16 results on '"Gelenbe, Erol"'
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2. Security in Computer and Information Sciences
- Author
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Gelenbe, Erol, Jankovic, Marija, Kehagias, Dionysios, Marton, Anna, and Vilmos, Andras
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architecture types ,artificial intelligence ,communication systems ,computer crime ,computer hardware ,computer networks ,computer security ,computer systems ,cryptography ,data security ,Internet of Things (IoT) ,network protocols ,network security ,signal processing ,software architecture ,software design ,software engineering ,telecommunication networks ,telecommunication systems ,bic Book Industry Communication::U Computing & information technology::UR Computer security ,bic Book Industry Communication::U Computing & information technology::UN Databases::UNH Information retrieval ,bic Book Industry Communication::U Computing & information technology::UK Computer hardware::UKN Network hardware ,bic Book Industry Communication::U Computing & information technology::UM Computer programming / software development::UMZ Software Engineering ,bic Book Industry Communication::U Computing & information technology::UB Information technology: general issues::UBL Legal aspects of IT ,bic Book Industry Communication::G Reference, information & interdisciplinary subjects::GP Research & information: general::GPJ Coding theory & cryptology - Abstract
This open access book constitutes the thoroughly refereed proceedings of the Second International Symposium on Computer and Information Sciences, EuroCybersec 2021, held in Nice, France, in October 2021. The 9 papers presented together with 1 invited paper were carefully reviewed and selected from 21 submissions. The papers focus on topics of security of distributed interconnected systems, software systems, Internet of Things, health informatics systems, energy systems, digital cities, digital economy, mobile networks, and the underlying physical and network infrastructures. This is an open access book.
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- 2022
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3. Power Savings in Packet Networks via Optimised Routing
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Gelenbe, Erol and Morfopoulou, Christina
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- 2012
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4. Self-Aware Networks That Optimize Security, QoS, and Energy.
- Author
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Gelenbe, Erol, Domanska, Joanna, Frohlich, Piotr, Nowak, Mateusz P., and Nowak, Slawomir
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COGNITIVE science ,COMPUTER networks ,SOFTWARE-defined networking ,QUALITY of service ,ARTIFICIAL intelligence - Abstract
The need to adaptively manage computer systems and networks so as to offer good Quality of Service (QoS) and Quality of Experience (QoE) with secure operation at relatively low levels of energy consumption is challenged by their sheer complexity and the wide variability of the workloads. A possible way forward is through self-awareness, whereby self-measurement and self-observation, together with on-line control mechanisms, operate adaptively to attain the required performance and QoE. We survey the premises for these ideas arising from cognitive science and active networks and review recent work on self-aware computer systems and networks, including those that propose the use of software-defined networks as a means to implement these concepts. Then we provide some examples from the literature on self-aware systems to illustrate the performance gains that they can provide. Finally, we detail an example system and its working algorithms to allow the reader to understand how such a system may be implemented. Measurements showing how it can react rapidly to changing network conditions regarding QoS and security are presented. Some conclusions and suggestions for further work are listed. [ABSTRACT FROM AUTHOR]
- Published
- 2020
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5. ADAPTIVE WEB SERVICE FOR QOS IMPROVEMENT.
- Author
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Gelenbe, Erol and Núñez, Arturo
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QUALITY of service ,INTERNET servers ,ADAPTIVE computing systems ,WEBSITES ,COMPUTER networks - Abstract
In this paper we investigate how "self-awareness'', through on-line self-monitoring and measurement, coupled with intelligent adaptive behaviour in response to observed data, can be used to offer adaptive web service for the end-user. Through this mechanism the end-user will notice a Quality of Service (QoS) improvement, every time a web page is requested. We first describe the general principles which govern our design, and briefly describe the experimental packet network system we have built in which end-users(web clients) are allowed to specify their QoS objectives. The network uses on-line adaptive traffic routing to try to meet the users' QoS requests. Cognitive or smart packets are used for selfobservation, and reinforcement learning with neural networks is implemented at network nodes to seek new paths and deduce improved paths from existing routes. We present two sets of experiments showing how the network is actually able to discover viable behaviours and adapt its behaviour. First we show how the network is able to discover routes, beginning with an "empty state'' and starting from a random search. Secondly we show how our network can intelligently direct traffic through the Internet to optimize web traffic for a user by offering the best QoS through different Internet Service Providers. [ABSTRACT FROM AUTHOR]
