The migration process of mobile agents: implementation, classification, and optimization

Mobile Agenten stellen ein neues faszinierendes Design-Paradigma für den Aufbau und die Programmierung von verteilten Systemen dar. Ein mobiler Agent ist eine Software-Entität, die von ihrem Besitzer mit einem Auftrag auf einem Knoten eines verteilten Systems gestartet wird und dann zur Laufzeit auf andere Knoten des Netzwerkes migriert. Diese Arbeit konzentriert sich auf den Migrationsprozess für mobile Agenten, dem in der Literatur bisher wenig Aufmerksamkeit geschenkt wurde, obwohl er die Ausführungsgeschwindigkeit eines Agenten entscheidend beeinflusst. Eine detaillierte Analyse der Netzbelastung von mobilen Agenten im Vergleich zum traditionellen Client-Server Ansatz in mehreren typischen Anwendungsszenarien zeigt das Potential von mobilen Agenten zur Verringerung von Verarbeitungszeiten. Allerdings zeigt die Analyse ebenso die Nachteile der in heutigen Agentensystemen verwendenten sehr einfachen Migrationstechniken. Es wird ein neues Migrationsmodell mit Namen Kalong vorgestellt, das den Nachteil der fehlenden Anpassbarkeit heutiger Agentensysteme beseitigt und dem Programmierer eines mobilen Agenten eine sehr flexible Technik für die Migration zur Verfügung stellt

Expanding the Horizons of Manufacturing: Towards Wide Integration, Smart Systems and Tools

This research topic aims at enterprise-wide modeling and optimization (EWMO) through the development and application of integrated modeling, simulation and optimization methodologies, and computer-aided tools for reliable and sustainable improvement opportunities within the entire manufacturing network (raw materials, production plants, distribution, retailers, and customers) and its components. This integrated approach incorporates information from the local primary control and supervisory modules into the scheduling/planning formulation. That makes it possible to dynamically react to incidents that occur in the network components at the appropriate decision-making level, requiring fewer resources, emitting less waste, and allowing for better responsiveness in changing market requirements and operational variations, reducing cost, waste, energy consumption and environmental impact, and increasing the benefits. More recently, the exploitation of new technology integration, such as through semantic models in formal knowledge models, allows for the capture and utilization of domain knowledge, human knowledge, and expert knowledge toward comprehensive intelligent management. Otherwise, the development of advanced technologies and tools, such as cyber-physical systems, the Internet of Things, the Industrial Internet of Things, Artificial Intelligence, Big Data, Cloud Computing, Blockchain, etc., have captured the attention of manufacturing enterprises toward intelligent manufacturing systems

Multi-Agent Modeling for Integrated Process Planning and Scheduling

Multi-agent systems have been used for modelling various problems in the social, biological and technical domain. When comes to technical systems, especially manufacturing systems, agents are most often applied in optimization and scheduling problems. Traditionally, scheduling is done after creation of process plans. In this paper, agent methodology is used for integration of these two functions. The proposed multi-agent architecture provides simultaneous performance of process planning and scheduling and it consists of four intelligent agents: part and job agents, machine agent, and optimization agent. Verification and feasibility of a proposed approach is conducted using agent based simulation in AnyLogic software

Multi-Agent Modeling for Integrated Process Planning and Scheduling

Multi-agent systems have been used for modelling various problems in the social, biological and technical domain. When comes to technical systems, especially manufacturing systems, agents are most often applied in optimization and scheduling problems. Traditionally, scheduling is done after creation of process plans. In this paper, agent methodology is used for integration of these two functions. The proposed multi-agent architecture provides simultaneous performance of process planning and scheduling and it consists of four intelligent agents: part and job agents, machine agent, and optimization agent. Verification and feasibility of a proposed approach is conducted using agent based simulation in AnyLogic software

An Energy-Efficient and Reliable Data Transmission Scheme for Transmitter-based Energy Harvesting Networks

Energy harvesting technology has been studied to overcome a limited power resource problem for a sensor network. This paper proposes a new data transmission period control and reliable data transmission algorithm for energy harvesting based sensor networks. Although previous studies proposed a communication protocol for energy harvesting based sensor networks, it still needs additional discussion. Proposed algorithm control a data transmission period and the number of data transmission dynamically based on environment information. Through this, energy consumption is reduced and transmission reliability is improved. The simulation result shows that the proposed algorithm is more efficient when compared with previous energy harvesting based communication standard, Enocean in terms of transmission success rate and residual energy.This research was supported by Basic Science Research Program through the National Research Foundation by Korea (NRF) funded by the Ministry of Education, Science and Technology(2012R1A1A3012227)

Contemporary Robotics

This book book is a collection of 18 chapters written by internationally recognized experts and well-known professionals of the field. Chapters contribute to diverse facets of contemporary robotics and autonomous systems. The volume is organized in four thematic parts according to the main subjects, regarding the recent advances in the contemporary robotics. The first thematic topics of the book are devoted to the theoretical issues. This includes development of algorithms for automatic trajectory generation using redudancy resolution scheme, intelligent algorithms for robotic grasping, modelling approach for reactive mode handling of flexible manufacturing and design of an advanced controller for robot manipulators. The second part of the book deals with different aspects of robot calibration and sensing. This includes a geometric and treshold calibration of a multiple robotic line-vision system, robot-based inline 2D/3D quality monitoring using picture-giving and laser triangulation, and a study on prospective polymer composite materials for flexible tactile sensors. The third part addresses issues of mobile robots and multi-agent systems, including SLAM of mobile robots based on fusion of odometry and visual data, configuration of a localization system by a team of mobile robots, development of generic real-time motion controller for differential mobile robots, control of fuel cells of mobile robots, modelling of omni-directional wheeled-based robots, building of hunter- hybrid tracking environment, as well as design of a cooperative control in distributed population-based multi-agent approach. The fourth part presents recent approaches and results in humanoid and bioinspirative robotics. It deals with design of adaptive control of anthropomorphic biped gait, building of dynamic-based simulation for humanoid robot walking, building controller for perceptual motor control dynamics of humans and biomimetic approach to control mechatronic structure using smart materials