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Rossi M.,University of Padua | Bui N.,Consorzio Ferrara Ricerche | Zanca G.,University of Padua | Stabellini L.,KTH Royal Institute of Technology | And 2 more authors.
IEEE Transactions on Mobile Computing | Year: 2010

This paper presents SYNAPSE++, a system for over the air reprogramming of wireless sensor networks (WSNs). In contrast to previous solutions, which implement plain negative acknowledgment-based ARQ strategies, SYNAPSE++ adopts a more sophisticated error recovery approach exploiting rateless fountain codes (FCs). This allows it to scale considerably better in dense networks and to better cope with noisy environments. In order to speed up the decoding process and decrease its computational complexity, we engineered the FC encoding distribution through an original genetic optimization approach. Furthermore, novel channel access and pipelining techniques have been jointly designed so as to fully exploit the benefits of fountain codes, mitigate the hidden terminal problem and reduce the number of collisions. All of this makes it possible for SYNAPSE++ to recover data over multiple hops through overhearing by limiting, as much as possible, the number of explicit retransmissions. We finally created new bootloader and memory management modules so that SYNAPSE++ could disseminate and load program images written using any language. At the end of this paper, the effectiveness of SYNAPSE++ is demonstrated through experimental results over actual multihop deployments, and its performance is compared with that of Deluge, the de facto standard protocol for code dissemination in WSNs. The TinyOS 2 code of SYNAPSE++ is available at http://dgt.dei.unipd.it/download. © 2006 IEEE. Source

Stamatiou K.,Catalonia Technology Center of Telecomunications | Casari P.,University of Padua | Zorzi M.,Consorzio Ferrara Ricerche
IEEE Transactions on Wireless Communications | Year: 2013

We propose a theoretical framework to evaluate the expected throughput of underwater networks over an ensemble of node topologies and propagation environments. The analysis is based on the assumptions that the transmitters are spatially distributed according to a Poisson point process, and that the channel follows a Rayleigh fading distribution, with a mean that is determined by spreading loss and frequency-dependent absorption. We evaluate the probability of a successful transmission, i.e., the probability that the signal-to-interference-and-noise ratio at the typical receiver is greater than a given threshold, and determine the maximum network throughput density over the transmitter density and the operating frequency. The theoretical results are validated using a realistic underwater channel simulator based on ray tracing. It is demonstrated that, for a number of practical scenarios, the theoretical and simulated throughput match provided that the spreading-loss exponent is appropriately fitted to the simulation scenario. Overall, the proposed framework provides easy-to-obtain network throughput results, which can be used as a complement or an alternative to time-costly, deployment-dependent network simulations. © 2002-2012 IEEE. Source

Agency: Cordis | Branch: FP7 | Program: CP | Phase: ICT-2007.1.1 | Award Amount: 23.17M | Year: 2008

In order to realise the vision of Ambient Intelligence in a future network and service environment, heterogeneous wireless sensor and actuator networks (WS&AN) have to be integrated into a common framework of global scale and made available to services and applications via universal service interfaces. SENSEI creates an open, business driven architecture that fundamentally addresses the scalability problems for a large number of globally distributed WS&A devices. It provides necessary network and information management services to enable reliable and accurate context information retrieval and interaction with the physical environment. By adding mechanisms for accounting, security, privacy and trust it enables an open and secure market space for context-awareness and real world interaction.\n\nTangible results of the SENSEI project are: 1) A highly scalable architectural framework with corresponding protocol solutions that enable easy plug and play integration of a large number of globally distributed WS&AN into a global system -providing support for network and information management, security, privacy and trust and accounting. 2) An open service interface and corresponding semantic specification to unify the access to context information and actuation services offered by the system for services and applications. 3) Efficient WS&AN island solutions consisting of a set of cross-optimised and energy aware protocol stacks including an ultra low power multi-mode transceiver targeting 5nJ/bit. 4) Pan European test platform, enabling large scale experimental evaluation of the SENSEI results and execution of field trials - providing a tool for long term evaluation of WS&AN integration into the Future Internet.\n\nTechnology developed by SENSEI will play an essential part in transforming the existing Internet, Mobile Networks and Service Infrastructures into a Network of the Future that is capable to deal with the challenging demands of a Future Networked Society.

Michelusi N.,University of Southern California | Badia L.,University of Padua | Carli R.,University of Padua | Corradini L.,University of Padua | Zorzi M.,Consorzio Ferrara Ricerche
IEEE Transactions on Communications | Year: 2013

Energy Harvesting Wireless Sensor Devices are increasingly being considered for deployment in sensor networks, due to their demonstrated advantages of prolonged lifetime and autonomous operation. However, irreversible degradation mechanisms jeopardize battery lifetime, calling for intelligent management policies, which minimize the impact of these phenomena while guaranteeing a minimum Quality of Service (QoS). This paper explores a mathematical characterization of these devices, focusing on the interplay between the battery discharge policy and the irreversible degradation of the storage capacity. We propose a stochastic Markov chain framework, suitable for policy optimization, which captures the degradation status of the battery. We present a general result of Markov chains, which exploits the timescale separation between the communication time-slot of the device and the battery degradation process, and enables an efficient optimization. We show that this model fits well the behavior of real batteries for what concerns their storage capacity degradation over time. We demonstrate that a degradation-aware policy significantly improves the lifetime of the sensor compared to "greedy" policies, while guaranteeing the minimum required QoS. Finally, a simple heuristic policy, which never discharges the battery below a given threshold, is shown to achieve near-optimal performance in terms of battery lifetime. © 2013 IEEE. Source

Agency: Cordis | Branch: FP7 | Program: CP | Phase: ICT-2007.1.1 | Award Amount: 4.18M | Year: 2008

The primary aim of the ARAGORN project is to research and develop a Cognitive Resource Manager (CRM) that aims to ensure that efficient use is made of both node-local and shared resources in a collaborative wireless system. These include, for example, local energy consumption and shared use of available bandwidth. In order to achieve this, ARAGORN will develop a range of standardised interfaces, using which the CRM will be able both to obtain information from and to update the configuration of each layer of the protocol stack, including at the application layer. Given this, the CRM will seek to optimise cross-layer and inter-node performance using multi-dimensional optimisation algorithms provided by partners from the machine learning and artificial intelligence communities. The proposed approaches have been selected because of the need to synthesise a relatively low-dimensional response from the many potential dimensions that could affect the optimal, all in the presence of incomplete and out-of-date information.\nIn contrast to other cognitive radio research, the ARAGORN project does not focus on dynamic spectrum access networks but aims to add real cognition to mobile devices, enabling them to take reasonable decisions autonomously.\nThe main expected outcomes of the project are a solid basis of theoretical and architectural work for next generation cognitive radios and networks and a working prototype implementation. The prototype will apply the techniques developed and prove their practical feasibility working in one of the ISM frequency-bands. As key components of ARAGORN, exploitable interfaces and the Cognitive Resource Manager Framework will be implemented.\nThe high quality consortium possesses a unique combination of expertise from across the wireless, software and AI communities, and forms a well balanced team of academic and industrial partners, some of whom already participate in pertinent standardisation work.

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