Marcelo Antonio Marotta

Internet of Things in healthcare: Interoperatibility and security issues

Internet of Things devices being used now expose limitations that prevent their proper use in healthcare systems. Interoperability and security are especially impacted by such limitations. In this paper, we discuss todays issues, including benefits and difficulties, as well as approaches to circumvent the problems of employing and integrating Internet of Things devices in healthcare systems. We present this discussion in the context of the REMOA project, which targets a solution for home care/telemonitoring for patients with chronic illnesses.

Resource sharing in heterogeneous cloud radio access networks

Heterogeneous cloud radio access networks incorporate the heterogeneous network and cloud radio access network concepts for next generation cellular networks. H-CRANs exploit the heterogeneity of macro and small cells from HetNets, enabling cellular networks to achieve higher spectral efficiency. Meanwhile, concepts from C-RANs involving baseband units and remote radio heads enable H-CRANs to insert a centralized point of processing for cellular networks, reducing capital and operational expenditures. In this article, we investigate resource sharing in H-CRANs at three levels: spectrum, infrastructure, and network. For each level, we discuss the benefits and challenges, highlighting key enabling technologies that make resource sharing feasible in H-CRANs, such as software defined radio, virtualization, network function virtualization, and software defined networking. Through these technologies, H-CRANs can be virtualized in an overlay network capable of achieving enhanced infrastructure and spectrum sharing.

Managing mobile cloud computing considering objective and subjective perspectives

Mobile Cloud Computing enables mobile devices to augment constrained resources such as processing, storage, and battery autonomy by using the cloud infrastructure. As the network is a key element in integrating mobile devices to the cloud, a proper management of the mobile cloud computing environment is necessary. Such a management must take into account two main perspectives: administrators and end-users perspectives. The administrator is usually concerned with a more objective perspective based on Quality of Service parameters, such as throughput, delay, and jitter. On the other hand, the end-user has a more subjective perspective, observing his/her Quality of Experience when using a mobile cloud application or service. In this article, we introduce a management model and architecture for mobile cloud computing, exploiting both objective and subjective perspectives. As a proof of concept, we prototyped the architecture in a management system called CoLisEU, which allowed us to investigate this architecture and we discuss the benefits of the combined objective and subjective perspectives in our management architecture.

Evaluating management architectures for Internet of Things devices

The Internet of Things (IoT) is foreseen as a global network infrastructure that provides wireless communication among any kind of objects. One immediate challenge holds: how to manage these objects, considering that they may have limited computational resources. This management can be achieved through the use of gateways, i.e., devices that intermediate wireless communications, minimizing resource consumption of the restrained objects. The communication between gateways and objects can be performed over many architectures. Among these architectures, we highlight the Simple Network Management Protocol (SNMP), the Service Oriented Architecture (SOA), and the Resource Oriented Architecture (ROA). However, there is a lack of deeper investigations to define which is the best architecture to model the communication between gateways and objects. Therefore, the main contribution of this paper is a quantitative evaluation of SNMP, SOA, and ROA as means for the communication between gateways and objects. Results analysis pointed ROA as the most interesting architecture to model the management communication.

Adaptive threshold architecture for spectrum sensing in public safety radio channels

Cognitive radio make use of spectrum sensing techniques to detect licensed users transmissions and avoid causing interference. The major drawback in current spectrum sensing techniques is the use of static decision thresholds to detect such transmissions, which may be infeasible in public safety radio channels. More precisely, the cognitive radio may find different noise or interference levels when switching among these channels. This can lead to a wrong picture of the channel occupancy status, which in turn can increase the interference caused to licensed users. In this paper we propose an Adaptive Threshold Architecture, which uses machine learning algorithms to dynamically adapt the decision threshold, enabling the detection of licensed users transmissions in public safety radio channels. Results showed that the proposed architecture increased the sensing accuracy up to 2 times, providing results up to 6 times faster when compared to other solutions of the literature.

