Use of Self-Healing Techniques for Highly-Available Distributed Monitoring

The paper addresses the self-healing aspects of the monitoring systems. Nowadays, when the complex distributed systems are concerned, the monitoring system should become "intelligent" - as the first step it can guide the user what should be monitored. The next level of the "intelligence" can be described by the term "self-healing". The goal is to provide the capability that a decision made automatically by the monitoring system should force the system under monitoring to behave more stable, reliable and predictable. In the paper a new monitoring system is presented: AgeMon is an agent based, distributed monitoring system with strictly defined roles which can be performed by the agents. In the paper we discuss self-healing in the context of monitoring. When the self-healing of the monitoring system is concerned, a good example is the case where it is possible to lose the monitoring data due to the storage problems. AgeMon can handle such problems and automatically elects substitute persistence agents to store the data

Improving the decision-making process using an information management system

Research article published on Special Issue of International Journal of Current Research. Also available online at http://www.journalcra.com.The ability to make effective decisions is crucial to an organization’s survival in today’s tumultuous business environment. In order for firms to evaluate alternatives and make informed choices they must have reliable and timely data upon which to make their decisions. Consequently, the development of effective information management techniques is critical. In this research a web-based information management system is developed for better decisionmaking. Two agents are integrated in the system, namely; mapping agent and extraction agent. The mapping agent reduces the workload for users charged with the responsibility of data entry. The extraction agent is designed to aid in the retrieval of current, timely and relevant data, eliminating unnecessary information. The critical information requirements are identified and a prototype is developed for verification. The prototype is developed using PHP language for the system interfaces with GD for providing a graphical reporting supported by a MySQL database. The system is implemented and tested at a Kenyan based Internet Service Provider. As a result, the organization under study increases its sales through improved targeted marketing and monitoring of the outcome. The user load is also reduced by half and the risk of data input errors minimized by 80%.The ability to make effective decisions is crucial to an organization’s survival in today’s tumultuous business environment. In order for firms to evaluate alternatives and make informed choices they must have reliable and timely data upon which to make their decisions. Consequently, the development of effective information management techniques is critical. In this research a web-based information management system is developed for better decisionmaking. Two agents are integrated in the system, namely; mapping agent and extraction agent. The mapping agent reduces the workload for users charged with the responsibility of data entry. The extraction agent is designed to aid in the retrieval of current, timely and relevant data, eliminating unnecessary information. The critical information requirements are identified and a prototype is developed for verification. The prototype is developed using PHP language for the system interfaces with GD for providing a graphical reporting supported by a MySQL database. The system is implemented and tested at a Kenyan based Internet Service Provider. As a result, the organization under study increases its sales through improved targeted marketing and monitoring of the outcome. The user load is also reduced by half and the risk of data input errors minimized by 80%

Large structural impact localization based on multi-agent system

In practical applications of structural health monitoring, a huge amount of distributed sensors are usually used to monitor structures of large dimensions. In order to obtain fast and accurate evaluation of a structure, a multi-agent system is introduced to manage different sensor sets and to fuse distributed information. In this paper, a multi-agent system based on impact location is presented to deal with the impact load localization problem for large-scale structures. The monitoring system firstly detects whether an impact event happens in the monitored subregion, and focuses on the impact source on the sub-region boundary to obtain the sensor network data with blackboard systems. Then the collaborative evaluation of both the acoustic emission and the inverse analysis localization method is employed to obtain precise and fast localization result. Finally, a reliable assessment for the whole structure is provided by fusing evaluation results from the sub-regions. The performance of the proposed multi-agent system is illustrated by means of experimental on a large aerospace aluminum plate structure. Extensive testing of the proposed system demonstrated its effectiveness for the impact load localization in each sub-region, particularly for impacts lying next to the borders of the sub-regions

