Industry 4.0 is originally a future vision described in the high-tech strategy of the German government that is conceived upon information and communication technologies like Cyber-Physical Systems, Internet of Things, Physical Internet, and Internet of Services to achieve a high degree of flexibility in production (individualized mass production), higher productivity rates through real-time monitoring and diagnosis, and a lower wastage rate of material in production. An important part of the tasks in the preparation for Industry 4.0 is the adaption of the higher education to the requirements of this vision, in particular the engineering education. In this work, we introduce a road map consisting of three pillars describing the changes/enhancements to be conducted in the areas of curriculum development, lab concept, and student club activities. We also report our current application of this road map at the Turkish German University, Istanbul.

Storage Area Networks (SANs) connect groups of storage devices to servers over fast interconnects. An important challenge lies in managing the complexity of the resulting massive SAN configurations. Policy-based validation using new logical frameworks has been proposed earlier as a solution to this configuration problem. SANchk offers a new solution that uses standard technologies such as SQL, XML, and Java, to implement a rule-based configuration checker. SANchk works as a light-weight extension to the relational databases of storage management systems; current support includes IBM's TPC and the open source Aperi storage manager. Some five dozen best practices rules for SAN configuration are implemented in SANchk, many of them with configurable parameters. Empirical results with several commercial SANs show that the approach is viable in practice.

Storage area networks (SANs) connect storage devices to servers over fast network interconnects. We consider the problem of optimal SAN configuration with the goal of meeting service level agreements (SLAs) for server processes while retaining flexibility for future changes. Our approach proceeds in two stages, by setting up pseudo-Boolean constraint problems and solving them with an off-the-shelf solver. First, we give an algorithm for assigning storage devices to applications running on the SANpsilas hosts. This algorithm tries to balance the workload as evenly as possible over all storage devices. Our second algorithm takes these assignments and computes the interconnections (data paths) that are necessary to achieve the desired configuration while respecting redundancy (safety)requirements in the SLAs. Again, this algorithm tries to balance the workload of all connections and devices in proportion to their capacity. Thus, our network configurations respect all SLAs and provide flexibility for future changes by avoiding bottlenecks on storage devices or switches.

Storage area networks (SANs) connect groups of storage devices to servers over fast interconnects using protocols like Fibre Channel or iSCSI, so that storage resources can be assigned to servers in a flexible and scalable way. An important challenge is controlling the complexity of the SAN configuration resulting from the high scalability of the network and the diversity and the interconnectivity of the devices. Policy- based validation has been proposed earlier as a solution to this configuration problem. We propose a light-weight, SQL-based solution that uses existing well-known technologies to implement such a validation system. Our approach is based on a relational database which stores configuration data extracted from the system via a WBEM standard interface. In contrast to other approaches, we use SQL to define our policy rules as executable checks on these configuration data. Each rule is embedded in a test case, defined by an XML schema, which combines each check with an explanation component and an action component. These components retrieve information about the SAN components that cause the check to fail and provide methods that will be invoked on a success or a failure of the test. Although the approach is more general, we focus on the application for Storage Area Networks. We also give some example policies for SAN configuration and their implementations and show how in addition all policy types presented by Agrawal et al. (2004) can be formulated as SQL queries by our method.

Storage Area Networks (SANs) connect storage devices to servers over fast network interconnects. We consider the problem of optimal SAN configuration with the goal of retaining more security in meeting service level agreements (SLAs) on unexpected peaks. First, we give an algorithm for assigning storage devices to applications running on the SAN's hosts. This algorithm tries to balance the workload as evenly as possible over all storage devices. Our second algorithm takes these assignments and computes the interconnections (data paths) that are necessary to achieve the desired configuration while respecting redundancy (safety) requirements in the SLAs. Again, this algorithm tries to balance the workload of all connections and devices. Thus, our network configurations respect all SLAs and provide flexibility for future changes by avoiding bottlenecks on storage devices or switches. We also discuss integrating our solution with the open source SAN management software Aperi.