Dynamic Approach and Testbed for Small and Medium Players Simulation in Smart Grid Environments

The Smart Grid environment allows the integration of resources of small and medium players through the use of Demand Response programs. Despite the clear advantages for the grid, the integration of consumers must be carefully done. This paper proposes a system which simulates small and medium players. The system is essential to produce tests and studies about the active participation of small and medium players in the Smart Grid environment. When comparing to similar systems, the advantages comprise the capability to deal with three types of loads – virtual, contextual and real. It can have several loads optimization modules and it can run in real time. The use of modules and the dynamic configuration of the player results in a system which can represent different players in an easy and independent way. This paper describes the system and all its capabilities.

Dynamic task allocation and coordination in cooperative multi-agent environments

La coordinació i assignació de tasques en entorns distribuïts ha estat un punt important de la recerca en els últims anys i aquests temes són el cor dels sistemes multi-agent. Els agents en aquests sistemes necessiten cooperar i considerar els altres agents en les seves accions i decisions. A més a més, els agents han de coordinar-se ells mateixos per complir tasques complexes que necessiten més d'un agent per ser complerta. Aquestes tasques poden ser tan complexes que els agents poden no saber la ubicació de les tasques o el temps que resta abans de que les tasques quedin obsoletes. Els agents poden necessitar utilitzar la comunicació amb l'objectiu de conèixer la tasca en l'entorn, en cas contrari, poden perdre molt de temps per trobar la tasca dins de l'escenari. De forma similar, el procés de presa de decisions distribuït pot ser encara més complexa si l'entorn és dinàmic, amb incertesa i en temps real. En aquesta dissertació, considerem entorns amb sistemes multi-agent amb restriccions i cooperatius (dinàmics, amb incertesa i en temps real). En aquest sentit es proposen dues aproximacions que permeten la coordinació dels agents. La primera és un mecanisme semi-centralitzat basat en tècniques de subhastes combinatòries i la idea principal es minimitzar el cost de les tasques assignades des de l'agent central cap als equips d'agents. Aquest algoritme té en compte les preferències dels agents sobre les tasques. Aquestes preferències estan incloses en el bid enviat per l'agent. La segona és un aproximació d'scheduling totalment descentralitzat. Això permet als agents assignar les seves tasques tenint en compte les preferències temporals sobre les tasques dels agents. En aquest cas, el rendiment del sistema no només depèn de la maximització o del criteri d'optimització, sinó que també depèn de la capacitat dels agents per adaptar les seves assignacions eficientment. Addicionalment, en un entorn dinàmic, els errors d'execució poden succeir a qualsevol pla degut a la incertesa i error de accions individuals. A més, una part indispensable d'un sistema de planificació és la capacitat de re-planificar. Aquesta dissertació també proveeix una aproximació amb re-planificació amb l'objectiu de permetre als agent re-coordinar els seus plans quan els problemes en l'entorn no permeti la execució del pla. Totes aquestes aproximacions s'han portat a terme per permetre als agents assignar i coordinar de forma eficient totes les tasques complexes en un entorn multi-agent cooperatiu, dinàmic i amb incertesa. Totes aquestes aproximacions han demostrat la seva eficiència en experiments duts a terme en l'entorn de simulació RoboCup Rescue.

Dynamic virtual environments using really simple syndication

This paper investigates the use of really simple syndication (RSS) to dynamically change virtual environments. The case study presented here uses meteorological data downloaded from the Internet in the form of an RSS feed, this data is used to simulate current weather patterns in a virtual environment. The downloaded data is aggregated and interpreted in conjunction with a configuration file, used to associate relevant weather information to the rendering engine. The engine is able to animate a wide range of basic weather patterns. Virtual reality is a way of immersing a user into a different environment, the amount of immersion the user experiences is important. Collaborative virtual reality will benefit from this work by gaining a simple way to incorporate up-to-date RSS feed data into any environment scenario. Instead of simulating weather conditions in training scenarios, actual weather conditions can be incorporated, improving the scenario and immersion.

Modeling a dynamic data replication strategy to increase system availability in cloud computing environments

Failures are normal rather than exceptional in the cloud computing environments. To improve system avai-lability, replicating the popular data to multiple suitable locations is an advisable choice, as users can access the data from a nearby site. This is, however, not the case for replicas which must have a fixed number of copies on several locations. How to decide a reasonable number and right locations for replicas has become a challenge in the cloud computing. In this paper, a dynamic data replication strategy is put forward with a brief survey of replication strategy suitable for distributed computing environments. It includes: 1) analyzing and modeling the relationship between system availability and the number of replicas; 2) evaluating and identifying the popular data and triggering a replication operation when the popularity data passes a dynamic threshold; 3) calculating a suitable number of copies to meet a reasonable system byte effective rate requirement and placing replicas among data nodes in a balanced way; 4) designing the dynamic data replication algorithm in a cloud. Experimental results demonstrate the efficiency and effectiveness of the improved system brought by the proposed strategy in a cloud.

