Efficient peerGroup management in JXTA-Overlay P2P system for developing groupware tools

With the fast development of IT technologies, virtual organizations are more and more present in the current collaborative work and learning activity. For instance, many subjects in virtual distance learning are organized as online groups of students, who use groupware tools to complete their learning tasks. In this paper, we address the efficient management of peer groups in JXTA-based P2P systems as a key issue in many P2P applications that use peer group as a unit such as for remote execution of tasks in parallel and distributed applications. From this perspective, we consider peer grouping as the basis in the development of groupware tools in P2P systems.     

Local search methods for efficient router nodes placement in wireless mesh networks

Wireless Mesh Networks (WMNs) are an important networking infrastructure for providing cost-efficient broadband wireless connectivity to a group of users. WMNs are increasingly being used in urban, metropolitan and municipal area networks for deployment of medical, transport, surveillance systems, etc. The performance and operability of WMNs largely depends on placement of mesh routers nodes in the geographical area to achieve network connectivity and stability. The objective is to find an optimal and robust topology of the mesh router network to support intelligent telecommunication services to clients such as adaptive and flexible wireless Internet access, mobile data, voice, video in addition to supporting other preferred client services. In this work, we propose and evaluate local search methods for intelligent placement of mesh routers in WMNs with a two fold objective: maximizing the size of the giant component in the network and user coverage. Given a grid area where to distribute a given number of mesh router nodes, which can have different radio coverage, and a number of fixed clients a priori distributed in the given area, local search methods explore different local movements and incrementally improve the quality of the router nodes placement in terms of network connectivity and user coverage. We have experimentally evaluated the proposed local search methods through a benchmark of generated instances of varying sizes. Moreover, different distributions of mesh clients (Uniform, Normal, Exponential and Weibull) are used. The experimental evaluation showed the good performance of local search methods for optimizing network connectivity and user coverage in WMNs.     

Prioritization methodology of dangerous substances for water quality monitoring with scarce data

Monitoring and control of dangerous substances discharged into receiving waters have attracted more attention lately. Since it is not possible to analyze every single substance, a prioritization methodology is needed for the selection of those to be monitored. Existing well-developed models require significant amount of data for reliable outcomes. This paper presents a methodology to prioritize the dangerous substances having adverse effects on freshwaters in Turkey, where data are scarce. Such a methodology will also serve as a solid model for other countries with limited background data. The adopted methodology enabled the elimination of chemicals to generate a candidate list composed of 608 substances among more than 5000 substances. Further screening and prioritization were conducted using different assessment methods (i.e., Total Hazard Value, Total Impact Value, Combined Monitoring-based, and Modelling-based Priority Setting) to obtain a proposed Final Candidate Specific Pollutants List of 150 dangerous substances. The proposed Candidate National Pollutant List of Turkey was established by combining 45 priority pollutants of the European Union with a list of candidate specific pollutants. According to the outcomes of this study, monitoring and controlling of 195 dangerous substances in freshwaters are recommended. Further detailed studies should be conducted in order to observe the actual levels of these dangerous substances in freshwaters followed by a review of the monitoring list accordingly. Moreover, further revisions might be required in the proposed list due to some possible versatile conditions in terms of sampling points (i.e., change in the location of industries).     

On the capacity limits of HVAC duct channel for high-speed Internet access

In this paper, we report theoretical and experimental channel-capacity estimates of heating, ventilation, and air conditioning (HVAC) ducts based on multicarrier transmission that uses M-ary quadrature amplitude modulation and measured channel responses at the 2.4-GHz industrial, scientific, and medical band. It is shown theoretically that data rates in excess of 1 Gb/s are possible over distances up to 500 m in straight ducts in which reflections have been suppressed. Our experimental results also show that even in the case of more complex HVAC duct networks (i.e., HVAC duct networks that include bends, tees, etc.) data rates over 2 Gb/s are possible. Our estimations in this case are valid for distances of up to 22 m, which was the maximum distance of our experimental setup. These experimental results, measured with a large-scale testbed set up at Carnegie Mellon University, Pittsburgh, PA, albeit limited in terms of transmitter-receiver separation distance, provide further evidence on the potential of HVAC systems as an attractive solution for providing communications in indoor wireless networks.     

