Sub-agent elements for control methods in multi-agent energy management system

Increased penetration of generation and decentralised control are considered to be feasible and effective solution for reducing cost and emissions and hence efficiency associated with power generation and distribution. Distributed generation in combination with the multi-agent technology are perfect candidates for this solution. Pro-active and autonomous nature of multi-agent systems can provide an effective platform for decentralised control whilst improving reliability and flexibility of the grid.

The causal surface and its effect on distribution transparency in a distributed virtual environment

One goal in the development of distributed virtual environments (DVEs) is to create a system such that users are unaware of the distribution-the distribution should be transparent. The paper begins by discussing the general issues in DVEs that might make this possible, and a system that allows some level of distribution transparency is described. The system described suffers from effects of inconsistency, which in turn cause undesirable visual effects. The causal surface is introduced as a solution that removes these visual effects. The paper then introduces two determining factors of distribution transparency relating to user perception and performance. With regard to these factors, two hypotheses are stated relating to the causal surface. A user-trial on forty-five subjects is used to validate the hypotheses. A discussion of the results of the trial concludes that the causal surface solution does significantly improve the distribution transparency in a DVE.

Distortion in Distributed Virtual Environments

This paper proposes a solution to the problems associated with network latency within distributed virtual environments. It begins by discussing the advantages and disadvantages of synchronous and asynchronous distributed models, in the areas of user and object representation and user-to-user interaction. By introducing a hybrid solution, which utilises the concept of a causal surface, the advantages of both synchronous and asynchronous models are combined. Object distortion is a characteristic feature of the hybrid system, and this is proposed as a solution which facilitates dynamic real-time user collaboration. The final section covers implementation details, with reference to a prototype system available from the Internet.

Random-walk-based characterisation of multiple access interference in a DS/SSMA system

The problem of calculating the probability of error in a DS/SSMA system has been extensively studied for more than two decades. When random sequences are employed some conditioning must be done before the application of the central limit theorem is attempted, leading to a Gaussian distribution. The authors seek to characterise the multiple access interference as a random-walk with a random number of steps, for random and deterministic sequences. Using results from random-walk theory, they model the interference as a K-distributed random variable and use it to calculate the probability of error in the form of a series, for a DS/SSMA system with a coherent correlation receiver and BPSK modulation under Gaussian noise. The asymptotic properties of the proposed distribution agree with other analyses. This is, to the best of the authors' knowledge, the first attempt to propose a non-Gaussian distribution for the interference. The modelling can be extended to consider multipath fading and general modulation

Grid computing solutions for distributed repositories of protein folding and unfolding simulations

The P-found protein folding and unfolding simulation repository is designed to allow scientists to perform analyses across large, distributed simulation data sets. There are two storage components in P-found: a primary repository of simulation data and a data warehouse. Here we demonstrate how grid technologies can support multiple, distributed P-found installations. In particular we look at two aspects, first how grid data management technologies can be used to access the distributed data warehouses; and secondly, how the grid can be used to transfer analysis programs to the primary repositories --- this is an important and challenging aspect of P-found because the data volumes involved are too large to be centralised. The grid technologies we are developing with the P-found system will allow new large data sets of protein folding simulations to be accessed and analysed in novel ways, with significant potential for enabling new scientific discoveries.

Distributed classification for pocket data mining

Distributed and collaborative data stream mining in a mobile computing environment is referred to as Pocket Data Mining PDM. Large amounts of available data streams to which smart phones can subscribe to or sense, coupled with the increasing computational power of handheld devices motivates the development of PDM as a decision making system. This emerging area of study has shown to be feasible in an earlier study using technological enablers of mobile software agents and stream mining techniques [1]. A typical PDM process would start by having mobile agents roam the network to discover relevant data streams and resources. Then other (mobile) agents encapsulating stream mining techniques visit the relevant nodes in the network in order to build evolving data mining models. Finally, a third type of mobile agents roam the network consulting the mining agents for a final collaborative decision, when required by one or more users. In this paper, we propose the use of distributed Hoeffding trees and Naive Bayes classifers in the PDM framework over vertically partitioned data streams. Mobile policing, health monitoring and stock market analysis are among the possible applications of PDM. An extensive experimental study is reported showing the effectiveness of the collaborative data mining with the two classifers.

