Computing on the Edge: A Platform for Replicating Internet Applications

Rabinovich, Michael; Xiao, Zhen; Aggarwal, Amit

doi:10.1007/1-4020-2258-1_4

Cited by 63 publications

(65 citation statements)

References 9 publications

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“…Optimal solutions for specific topologies [9,10] and heuristics for more general topologies [6,13,15] have been proposed. Content placement for dynamic client demand has been studied only very recently [3,5,8,18,14]. In [3], the authors address the problem with the goal of minimizing the number of replicas deployed in a tree topology while meeting client QoS and server capacity constraints.…”

Section: Content Distribution Networkmentioning

confidence: 99%

“…A replication cost optimization models targeting system availability is proposed and formalized in [18]. Finally, Rabinovich et al [14] study the problem in the context of Internet application replication in general topologies. They propose a heuristic, called ACDN, for dynamic replica placement based on the observed past demand that aims at minimizing the network bandwidth requirements.…”

Section: Content Distribution Networkmentioning

confidence: 99%

“…In [3,5], the authors address the problem for specific network topologies. A heuristic for dynamic replication of Internet applications in more general topologies was recently proposed in [14]. Optimization models targeting system availability [18] and for providing lower bounds on the cost-effectiveness of different replica placement heuristics [8] have also been proposed.…”

Section: Introductionmentioning

confidence: 99%

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Dynamic Content Placement for Mobile Content Distribution Networks

Aioffi

Mateus

Almeida

et al. 2004

Web Content Caching and Distribution

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Abstract. As wireless networks increase in popularity, the development of efficient content distribution techniques to meet the growing and constantly changing client demand becomes a necessity. Previous content distribution network proposals, targeting mainly wired networks, are not adequate to handle the high temporal and spatial variability in client demand caused by user mobility. This paper proposes and analyzes a wireless dynamic content distribution network framework that replicates content in response to changes in client demand in order to reduce the total traffic over the network backbone. We propose a mathematical programming model to determine the offline optimal solution as well as an online algorithm based on demand forecasting. Using a previously developed mobility simulator, we show our new online algorithm outperforms the traditional centralized and distributed static placement approaches, reducing the total traffic over the network backbone in up to 78%, compared to the best previous approach analyzed.

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Section: Content Distribution Networkmentioning

confidence: 99%

Section: Content Distribution Networkmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Dynamic Content Placement for Mobile Content Distribution Networks

Aioffi

Mateus

Almeida

et al. 2004

Web Content Caching and Distribution

View full text Add to dashboard Cite

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“…[11] propose a evaluation what when Figure 1. Issues in a self-adaptive system CDN for serving applications.…”

Section: Related Workmentioning

confidence: 99%

“…In the future, we anticipate more acute problems when CDNs will be required to serve personalised content, dynamic content and applications. Providing such capability represents a unique opportunity for CDNs as it gives the latter a competitive advantage over client-side caching technologies [11].…”

Section: Introductionmentioning

confidence: 99%

Building a self-adaptive content distribution network

Jawaheer¹,

McCann²

2004

Proceedings. 15th International Workshop on Database and Expert Systems Applications, 2004.

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Providing ultra‐short latency to user‐centric 5G applications at the mobile network edge

Farris

Taleb

Flinck

2017

Trans Emerging Tel Tech

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Mobile Edge Computing (MEC) will play a key role in next-generation mobile networks to extend the range of supported delay-sensitive applications. Furthermore, an increasing attention is paid to provide user-centric services, to better address the strict requirements of novel immersive applications. In this scenario, MEC solutions need to efficiently cope with user mobility, which requires fast relocation of service instances to guarantee the desired Quality of Experience. However, service migration is still an open issue, especially for resource-constrained edge nodes interconnected by high-latency and low-bandwidth links. In this paper, by leveraging the potential of lightweight container-based virtualization techniques, we investigate a novel approach to support service provisioning in dynamic MEC environments. In particular, we present a framework where proactive service replication for stateless applications is exploited to drastically reduce the time of service migration between different cloudlets and to meet the latency requirements. The performance evaluation shows promising results of our approach with respect to classic reactive service migration. INTRODUCTIONSeveral classes of new applications are challenging the current network and cloud infrastructures. As illustrated in a recent report from International Telecommunication Union, 1 applications such as tactile internet, mobile gaming, and augmented reality are pushing new requirements, especially in terms of latency. To guarantee the desired Quality of Experience (QoE) for the end user, not only the network access delay, but also the cloud service processing should be performed within a few milliseconds. To achieve the 1 ms latency dream for the next-generation 5G cloud-enabled services, both network and cloud providers should jointly cooperate and investigate novel approaches. In this regard, academic and industrial research communities have focused on Mobile Edge Computing (MEC) solutions to exploit processing and storage capabilities at the edge of the network, as near as possible to the end user. 2,3 Indeed, the deployment of micro datacentres in the network access points, known as cloudlets, 4,5 can guarantee remarkable benefits of low latency interaction and scalability, by balancing the workload over the distributed edge infrastructure. Furthermore, bringing the cloudlet concept into the Internet of Things (IoT) scenario results in the definition of the so-called Fog Computing paradigm, which envisages a highly virtualized infrastructure composed of distributed edge nodes to monitor and analyse the most time-sensitive data generated by network connected devices. [6][7][8] In a MEC environment, a key challenge is represented by the user mobility, which could cause significant application degradation, even in small scenarios, as reported in a previous study.9,10 To guarantee service continuity and to meet the strict requirements of application latency, the MEC framework needs to properly cope with service migration between edge nodes. I...

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Computing on the Edge: A Platform for Replicating Internet Applications

Cited by 63 publications

References 9 publications

Dynamic Content Placement for Mobile Content Distribution Networks

Dynamic Content Placement for Mobile Content Distribution Networks

Building a self-adaptive content distribution network

Providing ultra‐short latency to user‐centric 5G applications at the mobile network edge

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