Research Academic Computer Technology Institute

Pátra, Greece

Research Academic Computer Technology Institute

Pátra, Greece

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Garofalakis J.,University of Patras | Garofalakis J.,Research Academic Computer Technology Institute | Stergiou E.,ATEI of Epirus
Future Generation Computer Systems | Year: 2013

The aim of this paper is to develop an analytical method for performance evaluation of double prioritized Multistage Interconnected Networks (MINs) with single or multilayers and backpressure operation which provide service differentiation and QoS guarantee to an end application running over next generation Internet or Grid systems. Specifically, a new architecture of switching elements is used for the construction of MINs. This switch element uses two parallel queues in order to serve dual priority traffic. Besides this, uniform traffic conditions are presupposed and the bulk of packet arrivals in each cycle to the network inputs follow a Bernoulli distribution. A new analytical model for evaluating single buffered MIN's with 2×2 special switching elements supporting internally two classes' priority traffic is presented. Equations for the steady state are derived. These equations are then used in finding the most important multistage network performance metrics, such as throughput, and packet latency. The results are also validated using simulation and compared with previous related work in marginal cases. This proposed analytical model is accurate for various network sizes and various values of offered traffic to the multistage network inputs. © 2012 Published by Elsevier B.V. All rights reserved.

Christodoulopoulos K.,University of Patras | Christodoulopoulos K.,Research Academic Computer Technology Institute | Tomkos I.,Athens Information Technology | Varvarigos E.A.,University of Patras | Varvarigos E.A.,Research Academic Computer Technology Institute
Journal of Lightwave Technology | Year: 2011

Orthogonal Frequency Division Multiplexing (OFDM) has recently been proposed as a modulation technique for optical networks, because of its good spectral efficiency, flexibility, and tolerance to impairments. We consider the planning problem of an OFDM optical network, where we are given a traffic matrix that includes the requested transmission rates of the connections to be served. Connections are provisioned for their requested rate by elastically allocating spectrum using a variable number of OFDM subcarriers and choosing an appropriate modulation level, taking into account the transmission distance. We introduce the Routing, Modulation Level and Spectrum Allocation (RMLSA) problem, as opposed to the typical Routing and Wavelength Assignment (RWA) problem of traditional WDM networks, prove that is also NP-complete and present various algorithms to solve it. We start by presenting an optimal ILP RMLSA algorithm that minimizes the spectrum used to serve the traffic matrix, and also present a decomposition method that breaks RMLSA into its two substituent subproblems, namely 1) routing and modulation level and 2) spectrum allocation (RML + SA), and solves them sequentially. We also propose a heuristic algorithm that serves connections one-by-one and use it to solve the planning problem by sequentially serving all the connections in the traffic matrix. In the sequential algorithm, we investigate two policies for defining the order in which connections are considered. We also use a simulated annealing meta-heuristic to obtain even better orderings. We examine the performance of the proposed algorithms through simulation experiments and evaluate the spectrum utilization benefits that can be obtained by utilizing OFDM elastic bandwidth allocation, when compared to a traditional WDM network. © 2011 IEEE.

Agency: European Commission | Branch: FP7 | Program: CP | Phase: ICT-2007.1.1 | Award Amount: 4.84M | Year: 2008

The DICONET proposal is targeting a novel approach to optical networking providing a disruptive solution for the development of the core network of the future. It is the vision and goal of our consortium to provide ultra high speed end-to-end connectivity with quality of service and high reliability through the use of optimised protocols and routing algorithms that will complement a flexible control and management plane offering flexibility for the future network infrastructure. We plan to investigate, design, implement and test new routing and wavelength assignment algorithms considering as constraints physical impairments that arise in transparent core networks. These algorithms will be incorporated into a novel dynamic network planning tool that would consider dynamic traffic characteristics, varying physical impairment and component characteristics and a reconfigurable optical layer. The use of this novel planning tool in conjunction with proper extensions to the control plane of core optical networks that will be designed, implemented and tested by our consortium will make possible to realize the vision of transparency, while offering efficient resource utilization and strict quality of service guarantees based on certain service level agreements. The combinations of the tools, algorithms and protocols that will developed by the uniquely qualified DICONET consortium together with new technologies and architectures that will be considered as enablers for the network of the future will assist in overcoming the expected long term limitations of current core network capabilities. The DICONET scope and objectives, address dynamic cross-layer network planning and optimization while considering the development of a future transport network infrastructure which ensures fail-safe network configuration and operation. Our approach will greatly contribute as a basic element in achieving resilience and transparency of the Future Internet.

