A unified radio control architecture for prototyping adaptive wireless protocols

Experimental optimization of wireless protocols and validation of novel solutions is often problematic, due to limited configuration space present in commercial wireless interfaces as well as complexity of monolithic driver implementation on SDR-based experimentation platforms. To overcome these limitations a novel software architecture is proposed, called WiSHFUL, devised to allow: i) maximal exploitation of radio functionalities available in current radio chips, and ii) clean separation between the logic for optimizing the radio protocols (i.e. radio control) and the definition of these protocols

Building Programmable Wireless Networks: An Architectural Survey

In recent times, there have been a lot of efforts for improving the ossified Internet architecture in a bid to sustain unstinted growth and innovation. A major reason for the perceived architectural ossification is the lack of ability to program the network as a system. This situation has resulted partly from historical decisions in the original Internet design which emphasized decentralized network operations through co-located data and control planes on each network device. The situation for wireless networks is no different resulting in a lot of complexity and a plethora of largely incompatible wireless technologies. The emergence of "programmable wireless networks", that allow greater flexibility, ease of management and configurability, is a step in the right direction to overcome the aforementioned shortcomings of the wireless networks. In this paper, we provide a broad overview of the architectures proposed in literature for building programmable wireless networks focusing primarily on three popular techniques, i.e., software defined networks, cognitive radio networks, and virtualized networks. This survey is a self-contained tutorial on these techniques and its applications. We also discuss the opportunities and challenges in building next-generation programmable wireless networks and identify open research issues and future research directions.Comment: 19 page

Developing a neighborhood-scale wireless notification prototype

We outline an innovative approach to thedevelopment of a prototype of a neighborhoodnotification system (NNS). The NNS applicationresiding on smart phones will use software definedradio and cognitive radio components to interfacewith radio frequency transceivers. Mesh networkingis proposed for emergency notification and disasterresponse coordination using NNS. Our focus hasbeen on the IEEE 802.15.4 and the very recent IEEE802.15.5 mesh networking standard for low data rateconnectivity among low power nodes (or nodeswhose power consumption needs to be low). Theinnovation stems from bringing together differenthardware and software components – some of which,like our Software Defined Radio (SDR) platform, arethemselves still evolving and others, like themeshing platform, are very new – to propose anadaptive, reconfigurable, infrastructure-less ad hocwireless solution to emergency communications inthe unlicensed ISM RF band

WiSHFUL : enabling coordination solutions for managing heterogeneous wireless networks

The paradigm shift toward the Internet of Things results in an increasing number of wireless applications being deployed. Since many of these applications contend for the same physical medium (i.e., the unlicensed ISM bands), there is a clear need for beyond-state-of-the-art solutions that coordinate medium access across heterogeneous wireless networks. Such solutions demand fine-grained control of each device and technology, which currently requires a substantial amount of effort given that the control APIs are different on each hardware platform, technology, and operating system. In this article an open architecture is proposed that overcomes this hurdle by providing unified programming interfaces (UPIs) for monitoring and controlling heterogeneous devices and wireless networks. The UPIs enable creation and testing of advanced coordination solutions while minimizing the complexity and implementation overhead. The availability of such interfaces is also crucial for the realization of emerging software-defined networking approaches for heterogeneous wireless networks. To illustrate the use of UPIs, a showcase is presented that simultaneously changes the MAC behavior of multiple wireless technologies in order to mitigate cross-technology interference taking advantage of the enhanced monitoring and control functionality. An open source implementation of the UPIs is available for wireless researchers and developers. It currently supports multiple widely used technologies (IEEE 802.11, IEEE 802.15.4, LTE), operating systems (Linux, Windows, Contiki), and radio platforms (Atheros, Broadcom, CC2520, Xylink Zynq,), as well as advanced reconfigurable radio systems (IRIS, GNURadio, WMP, TAISC)

Cognition-Based Networks: A New Perspective on Network Optimization Using Learning and Distributed Intelligence

IEEE Access Volume 3, 2015, Article number 7217798, Pages 1512-1530 Open Access Cognition-based networks: A new perspective on network optimization using learning and distributed intelligence (Article) Zorzi, M.a , Zanella, A.a, Testolin, A.b, De Filippo De Grazia, M.b, Zorzi, M.bc a Department of Information Engineering, University of Padua, Padua, Italy b Department of General Psychology, University of Padua, Padua, Italy c IRCCS San Camillo Foundation, Venice-Lido, Italy View additional affiliations View references (107) Abstract In response to the new challenges in the design and operation of communication networks, and taking inspiration from how living beings deal with complexity and scalability, in this paper we introduce an innovative system concept called COgnition-BAsed NETworkS (COBANETS). The proposed approach develops around the systematic application of advanced machine learning techniques and, in particular, unsupervised deep learning and probabilistic generative models for system-wide learning, modeling, optimization, and data representation. Moreover, in COBANETS, we propose to combine this learning architecture with the emerging network virtualization paradigms, which make it possible to actuate automatic optimization and reconfiguration strategies at the system level, thus fully unleashing the potential of the learning approach. Compared with the past and current research efforts in this area, the technical approach outlined in this paper is deeply interdisciplinary and more comprehensive, calling for the synergic combination of expertise of computer scientists, communications and networking engineers, and cognitive scientists, with the ultimate aim of breaking new ground through a profound rethinking of how the modern understanding of cognition can be used in the management and optimization of telecommunication network