Athina Bourdena

Energy efficient resource sharing using a trafficoriented routing scheme for cognitive radio networks

This study proposes a resource intensive traffic-aware scheme, incorporated into an energy-efficient routing protocol that enables maximum energy conservation and efficient data flow coordination, among secondary communicating nodes with heterogeneous spectrum availability in cognitive radio networks. The proposed scheme associates the backward difference of the traffic moments of each node according to a Fibonacci model, with the sleep-time duration, in order to tune the activity periods for achieving optimal energy conservation. Efficient routing protocol operation, as a matter of maximum-possible routing paths establishments and minimum delays is obtained, by utilising a signalling mechanism, developed based on a simulation scenario that includes secondary communication nodes, operating over television white spaces. The validity of the proposed Fibonacci-based backward traffic difference is verified, by conducting experimental simulation tests. Simulation results validate the efficiency of the proposed traffic-aware scheme for minimising energy consumption and routing delays, as well as maximising resources exchange between secondary communication nodes.

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.

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.

Performance evaluation of dynamic cloud resource migration based on temporal and capacity-aware policy for efficient resource sharing

This paper elaborates on practical considerations, such as location and capacity issues to offload resources, by adopting a rack based approach for the implementation. The proposed cooperative migration of resources enables efficient resource manipulation without any intermittent execution of the claimed tasks by the mobile devices, while it significantly reduces crash failures that lead all servers to become unavailable within a rack. In addition, this paper presents a modular resource migration scheme for failure-aware resource allocation, where according to the estimated performance of the resource sharing process (e.g. access time, service delay etc.) resources are migrated to another cloud rack based on the associated performance-oriented metrics. The proposed architecture is thoroughly evaluated through simulation tests for the resource migration policy used in the context of cloud rack failures for delay-bounded resource availability of mobile users, as well as for the efficiency of the proposed resource migration scheme.

Energy Consumption Optimization Using Social Interaction in the Mobile Cloud

This paper addresses the issue of resource offloading for energy usage optimization in the cloud, using the centrality principle of social networks. Mobile users take advantage of the mobile opportunistic cloud, in order to increase their reliability in service provision by guaranteeing sufficient resources for the execution of mobile applications. This work elaborates on the improvement of the energy consumption for each mobile device, by using a social collaboration model that allows for a cooperative partial process offloading scheme. The proposed scheme uses social centrality as the underlying mobility and connectivity model for process offloading within the connected devices to maximize the energy usage efficiency, node availability and process execution reliability. Furthermore, this work considers the impact of mobility on the social-oriented offloading, by allowing partitionable resources to be executed according to the social interactions and the associated mobility of each user during the offloading process. The proposed framework is thoroughly evaluated through event driven simulations, towards defining the validity and offered efficiency of the proposed offloading policy in conjunction to the energy consumption of the wireless devices.

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.

A centralised broker-based CR network architecture for TVWS exploitation under the RTSSM policy

The paper discusses the TV white spaces exploitation by a prototype centralised cognitive radio network architecture, under the real time secondary spectrum management scheme. Vital part of this architecture is a spectrum broker that coordinates the radio resources allocation process among secondary systems, as well as the transactions of spectrum trading following a fixed-price policy. Efficient broker operation as a matter of maximum-possible spectrum utilisation and minimum fragmentation is obtained by decision-making methods based on Backtracking, Simulated Annealing and Genetic algorithm. The validity of the proposed approach is verified via a number of experiments under controlled conditions, while its performance is evaluated against a number of secondary systems competing for TVWS exploitation, each one featuring different transmission characteristics.

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.