P-found: grid-enabling distributed repositories of protein folding and unfolding simulations for data mining

The P-found protein folding and unfolding simulation repository is designed to allow scientists to perform data mining and other analyses across large, distributed simulation data sets. There are two storage components in P-found: a primary repository of simulation data that is used to populate the second component, and a data warehouse that contains important molecular properties. These properties may be used for data mining studies. Here we demonstrate how grid technologies can support multiple, distributed P-found installations. In particular, we look at two aspects: firstly, how grid data management technologies can be used to access the distributed data warehouses; and secondly, how the grid can be used to transfer analysis programs to the primary repositories — this is an important and challenging aspect of P-found, due to the large data volumes involved and the desire of scientists to maintain control of their own data. The grid technologies we are developing with the P-found system will allow new large data sets of protein folding simulations to be accessed and analysed in novel ways, with significant potential for enabling scientific discovery.

Demand response — a different form of distributed storage?

Reduced flexibility of low carbon generation could pose new challenges for future energy systems. Both demand response and distributed storage may have a role to play in supporting future system balancing. This paper reviews how these technically different, but functionally similar approaches compare and compete with one another. Household survey data is used to test the effectiveness of price signals to deliver demand responses for appliances with a high degree of agency. The underlying unit of storage for different demand response options is discussed, with particular focus on the ability to enhance demand side flexibility in the residential sector. We conclude that a broad range of options, with different modes of storage, may need to be considered, if residential demand flexibility is to be maximised.

Cost function for sub-agent elements in multi-agent energy management system

Distributed generation plays a key role in reducing CO2 emissions and losses in transmission of power. However, due to the nature of renewable resources, distributed generation requires suitable control strategies to assure reliability and optimality for the grid. Multi-agent systems are perfect candidates for providing distributed control of distributed generation stations as well as providing reliability and flexibility for the grid integration. The proposed multi-agent energy management system consists of single-type agents who control one or more gird entities, which are represented as generic sub-agent elements. The agent applies one control algorithm across all elements and uses a cost function to evaluate the suitability of the element as a supplier. The behavior set by the agent's user defines which parameters of an element have greater weight in the cost function, which allows the user to specify the preference on suppliers dynamically. This study shows the ability of the multi-agent energy management system to select suppliers according to the selection behavior given by the user. The optimality of the supplier for the required demand is ensured by the cost function based on the parameters of the element.

Using Distributed Temperature Sensing to monitor field scale dynamics of ground surface temperature and related substrate heat flux

We present one of the first studies of the use of Distributed Temperature Sensing (DTS) along fibre-optic cables to purposely monitor spatial and temporal variations in ground surface temperature (GST) and soil temperature, and provide an estimate of the heat flux at the base of the canopy layer and in the soil. Our field site was at a groundwater-fed wet meadow in the Netherlands covered by a canopy layer (between 0-0.5 m thickness) consisting of grass and sedges. At this site, we ran a single cable across the surface in parallel 40 m sections spaced by 2 m, to create a 40×40 m monitoring field for GST. We also buried a short length (≈10 m) of cable to depth of 0.1±0.02 m to measure soil temperature. We monitored the temperature along the entire cable continuously over a two-day period and captured the diurnal course of GST, and how it was affected by rainfall and canopy structure. The diurnal GST range, as observed by the DTS system, varied between 20.94 and 35.08◦C; precipitation events acted to suppress the range of GST. The spatial distribution of GST correlated with canopy vegetation height during both day and night. Using estimates of thermal inertia, combined with a harmonic analysis of GST and soil temperature, substrate and soil-heat fluxes were determined. Our observations demonstrate how the use of DTS shows great promise in better characterising area-average substrate/soil heat flux, their spatiotemporal variability, and how this variability is affected by canopy structure. The DTS system is able to provide a much richer data set than could be obtained from point temperature sensors. Furthermore, substrate heat fluxes derived from GST measurements may be able to provide improved closure of the land surface energy balance in micrometeorological field studies. This will enhance our understanding of how hydrometeorological processes interact with near-surface heat fluxes.