Understanding data quality issues in dynamic organisational environments – a literature review

Technology has been the catalyst that has facilitated an explosion of organisational data in terms of its velocity, variety, and volume, resulting in a greater depth and breadth of potentially valuable information, previously unutilised. The variety of data accessible to organisations extends beyond traditional structured data to now encompass previously unobtainable and difficult to analyse unstructured data. In addition to exploiting data, organisations are now facing an even greater challenge of assessing data quality and identifying the impacts of lack of quality. The aim of this research is to contribute to data quality literature, focusing on improving a current understanding of business-related Data Quality (DQ) issues facing organisations. This review builds on existing Information Systems literature, and proposes further research in this area. Our findings confirm that the current literature lags in recognising new types of data and imminent DQ impacts facing organisations in today’s dynamic environment of the so-called “Big Data”. Insights clearly identify the need for further research on DQ, in particular in relation to unstructured data. It also raises questions regarding new DQ impacts and implications for organisations, in their quest to leverage the variety of available data types to provide richer insights.

Collaborative data stream mining in ubiquitous environments using dynamic classifier selection

In ubiquitous data stream mining applications, different devices often aim to learn concepts that are similar to some extent. In these applications, such as spam filtering or news recommendation, the data stream underlying concept (e.g., interesting mail/news) is likely to change over time. Therefore, the resultant model must be continuously adapted to such changes. This paper presents a novel Collaborative Data Stream Mining (Coll-Stream) approach that explores the similarities in the knowledge available from other devices to improve local classification accuracy. Coll-Stream integrates the community knowledge using an ensemble method where the classifiers are selected and weighted based on their local accuracy for different partitions of the feature space. We evaluate Coll-Stream classification accuracy in situations with concept drift, noise, partition granularity and concept similarity in relation to the local underlying concept. The experimental results show that Coll-Stream resultant model achieves stability and accuracy in a variety of situations using both synthetic and real world datasets.

Multi-robot control in highly dynamic, competitive environments

The control and coordination of multiple mobile robots is a challenging task; particularly in environments with multiple, rapidly moving obstacles and agents. This paper describes a robust approach to multi-robot control, where robustness is gained from competency at every layer of robot control. The layers are: (i) a central coordination system (MAPS), (ii) an action system (AES), (iii) a navigation module, and (iv) a low level dynamic motion control system. The multi-robot coordination system assigns each robot a role and a sub-goal. Each robot’s action execution system then assumes the assigned role and attempts to achieve the specified sub-goal. The robot’s navigation system directs the robot to specific goal locations while ensuring that the robot avoids any obstacles. The motion system maps the heading and speed information from the navigation system to force-constrained motion. This multi-robot system has been extensively tested and applied in the robot soccer domain using both centralized and distributed coordination.

Knowledge creation in dynamic learning environments

Researchers have extensively discussed using knowledge management to achieve sustainable competitive advantages; however, the successful implementation of knowledge management programs in organizations remains challenging. Problems with knowledge management arise primarily from issues related to inter-subjective creation of meaning by diverse individuals in a dynamic learning environment. ^ The first part of this dissertation examined the concepts of shared interpretive resources referring to background assumptions, shared language, and symbolic resources upon which individuals draw in their interactions in the community. The discussion adopted an interpretive research approach to underscore how community members develop shared interpretive resources over time. The second part examined how learners' behaviors influence knowledge acquisition in the community, emphasizing the associations between learners' learning approaches and learning contexts. An empirical survey of learners provided significant evidence to demonstrate the influences of learners' learning approaches. The third part examined an instructor's strategy—namely, advance organizer—to enhance learners' knowledge assimilation process. Advance organizer is an instructor strategy that refers to a set of inclusive concepts that introduce and sum up new material, and refers to a method of bridging and linking old information with something new. In this part, I underscore the concepts of advance organizer, and the implementations of advance organizer in one learning environment. A study was conducted in one higher educational environment to show the implementation of advance organizer. Additionally, an advance organizer instrument was developed and tested, and results from learners' feedback were analyzed. The significant empirical evidence showed the association between learners' learning outcomes and the implementation of advance organizer strategy. ^