Generic event‐based monitoring and adaptation methodology for heterogeneous distributed systems

The Cloud computing paradigm provides the basis for a class of platforms and applications that face novel challenges related to multi‐tenancy, adaptivity, and elasticity. To account for service delivery guarantees in the face of ever increasing levels of heterogeneity, scale, and dynamism, service provisioning in the Cloud has raised the demand for systematic and flexible approaches to monitoring and adaptation of applications. In this paper, we tackle this issue and present a framework for efficient runtime management of Cloud environments and distributed heterogeneous systems in general. A novel domain‐specific language termed MONINA is introduced that allows to define integrated monitoring and adaptation functionality for controlling such systems. We propose a mechanism for optimal deployment of the defined control operators onto available computing resources. Deployment is based on solving a quadratic programming problem, which aims at achieving minimized reaction times, low overhead, and scalable monitoring and adaptation. The monitoring infrastructure is based on a distributed messaging middleware, providing high level of decoupling and allowing new monitoring nodes to join the system dynamically. We provide a detailed formalization of the problem domain, discuss architectural details, highlight the implementation of the developed prototype, and put our work into perspective with existing work in the field. Copyright © 2014 John Wiley & Sons, Ltd.

[1]  Calton Pu,et al.  Generating Adaptation Policies for Multi-tier Applications in Consolidated Server Environments , 2008, 2008 International Conference on Autonomic Computing.

[2]  Margo I. Seltzer,et al.  Network-Aware Operator Placement for Stream-Processing Systems , 2006, 22nd International Conference on Data Engineering (ICDE'06).

[3]  Schahram Dustdar,et al.  Towards Identifying Root Causes of Faults in Service-Based Applications , 2012, 2012 IEEE 31st Symposium on Reliable Distributed Systems.

[4]  Randy H. Katz,et al.  A view of cloud computing , 2010, CACM.

[5]  Setsuo Ohsuga,et al.  INTERNATIONAL CONFERENCE ON VERY LARGE DATA BASES , 1977 .

[6]  Ying Xing,et al.  Dynamic load distribution in the Borealis stream processor , 2005, 21st International Conference on Data Engineering (ICDE'05).

[7]  Ying Li,et al.  Placement Strategies for Internet-Scale Data Stream Systems , 2008, IEEE Internet Computing.

[8]  Peter R. Pietzuch,et al.  Distributed event-based systems , 2006 .

[9]  Florian Rosenberg,et al.  Testing Idempotence for Infrastructure as Code , 2013, Middleware.

[10]  Schahram Dustdar,et al.  Winds of Change: From Vendor Lock-In to the Meta Cloud , 2013, IEEE Internet Computing.

[11]  Dawn M. Tilbury,et al.  Event-Condition-Action Systems for Reconfigurable Logic Control , 2007, IEEE Transactions on Automation Science and Engineering.

[12]  Oliver Kramer,et al.  Goal distance estimation for automated planning using neural networks and support vector machines , 2013, Natural Computing.

[13]  Kurt Rothermel,et al.  Efficient and Distributed Rule Placement in Heavy Constraint-Driven Event Systems , 2011, 2011 IEEE International Conference on High Performance Computing and Communications.

[14]  Schahram Dustdar,et al.  Cost-Based Optimization of Service Compositions , 2013, IEEE Transactions on Services Computing.

[15]  Dejan S. Milojicic,et al.  SLA Decomposition: Translating Service Level Objectives to System Level Thresholds , 2007, Fourth International Conference on Autonomic Computing (ICAC'07).

[16]  Steve Vinoski,et al.  Advanced Message Queuing Protocol , 2006, IEEE Internet Computing.

[17]  Ying Xing,et al.  Providing resiliency to load variations in distributed stream processing , 2006, VLDB.

[18]  George Spanoudakis,et al.  Establishing and Monitoring SLAs in Complex Service Based Systems , 2009, 2009 IEEE International Conference on Web Services.

[19]  Yushun Fan,et al.  Complex event processing in enterprise information systems based on RFID , 2007, Enterp. Inf. Syst..

[20]  Benjamin Satzger,et al.  Using Automated Planning for Trusted Self-organising Organic Computing Systems , 2008, ATC.

[21]  Schahram Dustdar,et al.  Specification and Deployment of Distributed Monitoring and Adaptation Infrastructures , 2012, ICSOC Workshops.

[22]  Schahram Dustdar,et al.  Non-intrusive policy optimization for dependable and adaptive service-oriented systems , 2012, SAC '12.

[23]  Katta G. Murty,et al.  Nonlinear Programming Theory and Algorithms , 2007, Technometrics.

[24]  Schahram Dustdar,et al.  Dynamic Migration of Processing Elements for Optimized Query Execution in Event-Based Systems , 2011, OTM Conferences.

[25]  Jennifer Widom,et al.  Operator placement for in-network stream query processing , 2005, PODS.

[26]  Vincenzo Grassi,et al.  Qos-driven runtime adaptation of service oriented architectures , 2009, ESEC/SIGSOFT FSE.