Abstract

In this era of ubiquitous computing, coupled with the emergence of big data and internet of things, there have been constant changes in every aspect of cloud data center communications - its network connectivity, data storage, data transfer, and architectural design. As a result of this, the amount of data transferable, and the frequency of data transfer have tremendously increased; causing device failures and traffic congestions. To cope with these changes so that performance can be sustained amidst device failures and traffic congestion, the design of fault tolerant cloud data center is important. A fault tolerant cloud data center network should be able to provide alternative paths from source to destination during failures so that there will not be abrupt fall in performance. But still with the ongoing researches in this regard, there has not been a robust cloud data center design that can boast of being suitable for alleviating the poor fault tolerance of cloud data center. In this paper, we proposed the improved versions of fat-tree interconnection hybrid designs derived from the structure called Z-fat tree; to address the issues of fault tolerance. Then, we compared these designs with single fat tree architecture with the same amount of resources for client server communication pattern such as Email application in a cloud data center. The simulation results obtained based on failed switches and links, show that our proposed hybrid designs outperformed the single fat tree design as the inter arrival time of the packets reduces.

Abstract

This article discusses the results of supporting transition towards fully automated driving with remote operator support via the novel V2X channels. Automated passenger cars are equipped with multiple sensors (radars, cameras, LiDARs, inertia, GNSS, etc.), the operation of which is limited by weather, detection range, processing power and resolution. The study explores the use of a dedicated network for supporting automated driving needs. The MEC server latencies and bandwidths are compared between the Tampere, Finland test network and studies conducted in China to support remote passenger car operation. In China the main aim is to evaluate the network latencies in different communication planes, whereas the European focus is more on associated driving applications, thus making the two studies mutually complementary.5G revolutionizes connected driving, providing new avenues due to having lower and less latency variation and higher bandwidths. However, due to higher operating frequencies, network coverage is a challenge and one base station is limited to a few hundred meters and thus they deployed mainly to cities with a high population density. Therefore, the transport solutions are lacking so-called C-V2X (one form of 5G RAT) to enable data exchanges between vehicles (V2V) and also between vehicles and the digital infrastructure (V2I). The results of this study indicate that new edge-computing services do not cause a significant increase in latencies $(\\lt 100$ ms), but that latency variation (11 - 192 ms) remains a problem in the first new network configurations.