# Fuzzy Multi-Criteria Based Trust Management in Heterogeneous Federated Future Internet Testbeds
## 1 Introduction  
Nowadays, web services are shifting gradually from the client-server paradigm to more distributed delivery models consisting of several individual software components. The architecture of the on-line services can be categorized as single, composite and communities [1]. Single services do not interact with other services, while composite ones consist of a set of single services to offer more complex functionalities. Recently, various developed communities of services have distributed the computational load of a service's request among several individual users. Furthermore, people interact increasingly with e-services through mobile devices, which means many heterogeneous network and computing devices are involved in every on-line transaction. In such a complex environment, the user of a service must select the appropriate provider that fulfills his/her requirements, and this decision is based on numerous versatile technical and human-centric criteria. Similarly to the human transactions, a trust mechanism between the user and the provider is necessary. The trust is defined as the subjective belief of Entity A that Entity B will perform a given action [2]. Reputation is a complementary concept that helps entities trust each other. Reputation is defined as \"the general belief about a person's or thing's character or standing\", according to the Concise Oxford Dictionary. The main difference between these notions is that reputation is public and produced by a group of people or entities, while trust is personal and subjective. Over the last decade, many testbeds have been offered to academia and industry to deploy and evaluate novel network services and architectures. A single testbed usually offers a specific type of resource, which is suitable for small- or medium-scale experimentation. Thus, many research initiatives, such as FED4 FIRE [3], FED4 FIRE+ [4] and GENI [5], federate heterogeneous testbeds in terms of wired, wireless, computing and virtualized resources. The management framework of these projects supports all phases of the experimental lifecycle, i.e., discovering, booking and provisioning the appropriate resources. The federated environment enables the experimenters to select among different testbeds and services. According to each experiment scenario, a number of different resources with specific functionalities will be required. For most scenarios, testbed federations offer plenty of resources with the same or similar functionalities. In this case, the user should select the resources meeting his/her requirements. For example, an experiment on on-line gaming has strict low-latency requirements, while a video streaming experiment focuses mainly on a high and stable data transfer rate. Thus, it is important to establish a trust mechanism among the entities of the experiment in order to facilitate the successful conduction of the experiments and provide a comprehensible testbed reputation score based on specific performance metrics. In this paper, we design and deploy a scalable reputation-based trust framework for a federated testbed environment in order to enable the selection of the appropriate testbed according to the experimenters' requirements. The proposed system can process a set of diverse performance criteria and quantify the testbeds' reputation leveraging Quality of Service (QoS) and Quality of Experience (QoE) measurements. The trust framework is based on a modification of the fuzzy VIKOR multi-criteria decision-making method and leverages both numeric and linguistic values to infer the reputation score of the federated testbeds. Upon the completion of an experiment, the users are prompted to submit their rating for the performance of the infrastructure utilized using QoS and QoE criteria. The QoS metrics of each testbed, e.g., node availability and network latency, are measured by numerical values, while the QoE metrics, e.g., usability and support satisfaction, are evaluated by fuzzy numbers.