A Survey on Content Placement Algorithms for Cloud-Based Content Delivery Networks <s> I. INTRODUCTION <s> Studies the cache performance in a remote caching architecture. The authors develop a set of distributed object replication policies that are designed to implement different optimization goals. Each site is responsible for local cache decisions, and modifies cache contents in response to decisions made by other sites. The authors use the optimal and greedy policies as upper and lower bounds, respectively, for performance in this environment. Critical system parameters are identified, and their effect on system performance studied. Performance of the distributed algorithms is found to be close to optimal, while that of the greedy algorithms is far from optimal. > <s> BIB001 </s> A Survey on Content Placement Algorithms for Cloud-Based Content Delivery Networks <s> I. INTRODUCTION <s> Content distribution networks (CDNs) using storage clouds have recently started to emerge. Compared to traditional CDNs, storage cloud-based CDNs have the advantage of cost effectively offering hosting services to Web content providers without owning infrastructure. However, existing work on replica placement in CDNs does not readily apply in the cloud. In this paper, we investigated the joint problem of building distribution paths and placing Web server replicas in cloud CDNs to minimize the cost incurred on the CDN providers while satisfying QoS requirements for user requests. We formulate the cost optimization problem with accurate cost models and QoS requirements and show that the monthly cost can be as low as 2.62 US Dollars for a small Web site. We develop a suite of offline, online-static and online-dynamic heuristic algorithms that take as input network topology and work load information such as user location and request rates. We then evaluate the heuristics via Web trace-based simulation, and show that our heuristics behave very close to optimal under various network conditions. <s> BIB002 </s> A Survey on Content Placement Algorithms for Cloud-Based Content Delivery Networks <s> I. INTRODUCTION <s> The ongoing growth of the Internet traffic is largely due to video delivery platforms as well as to online social networks (OSNs), where both popular and long-tail content, such as user-generated content (UGC), is shared. UGC is not dealt with effectively by the traditional approaches of Web caches and CDNs, as it has different demand patterns: it is more likely to be exchanged within a local geographic region and has a more even popularity distribution with fewer popular objects. In this work, we propose an ISP-friendly mechanism for enhancing content delivery exploiting social information extracted from OSNs, e.g. social relationships, common interests and locality of content exchange, as a new ‘source’ of meta-information to characterize and predict the end-user's behavior. The basic components of our mechanism called SEConD are: (i) a socially-aware proxy server inserted in a local geographic region (e.g. an AS) to orchestrate content distribution, (ii) socially-aware messaging overlays employed to trigger video prefetching, (iii) content-based P2P overlays employed to perform video streaming in each region, and (iv) a two-level caching strategy both in the socially-aware proxy server and in the OSN user's device (UD) whenever online. We also develop an evaluation framework to simulate the generation of content in the environment of an OSN, in order to evaluate our mechanism and compare it with other approaches in the literature. The evaluation results show that our mechanism improves users' Quality of Experience (QoE) and simultaneously, reduces traffic in potentially expensive inter-domain links, as well as the origin content server contribution. Thus, the SEConD mechanism can lead to benefits for all involved stakeholders, i.e., ISPs, OSNs, CDNs, and end-users. The proposed mechanism is widely applicable, since it is deployable by ISPs, OSNs, as well as CDNs distributing content on behalf of an OSN provider. <s> BIB003 </s> A Survey on Content Placement Algorithms for Cloud-Based Content Delivery Networks <s> I. INTRODUCTION <s> The increasing popularity of online social networks (OSNs) has been transforming the dissemination pattern of social video contents. We can utilize the social information propagation pattern to improve the efficiency of social video distribution. In this paper, motivated by the social community classification, we present a social video replication and user request dispatching mechanism in the cloud content delivery network architecture to reduce the system operational cost, while guaranteeing the averaged service latency. Specifically, we first present a community classification method that clusters social users with social relationships, close geolocations, and similar video watching interests into various communities. Then, we conduct a large-scale measurement on a real OSN system to study the diversities of social video propagation and the effectiveness of our communities on smoothing the diversity. Finally, we propose the community-based video replication and request dispatching strategy and formulate it as a constrained optimization problem. Based on a stochastic optimization framework, we derive an online solution and rigorously prove the optimality. We evaluate our algorithm on a real trace under realistic settings and demonstrate that our algorithm can reduce the monetary cost by 30% against traditional approaches with the same service latency. <s> BIB004 </s> A Survey on Content Placement Algorithms for Cloud-Based Content Delivery Networks <s> I. INTRODUCTION <s> Content Delivery Networks (CDNs) have gained immense popularity over the years. Replica server placement is a key design issue in CDNs. It entails placing replica servers at meticulous locations, such that cost is minimized and Quality of Service (QoS) of end-users is satisfied. Many replica server placement models have been proposed in the literature of traditional CDN. As the CDN architecture is evolving through the adoption of emerging paradigms, such as, cloud computing and Network Functions Virtualization (NFV), new algorithms are being proposed. In this paper, we present a comprehensive survey of replica server placement algorithms in traditional and emerging paradigm based CDNs. We categorize the algorithms and provide a summary of their characteristics. Besides, we identify requirements for an efficient replica server placement algorithm and perform a comparison in the light of the requirements. Finally, we discuss potential avenues for further research in replica server placement in CDNs. <s> BIB005
