Autonomic resource provisioning for software business processes

Pautasso, Cesare; Heinis, Thomas; Alonso, Gustavo

doi:10.1016/j.infsof.2006.08.010

Cited by 21 publications

(14 citation statements)

References 43 publications

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“…Pautasso et al propose in [9] an autonomic controller for the JOpera distributed service composition engine over a cluster. The autonomic controller starts and stops navigation (i.e.…”

Section: Related Workmentioning

confidence: 99%

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An Economic Approach for Scalable and Highly-Available Distributed Applications

Bonvin

Papaioannou

Aberer

2010

2010 IEEE 3rd International Conference on Cloud Computing

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Abstract-Service-oriented architecture (SOA) paradigm for orchestrating large-scale distributed applications offers significant cost savings by reusing existing services. However, the high irregularity of client requests and the distributed nature of the approach may deteriorate service response time and availability. Static replication of components in datacenters for accommodating load spikes requires proper resource planning and underutilizes the cloud infrastructure. Moreover, no service availability guarantees are offered in case of datacenter failures. In this paper, we propose a cost-efficient approach for dynamic and geographically-diverse replication of components in a cloud computing infrastructure that effectively adapts to load variations and offers service availability guarantees. In our virtual economy, components rent server resources and replicate, migrate or delete themselves according to selfoptimizing strategies. We experimentally prove that such an approach outperforms in response time even full replication of the components in all servers, while offering service availability guarantees under failures.

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“…Pautasso et al propose in [9] an autonomic controller for the JOpera distributed service composition engine over a cluster. The autonomic controller starts and stops navigation (i.e.…”

Section: Related Workmentioning

confidence: 99%

“…The autonomic component also has self-healing capabilities. However, proper thread placement in the cluster and communication overhead among threads are not considered in [9]. Also, in [10], SLA agreements for a specific QoS level for web services are established.…”

Section: Related Workmentioning

confidence: 99%

An Economic Approach for Scalable and Highly-Available Distributed Applications

Bonvin

Papaioannou

Aberer

2010

2010 IEEE 3rd International Conference on Cloud Computing

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“…Due to the complexity of real-world service systems, autonomic approaches dominate this area [49]. However, in most cases, the capabilities of resources are not explicitly modeled, but rather are implicitly embedded in the frameworks.…”

Section: Resource Modeling and Reasoningmentioning

confidence: 99%

A roadmap towards sustainable self-aware service systems

Dustdar

Dorn

et al. 2010

Proceedings of the 2010 ICSE Workshop on Software Engineering for Adaptive and Self-Managing Systems

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Self-awareness and self-adaptation have become primary concerns in large-scale systems as they have become too complex to be managed by human administrators alone, but rather require a new blend of coordination mechanisms between people and software services. This paper presents a roadmap to effective and efficient system adaptation through coupling self-awareness of globallevel goals with sustainability constraints. Sustainability of large-scale systems challenges self-adaptation approaches by its intrinsic characters of global and long-lasting effects. We introduce five levels of awareness: (i) event-awareness, (ii) situation-awareness, (iii) adaptability awareness, (iv) goalawareness, and (v) future-awareness. Within each level we introduce applicable principles and subsequently outline necessary models, algorithms, and protocols. The approach puts special focus on the interdependencies of human and service elements.

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“…The controller then executes the process instance by initiating the entire goal hierarchy and waiting for appropriate triggers to be sensed within the system environment to activate goals and move forward with process execution. Each process controller is at the heart of its own autonomic feedback control loop (Pautasso et al, 2007;Tesauro et al, 2004) which uses observations made of the system 1 being affected by the process instance to effect decisions within the corresponding process instance relating to, for example, which goals should be activated and which plans selected to meet goal requirements. Such autonomic control allows process instances to be self-configured and self-optimized bringing about both process flexibility and resilience.…”

Section: Ls/abpm Process Navigation Enginementioning

confidence: 99%