Virgilios Passas

Online energy consumption monitoring of wireless testbed infrastructure through the NITOS EMF framework

Development of energy-efficient protocols and algorithms requires in-depth understanding of the power consumption characteristics of real world devices. To this aim, energy efficiency analysis is performed by the research community, mainly focusing on the development of power consumption models. However, recent studies [1] have highlighted the inability of existing models to accurately estimate energy consumption even in non-composite scenarios, where the operation of a single device is analyzed. The inability of such models is further highlighted under real life scenarios, where the impact induced by the simultaneous operation of several devices renders the application of traditional models completely inappropriate. As a result, energy efficiency evaluation under complex configurations and topologies, needs to be experimentally investigated through the application of online monitoring solutions. In this work, we propose the innovative NITOS Energy consumption Monitoring Framework (EMF) able to support online monitoring of energy expenditure, along with the experiment execution. The developed framework is built on a distributed network of low-cost, but highly accurate devices and is fully integrated with the large-scale wireless NITOS testbed. Framework evaluation is performed under both low-level experiments that demonstrate the platforms high-level accuracy, as well as through high-level experiments that showcase how online and distributed monitoring can facilitate energy performance assessment of realistic testbed experiments.

NITOS energy monitoring framework: real time power monitoring in experimental wireless network deployments

Development of energy-efficient protocols and algorithms requires in-depth understanding of the power consumption characteristics of real world devices. To this aim, energy efficiency analysis is performed by the research community, mainly focusing on the development of power consumption models. However, recent studies [1] have highlighted the inability of existing models to accurately estimate energy consumption even in non-composite scenarios, where the operation of a single device is analyzed. The inability of such models is further highlighted under real life scenarios, where the impact induced by the simultaneous operation of several devices renders the application of traditional models completely inappropriate. As a result, energy efficiency evaluation under complex configurations and topologies, needs to be experimentally investigated through the application of online monitoring solutions. In this work, we propose the innovative NITOS Energy consumption Monitoring Framework (EMF) able to support online monitoring of energy expenditure, along with the experiment execution. The developed framework is built on a distributed network of low-cost, but highly accurate devices and is fully integrated with the large-scale wireless NITOS testbed. The framework evaluation is performed under both low-level experiments that demonstrate the platforms high-level accuracy, as well as through high-level experiments that showcase how online and distributed monitoring can facilitate energy performance assessment of realistic testbed experiments.

Towards the efficient performance of LTE-A systems: Implementing a cell planning framework based on cognitive sensing

LTE and LTE-A have dominated as a 4G enabler protocol, adopted by the majority of the network providers worldwide. The efficient performance of an LTE network relies on the selected frequency within an operating band that the cell operates, by taking into account all the potential factors that can affect it. Since cognitive radio is targeting towards the maximization of spectrum utilization, it is crucial that it is adopted in the spectrum allocation process. In this work, we propose an efficient scheme for cell planning by employing spectrum sensing techniques. By exploiting spectral information collected by several sensing devices, we appropriately select the center frequency inside the operating band, towards maximizing the quality of the end user experience. Our algorithms are implemented for the downlink channel, considering a variety of configurations and topologies. Finally, our implemented mechanism is evaluated in the real world deployment of the NITOS Future Internet facility, using commercial LTE enabled femto cells and UEs, while USRP sensing devices are employed for high quality spectral information provisioning.

Paris Metro Pricing for 5G HetNets

Heterogeneous network access has been proposed as a solution for the continuously deteriorating congestion problem of cellular infrastructures. In this paper we focus on a multi- Radio Access Technology (RAT) environment and we provide a solution based on the Paris Metro Pricing (PMP) scheme, which was first applied in Paris metro. The concept of this pricing scheme was to provide differentiated service classes for customers who desired to avoid being congested, while maintaining the same wagons, characterized only by a different ticket price. The proposed solution extends the classic PMP policy by inducing dynamic prices formed by the congestion of each available technology. We investigate the performance of our dynamic PMP scheme taking into consideration a mobility model of the interested users. Through simulations and testbed experimentation we provide evaluation results on the average throughput, the acceptance capability of the incoming users and how these performance metrics are affected under different mobility conditions.