Recent advances in utility and cloud computing allow leasing resources, such as storage and bandwidth, to build Content Delivery Networks (CDNs) in the cloud BIB002 . There is a growing trend to deploy cloud-based CDNs (CCDNs) or to complement traditional CDN infrastructure with cloud-based delivery, management and analytic services. Undoubtedly, there is a move to CCDNs -which is evident by the increase in traffic across datacenters, attributed largely to CCDNs  . CCDNs alleviate major limitations of traditional CDNs. In comparison to CDNs, CCDNs have increased scalability [3] , flexibility [3] , elasticity [3] , reliability  and security against threats and attacks (e.g., denial of service)  and the orders of magnitude lower prices for content storage and delivery BIB002 . They reduce capital expenditure (CAPEX) and operational expenditure (OPEX) since the cost of deploying and maintaining infrastructure is significantly reduced. This makes CCDNs affordable for small and large-scale content providers, such as small businesses, government and educational organizations  . Moreover, CCDNs leverage the agility, scalability and elasticity of the cloud to dynamically provision resources to cater to changing demands BIB002 . There are various operational subsystems in a content delivery network, including content management and request routing  . The content management subsystem, illustrated in Fig. 1 , is responsible for selecting content to be replicated and the surrogate server(s) that will host replicated content for meeting end-user requests with quality of service (QoS). The request router has a set of policies for directing end-user requests to surrogate server(s) either for load-balancing or QoS. The content management subsystem (CMS) is vital for QoS. In the context of CCDNs, CMS decides where to place surrogate servers, what to replicate and which surrogate servers will hold replicas of content. Though these subsubsystems are tightly coupled, they are studied jointly BIB004 and independently. In this paper, we critically review the CP algorithms for CCDNs. In general terms, content placement algorithms are either pull or push, based on how surrogate servers get content from the origin server. Caching is a popular, pull-based technique employed to increase content availability and reduce content access latency. Push-based algorithms preemptively store content to meet an estimated demand. Cooperative and hybrid content placement algorithms retrieve missing content from the neighboring surrogates or employ push-and pull-based techniques, respectively. The efficiency of CP algorithms is dependent on costeffectively placing right content on the right surrogate servers. For QoS, it would mean placing popular content on servers in close proximity to end-users. This is easier said than done. Traditional CDNs were designed for static content  and as content evolved, the traditional CDNs evolved to meet the requirements. However, today's content, such as user-generated content and video (UGC/UGV), video-ondemand (VoD) and online gaming, is myriad, high-resolution and volatile due to social media sharing BIB003 . The petabytes of video traffic flowing through CDNs  show that the content catalogue is immense and it is non-trivial to identify and select popular content to store on the capacitated surrogate servers. Therefore, CP algorithms must accommodate for high resolution content, which is highly susceptible to unpredictability, while it provides low latency. The unpredictability is primarily due to end-user behavior and Online Social Networking (OSN) relationships, which influence the upload time and size of content and various other aspects of content access (e.g., temporal and spatial patterns). These inherent content characteristics and end-user relationships are not adequately supported by traditional CP algorithms BIB003 and they must be leveraged to design efficient CP algorithms for CCDNs. Furthermore, the underlying cost model of cloud computing poses a unique set of requirements for the CP algorithms impacting its efficiency, with respect to cost and QoS. For instance, in CCDNs, there is operational cost (e.g., leasing computing resources) that is incurred for the cooperation amongst surrogates across datacenters and for pulling content from the origin server(s). In contrast, in CDNs, there is no operational cost associated with pulling content from the origin or other surrogate servers. Instead, billing is proportional to the traffic delivered to end-users  . Readers interested in the evolution of CDN to CCDN and the interplay between the various actors are referred to BIB005 . The contributions of this survey are as follows: 1) We provide an overview of content and CCDN infrastructure, the two critical components that influence the content placement algorithms for CCDNs. Primarily, cost is determined by the underlying cost model of the CCDN infrastructure while the QoS delivered by CP is determined by where content is placed in CCDN. 2) We present critical and well-motivated design criteria for the CP algorithms for CCDNs based on practical implications from the content characteristics, end-user behavior, OSN relationships and the cloud model. 3) We review and thoroughly discuss the state-of-the-art CP algorithms for CCDNs and evaluate their effectiveness in the light of the design criteria. 4) We identify limitations and future research challenges in designing CP algorithms for CCDNs. This is a timely survey and, to the best of our knowledge, is the first of its kind. It provides a reference for future research in the area of CP for CCDNs. This survey is unique, since it enlightens researchers to design CP algorithms from a holistic perspective. It emphasizes the effect of the cloud cost model, content characteristics, end-user behavior and OSN relationships on CP algorithms. There are several surveys (  - BIB001 ) on content placement in traditional CDNs, but unlike this survey, they do not tackle the algorithms specific to CCDNs. There is also a survey  on CCDN architectures, but it does not discuss algorithms. Furthermore, there is a survey that addresses algorithms BIB005 for CCDNs. However, it explicitly focuses on surrogate server placement algorithms and does not tackle the algorithms for content placement. The rest of this paper is organized as follows: In Section II, we present the content placement problem and discuss the flow of content and problem solving approaches for CP. We also discuss various objectives and constraints in modeling CP problem and the parameter settings for solving it. Evidently, the key objectives of CP are competing: QoS versus cost. The delivered QoS is determined by the content placed in CCDN, while the cost is determined by the underlying cost model of the CCDN infrastructure. Therefore, we discuss content characteristics, end-user behavior and non-trivial OSN relationships that influence the efficiency of CP algorithms and derive critical design criteria that meet the requirements of today's content, in Sections III and IV, respectively. Furthermore, we give an overview of CCDN infrastructure, its elasticity and cost model and discuss the design criteria for CP algorithms to meet the requirements of the underlying CCDN infrastructure in Sections V and VI, respectively. In Section VII, we discuss the pull-and push-based CP algorithms for CCDNs and evaluate them against our well-motivated design criteria. Section VIII deals with practical implications and future research challenges in designing efficient CP algorithms. We conclude in Section IX with an overview of the survey and its contributions.