- Published
- 2003
6. ENERGY AWARENESS AND AD HOC ROUTING.
- Author
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GELENBE, EROL and LENT, RICARDO
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AD hoc computer networks ,WIRELESS communications ,ROUTING (Computer network management) ,COMPUTER networks ,TELECOMMUNICATION systems routing - Published
- 2003
7. Spatial Computers for Emergency Support.
- Author
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Filippoupolitis, Avgoustinos, Gorbil, Gokce, and Gelenbe, Erol
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COMPUTER systems ,COMPUTER networks ,COMPUTER simulation ,BUILDING evacuation ,PERFORMANCE evaluation - Abstract
We present two spatially distributed computing systems that operate in a building and provide intelligent navigation services to people for evacuation purposes. These systems adapt to changing conditions by monitoring the building and using local communication and computation for determining the best evacuation paths. The first system, called distributed evacuation system (DES), comprises a network of decision nodes (DNs) positioned at specific locations inside the building. DNs provide people with directions regarding the best available exit. The second system, called opportunistic emergency support system (OESS), consists of mobile communication nodes (CNs) carried by people. CNs form an opportunistic network in order to exchange information regarding the hazard and to direct the evacuees towards the safest exit. Both DES and OESS employ sensor nodes deployed at fixed locations for monitoring the hazard. We evaluate the spatial systems using simulation experiments with a purpose-built emergency simulator called DBES. We show how parameters such as the frequency of information exchange and communication range affect the system performance and evacuation outcome. [ABSTRACT FROM AUTHOR]
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- 2013
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8. Adaptive Random Re-Routing for Differentiated QoS in Sensor Networks.
- Author
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GELENBE, EROL and NGAI, EDITH
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SENSOR networks , *QUALITY of service , *COMPUTER networks , *ELECTRONIC data processing , *COMPUTER science - Abstract
Sensor networks (SNs) consist of spatially distributed sensors which monitor an environment, and which are connected to some sinks or backbone system to which the sensor data is being forwarded. In many cases, the sensor nodes themselves can serve as intermediate nodes for data coming from other nodes, on the way to the sinks. Much of the traffic carried by SNs will originate from routine measurements or observations by sensors that monitor a particular situation, such as the temperature and humidity in a room or the infrared observation of the perimeter of a house, so that the volume of routine traffic resulting from such observations may be quite high. When important and unusual events occur, such as a sudden fire breaking out or the arrival of an intruder, it will be necessary to convey this new information very urgently through the network to a designated set of sink nodes where this information can be processed and dealt with. This paper addresses the important challenge by avoiding the routine background traffic from creating delays or bottlenecks that impede the rapid delivery of high priority traffic resulting from the unusual events. Specifically we propose a novel technique, the ‘Randomized Re-Routing Algorithm (RRR)’, which detects the presence of novel events in a distributed manner, and dynamically disperses the background traffic towards secondary paths in the network, while creating a ‘fast track path’ which provides better delay and better quality of service (QoS) for the high priority traffic which is carrying the new information. When the surge of new information has subsided, this is again detected by the nodes and the nodes progressively revert to best QoS or shortest-path routing for all the ongoing traffic. The proposed technique is evaluated using a mathematical model as well as simulations, and is also compared with a standard node by a node priority scheduling technique. [ABSTRACT FROM PUBLISHER]
- Published
- 2010
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9. Admission of QoS Aware Users in a Smart Network.
