Design and control approaches for energy harvesting wireless sensor networks

Wireless Networks are monitoring infrastructures composed of sensing (measuring), computing, and communication devices used to observe, supervise and monitor environmental phenomena. Energy Harvesting Wireless Sensor Networks (EH-WSN) have the additional feature to save energy from the environment in order to ensure long life autonomy of the entire network, without ideally the human intervention over long periods of time. The present work is aimed to address some of the most significant limitations of the actual EH-WSN, making a step forward the perpetual operation of EH-WSN. In this dissertation, design methodology and management policies are proposed to improve EH-WSN in terms of application performances, traffic congestion and energy efficiency. The study explicitly targets to energy-efficient affordable ways to develop more reliable and trustworthy EH-WSN, capable to ensure long life and desired performances. The presentation is organized into two macro sections, or Parts: the first one is dedicated to design the main EH-WSN hardware and software parameters that affect the energy efficiency of a sensor node, while in the second part three dynamic control strategies are proposed to outperform the EH-WSN in terms of energy efficiency, traffic congestion and application requirements

MicroRNA deregulation in thyroid cancer

In cancer microRNAs are often dysregulated with their expression patterns being correlated with clinically relevant tumor characteristics. Recently, microRNAs were shown to be directly involved in cancer initiation and progression. Despite the large amount of data showing strong correlations between cancer phenotype and microRNAs aberrant expression, very little is known about the molecular mechanisms inducing such deregulation. Thyroid carcinomas comprise a heterogeneous group of neoplasms with distinctive clinical and pathological characteristics. Activating mutations in Ras genes are frequently found in poorly differentiated and in anaplastic thyroid carcinomas. We have recently shown that oncogenic activation of Ras is able to change the expression of several microRNAs in thyroid epithelial cells. One of the top aberrantly expressed ones is miR-21, a microRNA prevoiusly reported overexpressed in a wide variety of cancers and causally linked to cellular proliferation, survival and migration. By using an inducible Ras oncogene we demonstrated that constitutively active Ras induce overexpression of miR-21 at very early times after its activation, and that such overexpression is maintained at later times as well as in chronically Ras-transformed cells. Analysis of a panel of thyroid tumors with different hystotypes revealed that miR-21 is overexpressed mainly in anaplastic carcinomas, thus correlating with the most aggressive phenotype. Interestingly, this induction seems to be cell-type specific, since the inducible Ras oncogene is unable to increase miR-21 levels in cultured fibroblasts. Moreover, our data show that at least two different Ras downstream pathways are necessary to induce miR-21 expression. We then asked if the ability of Ras in inducing miR-21 overexpression is verified in vivo. To answer this question we analyzed the expression of this microRNA in a mouse model of Ras-induced lung tumorigenesis, showing that Ras constitutive activation is able to increase miR-21 levels in normal lung and that the Ras-initiated lung cancer progression is accompained by a further increase in miR-21 expression. Taken together, our data strongly suggest that the oncogenic activation of Ras could be responsible for the increased expression of miR-21 frequently observed in human cancers

The microRNA-Processing Enzyme Dicer Is Essential for Thyroid Function

Dicer is a type III ribonuclease required for the biogenesis of microRNAs (miRNAs), a class of small non-coding RNAs regulating gene expression at the post-transcriptional level. To explore the functional role of miRNAs in thyroid gland function, we generated a thyrocyte-specific Dicer conditional knockout mouse. Here we show that development and early differentiation of the thyroid gland are not affected by the absence of Dicer, while severe hypothyroidism gradually develops after birth, leading to reduced body weight and shortened life span. Histological and molecular characterization of knockout mice reveals a dramatic loss of the thyroid gland follicular architecture associated with functional aberrations and down-regulation of several differentiation markers. The data presented in this study show for the first time that an intact miRNAs processing machinery is essential for thyroid physiology, suggesting that deregulation of specific miRNAs could be also involved in human thyroid dysfunctions

EMT and induction of miR-21 mediate metastasis development in Trp53-deficient tumours

