Analysis of end-to-end multi-domain management and orchestration frameworks for software defined infrastructures: an architectural survey <s> Service orchestration models: Multi-operator service level agreement aspects <s> Cloud computing providers have setup several data centers at different geographical locations over the Internet in order to optimally serve needs of their customers around the world However, existing systems do not support mechanisms and policies for dynamically coordinating load distribution among different Cloud-based data centers in order to determine optimal location for hosting application services to achieve reasonable QoS levels Further, the Cloud computing providers are unable to predict geographic distribution of users consuming their services, hence the load coordination must happen automatically, and distribution of services must change in response to changes in the load To counter this problem, we advocate creation of federated Cloud computing environment (InterCloud) that facilitates just-in-time, opportunistic, and scalable provisioning of application services, consistently achieving QoS targets under variable workload, resource and network conditions The overall goal is to create a computing environment that supports dynamic expansion or contraction of capabilities (VMs, services, storage, and database) for handling sudden variations in service demands. ::: ::: This paper presents vision, challenges, and architectural elements of InterCloud for utility-oriented federation of Cloud computing environments The proposed InterCloud environment supports scaling of applications across multiple vendor clouds We have validated our approach by conducting a set of rigorous performance evaluation study using the CloudSim toolkit The results demonstrate that federated Cloud computing model has immense potential as it offers significant performance gains as regards to response time and cost saving under dynamic workload scenarios. <s> BIB001 </s> Analysis of end-to-end multi-domain management and orchestration frameworks for software defined infrastructures: an architectural survey <s> Service orchestration models: Multi-operator service level agreement aspects <s> The objectives of Cross Stratum Optimization (CSO) and SLA Management in multi-domain infrastructure services lead to challenges for maintaining autonomy of resource control and coordination of the SLA lifecycle. The GEYSERS project includes an approach and architecture for SLA Management to address these two problems. The conceptual foundations and blueprint of this architecture are presented and assessed. <s> BIB002
In a multi-operator environment, the services offered by each operator may require NFs and resources from different locations in several neighbour domains (with different capabilities, requirements, constraints and different administrators) for its deployment. This can be managed by resource and service slicing and a contract becomes necessary between the different providers, including quality assurance by means of an SLA. Operators delivering the service from a service topology can either be a star (customer-facing operator handles all contracts) or a multilevel tree (operators handle contracts in a cascading fashion). These topologies can be realised by means of MdO interface I2 for inter-operator relations and MdO interface I1 for customer to operator relations as depicted in Figure 2 . For each resource or service slice, there should be a parent SLA contract that is subdivided in several child SLA contracts, one for each operator that provides resource or service slices for composing the customer demanded service. As resource and KPI monitoring is operator-internal, an SLA aggregator functions for all the contracts that are attached to the parent and aggregates the results of the partial SLA evaluations of each subcontract. While some of the aforementioned issues have been brought up earlier in the context of cloud federations BIB001 , much challenges remain with regard to SLA handling in a multi-operator, composite service environment. First, today's SLAs in general contain very simple conditions that may not capture all details. When it comes to composite services requesting compute, storage and networking resources at the same time, currently used simplistic SLAs (both in the cloud and telco environment) would probably fail to assure the inherently complex service requirements and the intricate interplay of resources of very different types. In order to mitigate such inefficiency of the contracts, KPIs relevant for composite services should be devised and integrated into SLAs with a holistic view to the service under consideration. Second, the granularity and amount of internal information shared among operators is key to defining efficient SLAs and estimate the risk of not fulfilling them. In certain cases, operators might want to share finer grain information (e.g. a partial network topology with KPI measurements on the links) with each other to provide high and ASQ, if the end-user is willing to pay for such a service. In other cases, operators like to keep it simple and reveal the least amount of information about their own administrative domain (e.g. a totally abstract view of their network, i.e. a 'black box'), provided such a view is adequate for the given service to be delivered successfully. The key observation here is that a flexible information-sharing framework is needed, where any level of details could be shared and incorporated into contracts. Third, how the parent SLA is subdivided into several partial SLAs, how income is divided based on (un)fulfilled contracts, and how to share the costs of remunerating the customer in case of not meeting KPIs are all important issues to deal with. Note that there are a number of theoretical solutions to this problem published by the research community, drawing on proportional fairness and coalitional game theory [11] ; however, a practical, carriergrade implementation of these mechanisms is still missing. Such computational issues are becoming even more relevant, as the potential for on-demand service negotiation and creation (as opposed to a strictly service catalogue based system) brings with itself the need for calculating (partial) SLA parameters on the fly. Different strategies can be taken under consideration for multi-domain SLA management: (i) a bottom-up strategy that is initiated by providers; (ii) a top-down strategy that is initiated by consumers; and (iii) a mixed/negotiated strategy, which is a combination of strategies 1 and 2 with additional message exchanges. In BIB002 , authors provide a detailed insight on these strategies.