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In this paper, we propose a new restoration algorithm for disaster recovery in Elastic Optical Networks (EONs). The algorithm considers the different requirements on restoration delay and bandwidth degradation while restoring over multiple routes. Furthermore, the algorithm is able to adapt the connection recover process to the post-disaster network conditions and, consequently, increase the number of restored connections. Results indicate that the proposed strategy is able to improve connections restorability and decrease bandwidth blocking probability when compared to restoration approach based on bandwidth degradation and multipath recovery.

All-optical (transparent) wavelength-division multiplexing (WDM), a cost-effective and low power consumption solution for core transport networks, suffers from physical-layer impairments that accumulate along optical paths. In this context, it is important to find dynamic routing schemes with good performance that can consider the optical-layer constraints. In this paper, we propose the alternative least loaded under physical impairments (ALLPI) and the ALLPI with threshold (ALLPI-TH) algorithms. These are heuristic routing methods by which the lightpath requests that cannot be provisioned based on the shortest physical distance are established over least-loaded routes, provided that the selected lightpaths satisfy the impairment constraints (OSNR and PMD). Either dispersion-limited or noise-limited network scenarios were studied, for the bit rate of 40 Gbps. The results indicate that the ALLPI-type algorithms produce significantly lower blocking probabilities when compared to the reference algorithms, especially for a highly-connected network and at higher loads.

The use of an optical fiber infrastructure to accommodate cloud services is gaining a lot of momentum. This is mainly driven by the bandwidth and latency performance that optical transmission can guarantee. On the other hand failures in the optical infrastructure may result in the concurrent loss of a possibly high number of cloud services. For this reason, being able to offer cloud service resiliency at a contained cost is of the utmost importance for operators. This paper proposes a heuristic for the restoration of optical cloud services in the presence of a single fiber link failure. The heuristic leverages on two parameters specified in the service class (i.e., restoration delay and bandwidth degradation) in order to make the best use of the available optical resources during the recovery process. The numerical results presented in the paper show that the proposed restoration algorithm is able to improve cloud service restorability without a negative impact on the cloud service blocking probability.

The dynamics between technologies and everyday life is increasingly volatile, pushing for greater convenience and ease of both trivial and complex processes. A consequence of the wide implementation of Internet of Things-based devices in smart city applications clearly reflects the mentioned dynamics by the huge amount of data to be handled. To extract useful information from such data, a clever approach to conduct data analysis is the interdisciplinary one, i.e., engineering and computer scientists as close partners of the problem domain experts. This paper addresses IoT data of a Public transportation System (PTS) aiming at contributing to the data analysis process for new insights about bus based PTS applications. Open Data of Curitiba PTS was explored looking for approaches to handle and analyze this kind of data, aiming to find important information for users, managers and planners of the public transport network in Curitiba.