Book Chapters

@inbook{dabedadiadcafe:2023:thecityproject,

title = {Data Integration in a Smart City: A Real Case},

author = {Luca Davoli and Laura Belli and Alessandro Dall'Olio and Francesco Di Nocera and Paolo Adorni and Alessandro Cantelli and Gianluigi Ferrari},

doi = {10.1007/978-3-031-39446-1_2},

year  = {2024},

date = {2024-01-01},

urldate = {2024-01-01},

booktitle = {Information and Communications Technologies for Smart Cities and Societies},

volume = {5},

pages = {11-24},

publisher = {Springer Nature Switzerland},

chapter = {2},

series = {THE CITY PROJECT},

abstract = {The introduction and continuous integration of Internet of Things (IoT)-oriented technologies in urban environments leads to enhanced solutions in several domains (such as mobility, health, energy management, environmental monitoring, etc.), thus making a city “smart” and ultimately benefiting the everyday life of its citizens. As IoT systems are widely known to be producers of (often a very large amount of) heterogeneous data, in this chapter we discuss a modular and scalable approach to handle IoT-based data collection and management in a real smart city case, namely, that of the city of Parma, Italy. The proposed IoT infrastructure, the core component of which is a logical processing entity, acting as middleware and denoted as “city2i®,” in charge of "digesting" the heterogeneous information generated by multiple data sources, allows the municipality to monitor the city status (from multiple perspectives) and to highlight “hidden” correlations among collected data.},

keywords = {},

pubstate = {published},

tppubtype = {inbook}

}

@inbook{damofe:2022:bll,

title = {A Sink-oriented Routing Protocol for Blue Light Link-based Mesh Network},

author = { Luca Davoli and Massimo Moreni and Gianluigi Ferrari},

editor = {Luca Davoli and Gianluigi Ferrari},

doi = {10.1049/PBTE101E_ch2},

year  = {2022},

date = {2022-06-15},

urldate = {2022-01-01},

booktitle = {Wireless Mesh Networks for IoT and Smart Cities: Technologies and Applications},

pages = {21-31},

publisher = {Institution of Engineering and Technology},

series = {Telecommunications},

keywords = {},

pubstate = {published},

tppubtype = {inbook}

}

@inbook{cidabefe:2022:wmn,

title = {Seamless IoT Mobile Sensing through Wi-Fi Mesh Networking},

author = { Antonio Cilfone and Luca Davoli and Laura Belli and Gianluigi Ferrari},

editor = {Luca Davoli and Gianluigi Ferrari},

doi = {10.1049/PBTE101E_ch4},

year  = {2022},

date = {2022-06-15},

urldate = {2022-01-01},

booktitle = {Wireless Mesh Networks for IoT and Smart Cities: Technologies and Applications},

pages = {67-80},

publisher = {Institution of Engineering and Technology},

series = {Telecommunications},

keywords = {},

pubstate = {published},

tppubtype = {inbook}

}

@inbook{dafe:2022:conclusions:wmn,

title = {Conclusions and future perspectives},

author = { Luca Davoli and Gianluigi Ferrari},

doi = {10.1049/PBTE101E_ch13},

year  = {2022},

date = {2022-06-15},

urldate = {2022-01-01},

booktitle = {Wireless Mesh Networks for IoT and Smart Cities: Technologies and Applications},

pages = {265-266},

publisher = {Institution of Engineering and Technology},

series = {Telecommunications},

keywords = {},

pubstate = {published},

tppubtype = {inbook}

}

@inbook{damagabecamasgrafe:2021:iomt:bc,

title = {Non-Invasive Psycho-Physiological Driver Monitoring through IoT-Oriented Systems},

author = {Luca Davoli and Veronica Mattioli and Sara Gambetta and Laura Belli and Luca Carnevali and Marco Martalò and Andrea Sgoifo and Riccardo Raheli and Gianluigi Ferrari},

editor = {Subhendu Kumar Pani and Priyadarsan Patra and Gianluigi Ferrari and Radoslava Kraleva and Xinheng Wang},

doi = {10.1049/PBHE034E_ch2},

isbn = {9781839532733},

year  = {2021},

date = {2021-12-28},

urldate = {2021-01-01},

booktitle = {The Internet of Medical Things: Enabling technologies and emerging applications},

