Bandwidth on demand for inter-data center communication

Mahimkar, Ajay; Chiu, Angela; Doverspike, Robert; Feuer, M.D.; Magill, Peter; Mavrogiorgis, Emmanuil; Pastor, Jorge; Woodward, S.L.; Yates, Jennifer

doi:10.1145/2070562.2070586

Cited by 93 publications

(56 citation statements)

References 26 publications

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“…In 2010, GRIPhoN (globally reconfigurable intelligent photonic network) was proposed as an advanced ROADM architecture able to improve the performance and operational flexibility of optical transport networks [16], and was then extensively studied to provide bandwidth on demand for inter-DC connectivity through backbone optical networks [17]. Moreover, optical circuit switching has been proposed to combine both inter-and intra-DC connectivity for long-lived flows [18].…”

Section: B Inter-datacenter Assumptions / Requirementsmentioning

confidence: 99%

Traffic Allocation Strategies in WSS-Based Dynamic Optical Networks

Shakeri¹,

Garrich

Bravalheri³

et al. 2017

J. Opt. Commun. Netw.

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-Elastic optical networking (EON) is a viable solution to meet future dynamic capacity requirements of Internet Service Provider (ISP) and inter-datacenter networks. At the core of EON, Wavelength Selective Switches (WSSs) are applied to individually route optical circuits, while assigning an arbitrary bandwidth to each circuit. Critically, the WSS control scheme and configuration time may delay the creation time of each circuit in the network. In this paper, we first detail the WSS-based optical data-plane implementation of a metropolitan network test-bed. Then, we review an SDN application, designed to enable dynamic and fast circuit setup. Subsequently, we introduce a WSS logical model that captures the WSS time-sequence and is used to estimate the circuit setup response time. Then, we present two batch service policies that aim to reduce the circuit-setup response time by bundling multiple WSS reconfiguration steps into a single SDN command. Resulting performance gains are estimated through simulation.

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Section: B Inter-datacenter Assumptions / Requirementsmentioning

confidence: 99%

Traffic Allocation Strategies in WSS-Based Dynamic Optical Networks

Shakeri¹,

Garrich

Bravalheri³

et al. 2017

J. Opt. Commun. Netw.

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“…The authors in [17] study the cost savings obtained by inter-connecting the DCs belonging to a federation. In [18], the authors propose an architecture to provide dynamic bandwidth on demand over WDM; in case of failure, dynamic restoration is used. A specific module running on top of ABNO, named as Application Service Orchestrator (ASO), was first proposed in [19] to coordinate DC and network elastically aiming at improving resource utilization and save costs.…”

Section: 1mentioning

confidence: 99%

ABNO-driven content distribution in the telecom cloud

Gifre

Tornatore

Contreras

et al. 2017

Optical Switching and Networking

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Abstract-As current sustained traffic growth is expected to strain capacity of today's metro network, novel content distribution architectures where contents are placed closer to the users are being investigated. In that regard, telecom operators can deploy datacenters (DCs) in metro areas, thus reducing the impact of the traffic going from users to DCs. However, effective solutions to distribute contents to those metro DCs and to synchronize contents among them need to be investigated. In this paper, a hierarchical content distribution architecture for the telecom cloud is investigated: core DCs placed in geographically distributed locations, are interconnected through permanent "per content provider" (CP) virtual network topology (CP-VNT); additionally, metro DCs are placed close to users, and need also to be interconnected with the core DCs. CP's data is replicated in the core DCs through the CP-VNT, while metro-to-core (M2C) anycast connections are established periodically for metro DCs to synchronize contents. Since failures in the interconnection network might disconnect the CP-VNTs, in this paper recovery mechanisms are proposed to reconnect topologies and anycast connections. Topology creation, anycast provisioning and recovery problems are first formally stated and modelled as Integer Linear Programs (ILP). Solving these models, however, becomes impractical for realsized scenarios, so heuristic algorithms are also proposed. Exhaustive simulation results show that the investigated architecture provides significant improvements in both supported traffic and restorability compared to the case of a single core DC. Workflows to implement the algorithms within the Applications-based Network Operations (ABNO) architecture and extensions for PCEP are proposed. Finally, the architecture is experimentally validated in our ABNObased iONE test-bed.Keywords: Datacenter interconnection, Optical networks, Content distribution. INTRODUCTIONCloud-based contents are experiencing an exponential growth in users and data volume. In [1], Cisco forecast a yearly global growth of 23% in datacenter (DC)-to-user traffic, 29% in DC-to-DC traffic, and 22% in the intra-DC traffic. Likewise, Alcatel-Lucent highlights that metro traffic will increase 560% by 2017 mainly driven by IP video and cloud traffic [2], growing two times faster than core network traffic. They conclude that placing contents in DCs closer to users can result in a 41% bandwidth reduction in the metro networks. The resulting distributed DC architecture should come together with the extension of the core network functionalities towards the metro, as proposed in [3].Robust telecom infrastructures are needed to minimize the impact of failures on the services [4]; this is especially relevant in the case of video distribution. In fact, prolonged service outages and disruptions have negatively impacted the confidence of important companies toward cloud environments. Telecom operators are in a vantage position to capitalize on highly-reliable cloud services since they o...

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“…However, as WAN usage increases, network owners [15], [5] offer Bandwidth-on-Demand services, especially for r-datacenter applications [1]. Additionally, the WAN may take up to 40% of the total IT energy cost, and is expected to continue growing as demand for distributed data processing continues to rise [17] and as the server hardware becomes more energy efficient [11].…”

Section: Introductionmentioning

confidence: 99%

Renewable Energy Prediction for Improved Utilization and Efficiency in Datacenters and Backbone Networks

Akşanlı

Venkatesh

Monga

et al. 2016

Computational Sustainability

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Datacenters are one of the important global energy consumers and carbon producers. However, their tight service level requirements prevent easy integration with highly variable renewable energy sources. Short-term green energy prediction can mitigate this variability. In this work, we first explore the existing short-term solar and wind energy prediction methods, and then leverage prediction to allocate and migrate workloads across geographically distributed datacenters to reduce brown energy consumption costs. Unlike previous works, we also study the impact of wide area networks (WAN) on datacenters, and investigate the use of green energy prediction to power WANs. Finally, we present two different studies connecting datacenters and WANs: the case where datacenter operators own and manage their WAN and the case where datacenters lease networks from WAN providers. The results show that prediction enables up to 90% green energy utilization, a 3x improvement over the existing methods. The cost minimization algorithm reduces expenses by up to 16% and increases performance by 27% when migrating workloads across datacenters. Furthermore, the savings increase up to 30% compared with no migration when servers are made energy-proportional. Finally, in the case of leasing the WAN, energy proportionality in routers can in-crease the profit of network providers by 1.6x.

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Bandwidth on demand for inter-data center communication

Cited by 93 publications

References 26 publications

Traffic Allocation Strategies in WSS-Based Dynamic Optical Networks

Traffic Allocation Strategies in WSS-Based Dynamic Optical Networks

ABNO-driven content distribution in the telecom cloud

Renewable Energy Prediction for Improved Utilization and Efficiency in Datacenters and Backbone Networks

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