- Author
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Gelenbe, Erol, Sakellari, Georgia, and D'arienzo, Maurizio
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COMPUTER networks ,QUALITY of service ,ALGORITHMS ,ALGEBRA ,MATHEMATICS - Abstract
Smart networks have grown out of the need for stable, reliable, and predictable networks that will guarantee packet delivery under Quality of Service (QoS) constraints. In this article we present a measurement-based admission control algorithm that helps control traffic congestion and guarantee QoS throughout the lifetime of a connection. When a new user requests to enter the network, probe packets are sent from the source to the destination to estimate the impact that the new connection will have on the QoS of both the new and the existing users. The algorithm uses a novel algebra of QoS metrics, inspired by Warshall's algorithm, to look for a path with acceptable QoS values to accommodate the new flow. We describe the underlying mathematical principles and present experimental results obtained by evaluating the method in a large laboratory test-bed operating the Cognitive Packet Network (CPN) protocol. [ABSTRACT FROM AUTHOR]
- Published
- 2008
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10. Genetic Algorithms for Route Discovery.
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Gelenbe, Erol, Peixiang Liu, and Lamé, Jeremy
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GENETIC algorithms , *PACKET switching (Data transmission) , *NETWORK routers , *COMPUTER networks , *QUALITY of service , *COMPUTER network architectures - Abstract
Packet routing in networks requires knowledge about available paths, which can be either acquired dynamically while the traffic is being forwarded, or statically (in advance) based on prior information of a network's topology. This paper describes an experimental investigation of path discovery using genetic algorithms (GAs). We start with the quality-of-service (QoS)-driven routing protocol called ‘cognitive packet network’ (CPN), which uses smart packets (SPs) to dynamically select routes in a distributed autonomic manner based on a user's QoS requirements. We extend it by introducing a GA at the source routers, which modifies and filters the paths discovered by the CPN. The GA can combine the paths that were previously discovered to create new untested but valid source-to-destination paths, which are then selected on the basis of their ‘fitness.’ We present an implementation of this approach, where the GA runs in background mode so as not to overload the ingress routers. Measurements conducted on a network test bed indicate that when the background-traffic load of the network is light to medium, the GA can result in improved QoS. When the background-traffic load is high, it appears that the use of the GA may be detrimental to the QoS experienced by users as compared to CPN routing because the GA uses less timely state information in its decision making. [ABSTRACT FROM AUTHOR]
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- 2006
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11. Power-aware ad hoc cognitive packet networks.
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Gelenbe, Erol and Lent, Ricardo
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PACKET switching (Data transmission) ,NETWORK routers ,COMPUTER networks ,DATA transmission systems - Abstract
This paper proposes a new energy efficient algorithm to find and maintain routes in mobile ad hoc networks. The proposal borrows the notion of learning from a previous research on cognitive packet networks (CPN) to create a robust routing protocol. Our idea uses smart packets that exploit the use of unicasts and broadcasts to search for routes. Because unicasts impose lower overall overhead, their use is preferred. Smart packets learn how to make good unicast routing decisions by employing a combined goal function which considers both the energy stored in the nodes and path delay. The end result is a dynamic discovery of paths that offer an equilibrium between low-delay routes and an efficient use of network resources that extends the working lifetime of the network. [Copyright &y& Elsevier]
- Published
- 2004
- Full Text
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12. QUEUES WITH SLOWLY VARYING ARRIVAL AND SERVICE PROCESSES.
