Georgios Kormentzas

An energy-aware scheme for efficient spectrum utilization in a 5G mobile cognitive radio network architecture

This paper proposes an energy-efficient delay-aware cooperative scheme, exploited for efficient resource management and maximum energy conservation in a 5G mobile cognitive radio network architecture. The proposed scheme is based on the comparison of the queuing delays of both the secondary nodes and the Radio Access Points, when delay sensitive transmission is requested, providing optimal TV White Spaces exploitation via a spectrum broker. The spectrum broker manages the process of the energy consumption of the 5G mobile communication systems, according to the proposed delay-aware cooperative scheme and the comparative evaluation of the queuing delays. The validity of the performance of the scheme is verified through extended simulation tests, carried out under controlled experimental conditions.

Resource usage prediction algorithms for optimal selection of multimedia content delivery methods

This paper proposes two algorithms adopted in a prototype network architecture, for optimal selection of multimedia content delivery methods, as well as balanced delivery load, by exploiting a novel resource prediction engine. The proposed architecture exploits both algorithms for the prediction of future multimedia services demands, by providing the ability to keep optimal the distribution of the streaming data, among Content Delivery Networks, cloud-based providers and Home Media Gateways. In addition, the prediction of the upcoming fluctuations of the network, provides the ability to the proposed network architecture, achieving optimized Quality of Service (QoS) and Quality of Experience (QoE) for the end users. Both algorithms were evaluated to establish their efficiency, towards effectively predicting future network traffic demands. The experimental results validated their performance and indicated fields for further research and experimentation.

QoS provisioning and policy management in a broker-based CR network architecture

The paper presents an infrastructure-based cognitive radio network architecture that enables for TV white spaces exploitation, QoS provisioning and policy management, under the real time secondary spectrum market policy. It describes the configuration of a spectrum broker that coordinates the radio resource management process (RRM) among LTE secondary systems as a matter of maximum possible TVWS utilisation and minimum frequency fragmentation, and also administrates the economics of such transactions towards maximum revenue following a fixed-price trading. The validity of the proposed architecture is verified via a number of tests carried under controlled experimental conditions (i.e. simulations) exploiting a decision-making algorithm.

Efficient entertainment services provision over a novel network architecture

The provision of entertainment services through current network infrastructures generates a significant part of global Internet traffic. Such traffic is created by users who are interconnected through social media networks, distributing multimedia content, as well as through their online games interaction, leading to a significant increase in data traffic demands. At the same time, users demand the high-quality content delivery necessary for such multimedia-based services and applications. In this article, a novel network architecture is proposed that exploits a resource prediction engine to predict the upcoming demands on resources for the optimal distribution of streaming data among content delivery networks, emerging mobile networks, cloudbased providers, and home media gateways. Performance evaluation experiments carried out under controlled conditions verify the validity of the proposed network architecture and establish its effectiveness for efficient resources prediction during the provision of entertainment services.

Joint energy and delay-aware scheme for 5G mobile cognitive radio networks

This paper proposes a delay-assisted cooperative scheme for optimal TV White Spaces (TVWS) exploitation and maximum energy conservation in a 5G mobile cognitive radio (CR) network architecture. This architecture utilizes a radio spectrum broker, which administrates the process of network resources management among several 5G base-stations to support Quality of Service (QoS) provision and minimum energy consumption. The proposed scheme is based on the comparison of the delays of both the secondary nodes and the Radio Access Points, when a delay sensitive transmission is requested. The validity of the proposed scheme is verified through several experimental tests, performed under controlled simulation conditions. The performance evaluation results include the energy consumption level and the lifetime span of each wireless node, the throughput response of the system during the delay-sensitive resource exchange process, as well as quantitative measurements of the energy efficiency levels of the proposed scheme.

Radio resource management algorithms for efficient QoS provisioning over cognitive radio networks

This paper proposes two radio resource management (RRM) algorithms for efficient QoS provisioning over an infrastructure-based cognitive radio network architecture that enables for TV White Spaces exploitation. QoS provisioning and policy management is achieved via a spectrum broker that coordinates the RRM process among LTE secondary systems, under the real time secondary spectrum market policy. The proposed RRM algorithms administrate the economics of the transactions between the spectrum broker and secondary systems, following a fixed-price and an auction-based trading process. The validity of the proposed algorithms is verified via a number of tests, carried under controlled experimental conditions (i.e. simulations), evaluating spectrum broker benefit and secondary systems service rate.

Maximizing energy conservation in a centralized cognitive radio network architecture

This paper proposes two energy-aware algorithms exploited for optimal resources administration and maximum energy conservation of secondary communication nodes in a centralized cognitive radio network architecture. The proposed algorithms optimally enable efficient TV White Spaces exploitation, through a radio spectrum broker that administrates the resources trading process, based on real-time secondary spectrum market policy. In addition, both algorithms adopt a joint path lifetime and utility maximization scheme, which encompasses a capacity-aware policy for achieving minimum energy consumption and reliability during the resource sharing process. Validity of both algorithms is verified through several sets of extended experimental/simulation tests, carried out under controlled conditions.

Performance analysis of IEEE 802.11 ad hoc networks in the presence of exposed terminals

The paper evaluates the performance effects of exposed terminals in IEEE 802.11 ad hoc networks in finite load conditions. It derives analytical models for the estimation of channel utilization and media access delay for IEEE 802.11 ad hoc networks in finite load conditions with and without exposed terminals. The simulation results show that the analytical estimated channel utilization and media access delay metrics are fairly accurate.

A dynamic spectrum management framework for efficient TVWS exploitation

This paper elaborates on a prototype spectrum management framework, for dynamic exploitation of underused radio spectrum, such as TV White Spaces (TVWS), QoS provisioning and policy management, under the real time secondary spectrum market policy. The proposed framework is applied in a centralised Cognitive Radio (CR) network architecture, where the exploitation of the available TVWS, as well as the administration of the economic transactions is orchestrated via a Spectrum Broker. Towards efficiently exploiting TVWS, a fixed-price algorithm is proposed that coordinates the available resources among Secondary Systems, in terms of maximum possible TVWS utilisation and minimum frequency fragmentation. Furthermore, an auction-based algorithm is proposed that considers both frequency and time domain during TVWS allocation process, where maximum payoff of Spectrum Broker is the optimization target. Experimental tests that were carried-out under controlled conditions environment, verified the validity of the proposed framework, besides identifying fields for further research.

Quantifying and evaluating the technical debt on mobile cloud-based service level

As network bandwidth and coverage continue to increase, the adoption rates of mobile devices are growing over time and the mobile technology is becoming increasingly industrialized. In mobile cloud marketplaces, the cloud-supported mobile services can be leased off. However, the mobile service selection may introduce technical debt (TD), which is essential to be predicted and quantified. In this context, this paper examines the incurrence of technical debt in the future when leasing cloud-based mobile services by proposing a novel quantitative model, which adopts a linear and symmetric approach as a linear growth in the number of users is predicted. The formulation of the problem is based on a cost-benefit analysis, elaborating on the potential profit that could be obtained if the number of users would be equal to the maximum value. The probability of overutilization of the selected service in the long run is also researched. Finally, a quantification tool has been developed as a proof of concept (PoC), which initiates the technical debt analysis and optimization on mobile cloud-based service level and aims to provide insights into the overutilization or underutilization of a web service when a linear increase in the number of users occurs.