DocumentCode :
2784972
Title :
Placement in Clouds for Application-Level Latency Requirements
Author :
Chang, Fangzhe ; Viswanathan, Ramesh ; Wood, Tom L.
fYear :
2012
fDate :
24-29 June 2012
Firstpage :
327
Lastpage :
335
Abstract :
CPU and device virtualization technology allows applications to be hosted on cloud platforms; some of the resulting benefits are lower cost and greater elasticity. In such cloud hosted applications, some components reside on the cloud while others, such as end users and components tied to physical devices, are located outside the cloud. Many applications, e.g., telecom services, have stringent latency requirements in terms of within how much time certain procedures must be completed. The application latency is strongly determined by the locations of all the interacting components that are both within and outside the cloud. In this paper, we study the problem of determining the optimal placement of the application components in the cloud so that the latency requirements of the application can be met. We present a precise formulation of the placement problem which includes a specification of the cloud platform, and collective latency expressions for application-level latency requirements. We show that Message Sequence Charts (MSCs), a widely-used mechanism for describing the execution of application procedures, can be naturally translated into our formalism of collective latency expressions. We present placement algorithms that exploit the Euclidean triangular inequality property of network topologies: (a) an exact algorithm for determining the most optimal placement but which has a worst-case exponential running time, and (b) an algorithm for determining a close to-optimal placement that has a fast polynomial running time. Additionally, we present an exact technique for partitioning a placement problem into smaller sub problems so that greater efficiency and accuracy can be achieved. We evaluate the performance of the algorithms on a representative telecom application --- a distributed deployment of the LTE Mobility Management Entity (MME). Our evaluation results show that our approximate algorithm can outperform a random placement by up to 49% for finding a success- ul placement.
Keywords :
Long Term Evolution; cloud computing; formal specification; mobility management (mobile radio); telecommunication computing; virtualisation; CPU; LTE mobility management entity; MME; MSC; application component optimal placement; application-level latency requirements; approximate algorithm; cloud placement; cloud platform specification; collective latency expressions; device virtualization technology; message sequence charts; network topology Euclidean triangular inequality property; representative telecom application; Additives; Approximation algorithms; Blades; Delay; Mobile handsets; Partitioning algorithms; Servers;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Cloud Computing (CLOUD), 2012 IEEE 5th International Conference on
Conference_Location :
Honolulu, HI
ISSN :
2159-6182
Print_ISBN :
978-1-4673-2892-0
Type :
conf
DOI :
10.1109/CLOUD.2012.91
Filename :
6253522
Link To Document :
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