Intelligent Agent-based Architecture Research Articles

An intelligent agent-based architecture for resilient digital twins in manufacturing

Digital twins (DTs) offer the potential for improved understanding of current and future manufacturing processes. This can only be achieved by DTs consistently and accurately representing the real processes. However, the robustness and resilience of the DT itself remain an issue. Accordingly, this paper offers an approach to deal with uncertainty and disruptions, as the DT detects these effectively and self-adapts as needed to maintain representativeness. The paper proposes an intelligent agent-based architecture to improve the robustness (including accuracy of representativeness) and resilience (including timely update) of the DT. The approach is demonstrated on a case of cryogenic secondary manufacturing.

Simulation of Agent-Based Negative Selection Model (ABNSM) for Reservoir Water Level Monitoring

Reservoir water level monitoring is an important process during heavy or light rainfall to determine the volume of reserved water. Mistakes in data recording by the dam operator can lead to disasters. Data from different gauging stations are collected to determine whether to release water in the dam or not. The decision to release water is critical because it can affect the volume of water left in the dam for both drought and flood seasons. Constant water level monitoring is difficult because of the changes in water level. To overcome this issue, intelligent agent-based architecture is proposed for reservoir water level monitoring by imitating the artificial immune system. This paper presents the agent technology where agents communicate with each other concurrently by sending online data from different gauging stations to the main reservoir. One of the techniques in the artificial immune system is known as negative selection and this technique has been chosen as a water level monitoring model.

Intelligent Agent-Based Architecture for Demand Side Management Considering Space Heating and Electric Vehicle Load

Contraction of resilience on generation side due to the introduction of inflexible renewable energy sources is demanding more elasticity on consumption side. It requires more intelligent systems to be implemented to maintain power balance in the grid and to fulfill the consumer needs. This paper is concerned about the energy balance management of the system using intelligent agent-based architecture. The idea is to limit the peak power of each individual household for different defined time regions of the day according to power production during those time regions. Monte Carlo Simulation (MCS) has been employed to study the behavior of a particular number of households for maintaining the power balance based on proposed technique to limit the peak power for each household and even individual load level. Flexibility of two major loads i.e. heating load (heat storage tank) and electric vehicle load (battery) allows us to shift the peaks on demand side proportionally with the generation in real time. Different parameters related to heating and Electric Vehicle (EV) load e.g. State of Charge (SOC), storage capacities, charging power, daily usage, peak demand hours have been studied and a technique is proposed to mitigate the imbalance of power intelligently.

New Optimal Solutions for Real-Time Reconfigurable Periodic Asynchronous Operating System Tasks with Minimizations of Response Time

Scheduling tasks is an essential requirement in most real-time and embedded systems, but leads to unwanted central processing unit (CPU) overheads. The authors present a real-time schedulability algorithm for preemptable, asynchronous and periodic reconfigurable task systems with arbitrary relative deadlines, scheduled on a uniprocessor by an optimal scheduling algorithm based on the earliest deadline first (EDF) principles and on the dynamic reconfiguration. A reconfiguration scenario is assumed to be a dynamic automatic operation allowing addition, removal or update of operating system’s (OS) functional asynchronous tasks. When such a scenario is applied to save the system at the occurrence of hardware-software faults, or to improve its performance, some real-time properties can be violated. The authors propose an intelligent agent-based architecture where a software agent is used to satisfy the user requirements and to respect time constraints. The agent dynamically provides precious technical solutions for users when these constraints are not verified, by removing tasks according to predefined heuristic, or by modifying the worst case execution times (WCETs), periods, and deadlines of tasks in order to meet deadlines and to minimize their response time. They implement the agent to support these services which are applied to a Blackberry Bold 9700 and to a Volvo system and present and discuss the results of experiments.

New Optimal Preemptively Scheduling for Real-Time Reconfigurable Sporadic Tasks Based on Earliest Deadline First Algorithm

This paper examines the problem of scheduling the mixed workload of both sporadic (on-line) and periodic (off-line) tasks on uniprocessor in a hard real-time environment. The authors introduce an optimal earliest deadline scheduling algorithm to optimize response time while ensuring that all periodic tasks meet their deadlines and to accept as many sporadic tasks. A necessary and sufficient schedulability test is presented, and an efficient O(n+m) guarantee algorithm is proposed. This optimal algorithm results in dynamic scheduling solutions. They are presented by a proposed intelligent agent-based architecture where a software agent is used to evaluate the response time, to calculate the processor utilization factor and also to verify the satisfaction of real-time deadlines. The agent dynamically provides technical solutions for users where the system becomes unfeasible by sending sporadic tasks to idle times, by modifying the deadlines of tasks, the worst case execution times (WCETs), the activation time, by tolerating some non critical tasks according to the (m, n) firm and a reasonable cost, or in the worst case by removing some non hard (soft) tasks according to predefined heuristic. The authors implement the agent to support these services which are applied to extensive experiments with real-life design examples in order to demonstrate the effectiveness and the excellent performance of the new optimal algorithm in normal and overload conditions.

Semantic Matchmaking and Decision Support System for Dependable Supplier Selection in the Extended Enterprise Supply Chain

Increasingly firms are competing through the formation of extended enterprises. An extended enterprise consists of a set of firms within a value chain that collaborate to produce a finished product. The case of dependable supplier selection, in the context of the extended enterprise, is complex where the focal firm has to select the supplier(s) for a specific class of customers depending on the value of those customers to the focal firm and the extended enterprise. This process requires careful consideration of a set of selection criteria to be used in selecting the suppliers. In this article, a semantic intelligent agent-based architecture and decision support system are presented for selecting dependable suppliers in the context of extended enterprise.

An intelligent agent-based architecture for strategic information system applications

Strategic information systems (SIS) focus on the use of information system (IS) and information technology (IT) in the strategic management process in business organizations. The emphasis is on the strategic view of IS and IT and their impact on organizational strategy. Increased competition and advances in information technologies push for considerable structural changes in SIS. Agents, as autonomous entities which either work on their own or cooperate with others, and agent architectures have enormous potentials to be applied in such critical systems. In this article, first we investigate the very fundamental concepts of strategic information systems and intelligent agent technology. Then, the discussion continues on the specification of the characteristics and implementation issues of a typical SIS. Afterwards, we make use of these concepts and integrate them into a state-of-the-art, intelligent architecture for strategic information systems, called intelligent agent-based SIS. This is a comprehensive framework for a SIS in IT era which may be put into practice by a team of professionals in the near future. The graphical representation of this model is intended to help the reader understand the concept much better. After explaining the suggested model in full details, we introduce some support agents and specify their corresponding roles in an intelligent agent-based SIS architecture. Discussions and concluding remarks regarding the proposed system are provided at the end of the paper.