REAL-TIME MONITORING OF WIND CONVERTERS BASED ON SOFTWARE AGENTS

Due to increasing numbers of wind energy converters, the accurate assessment of the lifespan of their structural parts and the entire converter system is becoming more and more paramount. Lifespan-oriented design, inspections and remedial maintenance are challenging because of their complex dynamic behavior. Wind energy converters are subjected to stochastic turbulent wind loading causing corresponding stochastic structural response and vibrations associated with an extreme number of stress cycles (up to 109 according to the rotation of the blades). Currently, wind energy converters are constructed for a service life of about 20 years. However, this estimation is more or less made by rule of thumb and not backed by profound scientific analyses or accurate simulations. By contrast, modern structural health monitoring systems allow an improved identification of deteriorations and, thereupon, to drastically advance the lifespan assessment of wind energy converters. In particular, monitoring systems based on artificial intelligence techniques represent a promising approach towards cost-efficient and reliable real-time monitoring. Therefore, an innovative real-time structural health monitoring concept based on software agents is introduced in this contribution. For a short time, this concept is also turned into a real-world monitoring system developed in a DFG joint research project in the authors’ institute at the Ruhr-University Bochum. In this paper, primarily the agent-based development, implementation and application of the monitoring system is addressed, focusing on the real-time monitoring tasks in the deserved detail

To Trust or Not: The Effects of Monitoring Intensity on Discretionary Effort, Honesty, and Problem Solving Ability

Managerial accounting researchers and practitioners are increasingly concerned with the effects of formal organizational controls on agent behavior. This three-paper dissertation extends this line of research by experimentally examining the effects of monitoring intensity on three important work behaviors which, generally, are not directly observable by the organizational control system: discretionary effort, problem solving ability, and honesty. Together, these studies help fill a gap in the managerial accounting literature by examining the relationship between the monitoring environment and agent behavior. The principal-agent theory of the firm suggests that tighter monitoring by the principal will increase the agent’s work effort at best, and have no effect at worst. However, the psychology literature suggests that monitoring may actually reduce effort by “crowding out” an individual’s intrinsic motivation to perform unmeasured or unrewarded work related tasks. In Paper 1, I test for the crowding out effect of monitoring and find mixed results. In Paper 2, I investigate the effects of monitoring intensity on various aspects of problem solving ability and creativity. Past research suggests that strict environmental controls can have detrimental effects on creative thinking. I extend this line of literature by investigating how monitoring affects an individual’s problem solving ability. In general, I find that monitoring intensity is negatively associated with problem solving ability. In Paper 3, I investigate how monitoring intensity affects an individual’s propensity toward dishonesty using a 3x2 experimental design where the participants are given a simple task, with a monetary reward based on performance, in one of the three monitoring treatments—trust, human monitoring, or electronic monitoring—and in one of two outcome reporting regimes—self-report or verified. I find an inverted-U shape relationship between monitoring intensity and dishonesty, where dishonesty is highest under human monitoring. Organizations are increasing their use of all types of surveillance and controls, and, in general, trust is increasingly discouraged within organizations. These papers add to the managerial accounting literature by shedding light on how different monitoring environments can change human behavior. This line of research can only increase in importance as regulation increases and monitoring technology becomes more advanced, reliable, and accessible

MonALISA : A Distributed Monitoring Service Architecture

The MonALISA (Monitoring Agents in A Large Integrated Services Architecture) system provides a distributed monitoring service. MonALISA is based on a scalable Dynamic Distributed Services Architecture which is designed to meet the needs of physics collaborations for monitoring global Grid systems, and is implemented using JINI/JAVA and WSDL/SOAP technologies. The scalability of the system derives from the use of multithreaded Station Servers to host a variety of loosely coupled self-describing dynamic services, the ability of each service to register itself and then to be discovered and used by any other services, or clients that require such information, and the ability of all services and clients subscribing to a set of events (state changes) in the system to be notified automatically. The framework integrates several existing monitoring tools and procedures to collect parameters describing computational nodes, applications and network performance. It has built-in SNMP support and network-performance monitoring algorithms that enable it to monitor end-to-end network performance as well as the performance and state of site facilities in a Grid. MonALISA is currently running around the clock on the US CMS test Grid as well as an increasing number of other sites. It is also being used to monitor the performance and optimize the interconnections among the reflectors in the VRVS system.Comment: Talk from the 2003 Computing in High Energy and Nuclear Physics (CHEP03), La Jolla, Ca, USA, March 2003, 8 pages, pdf. PSN MOET00

Towards security monitoring patterns

Runtime monitoring is performed during system execution to detect whether the system’s behaviour deviates from that described by requirements. To support this activity we have developed a monitoring framework that expresses the requirements to be monitored in event calculus – a formal temporal first order language. Following an investigation of how this framework could be used to monitor security requirements, in this paper we propose patterns for expressing three basic types of such requirements, namely confidentiality, integrity and availability. These patterns aim to ease the task of specifying confidentiality, integrity and availability requirements in monitorable forms by non-expert users. The paper illustrates the use of these patterns using examples of an industrial case study