pages = {19-33},

publisher = {Institution of Engineering and Technology},

address = {London, UK},

abstract = {The definition, analysis, and implementation of in-vehicle monitoring systems that collect data which are informative of the status of the joint driver-vehicle system, represent a topic of strong interest from both academic players and industrial manufacturers. Many external factors, such as road design, road layout, traffic flow and weather can influence and increase driving-related stress, potentially increasing risks. The ubiquitous diffusion of Internet of Things (IoT) technologies allows to collect heterogeneous data that can build the foundation for driver's psycho-physiological characterization, with the aim of improving safety and security while driving. This chapter evaluates and discusses the feasibility and usefulness of a non-invasive IoT-oriented driver monitoring infrastructure aiming at collecting physiological parameters (such as Heart Rate Variability, HRV) that may be adopted as biomarkers of the driver’s psycho-physiological state in different driving scenarios.},

keywords = {},

pubstate = {published},

tppubtype = {inbook}

}

@inbook{dabefe:2020:cnit,

title = {IoT-enabled Smart Monitoring and Optimization for Industry 4.0},

author = {Luca Davoli and Laura Belli and Gianluigi Ferrari},

editor = {Luigi Atzori and Gianluigi Ferrari},

url = {https://www.texmat.it/internet-of-things-technologies-challenges-and-impact.html},

isbn = {978-88-949-8239-8},

year  = {2020},

date = {2020-09-04},

booktitle = {Internet of Things: Techonologies, Challenges and Impact},

volume = {5},

pages = {207--226},

publisher = {TeXMAT},

address = {Roma, Italy},

chapter = {11},

abstract = {In the last decades, forward-looking companies have introduced Internet of Things (IoT) concepts in several industrial application scenarios, leading to the so-called Industrial IoT (IIoT) and, restricting to the manufacturing scenario, to Industry 4.0. Their ambition is to enhance, through proper field data collection and analysis, the productivity of their facilities and the creation of real-time digital twins of different industrial scenarios, aiming to significantly improve industrial management and business processes. Moreover, since modern companies should be as ``smart'' as possible and should adapt themselves to the varying nature of the digital supply chains, they need different mechanisms in order to (i) enhance the control of the production plant and (ii) comply with high-layer data analysis and fusion tools that can foster the most appropriate evolution of the company itself (thus lowering the risk of machine failures) by adopting a predictive approach. Focusing on the overall company management, in this chapter we present an example of a ``renovation'' process, based on: (i) digitization of the control quality process on multiple production lines, aiming at digitally collecting and processing information already available in the company environment; (ii) monitoring and optimization of the production planning activity through innovative approaches, aiming at extending the quantity of collected data and providing a new perspective of the overall current status of a factory; and (iii) a predictive maintenance approach, based on a set of heterogeneous analytical mechanisms to be applied to on-field data collected in different production lines, together with the integration of sensor-based data, toward a paradigm that can be denoted as Maintenance-as-a-Service (MaaS). In particular, these data are related to the operational status of production machines and the currently available warehouse supplies. Our overall goal is to show that IoT-based Industry 4.0 strategies allow to continuously collect heterogeneous Human-to-Things (H2T) and Machine-to-Machine (M2M) data, which can be used to optimize and improve a factory as a whole entity.},

keywords = {},

pubstate = {published},

tppubtype = {inbook}

}

@inbook{NguyenGia2020,

title = {Artificial Intelligence at the Edge in the Blockchain of Things},

author = {Tuan Nguyen Gia and Anum Nawaz and Jorge Peña Querata and Hannu Tenhunen and Tomi Westerlund},

doi = {10.1007/978-3-030-49289-2_21},

issn = {1867-822X},

year  = {2020},

date = {2020-01-01},

urldate = {2020-01-01},

booktitle = {Wireless Mobile Communication and Healthcare},

pages = {267–280},

publisher = {Springer International Publishing},

keywords = {},

pubstate = {published},

tppubtype = {inbook}

}

@inbook{becidafemei:2020:igi,

title = {Applying Security to a Big Stream Cloud Architecture for the Internet of Things},

