Ulrico Celentano

Resource management for QoS support in cognitive radio networks

Cognitive radio technology is a key enabler to reuse a finite, scarce, and expensive resource: the radio spectrum. Guaranteeing required levels of QoS to cognitive users and ensuring necessary protection to incumbent users are the two main challenges in opportunistic spectrum access. This article identifies the main requirements and challenges for QoS support in cognitive radio networks. A framework for a twofold cognitive manager is presented; one part managing spectrum availability on longer timescales and the other handling resource management on shorter timescales. This article gives particular focus to the functionalities of the latter cognitive manager related to resource management. Finally, we present a few key scenarios and describe how QoS can be managed with the proposed approach without disturbing the communications of incumbent users.

Energy Consumption of Beacon Period Extension and Contraction in Distributed Medium Access Control

Ultra-wide band (UWB) is a promising physical layer technology which potentially enables low power and high rate devices with applications for wireless personal area networks (WPANs) and for wireless body area networks (WBANs). The UWB technology considered in this paper, called multiband UWB, is based on orthogonal frequency division multiplexing (OFDM). Any physical layer technology requires a medium access control (MAC) protocol to be coupled with. This paper focuses on a distributed time division multiple access (TDMA) MAC protocol to support high data rate applications, developed within the WiMedia Alliance (2005). The aim of this paper is to study the dynamic beacon period extension and contraction when a newcomer device joins a existing beacon group (BG) and to evaluate the related energy consumption

Framework for dependable and pervasive eHealth services

Provision of health care and well-being services at end-user residence, together with its benefits, brings important concerns to be dealt with. This article discusses selected issues in dependable pervasive eHealth services support. Dependable services need to be implemented in a resource-efficient and safe way due to constrained and concurrent, pre-existing conditions and radio environment. Security is a must when dealing with personal information, even more critical when regarding health. Once these fundamental requirements are satisfied, and services designed in an effective manner, social significance can be achieved in various scenarios. After having discussed the above viewpoints, the article concludes with the future directions in eHealth IoT including scaling the system down to the nanoscale, to interact more intimately with biological organisms.

Effective capacity of imperfect adaptive wireless communication systems

This paper presents a model for the link service capacity that an imperfect adaptive radio link provides to upper layers. As the main contribution of this paper, the model includes a number of imperfections in the link adaptation chain, as well as implementation implications. The average goodput is expressed also in compact form and its dependence on the impairments is discussed using analytical, numerical, and simulations results. The model, to be used for analyses at upper layers, integrates physical channel, transceiver characteristics, and imperfections in a flexible way, by independent, separate matrices

Characterization of the link layer service capacity of adaptive air interfaces with imperfections

A model for the service capacity at link layer, for a wireless, link-adaptive system is presented. The model includes imperfections in the adaptation chain (estimation error, estimation delay, acquisition error), and implementation implications (switching hysteresis). Transceiver characteristics and imperfections are independently represented by separate matrices. The dependence of effective capacity Rmacrc on the impairments is discussed using analytical, numerical, and simulation results. Examples show that the above effects should not be neglected in realistic performance analysis at upper layers

IEEE Access Special Section Editorial: Recent Advances in Socially-Aware Mobile Networking

Mobile data traffic has been growing exponentially over the past few years. A report from Cisco shows that the mobile data traffic in 2014 grew 69 percent and was nearly 30 times the size of the entire global Internet in 2000 [item 1) in the Appendix]. One of the primary contributors to the explosive mobile traffic growth is the rapid proliferation of mobile social applications running on multimedia mobile devices (particularly smartphones). These sharp increases in mobile traffic (particularly from mobile social applications) are projected to continue in the foreseeable future. As mobile networks by and large are designed and deployed to meet people’s social needs, people’s behaviors and interactions in the social domain will shape their ways to access mobile services. Therefore, there is an urgent need to integrate social effects into the design of mobile networks.

Multi-robot Systems, Machine-Machine and Human-Machine Interaction, and Their Modelling

The control of multi-agent systems, including multi-robot systems, requires some level of context and environment awareness as well as interaction among the interworked cognitive entities, whether they are artificial or natural. Proper specification of the cognitive functionalities and of the corresponding interfaces helps in achieving the capability to reach interoperability across different operational domains, and to reuse the system design across different application domains. The model for interworking cognitive entities presented in this article, which includes explicitly interworking capabilities, is applied to two major classes of interaction in multi-robot systems. Being the model inspired by both artificial and natural systems, makes it suitable for both machine-machine and human-machine interaction.

Channel Assignment based on Iterative Exchange in Wireless Ad-Hoc Networks

This paper presents a novel iterative channel exchange algorithm to enhance a previous resource allocation. The objective is the improvement of network throughput in wireless ad-hoc networks by channel exchanges among neighbor nodes. The algorithm makes use of knowledge of channel status and usage, and can be implemented in a distributed manner. Due to the iterative approach, stepwise improvement can be achieved. Two channel exchange algorithms, i.e., a random channel exchange and a non-random channel exchange, which considers channel and node statuses, are investigated. The algorithms are evaluated under a time-invariant channel and network. Numerical results show that the algorithms can improve throughput performance and attain nearly equal performance although the random exchange has less complexity.