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  • 1.
    Borghol, Youmna
    et al.
    NICTA, Australia.
    Mitra, Siddharth
    Indian Institute Technology Delhi.
    Ardon, Sebastien
    NICTA, Australia.
    Carlsson, Niklas
    Linköpings universitet, Tekniska högskolan. Linköpings universitet, Institutionen för datavetenskap, Databas och informationsteknik.
    Eager, Derek
    University of Saskatchewan.
    Mahanti, Anirban
    NICTA, Australia.
    Characterizing and modelling popularity of user-generated videos2011Ingår i: Performance evaluation (Print), ISSN 0166-5316, E-ISSN 1872-745X, Vol. 68, nr 11, s. 1037-1055Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    This paper develops a framework for studying the popularity dynamics of user-generated videos, presents a characterization of the popularity dynamics, and proposes a model that captures the key properties of these dynamics. We illustrate the biases that may be introduced in the analysis for some choices of the sampling technique used for collecting data; however, sampling from recently-uploaded videos provides a dataset that is seemingly unbiased. Using a dataset that tracks the views to a sample of recently-uploaded YouTube videos over the first eight months of their lifetime, we study the popularity dynamics. We find that the relative popularities of the videos within our dataset are highly non-stationary, owing primarily to large differences in the required time since upload until peak popularity is finally achieved, and secondly to popularity oscillation. We propose a model that can accurately capture the popularity dynamics of collections of recently-uploaded videos as they age, including key measures such as hot set churn statistics, and the evolution of the viewing rate and total views distributions over time.

  • 2.
    Carlsson, Niklas
    et al.
    Linköpings universitet, Institutionen för datavetenskap, Databas och informationsteknik. Linköpings universitet, Tekniska fakulteten.
    Eager, Derek
    Univ Saskatchewan, Canada.
    Worst-case bounds and optimized cache on Mth request cache insertion policies under elastic conditions2018Ingår i: Performance evaluation (Print), ISSN 0166-5316, E-ISSN 1872-745X, Vol. 127, s. 70-92Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Cloud services and other shared third-party infrastructures allow individual content providers to easily scale their services based on current resource demands. In this paper, we consider an individual content provider that wants to minimize its delivery costs under the assumptions that the storage and bandwidth resources it requires are elastic, the content provider only pays for the resources that it consumes, and costs are proportional to the resource usage. Within this context, we (i) derive worst-case bounds for the optimal cost and competitive cost ratios of different classes of cache on Mth request cache insertion policies, (ii) derive explicit average cost expressions and bounds under arbitrary inter request distributions, (iii) derive explicit average cost expressions and bounds for short tailed (deterministic, Erlang, and exponential) and heavy-tailed (Pareto) inter-request distributions, and (iv) present numeric and trace-based evaluations that reveal insights into the relative cost performance of the policies. Our results show that a window-based cache on 2nd request policy using a single threshold optimized to minimize worst-case costs provides good average performance across the different distributions and the full parameter ranges of each considered distribution, making it an attractive choice for a wide range of practical conditions where request rates of individual file objects typically are not known and can change quickly. (C) 2018 Elsevier B.V. All rights reserved.

  • 3.
    Carlsson, Niklas
    et al.
    Linköpings universitet, Institutionen för datavetenskap, Databas och informationsteknik. Linköpings universitet, Tekniska högskolan.
    Eager, Derek
    University of Saskatchewan, Canada.
    Gopinathan, Ajay
    Linköpings universitet, Institutionen för datavetenskap, Databas och informationsteknik. Linköpings universitet, Tekniska högskolan.
    Li, Zongpeng
    University of Calgary, Canada.
    Caching and optimized request routing in cloud-based content delivery systems2014Ingår i: Performance evaluation (Print), ISSN 0166-5316, E-ISSN 1872-745X, Vol. 79, s. 38-55Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Geographically distributed cloud platforms enable an attractive approach to large-scale content delivery. Storage at various sites can be dynamically acquired from (and released back to) the cloud provider so as to support content caching, according to the current demands for the content from the different geographic regions.  When storage is sufficiently expensive that not all content should be cached at all sites, two issues must be addressed: how should requests for content be routed to the cloud provider sites, and what policy should be used for caching content using the elastic storage resources obtained from the cloud provider.  Existing approaches are typically designed for non-elastic storage and little is known about the optimal policies when minimizing the delivery costs for distributed elastic storage.

