A User Driven Dynamic Circuit Network Implementation

Guok, Chin; Robertson, David W.; Chaniotakis, Evangelos; Thompson, Megan M.; Johnston, William; Tierney, Brian

doi:10.1109/glocomw.2008.ecp.14

Cited by 41 publications

(28 citation statements)

References 11 publications

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“…For comparison, we use our own Green Energy Aware Routing algorithm (GEAR), which minimizes the amount of brown energy used [2]. GEAR is a powerand performance-constrained dynamic routing algorithm that performs online path computation and constructs virtual circuits [21]. We use different price models to calculate the network lease costs including, fixed bandwidth (BW) cost, where cost does not increase with utilization; and linear BW cost increase, which assumes that cost of operation and revenue are proportional to usage.…”

Section: Backbone Network Modelmentioning

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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Section: Backbone Network Modelmentioning

confidence: 99%

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

Akşanlı

Venkatesh

Monga

et al. 2016

Computational Sustainability

View full text Add to dashboard Cite

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“…Different aspects of OSCARS are described in detail in [13]. The strategy of path computation used in OSCARS is as follows: first, based on the parameters specified by the users in the virtual circuit reservation request, some vertices and edges that do not match the received parameters are removed from the base topology graph; then, Dijkstra's shortest path algorithm is run on the modified topology graph, trying to find out the path used to provision the virtual circuit.…”

Section: Related Workmentioning

confidence: 99%

“…Compared with the above similar algorithms, both FECT and FESD have additional new functions to deal with BRRs with different priorities and have the ability to process BRRs accumulated in a time interval to improve the overall scheduling efficiency. FECT and FESD combine these solution space narrowing down techniques in FRA, trimming process introduced in [13] and couples of additional new trimming techniques. Such optimization techniques attempt to shrink the order and size of the scheduling network topology and scale down the solution space, which is quantified as the number of timewindows in this paper, as much as possible when trying to schedule a BRR.…”

Section: Related Workmentioning

confidence: 99%

Fast and Efficient Bandwidth Reservation Algorithms for Dynamic Network Provisioning

Zuo

Zhu

2013

J Netw Syst Manage

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Large-scale collaborative e-science requires fast and reliable data transfer with guaranteed performance, which is made possible by reserving bandwidth as needed in advance in high-performance networks. In scientific applications, users typically know the data size, the data available time, and the deadline to finish the data transfer, and they always wish to achieve the earliest possible finish time or the minimum time duration for the data transfer. On the other hand, the network service provider wishes to serve as many users' bandwidth reservation requests (BRRs) as possible to maximize the network resource utilization without compromising their deadlines. Such multi-objective requirements and high system throughput call for a fast and efficient bandwidth reservation strategy that can quickly discover various reservation options in a time-varying network environment. We propose two bandwidth reservation algorithms with rigorous optimality proofs to compute the reservation options with the earliest completion time and with the shortest duration for a local BRR. Our algorithms aim to achieve the balanced resource utilization for the network system. Extensive simulation results demonstrate the superiority of the proposed algorithms in terms of execution time, success ratio, success ratio of BRRs with different priorities and searched complexity of BRRs in comparison with similar scheduling algorithms.

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“…Most advanced research networks have developed and deployed advance reservation based network resource provisioning systems for big data transfers to support various application areas, for example, DRAGON, OSCARS, DRAC, AutoBHAN, EnLIGHTened, PHOSPHOROUS, and G-Lambda, [1][2][3][4][5][6][7] . They have their own framework for only network resources or for both grid and network services.…”

Section: ⅰ Introductionmentioning

confidence: 99%

Advance Reservation Framework with Protection Management for Virtual Circuit Services

Lim¹,

Lee²,

Cha³

2013

The Journal of Korean Institute of Communications and Informati

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The most representative research network in Korea, KREONET, has developed DynamicKL, an advance reservation based Network Service Agent (NSA) for user driven virtual circuit services. DynamicKL provides reservation, provisioning, release, termination, and inquiry web services for network resources by using an open standard network service interface (NSI), as well as web services for network resources by using a GUI interface. In addition, it has the RICE interface to support a protection management function per VC for virtual circuits and reservations. In this article, a protection management per VC for provisioned VCs and reservations is addressed in the DynamicKL framework, as a contribution to the VC protection management issue, which results in more manageable and reliable VC services compared to other advance reservation frameworks. An administrator can detect successful or unsuccessful VC protections in the event of a primary link failure and successful or unsuccessful VC retrievals after a primary link repair, by using RICE.

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A User Driven Dynamic Circuit Network Implementation

Cited by 41 publications

References 11 publications

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

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

Fast and Efficient Bandwidth Reservation Algorithms for Dynamic Network Provisioning

Advance Reservation Framework with Protection Management for Virtual Circuit Services

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