Bouboulis P.,National and Kapodistrian University of Athens | Theodoridis S.,National and Kapodistrian University of Athens | Theodoridis S.,Research Academic Computer Technology Institute
IEEE Transactions on Signal Processing | Year: 2011

Over the last decade, kernel methods for nonlinear processing have successfully been used in the machine learning community. The primary mathematical tool employed in these methods is the notion of the reproducing kernel Hilbert space (RKHS). However, so far, the emphasis has been on batch techniques. It is only recently, that online techniques have been considered in the context of adaptive signal processing tasks. Moreover, these efforts have only been focussed on real valued data sequences. To the best of our knowledge, no adaptive kernel-based strategy has been developed, so far, for complex valued signals. Furthermore, although the real reproducing kernels are used in an increasing number of machine learning problems, complex kernels have not, yet, been used, in spite of their potential interest in applications that deal with complex signals, with Communications being a typical example. In this paper, we present a general framework to attack the problem of adaptive filtering of complex signals, using either real reproducing kernels, taking advantage of a technique called complexification of real RKHSs, or complex reproducing kernels, highlighting the use of the complex Gaussian kernel. In order to derive gradients of operators that need to be defined on the associated complex RKHSs, we employ the powerful tool of Wirtinger's Calculus, which has recently attracted attention in the signal processing community. Wirtinger's calculus simplifies computations and offers an elegant tool for treating complex signals. To this end, in this paper, the notion of Wirtinger's calculus is extended, for the first time, to include complex RKHSs and use it to derive several realizations of the complex kernel least-mean-square (CKLMS) algorithm. Experiments verify that the CKLMS offers significant performance improvements over several linear and nonlinear algorithms, when dealing with nonlinearities. © 2010 IEEE.

Bouboulis P.,National and Kapodistrian University of Athens | Slavakis K.,University of Peloponnese | Theodoridis S.,Research Academic Computer Technology Institute
IEEE Transactions on Neural Networks and Learning Systems | Year: 2012

This paper presents a wide framework for non-linear online supervised learning tasks in the context of complex valued signal processing. The (complex) input data are mapped into a complex reproducing kernel Hilbert space (RKHS), where the learning phase is taking place. Both pure complex kernels and real kernels (via the complexification trick) can be employed. Moreover, any convex, continuous and not necessarily differentiable function can be used to measure the loss between the output of the specific system and the desired response. The only requirement is the subgradient of the adopted loss function to be available in an analytic form. In order to derive analytically the subgradients, the principles of the (recently developed) Wirtinger's calculus in complex RKHS are exploited. Furthermore, both linear and widely linear (in RKHS) estimation filters are considered. To cope with the problem of increasing memory requirements, which is present in almost all online schemes in RKHS, the sparsification scheme, based on projection onto closed balls, has been adopted. We demonstrate the effectiveness of the proposed framework in a non-linear channel identification task, a non-linear channel equalization problem and a quadrature phase shift keying equalization scheme, using both circular and non circular synthetic signal sources. © 2012 IEEE.

Agency: European Commission | Branch: FP7 | Program: CP | Phase: ICT-2007.8.2 | Award Amount: 3.09M | Year: 2008

In the near future, it is reasonable to expect that new types of systems will appear, designed or emerged, of massive scale, expansive and permeating their environment, of very heterogeneous nature, and operating in a constantly changing networked environment. We expect that most such systems will have the form of a large society of networked artifacts that are small, have limited sensing, signal processing, and communication capabilities, and are usually of limited energy. Yet by cooperation, they will be organized in large societies to accomplish tasks that are difficult or beyond the capabilities of todays conventional centralized systems. The scale and nature of these systems requires naturally that they are pervasive and are expected to operate beyond the complete understanding and control of their designers, developers, and users. These systems or societies should have particular ways to achieve an appropriate level of organization and integration that is achieved seamlessly and with appropriate levels of flexibility. The aim of this project is to establish the foundations of adaptive networked societies of small or tiny heterogeneous artifacts. We indent to develop an understanding of such societies that will enable us to establish their fundamental properties and laws, as well as, their inherent trade-offs. We will approach our goal by working on a usable quantitative theory of networked adaptation based on rigorous and measurable gains. We also indent to apply our models, methods, and results to the scrutiny of large-scale simulations and experiments, from which we expect to obtain valuable feedback. The foundational results and the feedback from simulations and experiments will form a unifying framework for adaptive nets of artifacts that hopefully will enable us to come up with a coherent working set of design rules for such systems. In a nutshell, we will work towards a science of adaptive organization of pervasive networks of small or tiny artifacts.

