Gianluigi Ferrari

Bio: Gianluigi Ferrari is an academic researcher from University of Parma. The author has contributed to research in topics: Wireless sensor network & Wireless network. The author has an hindex of 36, co-authored 340 publications receiving 5194 citations. Previous affiliations of Gianluigi Ferrari include University of Siena & University of Southern California.

A Scalable and Self-Configuring Architecture for Service Discovery in the Internet of Things

Abstract: The Internet of Things (IoT) aims at connecting billions of devices in an Internet-like structure. This gigantic information exchange enables new opportunities and new forms of interactions among things and people. A crucial enabler of robust applications and easy smart objects’ deployment is the availability of mechanisms that minimize (ideally, cancel) the need for external human intervention for configuration and maintenance of deployed objects. These mechanisms must also be scalable, since the number of deployed objects is expected to constantly grow in the next years. In this work, we propose a scalable and self-configuring peer-to-peer (P2P)-based architecture for large-scale IoT networks, aiming at providing automated service and resource discovery mechanisms, which require no human intervention for their configuration. In particular, we focus on both local and global service discovery (SD), showing how the proposed architecture allows the local and global mechanisms to successfully interact, while keeping their mutual independence (from an operational viewpoint). The effectiveness of the proposed architecture is confirmed by experimental results obtained through a real-world deployment.

IoTChain: A blockchain security architecture for the Internet of Things

Abstract: In this paper, we propose IoTChain, a combination of the OSCAR architecture [1] and the ACE authorization framework [2] to provide an E2E solution for the secure authorized access to IoT resources. IoTChain consists of two components, an authorization blockchain based on the ACE framework and the OSCAR object security model, extended with a group key scheme. The blockchain provides a flexible and trustless way to handle authorization while OSCAR uses the public ledger to set up multicast groups for authorized clients. To evaluate the feasibility of our architecture, we have implemented the authorization blockchain on top of a private Ethereum network. We report on several experiments that assess the performance of different architecture components.

IoT-OAS: An OAuth-Based Authorization Service Architecture for Secure Services in IoT Scenarios

Abstract: Open authorization (OAuth) is an open protocol, which allows secure authorization in a simple and standardized way from third-party applications accessing online services, based on the representational state transfer (REST) web architecture. OAuth has been designed to provide an authorization layer, typically on top of a secure transport layer such as HTTPS. The Internet of Things (IoTs) refers to the interconnection of billions of resource-constrained devices, denoted as smart objects, in an Internet-like structure. Smart objects have limited processing/memory capabilities and operate in challenging environments, such as low-power and lossy networks. IP has been foreseen as the standard communication protocol for smart object interoperability. The Internet engineering task force constrained RESTful environments working group has defined the constrained application protocol (CoAP) as a generic web protocol for RESTful-constrained environments, targeting machine-to-machine applications, which maps to HTTP for integration with the existing web. In this paper, we propose an architecture targeting HTTP/CoAP services to provide an authorization framework, which can be integrated by invoking an external oauth-based authorization service (OAS). The overall architecture is denoted as IoT-OAS. We also present an overview of significant IoT application scenarios. The IoT-OAS architecture is meant to be flexible, highly configurable, and easy to integrate with existing services. Among the advantages achieved by delegating the authorization functionality, IoT scenarios benefit by: 1) lower processing load with respect to solutions, where access control is implemented on the smart object; 2) fine-grained (remote) customization of access policies; and 3) scalability, without the need to operate directly on the device.

