PHD THESES

Dr. Stefano Galzarano, "Autonomic Computing-Based Wireless Sensor Networks", 2013

Wireless Sensor Networks (WSNs) have grown in popularity in the last years by proving to be a beneficial technology for a wide range of application domains, including but not limited to health-care, environment and infrastructure monitoring, smart home automation, industrial control, intelligent agriculture, and emergency management. However, developing applications on such systems requires many efforts due to the lack of proper software abstractions and the diculties in managing resource-constrained embedded environments. Moreover, these applications have to meet a combination of conficting requirements. Achieving accuracy, efficiency, correctness, fault-tolerance, adaptability and reliability on WSN is a major issue because these features have to be provided beyond the design/implementation phase, notably at execution time. This thesis explores the viability and convenience of Autonomic Computing in the context of WSNs by providing a novel paradigm to support the development of autonomic WSN applications as well as speci c self-adaptive protocols at networking levels. In particular, this thesis provides three main contributions. The rst is the design and realization of a novel framework for the development of ecient distributed signal processing applications on heterogeneous WSNs, called SPINE2. It provides a programming abstraction based on the task-oriented paradigm for abstracting away low-level details and has a platform-independent architecture enabling code reusability and portability, application interoperability and platform heterogeneity. The second contribution is the development of SPINE-* which is an enhancement of SPINE2 by means of an autonomic plane, a way for separating out the provision of self-* techniques from the WSN application logic. Such a separation of concerns leads to an ease of deployment and run-time management of new applications. We find that this enhancement brings not only considerable functional improvements but also measurable performance bene ts. Third, since we advocate that the agent-oriented paradigm is a well-suited approach in the context of autonomic computing, we propose MAPS, an agent-based programming framework for WSNs. Specifically designed for supporting Java-based sensor platforms, MAPS allows the development of general-purpose mobile multi-agent applications by adopting a multi-plane state machine formalism for defining agents' behavior. Finally, the fourth contribution regards the design, analysis, and simulations of a self-adaptive AODV routing protocol enhancement, CG-AODV, and a novel contention-based MAC protocol, QL-MAC. CG-AODV adopts a "node concentration-driven gossipin"g approach for limiting the flooding of control packets, whereas QL-MAC, based on a Q-learning approach, aims to find an efficient radio wake-up/sleep scheduling strategy to reduce energy consumption on the basis of the actual network load of the neighborhood. Simulation results show that CG-AODV outperforms AODV, whereas QL-MAC provides better performance over standard MAC protocols.

Dr. Raffaele Gravina, "A Domain-Specific Approach for Programming Wireless Body Sensor Network Systems", 2011

Abstract: The progress of science and medicine during the last years has contributed to significantly increase the average life expectancy. The increase of elderly population will have a large impact especially on the health care system. Furthermore, especially in more developed countries, there is an always growing interest in maintaining, and improving the quality of life. Wireless Body Sensor Networks (BSNs) can contribute to improve the quality of health care services. BSNs involve wireless wearable physiological sensors applied to the human body for strictly medical and non medical purposes. They can enhance many human-centered application domains such as e-Health, sport and wellness, and even social applications such as physical/virtual social interactions. However, there are still open issues that limit their wide diffusion in real life; primarily, the programming complexity of these systems, due to lack of high-level software abstractions, and to hardware constraints of wearable devices. In contrast to low-level programming and general-purpose middleware, domain-specific frameworks are an emerging programming paradigm designed to fulfill the lack of suitable BSN programming support. With this aim, this thesis proposes a novel domain-specific approach for programming signal-processing intensive BSN applications. The definition of this approach resulted in a domain-specific programming framework named SPINE (Signal Processing in Node Environment) which is one important contribution of this thesis, along with other interesting contributions derived from enhancements and variants to the main proposal. Additionally, to provide validation and performance evaluation of the proposed approach, a number of BSN applications (including human activity monitoring, physical energy expenditure estimation, emotional stress detection, and step-counting) have been developed atop SPINE. These research prototypes showed the effectiveness and efficiency of the proposed approach and improved their respective state-of-the-art. Finally, a Platform-Based Design (PBD) methodology, which is widely adopted for the design of traditional embedded systems, is proposed for the design of BSN systems.

Dr. Antonio Guerrieri, "High-level Frameworks for the Development of Wireless Sensor Network Applications", 2011

Abstract: Wireless Sensor Networks (WSNs) are emerging as powerful platforms for distributed embedded computing supporting a variety of high-impact applications. A WSN is a group of small devices (nodes) capable to sample the real world through sensors, actuate commands through actuators, elaborate data on the node, and send messages to other nodes through radio communication. However, programming WSN applications is a complex task that requires suitable paradigms and technologies capable of supporting the specific characteristics of such networks which uniquely integrate distributed sensing, computation and communication. This thesis aims at providing new paradigms to support the development of WSN applications through both a domain-specific and a general-purpose approach. In particular, this thesis provides three main contributions. The first is related to the analysis, design and realization of a domain-speci c frame- work for heterogeneous WSNs for exible and ecient distributed sensing and actuation in buildings called Building Management Framework (BMF). BMF provides fast WSN reconfiguration, in-node processing algorithms, multi-hop networks, and multi-platform support, a programming abstraction to dynamically catch the morphology of buildings, actuators support, and an extensible human computer interface. The second contribution refers to the analysis, design and realization of a general-purpose mobile agent system for WSN, namely MAPS (Multi Agent Platform for SunSPOT). MAPS allows an effective Java-based development of agents and agent-based applications for WSNs by integrating agent oriented, event-driven and state-based programming paradigms. Finally, the third contribution regards the analysis, design and realization of a domain-specific framework for rapid prototyping of platform independent Wireless Body Sensor Network (WBSN) applications, namely SPINE2 (signal processing in-node environment version 2). SPINE2 aims at supporting the development of WSN applications raising the level of the used programming abstractions by providing a task-oriented programming model.

(MSc Thesis) Mr. Stefano Galzarano, "A lightweight framework for task oriented programming of signal processing applications on wireless sensor networks", 2010.

Abstract: Wireless sensor networks (WSNs) represent a form of pervasive and ubiquitous computing system. They have been successfully used in many different application areas and in future they will play an increasingly important role. It is not unreasonable to expect that sensor networks will be a fundamental part of our life, with profound impact on our daily activities. However, development of applications for WSNs is an extremely challenging and error-prone task since it requires programming individual nodes using low-level APIs. This implies knowledge from many different areas, ranging from sensor nodes hardware and radio communication to high-level concepts concerning the final user applications. The lack of easiness in programming WSNs represents the main obstacle to the current wide diffusion of this technology. The need for high-level programming approaches is quite evident and currently many frameworks and middlewares have been proposed. However, many of the existent solutions are not suitable for application domains (i.e. context recognition, health monitoring, medical assistance, etc) requiring collaborative sensor data processing in the network. This thesis proposes a novel framework enabling intensive distributed signal processing-based applications. In particular, the framework provides an intuitive application design model based on the task-oriented approach and supported by an high-level specification language. The framework design and implementation based on the software layering approach allows fast porting to every C-like sensor platform, whereas its modular software architecture allows to easily extend the functionalities and the services provided to developers. Finally, the framework has been fully implemented and tested on TinyOS sensor platforms.

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