Abstract. As for all kind of software, customers expect to find business process execution provided as a service (BPMaaS). They expect it to be provided at the best cost with guaranteed SLA. From the BPMaaS provider point of view it can be done thanks to the provision of an elastic cloud infrastructure. The provider still have to provide the service at the lowest possible cost while meeting customers expectation. We propose a customer-centric service model that link the BPM execution requirement to cloud resources, and that optimize the deployment of customer's (or tenants) processes in the cloud to adjust constantly the provision to the needs. However, migrations between cloud configurations can be costly in terms of quality of service and a provider should reduce the number of migration. We propose a model for BPMaaS cost optimization that take into account a maximum number of migrations for each tenants. We designed a heuristic algorithm and experimented using various customer load configurations based on customer data, and on an actual estimation of the capacity of cloud resources.

Even though the proven benefits of cloud computing paradigm, it must face a serious problem that can compromise its commercial success. It concerns the lack of efficient approach for using optimally the available resources. For this, several approaches have been proposed. However, they suffer from several shortcomings. For instance, often only one objective is taken into account expressing all operations in terms of cost. Furthermore, business processes should be insured with elasticity and multitenancy mechanism while adjusting the available resources to the dynamic load distribution. The proposed approach aims to optimize two conflicting objectives, namely the number of migrated tenants and the cost incurred using a set of resources. It allows to take into account the multi-tenancy property and the Cloud computing elasticity, and is efficient as shown by an extensive experimentation based on real data from Bonita BPM customers.

No abstract

Machine‐as‐a‐Service (MaaS) is an emerging service model for industrial appliances. With MaaS, machines are rented instead of being acquired, and their lifecycle is handled by an ecosystem of specialized actors, such as different independent maintenance companies certified for interventions on specific hardware. As the number of actors, clients, and providers involved in a MaaS ecosystem grows, maintaining mutual trust relationships between all involved parties and orchestrating MaaS operations in centralized fashion quickly becomes intractable. We present a blockchain‐based approach to providing MaaS in industrial settings where rented machines are equipped with IoT sensors, and where MaaS operations are orchestrated in a transparent, decentralized, and scalable way using a collection of smart contracts deployed over an infrastructure combining the Ethereum and InterPlanetary File System decentralized services. We detail the operations of MaaS, such as the lifecycle of management operations, and report on the performance of a prototype implementation deployed in the cloud.