author = { Laura Belli and Simone Cirani and Luca Davoli and Gianluigi Ferrari and Lorenzo Melegari and Marco Picone},

url = {https://doi.org/10.4018/978-1-5225-9866-4.ch057},

doi = {10.4018/978-1-5225-9866-4.ch057},

isbn = {9781522598664},

year  = {2020},

date = {2020-01-01},

booktitle = {Securing the Internet of Things: Concepts, Methodologies, Tools, and Applications},

pages = {1260--1284},

publisher = {IGI Global},

address = {Hershey, PA, USA},

abstract = {The Internet of Things (IoT) is expected to interconnect billions (around 50 by 2020) of heterogeneous sensor/actuator-equipped devices denoted as “Smart Objects” (SOs), characterized by constrained resources in terms of memory, processing, and communication reliability. Several IoT applications have real-time and low-latency requirements and must rely on architectures specifically designed to manage gigantic streams of information (in terms of number of data sources and transmission data rate). We refer to “Big Stream” as the paradigm which best fits the selected IoT scenario, in contrast to the traditional “Big Data” concept, which does not consider real-time constraints. Moreover, there are many security concerns related to IoT devices and to the Cloud. In this paper, we analyze security aspects in a novel Cloud architecture for Big Stream applications, which efficiently handles Big Stream data through a Graph-based platform and delivers processed data to consumers, with low latency. The authors detail each module defined in the system architecture, describing all refinements required to make the platform able to secure large data streams. An experimentation is also conducted in order to evaluate the performance of the proposed architecture when integrating security mechanisms.},

keywords = {},

pubstate = {published},

tppubtype = {inbook}

}

@inbook{BC_FoCiFe_IET19,

title = {A distributed approach to energy-efficient data confidentiality in the Internet of Things},

author = {Andrea G. Forte and Simone Cirani and Gianluigi Ferrari},

url = {https://digital-library.theiet.org/content/books/pc/pbpc025e},

isbn = {978-1-78561-636-5},

year  = {2019},

date = {2019-11-13},

pages = {75-92},

publisher = {IET},

address = {Stevenage, UK},

chapter = {5},

abstract = {In the Internet of Things (IoT) everything will be connected, from refrigerators to coffee machines, to shoes. Many such “things” will have a very limited amount of energy to operate, often harvested from their own environment. Providing data confidentiality for such energy constrained devices has proven to be a hard problem. In this article, we discuss existing approaches to data-confidentiality for energy-constrained devices and propose a novel approach to drastically reduce a node’s energy consumption during encryption and decryption. In particular, we propose to distribute encryption and decryption computations among a set of trusted nodes. We validate the proposed approach through both simulations and experiments. Initial results show that the proposed approach leads to energy savings (from a single node’s perspective) of up to 73% and up to 81% of the energy normally spent to encrypt and decrypt, respectively. With such great savings, our approach holds the promise to enable data confidentiality also for those devices, with extremely limited energy, which will become commonplace in the IoT.},

keywords = {},

pubstate = {published},

tppubtype = {inbook}

}

@inbook{dabefe:2019:ijdst,

title = {Enhancing Security in a Big Stream Cloud Architecture for the Internet of Things Through Blockchain},

author = { Luca Davoli and Laura Belli and Gianluigi Ferrari},

editor = { Gabor Kecskemeti},

doi = {10.4018/978-1-5225-8295-3.ch005},

isbn = {978-152-25-8295-3},

year  = {2019},

date = {2019-05-14},

booktitle = {Applying Integration Techniques and Methods in Distributed Systems and Technologies},

pages = {104-133},

publisher = {IGI Global},

address = {Hershey, PA},

abstract = {The Internet of Things (IoT) paradigm is foreseeing the development of our environment towards new enriched spaces in most areas of modern living, such as digital health, smart cities, and smart agriculture. Several IoT applications also have real-time and low-latency requirements and must rely on specific architectures. The authors refer to the paradigm that best fits the selected IoT scenario as “Big Stream” because it considers real-time constraints. Moreover, the blockchain concept has drawn attention as the next-generation technology through the authentication of peers that share encryption and the generation of hash values. In addition, the blockchain can be applied in conjunction with Cloud Computing and the IoT paradigms, since it avoids the involvement of third parties in a broker-free way. In this chapter, an analysis on mechanisms that can be adopted to secure Big Stream data in a graph-based platform, thus delivering them to consumers in an efficient and secure way, and with low latency, is shown, describing all refinements required employing federation-based and blockchain paradigms.},

