Advances in Service-Oriented and Cloud Computing: Workshops by Guadalupe Ortiz, Cuong Tran

Storage Retrieval

By Guadalupe Ortiz, Cuong Tran

This quantity comprises the technical papers awarded within the 4 top of the range workshops linked to the eu convention on Service-Oriented and Cloud Computing, ESOCC 2014, held in Manchester, united kingdom, in September 2014: 4th overseas Workshop on Adaptive companies for the longer term net, WAS4FI 2014, second overseas Workshop on Cloud for IoT, CLIoT 2014, second overseas Workshop on Cloud provider 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 rigorously reviewed and chosen from 39 submissions. They specialize in particular subject matters in service-oriented and cloud computing domain names as cloud computing, carrier buses, net companies, service-oriented architectures, event-driven architectures, company architectures, company strategy administration, software program choice and adaptation.

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Additional rules take care of stubbing the replication of Jolie services instances which present SLA violation and stubbing the removal of under-utilized Jolie services instances. 6 Experimental Evaluation In essence, the goal that we have achieved in PaaSSOA is represented by the elastic adaptation of services capacity. e. horizontal scalability), in this way it becomes possible to scale, enforce the services SLAs, and optimize the costs arising from the use of the infrastructure. It worth noting that the actions triggered by the Drools declarative rules with the aim to vary the number of running service’s instances are only stubbed, this means that such actions work only in the context of our purpose-built Simulation Toolkit.

In order to analyse and characterize the possible compensation functions, we identify the following list of interesting properties: Property P1 (Consistent) Let CFSP a compensation function, it is said to be consistent if the compensation for a lesser degree of fulfillment of service property is lesser or equal than the compensation for a greater degree of fullfillment of such property. This property assures the monotonicity of compensation functions. Samples 1 and 2 of Fig. 3 depict a decreasing and an increasing consistent compensation function, respectively.

4, we can see the result of the service replication on the duration of the operations, so the ability of the Elastic Scheduler to add service instances in order to keep the service’s response time within the SLA threshold. 28 A. 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.

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