Underwater video services could be a key application in the better scientific knowledge of the vast oceanic resources in our planet. However, limitations in the capacity of current available technology for underwater networks (UWSNs) raise the question of the feasibility of these services. When transmitting video, the main constraints are the limited bandwidth and the high propagation delays. At the same time the service performance depends on the needs of the target group. This paper considers the problems of estimations for the Mean Opinion Score (a standard quality measure) in UWSNs based on objective methods and addresses the topic of quality assessment in potential underwater video services from a subjective point of view. The experimental design and the results of a test planned according standardized psychometric methods are presented. The subjects used in the quality assessment test were ocean scientists. Video sequences were recorded in actual exploration expeditions and were processed to simulate conditions similar to those that might be found in UWSNs. Our experimental results show how videos are considered to be useful for scientific purposes even in very low bitrate conditions.
Underwater wireless sensor networks (UWSNs) are a promising technology to provide oceanographers with environmental data in real time. Suitable network topologies to monitor estuaries are formed by strings coming together to a sink node. This network may be understood as an oriented graph. A number of MAC techniques can be used in UWSNs, but Spatial-TDMA is preferred for fixed networks. In this paper, a scheduling procedure to obtain the optimal fair frame is presented, under ideal conditions of synchronization and transmission errors. The main objective is to find the theoretical maximum throughput by overlapping the transmissions of the nodes while keeping a balanced received data rate from each sensor, regardless of its location in the network. The procedure searches for all cliques of the compatibility matrix of the network graph and solves a Multiple-Vector Bin Packing (MVBP) problem. This work addresses the optimization problem and provides analytical and numerical results for both the minimum frame length and the maximum achievable throughput.
In this work, a multi-hop string network with a single sink node is analyzed. A periodic optimal scheduling for TDMA operation that considers the characteristic long propagation delay of the underwater acoustic channel is presented. This planning of transmissions is obtained with the help of a new geometrical method based on a 2D lattice in the space-time domain. In order to evaluate the performance of this optimal scheduling, two service policies have been compared: FIFO and Round-Robin. Simulation results, including achievable throughput, packet delay, and queue length, are shown. The network fairness has also been quantified with the Gini index.
Modern cities contain a wealth of information that is usually scattered among a myriad of organisms. For citizens it is many times difficult and confusing to access this information. Cities must find a way to put all this information at the disposal not only of the citizens but any employee that takes part in the operation and maintenance of the city. One of the problems that appear is that each city department has organized its information independently of others, thus leading to an heterogeneous ecosystem of databases and platforms. This paper describes a solution to access all the information available in a city through a mobile platform and a brief description on problems and solutions in the process of porting the application to web and SmartTV platforms. A customizable user application for the Android operating system is described. The solution can be deployed in any city as the application dynamically obtains the information from remote servers that hold access to the databases.
Video services are meant to be a fundamental tool in the development of oceanic research. The current technology for underwater networks (UWNs) imposes strong constraints in the transmission capacity since only a severely limited bitrate is available. However, previous studies have shown that the quality of experience (QoE) is enough for ocean scientists to consider the service useful, although the perceived quality can change significantly for small ranges of variation of video parameters. In this context, objective video quality assessment (VQA) methods become essential in network planning and real time quality adaptation fields. This paper presents two specialized models for objective VQA, designed to match the special requirements of UWNs. The models are built upon machine learning techniques and trained with actual user data gathered from subjective tests. Our performance analysis shows how both of them can successfully estimate quality as a mean opinion score (MOS) value and, for the second model, even compute a distribution function for user scores.
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