keywords = {},

pubstate = {published},

tppubtype = {inbook}

}

@inbook{davefeam:2019,

title = {Internet of Things on Power Line Communications: An Experimental Performance Analysis},

author = {Luca Davoli and Luca Veltri and Gianluigi Ferrari and Umberto Amadei},

editor = {Ersan Kabalci and Yasin Kabalci},

url = {https://link.springer.com/chapter/10.1007%2F978-981-13-1768-2_13},

doi = {10.1007/978-981-13-1768-2_13},

isbn = {978-981-13-1768-2},

year  = {2018},

date = {2018-09-02},

booktitle = {Smart Grids and Their Communication Systems},

pages = {465-498},

publisher = {Springer Singapore},

address = {Singapore},

edition = {1},

chapter = {13},

series = {Energy Systems in Electrical Engineering},

abstract = {The giant information exchange enabled by the Internet of Things (IoT) paradigm, i.e. by a "network of networks" of smart and connected devices, will likely exploit electrical lines as a ready-to-use infrastructure. Power Line Communications (PLC) have received a significant attention in the last decade, as electrical lines are not used as simple energy supply media, but as information carriers. Among the different aspects of PLC-based architectures, an interesting and important analysis have to be reserved to security aspects that should be adopted in similar infrastructures, having that they are crucial to deliver trustworthy and reliable systems and, hence, to support users relying on available services, especially in case in which they should be inherently secure at the physical level (e.g. against unauthorised signal removal/interruption and eavesdropping, since they are difficult and dangerous). Motivated by the relevant impact of PLC on IoT, in this chapter we investigate experimentally the performance of IoT systems on PLC in indoor environments, considering a vendor-provided application tool and a self-developed Java library. The experimental tests are carried out on both cold and hot electrical lines, evaluating both fixed-size and variable-length power lines. Our results show that IoT-oriented PLC can reach a throughput of 8 kbps on a 300-m cold line and of 6 kbps on a 300-m hot line. Further experimental efforts will be oriented to performance analyses in presence of the adoption of security measures.},

keywords = {},

pubstate = {published},

tppubtype = {inbook}

}

@inbook{Kheireddine2015,

title = {Genetic Centralized Dynamic Clustering in Wireless Sensor Networks},

author = {Mekkaoui Kheireddine and Rahmoun Abdellatif and Gianluigi Ferrari},

editor = {Abdelmalek Amine and Ladjel Bellatreche and Zakaria Elberrichi and Erich Neuhold and Robert Wrembel},

url = {http://dx.doi.org/10.1007/978-3-319-19578-0_41},

isbn = {978-3-319-19578-0},

year  = {2015},

date = {2015-01-01},

booktitle = {Computer Science and Its Applications: 5th IFIP TC 5 International Conference, CIIA 2015, Saida, Algeria, May 20-21, 2015, Proceedings},

pages = {503--511},

publisher = {Springer International Publishing},

address = {Cham},

abstract = {In order to overcome the energy loss involved by communications in wireless sensor networks (WSN), the use of clustering has proven to be effective. In this paper, we proposed a dynamic centralized genetic algorithm (GA)-based clustering approach to optimize the clustering configuration (cluster heads and cluster members) to limit node energy consumption. The obtained simulation results show that the proposed technique overcomes the LEACH clustering algorithm.},

keywords = {},

pubstate = {published},

tppubtype = {inbook}

}

@inbook{AbMaFe2015,

title = {Decision fusion in cognitive wireless sensor networks},

author = {Andrea Abrardo and Marco Martalò and Gianluigi Ferrari},

editor = {Hassen Fourati},

url = {https://www.crcpress.com/Multisensor-Data-Fusion-From-Algorithms-and-Architectural-Design-to-Applications/Fourati/p/book/9781482263749},