- Author
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Gelenbe, Erol and Rosenberg, Catherine
- Subjects
MARKOV processes ,COMPUTER networks ,QUEUING theory ,TIME-sharing computer systems ,COMPUTER systems ,PRODUCTION scheduling ,DECOMPOSITION method ,INVENTORIES ,BUSINESS models ,MANAGEMENT science - Abstract
We examine a generalisation of the M/G/1 queue. The arrival and service processes are governed by a Markov chain which determines the rate of arrival and the service time distribution from a finite set. This Markov chain is assumed to vary "slowly", so that we are able to derive analytical results for the stationary distribution of the queue length using an approach based on decomposability. The practical interest of this model stems from the numerous applications where the parameters of queueing systems are time varying, such as inventory models, telephone systems, time-sharing systems, computer networks with bursty traffic, etc. We also show how this approach can be extended to arbitrary networks of queues and in particular to those with product form solution. [ABSTRACT FROM AUTHOR]
- Published
- 1990
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13. G-networks: a unifying model for neural and queueing networks.
- Author
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Gelenbe, Erol
- Subjects
COMPUTER networks ,QUEUING theory ,ARTIFICIAL neural networks ,CUSTOMER relations ,ELECTRONIC systems - Abstract
We survey results concerning a new stochastic network we have developed [1–7], which was initially motivated by neural network modelling [1], or - as we called it - by queueing networks with positive and negative customers [2, 3]. Indeed, it is well known that signals in neural networks are formed by impulses or action potentials, traveling much like customers in a queueing network. We call this model a G-network because it serves as a unifying basis for diverse areas of stochastic modelling in queueing networks, computer networks, computer system performance and neural networks. In its simplest version, ‘negative’ and ‘positive’ signals or customers circulate among a finite set of units, modelling inhibitory and excitatory signals of a neural network, or ‘negative and positive customers’ of a queueing network. Signals can arrive either from other units or from the outside world. Positive signals are accumulated at the input of each unit, and constitute its signal potential. The state of each unit or neuron is its signal potential (which is equivalent to the queue length), while the network state is the vector of signal potentials at each neuron. If its potential is positive, a unit or neuron fires, and sends out signals to the other neurons or to the outside world. As it does so, its signal potential is depleted. In the Markovian case, this model has product form, i.e. the steady-state probability distribution of its potential vector is the product of the marginal probabilities of the potential at each neuron. The signal flow equations of the network, which describe the rate at which positive or negative signals arrive to each neuron, are non-linear. We discuss the relationship between this model and the usual connectionist (formal) model of neural networks, and present applications to combinatorial optimization and to image texture processing. Extensions of the model to the case of ‘multiple signal classes’, and to ‘networks with triggered customer motion’ are presented. We also examine the general stability conditions which guarantee that the network has a well-defined steady-state behaviour. [ABSTRACT FROM AUTHOR]
- Published
- 1994
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14. Guest Editor's Introduction to the Special Issue On Neural Network Software and Systems.
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Gelenbe, Erol
- Subjects
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ARTIFICIAL neural networks , *ARTIFICIAL intelligence , *COMPUTER software , *COMPUTER systems , *SOFTWARE engineering , *COMPUTER networks , *COMPUTER programming - Abstract
This guest editorial introduces a special issue of the periodical "IEEE Transactions on Software Engineering" which focuses on neural network software and systems. It outlines the history of artificial neural networks and their role in the origin of the theory of computing. The special issue addresses aspects of neural computation that are closely related to software engineering. The main problem at hand is the development of paradigms to deal effectively with the issues related to neural network programming. The papers in the issue highlight increasingly important issues of artificial neural network programming tools and systems, and suggest applications of neural networks to the diverse and difficult problems of software engineering.
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- 1992
15. Modelling Dynamics of TCP Flows in Very Large Network Topologies
- Author
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Nycz, Monika, Nycz, Tomasz, Czachórski, Tadeusz, Abdelrahman, Omer H., editor, Gelenbe, Erol, editor, Gorbil, Gokce, editor, and Lent, Ricardo, editor
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- 2016
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16. Heuristic Algorithms for Real-Time Unsplittable Data Dissemination Problem
- Author
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Atanak, Mustafa Müjdat, Doğan, Atakan, Gelenbe, Erol, editor, Lent, Ricardo, editor, and Sakellari, Georgia, editor
- Published
- 2012
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