Cost-Effective Content Delivery Networks Using Clouds and Nano Data Centers

Kurniawan, Ikhsan Putra; Febiansyah, Hidayat; Kwon, Jin Baek

doi:10.1007/978-3-642-41671-2_53

Cited by 7 publications

(12 citation statements)

References 7 publications

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“…For content delivery, a number of replication servers can be installer around the world to minimize latency with respect to geographical location [18]. NDCs allow saving considerable energy and still maintaining required scalability.…”

Section: B Ndcs and Overlay Networkmentioning

confidence: 99%

“…computing and storage services [1,18]. Such systems have been studied in the context of content distribution systems like video on demand, for example.…”

Section: Introductionmentioning

confidence: 99%

“…Relaying data may be facilitated by a NDC in such cases. This paper addresses the following problem: Given a set of geographically distributed sites with peer nodes with (a) their probability of using the system, (b) their inability to listen to incoming connections from other peers and (c) the requirement of a supporting content distribution system, the aim is to ensure optimal locations of NDCs with respect to geographic routing principles [16,18]. The Round Trip Time (RTT) between any two peers must be minimized subject to node capability constraints.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Latency-adaptive positioning of Nano Data Centers for peer-to-peer communication based on clustering

Maiti

Kist

Maxwell

2015

2015 IEEE International Conference on Communication Workshop (ICCW)

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A network topology based on Nano Data Centers (NDC) for an interactive collaborative system is discussed in this paper. The system operates over several nodes that differ in endpoint security and network access. Some nodes are prevented from initiating connections directly and require intermediate nodes to accept requests from third parties. The nodes also constitute a supporting content distribution network. In an interactive system, latency is an important factor in overall system performance. In the context of this paper, users are scattered over a large geographic area and connect to the system at their own convenience. Thus it is necessary to find optimal positions for NDC nodes such that relaying leads to minimal increases in response time for all users. In this paper, an extended hierarchical clustering algorithm is used to create a set of NDC locations across a geographic region. It generates a set of relay locations that can be used in P2P communication.

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Section: B Ndcs and Overlay Networkmentioning

confidence: 99%

“…computing and storage services [1,18]. Such systems have been studied in the context of content distribution systems like video on demand, for example.…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Latency-adaptive positioning of Nano Data Centers for peer-to-peer communication based on clustering

Maiti

Kist

Maxwell

2015

2015 IEEE International Conference on Communication Workshop (ICCW)

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“…Another interesting line of research is the use of relatively stable peer resources to build nano data centers [5], micro clouds, community clouds, or edge clouds [9]. For example, in [5] all the home appliances are controlled and managed centrally by the telecommunication provider.…”

Section: Related Fieldsmentioning

confidence: 99%

“…For example, in [5] all the home appliances are controlled and managed centrally by the telecommunication provider. In contrast, our vision of edge-centric computing systems is user-centric and the control comes from the edges towards the core, not the other way around.…”

Section: Related Fieldsmentioning

confidence: 99%

Edge-centric Computing

López

Montresor

Epema

et al. 2015

SIGCOMM Comput. Commun. Rev.

781

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In many aspects of human activity, there has been a continuous struggle between the forces of centralization and decentralization. Computing exhibits the same phenomenon; we have gone from mainframes to PCs and local networks in the past, and over the last decade we have seen a centralization and consolidation of services and applications in data centers and clouds. We position that a new shift is necessary. Technological advances such as powerful dedicated connection boxes deployed in most homes, high capacity mobile end-user devices and powerful wireless networks, along with growing user concerns about trust, privacy, and autonomy requires taking the control of computing applications, data, and services away from some central nodes (the "core") to the other logical extreme (the "edge") of the Internet. We also position that this development can help blurring the boundary between man and machine, and embrace social computing in which humans are part of the computation and decision making loop, resulting in a human-centered system design. We refer to this vision of human-centered edge-device based computing as Edge-centric Computing. We elaborate in this position paper on this vision and present the research challenges associated with its implementation.

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Placing it right!: optimizing energy, processing, and transport in Edge-Fog clouds

Mohan

Kangasharju

2018

Ann. Telecommun.

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Cost-Effective Content Delivery Networks Using Clouds and Nano Data Centers

Cited by 7 publications

References 7 publications

Latency-adaptive positioning of Nano Data Centers for peer-to-peer communication based on clustering

Latency-adaptive positioning of Nano Data Centers for peer-to-peer communication based on clustering

Edge-centric Computing

Placing it right!: optimizing energy, processing, and transport in Edge-Fog clouds

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