    In this paper, we propose an approach in which elastic storage resources are exploited using a simple dynamic caching policy, while request routing is updated periodically according to the solution of an optimization model.  Use of pull-based dynamic caching, rather than push-based placement, provides robustness to unpredicted changes in request rates.  We show that this robustness is provided at low cost \textendash{} even with fixed request rates, use of the dynamic caching policy typically yields content delivery cost within 10\% of that with the optimal static placement.  We compare request routing according to our optimization model to simpler baseline routing policies, and find that the baseline policies can yield greatly increased delivery cost relative to optimized routing.  Finally, we present a lower-cost approximate solution algorithm for our routing optimization problem that yields content delivery cost within 2.5\% of the optimal solution.

  • 4.
    Carlsson, Niklas
    et al.
    University of Saskatchewan.
    Eager, Derek L.
    University of Saskatchewan.
    Vernon, Mary K.
    University of Wisconsin-Madison.
    Multicast Protocols for Scalable On-demand Download2006Ingår i: Performance evaluation (Print), ISSN 0166-5316, E-ISSN 1872-745X, ISSN 0166-5316, Vol. 63, nr 9/10, s. 864-891Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Previous scalable protocols for downloading large, popular files from a single server include batching and cyclic multicast. With batching, clients wait to begin receiving a requested file until the beginning of its next multicast transmission, which collectively serves all of the waiting clients that have accumulated up to that point. With cyclic multicast, the file data is cyclically transmitted on a multicast channel. Clients can begin listening to the channel at an arbitrary point in time, and continue listening until all of the file data has been received.This paper first develops lower hounds on the average and maximum client delay for completely downloading a file, as functions of the average server bandwidth used to serve requests for that file, for systems with homogeneous clients. The results show that neither cyclic multicast nor batching consistently yields performance close to optimal. New hybrid download protocols are proposed that achieve within 15% of the optimal maximum delay and 20% of the optimal average delay in homogeneous systems.For heterogeneous systems in which clients have widely varying achievable reception rates, an additional design question concerns the use of high rate transmissions, which can decrease delay for clients that can receive at such rates, in addition to low rate transmissions that can be received by all clients. A new scalable download protocol for such systems is proposed, and its performance is compared to that of alternative protocols as well as to new lower bounds on maximum client delay. The new protocol achieves within 25% of the optimal maximum client delay in all scenarios considered.

  • 5.
    Carlsson, Niklas
    et al.
    Linköpings universitet, Institutionen för datavetenskap, Databas och informationsteknik. Linköpings universitet, Tekniska högskolan.
    Williamson, Carey
    University of Calgary, Canada.
    Hirt, Andreas
    University of Calgary, Canada.
    Jacobson, Micheal
    University of Calgary, Canada.
    Performance Modeling of Anonymity Protocols2012Ingår i: Performance evaluation (Print), ISSN 0166-5316, E-ISSN 1872-745X, Vol. 69, nr 12, s. 643-661Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Anonymous network communication protocols provide privacy for Internet-based communication. In this paper, we focus on the performance and scalability of anonymityprotocols. In particular, we develop performance models for two anonymityprotocols from the prior literature (Buses and Taxis), as well as our own newly proposed protocol (Motorcycles). Using a combination of experimental implementation, simulation, and analysis, we show that: (1) the message latency of the Buses protocol is O(N2), scaling quadratically with the number of participants; (2) the message latency of the Taxis protocol is O(N), scaling linearly with the number of participants; and (3) the message latency of the Motorcycles protocol is O(log2N), scaling logarithmically with the number of participants. Motorcycles can provide scalable anonymous network communication, without compromising the strength of anonymity provided by Buses or Taxis.

  • 6.
    Mahanti, Aniket
    et al.
    University of Calgary.
    Williamson, Carey
    University of Calgary.
    Carlsson, Niklas
    Linköpings universitet, Tekniska högskolan. Linköpings universitet, Institutionen för datavetenskap, Databas och informationsteknik.
    Arlitt, Martin
    University of Calgary.
    Mahanti, Anirban
    NICTA, Australia .
    Characterizing the file hosting ecosystem: A view from the edge2011Ingår i: Performance evaluation (Print), ISSN 0166-5316, E-ISSN 1872-745X, Vol. 68, nr 11, s. 1085-1102Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    We present a comprehensive, longitudinal characterization study of the file hosting ecosystem using HTTP traces collected from a large campus network over a one-year period. We performed detailed multi-level analysis of the usage behavior, infrastructure properties, content characteristics, and user-perceived performance of the top five services in terms of traffic volume, namely RapidShare, Megaupload, zSHARE, MediaFire, and Hotfile. We carefully devised methods to identify user clickstreams in the HIP traces, including the identification of free and premium user instances, as well as the identification of content that is split into multiple pieces and downloaded using multiple transactions. Throughout this characterization, we compare and contrast these services with each other as well as with peer-to-peer file sharing and other media sharing services.

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