isbn = {9781482263749},

year  = {2015},

date = {2015-01-01},

booktitle = {Multisensor Data Fusion: From Algorithms and Architectural Design to Applications},

pages = {349-362},

publisher = {CRC Press},

abstract = {In this chapter, we focus on a cognitive WSN, where a primary wireless sensor network (PWSN) is co-located with a cognitive (or secondary) sensor network (CWSN). In particular, the nodes of the CWSN reach their associated access point (AP) directly (single hop). The frequency spectrum that is shared by PWSN and CWSN is divided into subchannels, which can be assigned by the PWSN, whereas the nodes of the CWSN cooperate to sense the frequency spectrum and estimate the free subchannels that can be used to transmit their data. The secondary nodes transmit the packets containing the observations on the channels’ statuses to their FC, embedded in the secondary AP, which makes a final decision about the status (free or busy) of each subchannel and broadcasts this information to all secondary nodes. The correlation, in the sensing operation, among the secondary nodes is taken into account. In particular, we provide a simple analytical model to characterize the local sensing performance per subchannel, in terms of probabilities of missed detection (MD) and false alarm (FA). Moreover, we propose a joint source channel coding (JSCC) scheme, in the CWSN, to exploit the source correlation to improve the reliability of the final decision taken by the secondary FC. By relying on recent results on the design of practical decoding and fusion rules for multiple access schemes with correlated sources [9], we derive an effective fusion rule and an associated iterative decoding strategy for joint channel decoding (JCD) at the secondary FC.},

keywords = {},

pubstate = {published},

tppubtype = {inbook}

}

@inbook{Monica2015b,

title = {A Swarm Intelligence Approach to 3D Distance-Based Indoor UWB Localization},

author = {Stefania Monica and Gianluigi Ferrari},

editor = {Antonio M. Mora and Giovanni Squillero},

url = {http://dx.doi.org/10.1007/978-3-319-16549-3_8},

isbn = {978-3-319-16549-3},

year  = {2015},

date = {2015-01-01},

booktitle = {Applications of Evolutionary Computation: 18th European Conference, EvoApplications 2015, Copenhagen, Denmark, April 8-10, 2015, Proceedings},

pages = {91--102},

publisher = {Springer International Publishing},

address = {Cham},

abstract = {In this paper, we focus on the application of Ultra Wide Band (UWB) technology to the problem of locating static nodes in three-dimensional indoor environments, assuming to know the positions of a few nodes, denoted as “beacons.” The localization algorithms which are considered throughout the paper are based on the Time Of Arrival (TOA) of signals traveling between pairs of nodes. In particular, we propose to apply the Particle Swarm Optimization (PSO) algorithm to solve the localization problem and we compare its performance with that of the Two-Stage Maximum-Likelihood (TSML) algorithm. Simulation results show that the former allows achieving accurate position estimates even in scenarios where, because of ill-conditioning problems associated with the network topology, TSML fails.},

keywords = {},

pubstate = {published},

tppubtype = {inbook}

}

@inbook{Belli2015,

title = {A Graph-Based Cloud Architecture for Big Stream Real-Time Applications in the Internet of Things},

author = {Laura Belli and Simone Cirani and Gianluigi Ferrari and Lorenzo Melegari and Marco Picone},

editor = {Guadalupe Ortiz and Cuong Tran},

url = {http://dx.doi.org/10.1007/978-3-319-14886-1_10},

isbn = {978-3-319-14886-1},

year  = {2015},

date = {2015-01-01},

booktitle = {Advances in Service-Oriented and Cloud Computing: Workshops of ESOCC 2014, Manchester, UK, September 2-4, 2014, Revised Selected Papers},

pages = {91--105},

publisher = {Springer International Publishing},

address = {Cham},

abstract = {The Internet of Things (IoT) will consist of billions of interconnected heterogeneous devices denoted as “smart objects.” Smart objects are generally sensor/actuator-equipped and have constrained resources in terms of: (i) processing capabilities; (ii) available ROM/RAM; and (iii) communication reliability. To meet low-latency requirements, real-time IoT applications must rely on specific architectures designed in order to handle and process gigantic (in terms of number of sources of information and rate of received data) streams of data coming from smart objects. We refer to this smart object-generated data stream as “Big Stream,” in contrast to traditional “Big Data” scenarios, where real-time constraints are not considered. In this paper, we propose a novel Cloud architecture for Big Stream applications that can efficiently handle data coming from deployed smart objects through a graph-based processing platform and deliver processed data to consumer applications with lowest latency.},

