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The performance analysis of the 32 × 32 crosspoint-queued switch is presented in this paper. Switches with small buffers in crosspoints have been evaluated in the late 1980s but mostly for uniform traffic. However, due to technological limitations of that time, it was impractical to implement large buffers together with switching fabric. The crosspoint-queued switch architecture has been recently brought back into focus since modern technology enables an easy implementation of large buffers in crosspoints. An advantage of this solution is the absence of control communication between linecards and schedulers. In this paper, the performances of four algorithms (longest queue first, round robin, exhaustive round robin, and frame-based round robin matching) are analyzed and compared. The results obtained for the crosspoint-queued switch are compared with the output queued switch. Throughput, average cell latency and instantaneous packet delay variance are evaluated under uniform and nonuniform traffic patterns. The results will show that the longest queue first algorithm has the highest throughput in many simulated cases but the highest average cell latency and delay variance among observed algorithms. It will also be shown that the choice of the scheduling algorithm does not play a role in the switch performance if the buffers are long enough. This will prove that some form of round-robinbased algorithms become a better choice for implementation due to their simplicity, small hardware requirements, and avoidance of the starvation problem, which is a major drawback of the longest queue first algorithm.

The Internet of Things (IoT) is a leading trend with numerous opportunities accompanied by advantages as well as disadvantages. Parallel with IoT development, significant privacy and personal data protection challenges are also growing. In this regard, the General Data Protection Regulation (GDPR) is often considered the world’s strongest set of data protection rules and has proven to be a catalyst for many countries around the world. The concepts and interaction of the data controller, the joint controllers, and the data processor play a key role in the implementation of the GDPR. Therefore, clarifying the blurred IoT actors’ relationships to determine corresponding responsibilities is necessary. Given the IoT transformation reflected in shifting computing power from cloud to the edge, in this research we have considered how these computing paradigms are affecting IoT actors. In this regard, we have introduced identification of IoT actors according to a new five-computing layer IoT model based on the cloud, fog, edge, mist, and dew computing. Our conclusion is that identifying IoT actors in the light of the corresponding IoT data manager roles could be useful in determining the responsibilities of IoT actors for their compliance with data protection and privacy rules.

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