A simple path-loss prediction model for HVAC systems

In this paper, we present a simple path-loss prediction model for link budget analysis in indoor wireless local area networks that use heating, ventilation, and air conditioning (HVAC) cylindrical ducts in the 2.4-2.5-GHz industrial, scientific, and medical band. The model we propose predicts the average power loss between a transmitter-receiver pair in an HVAC duct network. This prediction model greatly simplifies the link budget analysis for a complex duct network, making it a convenient and simple tool for system design. The accuracy of our prediction model is verified by an extensive set of experimental measurements.     

Impulse response of the HVAC duct as a communication channel

Heating, ventilation, and air conditioning (HVAC) ducts in buildings behave as multimode waveguides when excited at radio frequencies and thus, can be used to distribute radio signals. The channel properties of the ducts are different from the properties of a usual indoor propagation channel. In this paper, we describe physical mechanisms which affect the HVAC channel impulse response and analyze their influence on the delay spread. Those mechanisms include antenna coupling, attenuation, and three types of dispersion: intramodal, intermodal, and multipath. We analyze each type separately and explore the behavior of the delay spread as a function of distance in straight ducts. Experimental channel measurements taken on real ducts confirm the validity of our model.     

Reflex sympathetic dystrophy syndrome due to arteriovenous fistula

A patient with end-stage renal disease presented with reflex sympathetic dystrophy syndrome (RSDS) on her left hand 1 month after arteriovenous fistula (AVF) surgery. Magnetic resonance angiography revealed steal syndrome at the AVF level. Bone scintigraphy revealed early-stage RSDS. We considered that arterial insufficiency because of steal phenomenon following AVF surgery and underlying occlusive arterial disease triggered RSDS development.     

Stochastic simulation and modelling of metabolic networks in a machine learning framework

Metabolomics is increasingly becoming an important field. The fundamental task in this area is to measure and interpret complex time and condition dependent parameters such as the activity or flux of metabolites in cells, their concentration, tissues elements and other biosamples. The careful study of all these elements has led to important insights in the functioning of metabolism. Recently, however, there is a growing interest towards an integrated approach to studying biological systems. This is the main goal in Systems Biology where a combined investigation of several components of a biological system is thought to produce a thorough understanding of such systems. Biological circuits are complex to model and simulate and many efforts are being made to develop models that can handle their intrinsic complexity. A significant part of biological networks still remains unknown even though recent technological developments allow simultaneous acquisition of many metabolite measurements. Metabolic networks are not only structurally complex but behave also in a stochastic fashion. Therefore, it is necessary to express structure and handle uncertainty to construct complete dynamics of these networks. In this paper we describe how stochastic modeling and simulation can be performed in a symbolic-statistical machine learning (ML) framework. We show that symbolic ML deal with structural and relational complexity while statistical ML provides principled approaches to uncertainty modeling. Learning is used to analyze traces of biochemical reactions and model the dynamicity through parameter learning, while inference is used to produce stochastic simulation of the network.     

Modeling and performance analysis of networking and collaborative systems

The special issue on Modeling and Performance Analysis of Networking and Collaborative Systems by leveraging current networks and collaborative applications. In addition, the incorporation of the latest and powerful technologies, based on distributed infrastructure, is also explored for the enhancement of these applications, resulting in complex and entangled systems that pose new issues and challenges, in terms of efficiency, security, mobility, and so on. The goal is to respond to the need for methods and tools for performance analysis and evaluation of current complex collaborative and networking systems and applications. To this direction, this special issue provides latest research on modeling and performance analysis of networking and collaborative systems from different perspectives.