QoS Management in SOAs. Service-Oriented Architectures

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1 QoS Management in Service-Oriented Architectures PhD progress presentation Gaetano F. Anastasi Scuola Superiore Sant Anna, Pisa, Italy Madrid, November 2010

2 1 Introduction 2 SOA for Industrial Automation 3 SOA for Virtualized Environment 4 SOA in Pervasive Computing 5 Conclusion

3 Motivations (1/2) Service-Oriented Architectures Approach for building systems: distributed configurable flexible open inter-operable

4 Motivations (2/2) Real-time need in SOA many apps are inherently real-time multimedia, interactive, financial, etc. time-bound applications execution time affects the perceived Quality-of-Service (QoS) SOA must cope with QoS constraints specified in Service Level Agreements

5 My Research Mission Obtain systems capable of guaranteeing QoS during service provisioning Idea Manage resources by using techniques borrowed from the real-time domain

6 Current contribution 1 Configuration and management of low-level service guarantees 2 Enforcement of guarantees through real-time scheduling 3 Exploring the effectiveness of these techniques in: Industrial Automation Service Oriented Infrastructures Pervasive Computing

7 1 Introduction 2 SOA for Industrial Automation 3 SOA for Virtualized Environment 4 SOA in Pervasive Computing 5 Conclusion

8 Industrial Automation (1/5) Paradigm shift for reducing time-to-market open standards autonomous components plug-and-play Issue Such new technologies lacks built-in QoS and real-time support

9 Industrial Automation (2/5) Problem statement functionalities as services self-configuration diagnostic commercial-off-the-shelf components standard OS standard protocols (HTTP, SOAP) provide real-time support

10 Industrial Automation (3/5) Contribution design a SOA for real-time service provisioning QoS configuration through SLA contracts (WS-Agreement) admission control mod reserve, resource reservation module for the Apache2 web server

11 Industrial Automation (4/5) mod reserve catch service requests attach services to reservations exploiting AQuoSA API Resource Reservation by CBS (Constant Bandwidth Server) CBS guarantee execution for exactly Q time units each P

12 Industrial Automation (5/5) Experimental Validation Without proper scheduling is not possible to ensure predictable QoS levels

13 1 Introduction 2 SOA for Industrial Automation 3 SOA for Virtualized Environment 4 SOA in Pervasive Computing 5 Conclusion

14 OS Virtualization (1/5) Distributed computing spread thanks to high speed Internet new software design (e.g. SOA) new business model emerging more resources provided remotely (computation, communication, storage) service providers & resource providers

15 OS Virtualization (2/5) Virtualization Allows a system to host other guest systems: scaling providers costs security and dependability transparent support of applications Issues interferences of multiple Virtual Machines on the same node uncontrollable behavior of services

16 OS Virtualization (3/5) Contribution Provide a proper scheduling mechanism (hierarchical real-time scheduling) RR inter-vm scheduling Each VM k is scheduled through a reservation RSV k = (Q k, P k ) guarantee execution for exactly Q time units each P

17 OS Virtualization (4/5) Experimental testbed VM a and VM b running Apache2 VM a serving 10 concurrent clients VM b serving 20 concurrent clients Two kind of services: - req1: 1000x1000 image rotation - req2: 2000x2000 image rotation

18 OS Virtualization (5/5) Experimental results Attaching reservation to VMs and requests inside: VM a by RSV a = (3, 10); VM b by RSV b = (6, 10) req1 by RSV = (4, 100); req2 by RSV = (5, 100) Response times for req2 inside VM b NO RSV RSV: VM RSV: VM + Req (s) (s) (s) avg max std.dev Flattened response times

19 1 Introduction 2 SOA for Industrial Automation 3 SOA for Virtualized Environment 4 SOA in Pervasive Computing 5 Conclusion

20 Pervasive computing (1/5) Pros low cost, standing (e.g. WSNs) satisfy the desperate need for data of enterprises Cons scarcity of energy/computing low-level programming difficult to integrate in informative systems

21 Pervasive computing (2/5) Issues for integration enabling QoS control device lifetime, sampling rate, monitored areas hide low-level details programming interface, embedded OS, etc. SOA proposed approach for seamless integration building flexible and inter-operable systems

22 Pervasive computing (3/5) Contribution service-oriented abstraction of WSNs QoS specification and management allowing applications to reconfigure and maintain the network during its lifetime middleware independence of the underlying WSN technology

23 Pervasive computing (4/5) Case study 3 apps consume a measurement service network star topology feat. TinyOS 2.0 Goal The middleware is capable of dynamic reconfiguration

24 Pervasive computing (5/5) 25.5 agr1-loc1 agr3-loc temperature (C) time (s) Varying of temperature on loc1 App Sampling (s) Location 1 30 loc1, loc loc loc1 applications independent of each other transparent support of requs

25 1 Introduction 2 SOA for Industrial Automation 3 SOA for Virtualized Environment 4 SOA in Pervasive Computing 5 Conclusion

26 Conclusion Under the hood you need proper scheduling and resource management

27 On-going & Future work QoSDB store & load QoS statistics resource and application modes estimation of QoS parameters for new application modes Future work QoS management for Multimedia Services

28

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