keywords = {},

pubstate = {published},

tppubtype = {inbook}

}

@inbook{Amoretti2015bc,

title = {Simulating wireless and mobile systems: The Integration of DEUS and Ns-3},

author = {Michele Amoretti and Marco Picone and Francesco Zanichelli and Gianluigi Ferrari},

editor = {Mohammad S. Obaidat and Petros Nicopolitidis and Faouzi Zarai},

url = {http://www.sciencedirect.com/science/article/pii/B978012800887400016X},

isbn = {978-0-12-800887-4},

year  = {2015},

date = {2015-01-01},

booktitle = {Modeling and Simulation of Computer Networks and Systems},

pages = {465 - 484},

publisher = {Morgan Kaufmann},

address = {Boston},

chapter = {16},

abstract = {Wireless and mobile experiments in the real world are not easily or accurately repeatable, reducing the usefulness of such experiments for validation. Most challenges are due to the complications and subtleties of physical movement and wireless propagation, making the system highly variable. Moreover, mobile and distributed applications are characterized by decentralized goals and control, with high levels of concurrency and asynchronous interaction. For the qualitative and quantitative analysis of such systems, discrete event modeling and simulation—in which time jumps from event to event—are usually adopted. Widely known discrete event simulation tools, such as ns-2, ns-3, and OMNeT++, are highly specialized in communication networks. As they are not general-purpose, they can hardly support the analysis of large-scale distributed applications. Conversely, general-purpose tools like DEUS and CD++ are not provided with sound, highly recognized packages for the simulation of networking aspects. To fill the gaps between the two families of discrete event simulators, a co-simulation (co-operative simulation) approach may be very efficient. In this chapter, we review the existing approaches for co-simulation of wireless and mobile systems. We then focus on a recently adopted co-simulation approach, allowing individual components to be simulated by different simulation tools, exchanging information in a collaborative manner. In particular, DEUS (which is application-level oriented, Java-based, and characterized by ease of use and flexibility) is integrated with ns-3 (which is generally known as a highly reliable and complete open-source C++ tool for the discrete event simulation of Internet systems). We then propose a specific application, where ns-3’s LTE-EPC package supports the DEUS-based simulation of a peer-to-peer overlay scheme called Distributed Geographic Table (DGT), which allows mobile nodes to efficiently share information without centralized control.},

keywords = {},

pubstate = {published},

tppubtype = {inbook}

}

@inbook{Giuberti2015,

title = {Motion Capture: From Radio Signals to Inertial Signals},

author = {Matteo Giuberti and Gianluigi Ferrari},

editor = {Sasan Adibi},

url = {http://dx.doi.org/10.1007/978-3-319-12817-7_34},

isbn = {978-3-319-12817-7},

year  = {2015},

date = {2015-01-01},

booktitle = {Mobile Health: A Technology Road Map},

pages = {791--812},

publisher = {Springer International Publishing},

address = {Cham},

abstract = {The study of the motion of individuals allows to gather relevant information on a person status, to be used in several fields (e.g., medical, sport, and entertainment). Over the past decade, the research activity in motion capture has benefited from the progress of portable and mobile sensors, paving the way toward the use of motion capture techniques in mHealth applications (e.g., remote monitoring of patients, and telerehabilitation). Indeed, even if the optical motion capture, which typically relies on a set of fixed cameras and body-worn reflecting markers, is generally perceived as the standard reference approach, other motion capture techniques, such as radio and inertial, are attracting an increasing attention because of their suitability in remote mHealth applications. Moreover, several hybrid approaches have been studied and proposed in order to overcome the limitations of component technologies considered independently. In this chapter, we present an overview of possible integration strategies between radio and inertial motion capture techniques. We start by investigating a radio-based approach, based on the fingerprinting radio localization technique. Then, the previous approach is improved by integrating inertial measurements: namely, accelerometers are used to provide an estimate of the nodes’ pitches. Finally, the radio signals are abandoned in favor of only inertialmeasurements (obtained through accelerometers, gyroscopes, and magnetometers). The advantages and limitations of all approaches are discussed in a comparative way, characterizing the similarities and differences between the various approaches.},

