Abstract-The constant evolution of access technologies are turning Internet access more ubiquitous, faster, better and cheaper. In connection with the proliferation of Internet access, Cloud Computing is changing the way users look at data, moving from local applications and installations to remote services, accessible from any device. This new paradigm presents numerous opportunities that even traditional businesses like telecoms cannot ignore, in particular, enabling new and more cost effective solutions to old problems.The work presented in this paper provides a detailed description of how a telecom application can be migrated to a NoSQL database. Particularly, by pointing out the necessary change of how we reason about data as well as the data structures that support it, in order to take full advantage of Cloud Computing. In addition, we also present a preliminary evaluation of different data persistency paradigms based on a fully tunable simulation platform that mimics the operation of a telecom business.

All companies developing their business on the Web, not only giants like Google or Facebook but also small companies focused on niche markets, face scalability issues in data management. The case study of this paper is the content management systems for classified or commercial advertisements on the Web. The data involved has a very significant growth rate and a read-intensive access pattern with a reduced update rate.Typically, data is stored in traditional file systems hosted on dedicated servers or Storage Area Network devices due to the generalization and ease of use of file systems. However, this ease in implementation and usage has a disadvantage: the centralized nature of these systems leads to availability, elasticity and scalability problems.The scenario under study, undemanding in terms of the system's consistency and with a simple interaction model, is suitable to a distributed database, such as Cassandra, conceived precisely to dynamically handle large volumes of data.In this paper, we analyze the suitability of Cassandra as a substitute for file systems in content management systems. The evaluation, conducted using real data from a production system, shows that when using Cassandra, one can easily get horizontal scalability of storage, redundancy across multiple independent nodes and load distribution imposed by the periodic activities of safeguarding data, while ensuring a comparable performance to that of a file system.

DNA metabarcoding is particularly helpful for monitoring taxonomically complex communities and hard to identify morphologically, such as several zoo and ichthyoplankton, which contain eggs and larval stages of unknown species. However, the efficiency of metabarcoding in diversity recovery is dependent on the targeted genetic markers and primers employed. In this work, we compared the performance of three different primer pairs from cytochrome oxidase subunit I (COI) genetic marker in species detection from marine mesozooplankton samples and its potential to be implemented in biomonitoring programs. We employed the mlCOIintF/LoboR1 primer combination targeting marine metazoans, and two newly designed fish-specific primer cocktails for targeting the ichthyoplankton. Mesozooplankton samples were collected at 4 locations on the Portuguese coast – 1 in the northwest (Viana do Castelo) and 3 in the south (coastal lagoons of Ria de Alvor and Ria Formosa, and in the river Guadiana estuary). Bulk community DNA was extracted using a non-destructive protocol and amplicon libraries produced for the 3 primers combinations. After quality-filtering bioinformatic steps, we obtained 3.04 x 105 usable sequences, of which 76.26% were clustered into OTUs (operational taxonomic units) and 46.30% were identified at species level - corresponding to 103 taxa from 8 different metazoan Phyla. The most diverse classes were Malacostraca, Actinopterygii, and Copepoda. As expected, the generic primer pair for marine metazoa (mlCOIintF/LoboR1) retrieved a higher number of species (94) compared with the fish-specific primer cocktails (30). Nevertheless, 9 % of the total species were identified exclusively by the cocktails, of which 42% were fish. These results confirmed the potential of metabarcoding as a tool for profiling zooplankton communities and to assess ichthyoplankton diversity. Multiple primers pairs increased species detection from different taxonomic groups, being the protocol optimization for fish-specific primer cocktails, the next step for its implementation in fish stock assessments.