Missense mutations in TP53 gene promote metastasis in human tumours. However, little is known about the complete loss of function of p53 in tumour metastasis. Here we show that squamous cell carcinomas generated by the specific ablation of Trp53 gene in mouse epidermis are highly metastatic. Biochemical and genome-wide mRNA and miRNA analyses demonstrated that metastases are associated with the early induction of epithelial-mesenchymal transition (EMT) and deregulated miRNA expression in primary tumours. Increased expression of miR-21 was observed in undifferentiated, prometastatic mouse tumours and in human tumours characterized by p53 mutations and distant metastasis. The augmented expression of miR-21, mediated by active mTOR and Stat3 signalling, conferred increased invasive properties to mouse keratinocytes in vitro and in vivo, whereas blockade of miR-21 in a metastatic spindle cell line inhibits metastasis development. Collectively these data identify novel molecular mechanisms leading to metastasis in vivo originated by p53 loss in epithelia

Design and experimental testing of an optimization-based flow control algorithm for Energy Harvesting Wireless Sensor Networks

In this paper a distributed flow control law is proposed to maximize throughput and to minimize energy consumption in Energy Harvesting Wireless Sensor Networks (EH-WSNs). We preliminary recast the control problem in terms of primal–dual optimization one taking into account the bandwidth and energy autonomy node constraint. Then, we devise a distributed flow rate control implemented at each node that allows the overall network to converge to the optimal solution of the original problem. The closed loop EH-WSN stability and convergence to the optimal equilibrium are proven. The effectiveness of the proposed control law in terms of throughput and network lifetime performance is experimentally validated by a small representative EH-WSN. The experimental results are in a good agreement with the theoretical ones

Evaluation of Energy Efficiency-Reconstruction Error Trade-Off in the Co-design of Compressive Sensing Techniques for Wireless Lossy Sensor Networks

In the recent years, the technological improvements on wireless sensor computational capability and versatility have caused a massive use of battery-supplied Wireless Sensor Network (WSN) in many different monitoring applications. The most relevant factors of reliability of such systems are related to the energetic autonomy and the accuracy of the sampled data delivered to the Fusion Center. These two factors are usually in trade off because a more reliable acquisition system requires more energy consumption and vice-versa. In this paper, we present a tool for the co-design of Compressive Sensing techniques to get the desired performance in terms of energy efficiency and reconstruction error. Preliminarily, we formulate a WSN model taking into account both node energy consumption and the traffic model. The effects of packet collision phenomena (that typically affect wireless communication) are also added to the traffic model. The provided WSN model is used to support a tool for the software co-design of parameters that are related to the compression method in order to fulfil given performance specifications on energetic autonomy or signal reconstruction error. To show the effectiveness of the proposed model and the feasibility of the co-design approach, the model is particularized to representative schemes of Compressive Sensing implemented over the network in the presence and in absence of packet loss. An example of software co-design aimed to improve both network autonomy and signal reconstruction error of the considered Compressive Sensing schemes is presented

A Two-Layer Controller Scheme for Efficient Signal Reconstruction and Lifetime Elongation in Wireless Sensor Networks

Abstract: Random sampling compressive sensing (RSCS) is a prominent compression algorithm suitable for wireless sensor network as it can significantly reduce the number of samples required for signal reconstruction. This improves the network lifetime, but can introduce uncertainty in the signal reconstruction. In this paper, we propose a two-layer controller that ensures efficient signal reconstruction (i.e., low level of reconstruction error) and high network lifetime. The proposed controller is composed of a global controller, developed at the fusion center layer, and two local controllers, implemented at each node layer. The former steers the RSCS reconstruction error to a desired value, while the latter are implemented to reduce the energy consumption of each node. A performance evaluation of the proposed scheme is carried out in terms of reconstruction error regulation and network lifetime. Simulation results show the effectiveness of the proposed scheme compared with two main strategies existing in the literature

Enhancing wireless networked monitoring system sustainability by multi-hop consensus algorithm

The widely studied consensus protocols have been increasingly used in industrial monitoring applications to support distributed process control. As the theoretical convergence rate covers vast interests in literature, techniques to speed up the convergence rate of consensus have been extensively explored, whereas their effects on the energetic consumption and on the sensor node technology have received a relatively lower attention. This work proposes to analyze jointly the energetic consumption and the consensus convergence rate in a Wireless Sensor Network scenario. Two different consensus techniques have been compared: the single-hop and the multi-hop algorithms. An environmental simulator has been built to validate the above techniques. Results show that multi-hop algorithm may be preferable to preserve the network lifetime, while the single-hop is more suitable in order to achieve higher speed of convergence