By Guadalupe Ortiz, Cuong Tran
This quantity comprises the technical papers awarded within the 4 top quality workshops linked to the ecu convention on Service-Oriented and Cloud Computing, ESOCC 2014, held in Manchester, united kingdom, in September 2014: 4th foreign Workshop on Adaptive prone for the long run net, WAS4FI 2014, second foreign Workshop on Cloud for IoT, CLIoT 2014, second foreign Workshop on Cloud carrier Brokerage, CSB 2014, and Seamless Adaptive Multi-cloud administration of Service-based purposes, SeaCloudS Workshop. the nineteen revised complete papers and three brief papers have been conscientiously reviewed and chosen from 39 submissions. They concentrate on particular issues in service-oriented and cloud computing domain names as cloud computing, provider buses, net prone, service-oriented architectures, event-driven architectures, firm architectures, enterprise procedure administration, software program choice and adaptation.
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Additional resources for Advances in Service-Oriented and Cloud Computing: Workshops of ESOCC 2014, Manchester, UK, September 2-4, 2014, Revised Selected Papers
Zuccato and T. Vardanega Fig. 4. Experimental evaluation of elastic scalability using the Simulation Toolkit. 3 Downward Scalability After the test of upward scalability we needed to experiment with downward scalability. The second phase of test was merely a continuation of the previous scenario, so we resumed from the point where we have left. The experiments were conducted by decreasing the frequency of operations in the use proﬁle. Therefore, when the Elastic Scheduler detects that the frequency of operations on a particular instance has fallen below the limit of 30 operation per minute, triggers the removeInstance operation on the Toolkit with the aim to reduce the number of instances.
G. replicate service to enforce the SLA) according to its input data and its knowledge through a chain of rules activations which translates in actions. Basically, the Drools inference engine receives raw events coming from monitored services, processes them updating its internal knowledge (POJO holding the statistics of monitored services), then logs and removes raw event from its working memory. The knowledge that we extract from raw events serves for a dual purpose: the ﬁrst is to keep track of the status and to maintain statistics of Implementing Elastic Capacity in a Service-Oriented PaaS 25 services executing in PaaSSOA, the second is to allow for a comparison of their current status in respect to their SLAs.
Comput. 7(2), 168–183 (2014) 8. : Managing violations in service level agreements. In: Grid Middleware and Services Chapter Title - Managing Violations in Service Level Agreements, pp. de Abstract. With the broad adoption of service-orientation for the realization of business applications and their provisioning and usage over open cloud infrastructures, the topology of the resulting service networks is becoming extremely complex. Due to the composition of services for value-added business capabilities and the reusability of a service in multiple compositions, the execution of one service often depends on other services and changes in its provisioning can aﬀect the health of large parts of the service network.