Toward Cost-Efficient Content Placement in Media Cloud: Modeling and Analysis

Jin, Yichao; Wen, Yonggang; Guan, Kyle

doi:10.1109/tmm.2016.2537199

Cited by 39 publications

(11 citation statements)

References 30 publications

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“…The ideal location search algorithm (Algorithm 1) computes the distance (w kl ) between nodes v k and v l (see lines [1][2][3][4][5]. In this context, our approach works in two phases.…”

Section: Algorithmsmentioning

confidence: 99%

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An eigenvalue‐based edge infrastructure for cloud‐based CDN

Sahoo

Turuk

2019

Int J Communication

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In today's dynamic video landscape, an end user needs services to be delivered to any devices anytime with less delay over the Internet. Now users' expectation has changed; they want faster time-to-market, cost reduction, and the ability to adjust according to the evolving requirements, which are a limit for the traditional server-based approach. The explosive growth of the internet multimedia application needs a new approach to content delivery to overcome the limitations of server-based techniques. Cloud-based content delivery networks (CCDNs) have recently started to emerge where contents are cached from the cloud storage and delivered through the distribution service to meet quality of services (QoS) of requested services. In this paper, we dealt with CCDN deployment problem and proposed a new eigenvalue-based edge infrastructure for a network service provider to serve the users with a variation on proximity interest concerning operational cost and user QoS satisfaction. The edge infrastructure designing is a two-step process: (a) ideal location search for placing edge server and (b) edge server placement and capacity provisioning. The performance of the proposed approach is appraised via modeling and simulation.Performance evaluation outcomes are exhibited to manifest the effectiveness and competitiveness of our approach when compared with existing algorithms.

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“…The ideal location search algorithm (Algorithm 1) computes the distance (w kl ) between nodes v k and v l (see lines [1][2][3][4][5]. In this context, our approach works in two phases.…”

Section: Algorithmsmentioning

confidence: 99%

“…Details of the first phase is discussed with the help of Algorithms 1 and 2. The ideal location search algorithm (Algorithm 1) computes the distance (w kl ) between nodes v k and v l (see lines [1][2][3][4][5]. Each edge in  between nodes v k and v l carries a nonnegative weight w kl ≥ 0 and if w kl = 0 nodes are not connected.…”

Section: Algorithmsmentioning

confidence: 99%

An eigenvalue‐based edge infrastructure for cloud‐based CDN

Sahoo

Turuk

2019

Int J Communication

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“…Besides byte transfer cost, Ref. [8] also considers storage cost when placing content to achieve a balance between content storage cost and byte transfer cost. (As intuition suggests, more content replicas (higher storage cost), if distributed properly across geographically located DCs, can reduce latency, thus reducing byte transfer cost.)…”

Section: Related Workmentioning

confidence: 99%

“…The path to be used while satisfying latency constraint can be preconfigured for different purposes such as energy saving, failure avoidance, etc. 8 We use Latency Island (LI) to model latency for both CF and CR. Given a pre-defined latency bound (Lth), a node's LI is defined as a set of nodes which can be reached by the current node via a path 1 no longer than Lth, shown as follows:…”

Section: A Latencymentioning

confidence: 99%

Content Fragmentation: A Redundancy Scheme to Save Energy in Cloud Networks

Tornatore

Martel

et al. 2018

IEEE Trans. on Green Commun. Netw.

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Due to rapid growth of content-based cloud services (e.g., video streaming), energy usage of cloud infrastructures, consisting of distributed Data Centers (DCs) interconnected by a highbandwidth long-distance network, keeps increasing. This energy usage could further increase due to requested content redundancy to ensure content-service resiliency. Typical content redundancy schemes are based on Content Replication (CR), i.e., each content is replicated in at least one secondary DC location, reachable in case of failure affecting the primary location, which induces at least 100% increase in storage energy consumption. To reduce storage energy overhead of CR, we investigate a new redundancy scheme, called Content Fragmentation (CF). CF exploits Reed-Solomon erasure code to fragment and encode content into blocks with less storage overhead (thus less storage energy usage) to guarantee content-service resiliency. But CF requires additional energy for content reconstruction and data transport in the core network. To determine which scheme is more energy efficient, we formulate, for both, the contentplacement problem using Mixed Integer Liner Program (MILP), with the objective to minimize energy consumption. Also, due to MILP's poor scalability, we propose a Meta-heuristic Content Placement and Routing Assignment algorithm (M-CPRA) for more efficient solutions. We observe the impact on energy usage of three main metrics, i.e., number of content requests (popularity), resiliency, and latency. Results from a realistic case study suggest that CF always consumes less energy than CR given the same resiliency requirement, and CF is particularly energy-efficient when stored contents are less popular and latency-tolerant.

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“…Among these solutions, infrastructure-based content delivery networks (CDNs) have proven effective [1,4]. But as load continues to grow, pressure to improve performance and reduce cost has led to experimentation with more sophisticated topologies [13,18].…”

Section: Introductionmentioning

confidence: 99%

CAPnet: A Defense Against Cache Accounting Attacks on Content Distribution Networks

Almashaqbeh

Kelley²,

Bishop

et al. 2019

2019 IEEE Conference on Communications and Network Security (CNS)

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Peer-assisted content distribution networks (CDNs) have emerged to improve performance and reduce deployment costs of traditional, infrastructure-based content delivery networks. This is done by employing peer-to-peer data transfers to supplement the resources of the network infrastructure. However, these hybrid systems are vulnerable to accounting attacks in which the peers, or caches, collude with clients in order to report that content was transferred when it was not. This is a particular issue in systems that incentivize cache participation, because malicious caches may collect rewards from the content publishers operating the CDN without doing any useful work. In this paper, we introduce CAPnet, the first technique that lets untrusted caches join a peer-assisted CDN while providing a bound on the effectiveness of accounting attacks. At its heart is a lightweight cache accountability puzzle that clients must solve before caches are given credit. This puzzle requires colocating the data a client has requested, so its solution confirms that the content (or at least an amount of data within a pre-configured bound) has actually been retrieved. We analyze the security and overhead of our scheme in realistic scenarios. The results show that a modest client machine using a single core can solve puzzles at a rate sufficient to simultaneously watch dozens of 1080p videos. The technique is designed to be even more scalable on the server side. In our experiments, one core of a single low-end machine is able to generate puzzles for 4.26 Tbps of bandwidth -enabling 870,000 clients to concurrently view the same 1080p video. This demonstrates that our scheme can ensure cache accountability without degrading system productivity.

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Toward Cost-Efficient Content Placement in Media Cloud: Modeling and Analysis

Cited by 39 publications

References 30 publications

An eigenvalue‐based edge infrastructure for cloud‐based CDN

An eigenvalue‐based edge infrastructure for cloud‐based CDN

Content Fragmentation: A Redundancy Scheme to Save Energy in Cloud Networks

CAPnet: A Defense Against Cache Accounting Attacks on Content Distribution Networks

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