A case study of the Tatweer school system in Saudi Arabia: the perceptions of leaders and teachers

School reform is a major concern in many countries that seek to improve their educational systems and enhance their performances. In consequence, many global schemes, theories, studies, attempts, and programmes have been introduced to promote education in recent years. Saudi Arabia is one of these countries that implemented educational change by introducing many initiatives. The Tatweer Programme is one of these initiatives and is considered as a major recent reform. The main purpose of this study is to investigate this reform in depth by examining the perceptions and experiences of the Tatweer leaders and teachers to find out which extent they have been enabled to be innovative, and to examine the types of leadership and decision-making that have been undertaken by such schools. This study adopted a qualitative case study that employed interviews, focus groups and documentary analysis. The design of the study has been divided into two phases; the first phase was the feasibility study and the second phase was the main study. The research sample of the feasibility study was head teachers, educational experts and Tatweer Unit’s members. The sample of the main study was three Tatweer schools, Tatweer Unit members and one official of Tatweer Project in Riyadh. The findings of this study identified the level of autonomy in managing the school; the Tatweer schools’ system is semi-autonomous when it comes to the internal management, but it lacks autonomy when it comes to staff appointment, student assessment, and curriculum development. In addition, the managerial work has been distributed through teams and members; the Excellence Team plays a critical role in school effectiveness leading an efficient change. Moreover, Professional Learning Communities have been used to enhance the work within Tatweer schools. Finally the findings show that there have been major shifts in the Tatweer schools’ system; the shifting from centralisation to semi-decentralisation; from the culture of the individual to the culture of community; from the traditional school to one focused on self-evaluation and planning; from management to leadership; and from an isolated school being open to society. These shifts have impacted positively on the attitudes of students, parents and staff.

Distributed access control and privacy for the internet of me

This article presents an experimental scalable message driven IoT and its security architecture based on Decentralized Information Flow Control. The system uses a gateway that exports SoA (REST) interfaces to the internet simplifying external applications whereas uses DIFC and asynchronous messaging within the home environment.

Dynamics of Aeromonas species isolated from wastewater treatment system

Aeromonas are widely distributed in the aquatic environment, and are considered to be emerging organisms that can produce a series of virulence factors. The present study was carried out in a sanitary sewage stabilization pond treatment system, located in Lins, State of Sao Paulo, Brazil. Most probable number was applied for estimation of the genus Aeromonas. Colony isolation was carried out on blood agar ampicillin and confirmed by biochemical characterization. Aeromonas species were isolated in 72.4% of influent samples, and in 55.2 and 48.3% of effluent from anaerobic and facultative lagoons, respectively. Thirteen Aeromonas species were isolated, representing most of the recognized species of these organisms. Even though it was possible to observe a tendency of decrease, total elimination of these organisms from the studied system was not achieved. Understanding of the pathogenic organism`s dynamics in wastewater treatment systems with a reuse potential is especially important because of the risk it represents.

A Unified Load Generator for Geographically Distributed Generation ofNetwork Traffic

During the last decade, the Internet usage has been growing at an enormous rate which has beenaccompanied by the developments of network applications (e.g., video conference, audio/videostreaming, E-learning, E-Commerce and real-time applications) and allows several types ofinformation including data, voice, picture and media streaming. While end-users are demandingvery high quality of service (QoS) from their service providers, network undergoes a complex trafficwhich leads the transmission bottlenecks. Considerable effort has been made to study thecharacteristics and the behavior of the Internet. Simulation modeling of computer networkcongestion is a profitable and effective technique which fulfills the requirements to evaluate theperformance and QoS of networks. To simulate a single congested link, simulation is run with asingle load generator while for a larger simulation with complex traffic, where the nodes are spreadacross different geographical locations generating distributed artificial loads is indispensable. Onesolution is to elaborate a load generation system based on master/slave architecture.

Chained Negotiation for Distributed Notification Services

Distributed notification services allow consumers and publishers of notifications to interact with different notification services. However, such a distributed infrastructure makes it difficult to share notifications between consumers when consumers are allowed to specify Quality of Service levels. In this paper, we present a chained negotiation engine, enabling distributed notification services to support negotiation and to reuse existing subscriptions. We demonstrate the benefit to the system as a whole by reducing load on service providers and enabling content to be shared.