Rallis C. Papademetriou

Reconstructing with moments

The relatively old problem of image reconstruction from a finite set of its geometric moments (inverse moment problem) is examined. The application of the information-theoretic method of Maximum Entropy (ME) is proposed and compared to the Legendre Moments (LM) approach. Several computer simulations are presented that demonstrate the superiority of the proposed technique. The comparative study is extended to include the case of noise-corrupted images.<<ETX>>

An improved multi-agent simulation methodology for modelling and evaluating wireless communication systems resource allocation algorithms

Multi-Agent Systems (MAS) constitute a well known approach in modelling dynamical real world systems. Recently, this technology has been applied to Wireless Communication Systems (WCS), where efficient resource allocation is a primary goal, for modelling the physical entities involved, like Base Stations (BS), service providers and network operators. This paper presents a novel approach in applying MAS methodology to WCS resource allocation by modelling more abstract entities involved in WCS operation, and especially the concurrent network procedures (services). Due to the concurrent nature of a WCS, MAS technology presents a suitable modelling solution. Services such as new call admission, handoff, user movement and call termination are independent to one another and may occur at the same time for many different users in the network. Thus, the required network procedures for supporting the above services act autonomously, interact with the network environment (gather information such as interference conditions), take decisions (e.g. call establishment), etc, and can be modelled as agents. Based on this novel simulation approach, the agent cooperation in terms of negotiation and agreement becomes a critical issue. To this end, two negotiation strategies are presented and evaluated in this research effort and among them the distributed negotiation and communication scheme between network agents is presented to be highly efficient in terms of network performance. The multi-agent concept adapted to the concurrent nature of large scale WCS is, also, discussed in this paper.

On the implementation of ant colony optimization scheme for improved channel allocation in wireless communications

Channel allocation in wireless communication systems is one of the fundamental issues. The corresponding allocation schemes can not be static due to the dynamically changing traffic conditions and network performance. Thus, more sophisticated strategies adapted to current network conditions must be investigated and applied. Recently, various approaches have been proposed for channel allocation based on intelligent techniques such as multi-agent technology and genetic algorithms. These approaches constitute heuristic solutions to resource management problem. On the other hand, the ant colony optimization approach has been proposed for solving optimization problems but this approach has not been proposed so far for solving the channel allocation problem in wireless communication systems. In this paper, a comprehensive heuristic approach for solving the channel allocation problem based on intelligent techniques such as multi-agents and ant colony optimization is proposed. Moreover, important implementation issues such as thread execution sequence are also presented. Finally, the simulation results show the performance improvement of the proposed ant colony optimization algorithm as well as the multi-agent modeling approach.

Experimental comparison of two information-theoretic spectral estimators

The use of the minimum cross-entropy (MCE) principle in spectrum estimation, resulting in an information-theoretic method that explicitly includes prior spectral information, has followed two philosophically different pathways leading to two distinct estimators, cross-entropy (CE) and spectral cross-entropy (SCE) respectively. These estimators are compared experimentally, regarding resolvability and fidelity. The data model assumed consists of two equal-amplitude sinusoidal signals, immersed in 1/f noise. The CE estimator appears to have evident superiority in this study.

On Multi Agent based modeling and control in large scale wireless communication systems for improved resource allocation performance

The goal of this paper is to investigate the application of the Multi Agent technology in modeling and simulating large scale wireless communication systems. There are very few studies using the multi agent concept as an alternative approach for designing and simulating resource allocation in cellular systems and especially in large scale ones. Thus, a novel modeling methodology of wireless network services exploiting multi agent technology and investigating in depth critical agent issues is proposed in this paper. It is shown that the multi agent concept proves to be a suitable solution for modeling and implementing cellular network services simulation even in the case of large scale wireless networks. The whole investigation is divided in two phases: (a) multi agent modeling analysis and (b) multi agent model development for controlling network performance. Simulation results show the effectiveness of the proposed multi agent model when is applied in combination with the state of the art event scheduling mechanism.

On the multi-threading approach of efficient multi-agent methodology for modelling cellular communications bandwidth management

There are very few studies using the multi agent concept as an alternative and efficient approach for bandwidth management. The goal of the paper is to propose a novel modelling methodology of wireless network services exploiting multi-agent technology and investigating in depth critical implementation issues of multi-threading techniques focused on network agents. Moreover, it is claimed that an advanced negotiation scheme between network service agents can lead to better model network performance. Thus, the multi agent concept seems a suitable solution for modelling and implementing cellular services simulation. The proposed agent based modelling as well as the proposed implementation methodology of the wireless services are herein presented in three levels; (a) multi agent modelling of the wireless services, (b) developing an advanced negotiation scheme based on current status and curve statistics of network performance and (c) investigating critical multi threading based implementation issues of the suggested multi agent modelling. Finally, simulation results show the effectiveness of the proposed multi agent approach as well as of the proposed negotiation scheme based on blocking and dropping probability curve statistics.

