based on real-world traces collected from a popular video website in China. Our numerical results suggest that, the optimal number of replica for each content follows a power law in respect to its popularity, under feasible storage and bandwidth constraints, in a set of deployed backbone networks. <s> BIB001 </s> A Survey on Content Placement Algorithms for Cloud-Based Content Delivery Networks <s> 2) MINING CONTENT <s> 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. <s> BIB002 </s> A Survey on Content Placement Algorithms for Cloud-Based Content Delivery Networks <s> 2) MINING CONTENT <s> A significantly large proportion of HTTP traffic results from bandwidth-intensive multimedia content circulating through online social networks (OSNs). With multimedia content providers, such as YouTube, often relying on content delivery network (CDN) infrastructures, the pursuit lies in exploiting the user activity extracted from OSNs to improve the content prefetching mechanism. Aiming to reduce bandwidth usage, we incorporated a dynamic mechanism to CDNsim, a stand-alone CDN traffic simulator. This mechanism is based on a dynamic policy that takes patterns of information transmission over OSNs into account. Herein, we demonstrate that the performance of CDNs can be improved, and the cost of copying to surrogate servers is taken into consideration. <s> BIB003
Future research challenges in CP for CCDNs must include the objective of leveraging analytics that will extract fundamental characteristics of content, enhancing the efficiency of CP algorithms. Researchers have leveraged content characteristics, such as correlation, popularity BIB001 , type (static or dynamic), refresh rates, temporal and spatial locality of endusers  , social network relationships BIB002 , etc. that can be leveraged to pre-fetch content by CP algorithms. Pre-fetching closely related content BIB003 or incorporating complex content dimensions increases content availability and reduces content access times. However, CCDNs cost model poses a challenge. Therefore, it is crucial to tackle CP problems with the objective of striking a balance between incorporating content relationships and the cost of leasing resources for content storage and bandwidth. Another research objective can be to scrutinize the effect of content personalization  on CP algorithms for CCDNs. Furthermore, recent advances in ubiquitous computing pose a challenge in designing CP algorithms for CCDNs such that the content of different resolutions are stored  .