Agency: European Commission | Branch: FP7 | Program: CP | Phase: ICT-2007.1.6 | Award Amount: 3.63M | Year: 2008

The aim of this project is to provide a multi-level infrastracture of interconnected testbeds of large-scale wireless sensor networks for research purposes, pursuing an interdisciplinary approach that integrates the aspects of hardware, software, algorithms, and data. This will demonstrate how heterogeneous small-scale devices and testbeds can be brought together to form well-organized, large-scale structures, rather than just some large network; it will allow research not only at a much larger scale, but also in different quality, due to heterogeneous structure and the ability to deal with dynamic scenarios, both in membership and location. For the interdisciplinary area of wireless sensor networks, establishing the foundations of distributed, interconnected testbeds for an integrated approach to hardware, software, algorithms, and data will allow a new quality of practical and theoretical collaboration, possibly marking a turning point from individual, hand-tailored solutions to large-scale, integrated ones. For this end, we will engage in implementing recent theoretical results on algorithms, mechanisms and protocols and transform them into software. We will apply the resulting code to the scrutiny of large-scale simulations and experiments, from which we expect to obtain valuable feedback and derive further requirements, orientations and inputs for the long-term research. We intend to make these distributed laboratories available to the European scientific community, so that other research groups will take advantage of the federated infrastructure. Overall, this means pushing the new paradigm of distributed, self-organizing structures to a different level.

Bouboulis P.,National and Kapodistrian University of Athens | Theodoridis S.,National and Kapodistrian University of Athens | Theodoridis S.,Research Academic Computer Technology Institute | Mavroforakis M.,University of Houston
IEEE Transactions on Signal Processing | Year: 2012

Recently, a unified framework for adaptive kernel based signal processing of complex data was presented by the authors, which, besides offering techniques to map the input data to complex reproducing kernel Hilbert spaces, developed a suitable Wirtinger-like calculus for general Hilbert spaces. In this short paper, the extended Wirtinger's calculus is adopted to derive complex kernel-based widely linear estimation filters suitable for applications involving noncircular data. Furthermore, we illuminate several important characteristics of the widely linear filters. We show that, although in many cases the gains from adopting widely linear estimation filters, as alternatives to ordinary linear ones, are rudimentary, for the case of kernel based widely linear filters significant performance improvements can be obtained. © 1991-2012 IEEE.

Kokkinos P.,University of Patras | Kokkinos P.,Research Academic Computer Technology Institute | Varvarigos E.A.,University of Patras | Varvarigos E.A.,Research Academic Computer Technology Institute
Future Generation Computer Systems | Year: 2012

We consider information aggregation as a method for reducing the information exchanged in a Grid network and used by the resource manager in order to make scheduling decisions. In this way, information is summarized across nodes and sensitive or detailed information can be kept private, while resources are still publicly available for use. We present a general framework for information aggregation, trying to identify issues that relate to aggregation in Grids. In this context, we describe a number of techniques, including single point and intra-domain aggregation, define appropriate grid-specific domination relations and operators for aggregating static and dynamic resource information, and discuss resource selection optimization functions. The quality of an aggregation scheme is measured both by its effects on the efficiency of the scheduler's decisions and also by the reduction it brings on the amount of resource information recorded, a tradeoff that we examine in detail. Simulation experiments demonstrate that the proposed schemes achieve significant information reduction, either in the amount of information exchanged, or in the frequency of the updates, while at the same time maintaining most of the value of the original information as expressed by a stretch factor metric we introduce. © 2010 Elsevier B.V. All rights reserved.

Agency: European Commission | Branch: FP7 | Program: CP | Phase: ICT-2007.1.1 | Award Amount: 4.08M | Year: 2008

PHYDYAS proposes an advanced physical layer, using filter bank-based multicarrier (FBMC) transmission, for the new concepts in radiocommunications: dynamic access spectrum management (DASM) and cognitive radio. It shows that the performance and operational flexibility of systems are enhanced by exploiting the spectral efficiency of filter banks and the independence of sub-channels. Combining with offset quadrature amplitude modulation (OQAM), no cyclic prefix is needed, all the radiated power is used and gains in maximum throughput compared to OFDM are achieved. Robustness to Doppler and jammers is obtained and new functionalities are possible. The high resolution spectrum analysis capability is exploited for DASM and cognitive radio and a single device can do spectrum sensing and reception simultaneously.\nResearch in signal processing is carried out to complete the knowledge in filter banks for transmission and satisfy requirements of new radio systems: fast initialization, optimum transmit-receive processing for single and multiple antenna (MIMO) systems, scalability. Research in communications concerns dynamic access and cross-layer aspects, and compatibility with OFDM. In cognitive radio, research deals with radio scene analysis and channel identification and the impact of the independence of sub-channels on transmit power control and dynamic spectrum management. A simulation software is developed for a typical WiMAX configuration and scenario and performance comparison with OFDM is carried out. A real time soft/hardware demonstrator is built to complete simulation results and show efficient architectures.\nThe expected impact of PHYDYAS is the migration of wireless systems to a physical layer that is more efficient and better responds to the needs of dynamic access and cognitive radio. The consortium consists of leading academic research groups across Europe, teamed with world leading companies in infrastructures, circuit design and instrumentation.

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