Ad Hoc Wireless Networks: A Communication-Theoretic Perspective

Abstract: Preface. List of Acronyms. 1 Related Work and Preliminary Considerations. 1.1 Introduction. 1.2 Related Work. 1.3 A New Perspective for the Design of Ad Hoc Wireless Networks. 1.4 Overview of the Underlying Assumptions in the Following Chapters. 1.5 The Main Philosophy Behind the Book. 2 A Communication-Theoretic Framework for Multi-hop Ad Hoc Wireless Networks: Ideal Scenario. 2.1 Introduction. 2.2 Preliminaries. 2.3 Communication-Theoretic Basics. 2.4 BER Performance Analysis. 2.5 Network Behaviour. 2.6 Concluding Remarks. 3 A Communication-Theoretic Framework for Multi-hop Ad Hoc Wireless Networks: Realistic Scenario. 3.1 Introduction. 3.2 Preliminaries. 3.3 Communication-Theoretic Basics. 3.4 Inter-node Interference. 3.5 RESGOMAC Protocol. 3.6 RESLIGOMAC Protocol. 3.7 Network Behavior. 3.8 Conclusions. 4 Connectivity in Ad Hoc Wireless Networks: A Physical Layer Perspective. 4.1 Introduction. 4.2 Quasi-regular Topology. 4.3 Random Topology. 4.4 Concluding Remarks and Discussion. 5 Effective Transport Capacity in Ad Hoc Wireless Networks. 5.1 Introduction. 5.2 Modeland Assumptions. 5.3 Preliminaries. 5.4 Single-Route Effective Transport Capacity. 5.5 Aggregate Effective Transport Capacity. 5.6 Comparison of the RESGO and RESLIGOMAC Protocols. 5.7 Spread-RESGO: Improved RESGOMAC Protocol with Per-route Spreading Codes. 5.8 Discussion. 5.9 Concluding Remarks. 6 Impact of Mobility on the Performance of Multi-hop Ad Hoc Wireless Networks. 6.1 Introduction. 6.2 Preliminaries. 6.3 Switching Models. 6.4 Mobility Models. 6.5 Numerical Results. 6.6 Conclusions. 7 Route Reservation in Ad Hoc Wireless Networks. 7.1 Introduction. 7.2 Related Work. 7.3 Network Models and Assumptions. 7.4 The Two Switching Schemes. 7.5 Analysis of the Two Switching Techniques. 7.6 Results and Discussion. 7.7 Concluding Remarks. 8 Optimal Common Transmit Power for Ad Hoc Wireless Networks. 8.1 Introduction. 8.2 Modeland Assumptions. 8.3 Connectivity. 8.4 BER at the End of a Multi-hop Route. 8.5 Optimal Common Transmit Power. 8.6 Performance Metrics. 8.7 Results and Discussion. 8.8 Related Work. 8.9 Conclusions. 9 Routing Problem in Ad Hoc Wireless Networks: A Cross-Layer Perspective. 9.1 Introduction. 9.2 Experimental Evidence. 9.3 Preliminaries: Analytical Models and Assumptions. 9.4 Route Selection: Simulation Study. 9.5 Network Performance Evaluation. 9.6 Discussion. 9.7 Related Work. 9.8 Conclusions. 10 Concluding Remarks. 10.1 Introduction. 10.2 Extensions of the Theoretical Framework: Open Problems. 10.3 Network Architectures. 10.4 Network Application Architectures. 10.5 Standards. 10.6 Applications. 10.7 Conclusions. Appendix A. Appendix B. Appendix C. Appendix D. Appendix E. References. Index.

Optimal Transmit Power in Wireless Sensor Networks

Abstract: Power conservation is one of the most important issues in wireless ad hoc and sensor networks, where nodes are likely to rely on limited battery power. Transmitting at unnecessarily high power not only reduces the lifetime of the nodes and the network, but also introduces excessive interference. It is in the network designer's best interest to have each node transmit at the lowest possible power while preserving network connectivity. In this paper, we investigate the optimal common transmit power, defined as the minimum transmit power used by all nodes necessary to guarantee network connectivity. This is desirable in sensor networks where nodes are relatively simple and it is difficult to modify the transmit power after deployment. The optimal transmit power derived in this paper is subject to the specific routing and medium access control (MAC) protocols considered; however, the approach can be extended to other routing and MAC protocols as well. In deriving the optimal transmit power, we distinguish ourselves from a conventional graph-theoretic approach by taking realistic physical layer characteristics into consideration. In fact, connectivity in this paper is defined in terms of a quality of service (QoS) constraint given by the maximum tolerable bit error rate (BER) at the end of a multihop route with an average number of hops