A Multi-agent Architecture for Designing and Simulating Large Scale Wireless Systems Resource Allocation

The simulation model adaptability to real network behavior is the key concept in wireless communications. In a cellular network, many procedures such as call admission, hand-off, etc take place simultaneously for every individual user. Every network procedure acts autonomously, interacts with the network environment (gathers information such as interference conditions), takes decisions (e.g. call establishment), etc. Although this is known in the literature, there is lack of suitable representations for such network procedures in the simulation systems proposed so far, thus compromising simulation model adaptability to real network behavior. To achieve such adaptability we herein propose to change the point of view in network procedure representation. Instead of viewing them as independent programming functions or even objects in a high level language, which are sequentially executed, due to their aforementioned properties it is proposed that such network procedures could be more efficiently modeled as agents. Considering this new approach, the agent cooperation and communication in terms of negotiation and agreement is a critical issue. In this paper we present a centralized cooperative multi-agent negotiation scheme applied to a multi-agent layered architecture for designing and simulating resource allocation in cellular communication systems, based on organizational modeling. Moreover, we show the way that the rules and implementation methods of agent negotiation affect the adaptation grade of simulation model to the real cellular network behavior.

Evaluating novel DCA variations for efficient channel assignment in cellular communications through a generic Java simulation system

In recent years, mobile telephony, computing and services have emerged as an important field of research. The rapid evolution of cellular technology and the augmentative user demand for advanced mobile services leads the industry to develop more efficient network structures. The increasing number of cellular users and the demand for broadband mobile communications (3rd and 4th generation) drives to the research of new methodologies for the design of cellular networks and services. One of the issues in such a design is selection of channel allocation schemes. This paper thoroughly reviews centralized and mainly distributed DCA schemes and presents several new efficient variations suitable for large scale cellular systems. On the other hand, Simulation environments more than ever offer the opportunity to develop and study with low cost new structures and methods for the implementation of new services. To this end, this paper proposes a comprehensive simulation system for evaluating channel assignment schemes incorporating their principles, entities and concepts involved. The proposed system is implemented in Java, in order to create a high performance generic simulation environment with the future capability of internetworking. The system is designed with the goal to be efficient in simulating large scale generic cellular telecommunication systems. Moreover, another goal of the proposed system is to serve as a test bed for the evaluation and development of DCA schemes (especially for educational purposes) involved in such large scale cellular systems towards their planning as effective cellular mobile radio networks.

On Cellular Network Channels Data Mining and Decision Making through Ant Colony Optimization and Multi Agent Systems Strategies

Finding suitable channels to allocate in order to serve increasing user demands in a cellular network, which is a dynamical system, constitute the most important issue in terms of network performance since they define the bandwidth management methodology. In modern cellular networks these strategies become challenging issues especially when advanced services are applied. The effectiveness of decision making for channel allocation in a cellular network is strongly connected to current traffic and wireless environment conditions. Moreover, in large scale environments, network states change dynamically and the network performance prediction is a hard task. In the recent literature, the network adaptation to current real user needs seems it could be achieved through computational intelligence based channel allocation schemes mainly involving genetic algorithms. In this paper, a quite new approach for communication channels decision making, based on ant colony optimization, which is a special form of swarm intelligence, modelled through multi agent methodology is presented. The main novelty of this research lies on modelling this optimization scheme through multi agent systems. The simulation model architecture which includes network and ant agents are also presented as well as the performance results based on the above techniques. Finally, the current study, also, shows that there is a great field of research concerning intelligent techniques modelled through multi-agent methodologies focused on channels decision making and bandwidth management in wireless communication systems.

A Multi-Agent Simulation Model for Wireless Communications Involving an Improved Agent Negotiation Scheme Based on Real Time Event Scheduling Mechanisms

An improved multi-agent simulation model is presented in this paper for modeling resource allocation strategies in wireless communications. It is based on a novel agent negotiation methodology based on real time event scheduling extending calendar queue algorithm. The application of the new scheme in modeling GSM cellular networks shows significant enhancements with regards to network modeling performance compared to rival simulation modeling techniques.