keywords = {},

pubstate = {published},

tppubtype = {inbook}

}

@inbook{MeLeDuRoDuRaFeGoCiVeMoDoDoViDu14,

title = {Bringing IP to Low-power Smart Objects: The Smart Parking Case in the CALIPSO Project},

author = {Paolo Medagliani and Jérémie Leguay and Andrzej Duda and Franck Rousseau and Simon Duquennoy and Shahid Raza and Gianluigi Ferrari and Pietro Gonizzi and Simone Cirani and Luca Veltri and Màrius Montón and Marc D. Prieto and Mischa Dohler and Ignacio Villajosana and Oliver Dupont},

editor = {Ovidiu Vermesan and Peter Friess},

url = {http://www.internet-of-things-research.eu/pdf/IERC_Cluster_Book_2014_Ch.3_SRIA_WEB.pdf},

isbn = {9788793102941},

year  = {2014},

date = {2014-06-23},

pages = {287-313},

publisher = {The River Publishers Series in Communications},

address = {Alborg, Denmark},

keywords = {},

pubstate = {published},

tppubtype = {inbook}

}

@inbook{SpiBu12,

title = {Heterogeneous Cellular Networks},

author = {Giovanni Spigoni and Stefano Busanelli and Marco Martalò and Gianluigi Ferrari and Nicola Iotti},

year  = {2012},

date = {2012-01-01},

publisher = {John Wiley & Sons},

chapter = {``Vertical Handover in Heterogeneous Net},

note = {Eds.: R. Q. Hu and Y. Qian},

keywords = {},

pubstate = {published},

tppubtype = {inbook}

}

@inbook{GoFeLeMe12,

title = {``Wireless Sensor Networks: From Theory to Applications''},

author = {Pietro Gonizzi and Gianluigi Ferrari and Jérémie Leguay and Paolo Medagliani},

isbn = {9781466518100},

year  = {2012},

date = {2012-01-01},

publisher = {CRC Press, Taylor and Francis Group},

chapter = {``Distributed Data Storage and Retrieval},

note = {Eds.: I. M. M. El Emary and S. Ramakrishnan},

keywords = {},

pubstate = {published},

tppubtype = {inbook}

}

@inbook{BuFe11,

title = {Communication and Networking, Part I},

author = {Stefano Busanelli and Gianluigi Ferrari},

year  = {2011},

date = {2011-01-01},

pages = {188-198},

publisher = {Springer-Verlag},

chapter = {``UWB-based Tracking of Autonomous Vehic},

note = {Eds.: C.-C. Chang, M. Li, C. Rong, C. Z. Patrikakis, and D. Slezak},

keywords = {},

pubstate = {published},

tppubtype = {inbook}

}

@inbook{BuMaFeSpIo11,

title = {Communication and Networking, Part I},

author = {Stefano Busanelli and Marco Martalò and Gianluigi Ferrari and Giovanni Spigoni and Nicola Iotti},

year  = {2011},

date = {2011-01-01},

pages = {137-146},

publisher = {Springer-Verlag},

chapter = {``Experimental Investigation of Vertical},

note = {Eds.: C.-C. Chang, M. Li, C. Rong, C. Z. Patrikakis, and D. Slezak},

keywords = {},

pubstate = {published},

tppubtype = {inbook}

}

@inbook{BuFe10,

title = {The Internet of Things: 20th Tyrrhenian Workshop on Digital Communications},

author = {Stefano Busanelli and Gianluigi Ferrari},

year  = {2010},

date = {2010-01-01},

pages = {59-68},

publisher = {Springer-Verlag},

chapter = {``Cluster-Based Irresponsible Forwarding},

note = {Eds.: D. Giusto, A. Iera, G. Morabito, and L. Atzori},

keywords = {},

pubstate = {published},

tppubtype = {inbook}

}

@inbook{MaFe10c,

title = {The Internet of Things: 20th Tyrrhenian Workshop on Digital Communications},

