An optimal query assignment for wireless sensor networks

With the increased use of large-scale real-time embedded sensor networks, new control mechanisms are needed to avoid congestion and meet required Quality of Service (QoS) levels. In this paper, we propose a Markov Decision Problem (MDP) to prescribe an optimal query assignment strategy that achieves a trade-off between two QoS requirements: query response time and data validity. Query response time is the time that queries spend in the sensor network until they are solved. Data validity (freshness) indicates the time elapsed between data acquisition and query response and whether that time period exceeds a predefined tolerance. We assess the performance of the proposed model by means of a discrete event simulation. Compared with three other heuristics, derived from practical assignment strategies, the proposed policy performs better in terms of average assignment costs. Also in the case of real query traffic simulations, results show that the proposed policy achieves cost gains compared with the other heuristics considered. The results provide useful insight into deriving simple assignment strategies that can be easily used in practice

Energy-delay trade-off of wireless data collection in the plane

We analyze the Pareto front of the delay of collecting data from wireless devices located in the plane according to a Poisson process and the energy needed by the devices to transmit their observations. Fundamental bounds on the energy-delay trade-off over the space of all achievable scheduling strategies are provided

Deployment vs. data retrieval costs for caches in the plane

We consider the problem of finding the Pareto front of the expected deployment cost of wireless caches in the plane and the expected retrieval cost of a client requesting data from the caches. The data is allocated at the caches according to partitioning and coding strategies. We show that under coding, it is optimal to deploy many caches with low storage capacity. For partitioning, we derive a simple relation between the cost of the cache deployment and the cost of retrieving the data from the caches. Lastly, we show that coding results in a lower Pareto front than partitioning

Data retrieval time for energy harvesting wireless sensors

We consider the problem of retrieving a reliable estimate of an attribute monitored by a wireless sensor network, where the sensors harvest energy from the environment independently, at random. Each sensor stores the harvested energy in batteries of limited capacity. Moreover, provided they have sufficient energy, the sensors broadcast their measurements in a decentralized fashion. Clients arrive at the sensor network according to a Poisson process and are interested in retrieving a fixed number of sensor measurements, based on which a reliable estimate is computed. We show that the time until an arbitrary sensor broadcasts has a phase-type distribution. Based on this result and the theory of order statistics of phase-type distributions, we determine the probability distribution of the time needed for a client to retrieve a reliable estimate of an attribute monitored by the sensor network. We also provide closed-form expression for the retrieval time of a reliable estimate when the capacity of the sensor battery or the rate at which energy is harvested is asymptotically large. In addition, we analyze numerically the retrieval time of a reliable estimate for various sizes of the sensor network, maximum capacity of the sensor batteries and rate at which energy is harvested. These results show that the energy harvesting rate and the broadcasting rate are the main parameters that influence the retrieval time of a reliable estimate, while deploying sensors with large batteries does not significantly reduce the retrieval time

An Optimal Query Assignment for Wireless Sensor Networks

A trade-off between two QoS requirements of wireless sensor networks: query waiting time and validity (age) of the data feeding the queries, is investigated. We propose a Continuous Time Markov Decision Process with a drift that trades-off between the two QoS requirements by assigning incoming queries to the wireless sensor network or to the database. To compute an optimal assignment policy, we argue, by means of non-standard uniformization, a discrete time Markov decision process, stochastically equivalent to the initial continuous process. We determine an optimal query assignment policy for the discrete time process by means of dynamic programming. Next, we assess numerically the performance of the optimal policy and show that it outperforms in terms of average assignment costs three other heuristics, commonly used in practice. Lastly, the optimality of the our model is confirmed also in the case of real query traffic, where our proposed policy achieves significant cost savings compared to the heuristics.Comment: 27 pages, 20 figure

Effective Scheduling for Coded Distributed Storage in Wireless Sensor Networks

A distributed storage approach is proposed to access data reliably and to cope with node failures in wireless sensor networks. This approach is based on random linear network coding in combination with a scheduling algorithm based on backpressure. Upper bounds are provided on the maximum rate at which data can be reliably stored. Moreover, it is shown that the backpressure algorithm allows to operate the network in a decentralized fashion for any rate below this maximum

AGILe:The First Lemmatizer for Ancient Greek Inscriptions

To facilitate corpus searches by classicists as well as to reduce data sparsity when training models, we focus on the automatic lemmatization of ancient Greek inscriptions, which have not received as much attention in this sense as literary text data has. We show that existing lemmatizers for ancient Greek, trained on literary data, are not performant on epigraphic data, due to major language differences between the two types of texts. We thus train the first inscription-specific lemmatizer achieving above 80% accuracy, and make both the models and the lemmatized data available to the community. We also provide a detailed error analysis highlighting peculiarities of inscriptions which again highlights the importance of a lemmatizer dedicated to inscriptions

Breve análisis de los factores que intervienen en el aprendizaje ortográfico

Si revisamos el rendimiento escolar de nuestros alumnos referido a la lengua escrita comprobaremos cómo uno de los problemas que frecuentemente se nos plantea, además de la alarmante pobreza de vocabulario y la precariedad de la expresión, son las faltas de ortografía. Ello se debe a la complejidad de los factores que intervienen en el proceso escritor donde está implicada esta disciplina lingüística. En este artículo estudiamos cada uno de estos elementos que, a nuestro juicio, deben considerarse al analizar el fracaso ortográfico de nuestros estudiantes.If we reexamine our students school efficiency relating written language, we will verify that one of the problems that we usually find, besides the alarming vocabulary poverty and the precarious expression, are orthographic mistakes. This fact is due to the complexity of the writing process factors where this linguistic discipline is implicated. In the present paper we specify every one of these elements that we must be considered on analysing the wrong spelling of our students.Facultad de Educación y Humanidades - Campus de Melilla (Universidad de Granada