國立虎尾科技大學 |

Analytical frameworks to evaluate performance in both traditional and elastic optical networks.

紀錄類型:	書目-語言資料,手稿 : Monograph/item
正題名/作者:	Analytical frameworks to evaluate performance in both traditional and elastic optical networks./
作者:	Yan, Shuyi.
面頁冊數:	1 online resource (157 pages)
附註:	Source: Dissertation Abstracts International, Volume: 78-03(E), Section: B.
標題:	Electrical engineering. -
電子資源:	click for full text (PQDT)
ISBN:	9781369079593

Analytical frameworks to evaluate performance in both traditional and elastic optical networks.
Yan, Shuyi.

Analytical frameworks to evaluate performance in both traditional and elastic optical networks. - 1 online resource (157 pages)

Source: Dissertation Abstracts International, Volume: 78-03(E), Section: B.

Thesis (Ph.D.)--The University of Texas at Dallas, 2016.

Includes bibliographical references

With the provisioning of network equipment becoming increasingly challenging due to the large number of application types that must be supported at once, it is generally expected that cloud based applications are going to experience improved end-to-end performance assurance while maintaining a competitive cost of service. Most applications must make use of various types of resources, including network bandwidth and server CPU cycles, among others. An application request may be blocked when one or more of the resource types that are required to achieve the desired QoS cannot be reserved due to their shortage.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2018

Mode of access: World Wide Web

ISBN: 9781369079593Subjects--Topical Terms:

596380
Electrical engineering.
Index Terms--Genre/Form:

554714
Electronic books.

Analytical frameworks to evaluate performance in both traditional and elastic optical networks.
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245 1 0 $a Analytical frameworks to evaluate performance in both traditional and elastic optical networks.
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300 $a 1 online resource (157 pages)
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500 $a Source: Dissertation Abstracts International, Volume: 78-03(E), Section: B.
500 $a Advisers: Andrea Fumagalli; Marco Tacca.
502 $a Thesis (Ph.D.)--The University of Texas at Dallas, 2016.
504 $a Includes bibliographical references
520 $a With the provisioning of network equipment becoming increasingly challenging due to the large number of application types that must be supported at once, it is generally expected that cloud based applications are going to experience improved end-to-end performance assurance while maintaining a competitive cost of service. Most applications must make use of various types of resources, including network bandwidth and server CPU cycles, among others. An application request may be blocked when one or more of the resource types that are required to achieve the desired QoS cannot be reserved due to their shortage.
520 $a Elastic Optical Networks (EONs) enable optical circuits to be assigned distinct numbers of spectrum slices. Individual circuits can then be assigned an optimal number of slices to best match their target transmission rates. A well-known drawback of EONs is spectrum fragmentation and its resulting uneven blocking probability, which circuit requests experience when the available spectrum slices in the fiber are insufficient or not contiguous. Capturing this spectrum fragmentation problem analytically is a challenging problem. Not surprisingly, most of the existing studies at this time mainly use simulation-based techniques to quantify blocking probability in EONs.
520 $a This dissertation proposes a Markov Chain (MC) model first to efficiently and accurately estimate the blocking probability caused by the multi-application and multi-resource (MA-MR) constraint. The strength of the model is its scalability and ability to account for hundreds of application types concurrently sharing multiple pools of distinct resources. Then a Steady State Probability (SSP) policy which is built upon this analytical MC model and a Network State (NS) policy are considered and proposed for joint allocation of network link and data center resources in the presence of dynamic application requests. The SSP policy is based on pre-computed probability to select data center and network resources and the NS policy is based on the knowledge of the network and data center state. An algorithm for optimally computing the probabilities based on the SSP policy is presented. Obtained simulation results demonstrate and numerically assess the trade-off between the system performance in terms of blocking probability and the signaling overhead.
520 $a In order to quantify blocking probability theoretically in EONs, two Markov Chain (MC) models are presented to characterize the fragmentation problem in a simplified scenario, i.e., only two types of circuit services are allowed over a single fiber link, which is mentioned as two-service spectrum-elastic optical fiber link. One is an approximation model which is more effective and easier to be implemented based on the fully-shared fiber spectrum and then it is extended to account for partially-shared fiber spectrum. The other is an accurate model which is remarkably accurate to capture the fragmentation. The initial analytical efforts are able to capture the non-monotonic behavior of the blocking probability in EONs. Two product form based on analytical models are finally presented for quantifying blocking probability in a two-service elastic fiber link effectively. There is a trade-off between the accuracy and the model complexity.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2018
538 $a Mode of access: World Wide Web
650 4 $a Electrical engineering. $3 596380
655 7 $a Electronic books. $2 local $3 554714
690 $a 0544
710 2 $a ProQuest Information and Learning Co. $3 1178819
710 2 $a The University of Texas at Dallas. $b Electrical Engineering. $3 1181534
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10152802 $z click for full text (PQDT)