author = {Marco Martalò and Gianluigi Ferrari},

year  = {2010},

date = {2010-01-01},

pages = {167-176},

publisher = {Springer-Verlag},

chapter = {``Low-Complexity Audio Signal Processing},

note = {Eds.: D. Giusto, A. Iera, G. Morabito, and L. Atzori},

keywords = {},

pubstate = {published},

tppubtype = {inbook}

}

@inbook{MeFeGeCa10,

title = {Cross-layer STP-based Networks: Analysis and Design},

author = {Paolo Medagliani and Gianluigi Ferrari and Gianpietro Germi and Fabio Cappelletti},

year  = {2010},

date = {2010-01-01},

publisher = {Nova Science Publisher},

note = {Ed.: J. E. Morris},

keywords = {},

pubstate = {published},

tppubtype = {inbook}

}

@inbook{MeFeMa10,

title = {Remote Instrumentation and Virtual Laboratories},

author = {Paolo Medagliani and Gianluigi Ferrari and Marco Martalò},

year  = {2010},

date = {2010-01-01},

pages = {473-491},

publisher = {Springer-Verlag},

chapter = {``Hybrid Zigbee-RFID Networks for Energy},

note = {Eds.: F. Davoli, N. Meyer, R. Pugliese, and S. Zappatore},

keywords = {},

pubstate = {published},

tppubtype = {inbook}

}

@inbook{DrFeDe09,

title = {Communication and Networking},

author = {Jean-Michel Dricot and Gianluigi Ferrari and Philippe De Doncker},

year  = {2009},

date = {2009-01-01},

pages = {324-333},

publisher = {Springer-Verlag},

chapter = {``Cross-Layering between Physical Layer },

note = {Eds.: D. Slezak, T.-H. Kim, A. C.-C. Chang, T. Vasilakos, M. Li, and K. Sakurai},

keywords = {},

pubstate = {published},

tppubtype = {inbook}

}

@inbook{FeMaSa07,

title = {Grid Enabled Instrumentation and Measurement},

author = {Gianluigi Ferrari and Marco Martalò and Marco Sarti},

year  = {2007},

date = {2007-01-01},

pages = {33-54},

publisher = {Springer-Verlag},

chapter = {``Reduced-complexity Decentralized Detec},

note = {Eds.: F. Davoli, N. Meyer, R. Pugliese, and S. Zappatore},

keywords = {},

pubstate = {published},

tppubtype = {inbook}

}

@inbook{FeMeMa07,

title = {Grid Enabled Instrumentation and Measurement},

author = {Gianluigi Ferrari and Paolo Medagliani and Marco Martalò},

year  = {2007},

date = {2007-01-01},

pages = {55-79},

publisher = {Springer-Verlag},

chapter = {``Performance Analysis of Zigbee Wireles},

note = {Eds.: F. Davoli, N. Meyer, R. Pugliese, and S. Zappatore},

keywords = {},

pubstate = {published},

tppubtype = {inbook}

}

@inbook{FePa06,

title = {Distributed Cooperative Laboratories: Networking, Instrumentation, and Measurements (Signals and Communication Technology)},

author = {Gianluigi Ferrari and Roberto Pagliari},

year  = {2006},

date = {2006-01-01},

pages = {233--249},

publisher = {Springer-Verlag},

chapter = {``Data Acqusition and Aggregation in Sen},

note = {Eds.: F. Davoli, S. Palazzo, and S. Zappatore},

keywords = {},

pubstate = {published},

tppubtype = {inbook}

}

@inbook{FeCoRa01b,

title = {Turbo Codes: Error-correcting Codes of Widening Application},

author = {Gianluigi Ferrari and Giulio Colavolpe and Riccardo Raheli},

year  = {2002},

date = {2002-01-01},

pages = {59-81},

publisher = {Hermes Penton Science},

address = {London},

chapter = {``Noncoherent iterative decoding of spec},

note = {Eds.: M. Jézéquel and R. Pyndiah},

keywords = {},

pubstate = {published},

tppubtype = {inbook}

}