Software-defined handover decision engine for heterogeneous cloud radio access networks

Abstract The current telecommunication infrastructure is reaching its limits, no longer able to cope with the ever-growing number of connected devices and data traffic summed to the future QoS demand of 5G. To overcome such limitations, the Heterogeneous Cloud Radio Access Network (H-CRAN) has been considered as a promising architecture that includes very dense Radio Access Networks (RAN) and the centralization of signal processing at baseband pools. In scenarios with severe constraints and very dynamic network conditions, mobile users may face poor handover (HO) performance. Therefore, in this paper, we propose a novel combination between Software-Defined Wireless Networking (SDWN) and Software-Defined Handover Decision Engine (SDHDE) to approach optimal HO performance in H-CRAN. In particular, in the baseband pool, a wireless controller is used to receive HO information from the Southbound API communicating with the end-users at the RAN. The controllers publish this information to the SDHDE through the Northbound API, and SDHDE processes the HO decision for each user in an optimal manner. The reported simulation results demonstrate the improvements that our approach can achieve, mainly regarding smaller HO percentage failure and increased throughput.

Kitsune: A management system for cognitive radio networks based on spectrum sensing

Software defined radio enables the improvement of the radio-frequency spectrum utilization through the design of cognitive radio devices. The implementation of these devices must be based on spectrum sensing function searching for vacant channels and, opportunistically, transmit over these channels in a cognitive radio network. Therefore, the configuration, monitoring and visualization of the spectrum sensing function are fundamentals to the continuous learning process of the network administrator. In this paper we propose Kitsune, a management system based on a hierarchical model allowing to manage summarized information about the spectrum sensing function in a cognitive radio networks. Moreover, a Kitsune prototype was developed and evaluated through a real IEEE 802.22 scenario using TV channels to Internet access. Results shown that Kitsune allows network administrator to achieve a higher knowledge about behavior of the users and improve the average throughput for each channel.

Integrating dynamic spectrum access and device-to-device via cloud radio access networks and cognitive radio

Funding information CAPES (Coordenação de Aperfeiçoamento de Pessoal de Nível Superior) has provided funding for this research. Summary Dynamic Spectrum Access (DSA) can be integrated with Device-to-Device (D2D) communications to enable the exploitation of unused spectrum portions and to address the spectrum scarcity problem. Spectrum management mechanisms integrated into DSA and D2D allow low-power communications between User Equipments without interfering with licensed primary users. However, these mechanisms tend to be energy and processing intensive, being unfeasible to implement in User Equipments with strict battery and processing limitations. On the other hand, Cloud Radio Access Networks already leverage the virtually unlimited computing capacity of clouds for baseband processing functions. Thus, in this article, we propose the Cognitive Radio Device-to-Device (CRD2D) approach aiming to offload spectrum management functionality to the cloud taking advantage of Cloud Radio Access Networks architecture to support the integration of DSA and D2D.

Impact of fog and cloud computing on an IoT service running over an optical/wireless network testbed

With the advance of the Internet of Things (IoT), the interaction between humans and smart objects is already a reality. New applications that are expected to operate in dynamic environments must support different modes of human/machine interaction (e.g., voice and sign language), exhibit same or better performance in heterogeneous wireless and optical networks, and be able to react in real time. In particular, dispersed computing has arisen as an approach to deal with latency issues in this context. In the work described herein, we design a smart lighting IoT system that allows control of light bulbs (turn on/off, color and brightness change) through voice and sign language. This work addresses the idea of dispersed computing, which is implemented through fog computing, and combines it with virtualized resources to mitigate latency in the convergence point between wireless and optical networks. The proof-of-concept implementation of our design demonstrates the viability of the approach.

Demo abstract: Assessing the impact of fog and cloud computing on an IoT service running over an optical/wireless network-An experimental approach

In this demonstration, we explore the impact of optical-wireless network infrastructure when we vary the locus of computing for Internet of Things (IoT) services. Those services could involve devices ranging from low complexity sensors and actuators (e.g., smart light bulbs) to more advanced ones (e.g., multimedia sensors and smart glasses); in our experiment, we focus on the former. We design a smart light system that allows the control of light bulbs (on/off, color, brightness) through voice and sign language. We vary the location at which the command processing (voice or sign recognition) takes place — locally or in the cloud — and assess its impact on the latency in the response to the command.