Online assessment of sensing performance in experimental spectrum sensing platforms

Dynamic Spectrum Access aims at exploiting underutilized frequency bands towards improving wireless network performance. In this context, spectrum sensing is employed, in order to monitor spectrum occupancy and drive appropriate adaptation decisions. Researchers in the field primarily evaluate proposed sensing approaches in terms of detection accuracy and efficiency of free spectrum utilization. In this work, we focus on online assessment of spectrum occupancy with respect to sensing delay and energy efficiency. Evaluation of spectrum sensing methods with respect to these two metrics is rather lagging in recent experimental developments. The first is related to the latency induced by the spectrum sensing process and its impact on sensing efficiency, which is tightly connected to the resulting performance of the cognitive solution. On the other hand, energy consumption is considered as a crucial issue in all types of wireless communications. Therefore, it is important to extend existing testbed experimentation tools and develop new ones, in order to equip cognitive testbeds with such advanced monitoring capabilities. To this aim, we integrated the proposed monitoring procedure with the experimentation tools of the CREW testbed federation. In order to demonstrate the applicability of our framework, we experimentally validate the performance of four different sensing platforms, as well as a real-time spectrum sensing engine that implements parallel processing on software defined radios, in terms of the aforementioned metrics.

An Experimental Framework for Channel Sensing through USRP/GNU Radios

In the last decade testbeds have been set-up to evaluate network protocols and algorithms under realistic settings. In order to draw solid conclusions about the corresponding experimental results, it is important for the experimenter to have a detailed view of the existing channel conditions. Moreover, especially in the context of non-RF-isolated wireless testbeds, where external interference severely impacts the resulting performance, the requirement of experimenters for accurate channel monitoring becomes a prerequisite. Toward, this direction, various channel sensing platforms have been introduced, where each one offers different operational characteristics. In this demo, we propose the NITOS Channel Sensing framework, which is based on software-defined radio (SDR) devices that feature highly flexible wireless transceivers and are able to provide highly accurate channel sensing measurements. Through this framework, online measurement gathering is automated and further simplified using specifically developed scripts, so that it becomes a transparent process for the experimenter. The proposed framework is also accompanied by a web user interface that allows the user to get a graphical representation of the gathered measurements.

Employing MEC in the Cloud-RAN: An Experimental Analysis

5G network access is expected to deliver high performance with low-latency network connections for the end-users, suitable for a plethora of different applications, as well as add up to the network flexibility and manageability from the operators perspective. In order to achieve low-latency, Multiple-access Edge Computing (MEC) is considered, whereas for achieving flexibility, the disaggregation of the base station elements and moving parts of their functionality to the Cloud is proposed. In this paper, we consider the case of disaggregated base stations based on the CU-DU paradigm, able to provision MEC functions in a per-packet and per-client basis, over real networks. We evaluate the placement of the MEC functions over the fronthaul interface or collocating them with the Core Network. We employ the OpenAirInterface platform and evaluate our MEC solution with dynamically adaptive video streams. Our results show significant gains for the service-to-UE path latency, complying with the requirements set for the 5G MEC operation.

Measuring LTE and WiFi coexistence in Unlicensed spectrum

The exponential growth in mobile services demand, along with the scarce licensed spectrum in the sub-6GHz bands, mandate the exploitation of bands other than the traditionally used by mobile broadband technologies. An example of such operation is the opportunistic access of the unlicensed bands by the LTE technology, as a means to increase the delivered end-user capacity and enhancing the overall quality of experience. In this paper, we present some extensive testbed measurements used for modeling the coexistence of LTE and WiFi technologies when operating within the same unlicensed environment. The experiments deal with different bandwidth settings for both the WiFi and LTE technologies, when LTE is operating closely or inside the primary or secondary channels of IEEE 802.11, taking into account the different threshold values for the Clear Channel Assessment functions that WiFi entails. We present exhaustive experimental measurements, collected under a real testbed setup, and present a cognitive algorithm for minimizing the impact of the two technologies to each other.