An efficient ant colony system based on receding horizon control for the aircraft arrival sequencing and scheduling problem

The aircraft arrival sequencing and scheduling (ASS) problem is a salient problem in air traffic control (ATC), which proves to be nondeterministic polynomial (NP) hard. This paper formulates the ASS problem in the form of a permutation problem and proposes a new solution framework that makes the first attempt at using an ant colony system (ACS) algorithm based on the receding horizon control (RHC) to solve it. The resultant RHC-improved ACS algorithm for the ASS problem (termed the RHC-ACS-ASS algorithm) is robust, effective, and efficient, not only due to that the ACS algorithm has a strong global search ability and has been proven to be suitable for these kinds of NP-hard problems but also due to that the RHC technique can divide the problem with receding time windows to reduce the computational burden and enhance the solution's quality. The RHC-ACS-ASS algorithm is extensively tested on the cases from the literatures and the cases randomly generated. Comprehensive investigations are also made for the evaluation of the influences of ACS and RHC parameters on the performance of the algorithm. Moreover, the proposed algorithm is further enhanced by using a two-opt exchange heuristic local search. Experimental results verify that the proposed RHC-ACS-ASS algorithm generally outperforms ordinary ACS without using the RHC technique and genetic algorithms (GAs) in solving the ASS problems and offers high robustness, effectiveness, and efficienc

A distributed scheduling algorithm for heterogeneous real-time systems

Much of the previous work on load balancing and scheduling in distributed environments was concerned with homogeneous systems and homogeneous loads. Several of the results indicated that random policies are as effective as other more complex load allocation policies. The effects of heterogeneity on scheduling algorithms for hard real time systems is examined. A distributed scheduler specifically to handle heterogeneities in both nodes and node traffic is proposed. The performance of the algorithm is measured in terms of the percentage of jobs discarded. While a random task allocation is very sensitive to heterogeneities, the algorithm is shown to be robust to such non-uniformities in system components and load

Random trees in queueing systems with deadlines

AbstractWe survey our research on scheduling aperiodic tasks in real-time systems in order to illustrate the benefits of modelling queueing systems by means of random trees. Relying on a discrete-time single-server queueing system, we investigated deadline meeting properties of several scheduling algorithms employed for servicing probabilistically arriving tasks, characterized by arbitrary arrival and execution time distributions and a constant service time deadline T. Taking a non-queueing theory approach (i.e., without stable-stable assumptions) we found that the probability distribution of the random time sT where such a system operates without violating any task's deadline is approximately exponential with parameter λT = 1μT, with the expectation E[sT] = μT growing exponentially in T. The value μT depends on the particular scheduling algorithm, and its derivation is based on the combinatorial and asymptotic analysis of certain random trees. This paper demonstrates that random trees provide an efficient common framework to deal with different scheduling disciplines and gives an overview of the various combinatorial and asymptotic methods used in the appropriate analysis

Application of lean scheduling and production control in non-repetitive manufacturing systems using intelligent agent decision support

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.Lean Manufacturing (LM) is widely accepted as a world-class manufacturing paradigm, its currency and superiority are manifested in numerous recent success stories. Most lean tools including Just-in-Time (JIT) were designed for repetitive serial production systems. This resulted in a substantial stream of research which dismissed a priori the suitability of LM for non-repetitive non-serial job-shops. The extension of LM into non-repetitive production systems is opposed on the basis of the sheer complexity of applying JIT pull production control in non-repetitive systems fabricating a high variety of products. However, the application of LM in job-shops is not unexplored. Studies proposing the extension of leanness into non-repetitive production systems have promoted the modification of pull control mechanisms or reconfiguration of job-shops into cellular manufacturing systems. This thesis sought to address the shortcomings of the aforementioned approaches. The contribution of this thesis to knowledge in the field of production and operations management is threefold: Firstly, a Multi-Agent System (MAS) is designed to directly apply pull production control to a good approximation of a real-life job-shop. The scale and complexity of the developed MAS prove that the application of pull production control in non-repetitive manufacturing systems is challenging, perplex and laborious. Secondly, the thesis examines three pull production control mechanisms namely, Kanban, Base Stock and Constant Work-in-Process (CONWIP) which it enhances so as to prevent system deadlocks, an issue largely unaddressed in the relevant literature. Having successfully tested the transferability of pull production control to non-repetitive manufacturing, the third contribution of this thesis is that it uses experimental and empirical data to examine the impact of pull production control on job-shop performance. The thesis identifies issues resulting from the application of pull control in job-shops which have implications for industry practice and concludes by outlining further research that can be undertaken in this direction

Performance Analysis in IP-Based Industrial Communication Networks

S rostoucím počtem řídicích systémů a jejich distribuovanosti získávájí komunikační sítě na důležitosti a objevují se nové výzkumné trendy. Hlavní problematikou v této oblasti, narozdíl od dřívějších řídicích systémů využívajících dedikovaných komunikačních obvodů, je časově proměnné zpoždění měřicích a řídicích signálů způsobené paketově orientovanými komunikačními prostředky, jako např. Ethernet. Aspekty komunikace v reálném čase byly v těchto sítích již úspěšně vyřešeny. Nicméně, analýzy trendů trhu předpovídají budoucí využití také IP sítí v průmyslové komunikaci pro časově kritickou procesní vyměnu dat. IP komunikace má ovšem pouze omezenou podporu v instrumentaci pro průmyslovou automatizace. Tato výzva byla nedávno technicky vyřešena v rámci projektu Virtual Automation Networks (virtuální automatizační sítě - VAN) zapojením mechanismů kvality služeb (QoS), které jsou schopny zajistit měkkou úroveň komunikace v reálném čase. Předložená dizertační práce se zaměřuje na aspekty výkonnosti reálného času z analytického hlediska a nabízí prostředek pro hodnocení využitelnosti IP komunikace pro budoucí průmyslové aplikace. Hlavním cílem této dizertační práce je vytvoření vhodného modelovacího rámce založeného na network calculus, který pomůže provést worst-case výkonnostní analýzu časového chování IP komunikačních sítí a jejich prvků určených pro budoucí použití v průmyslové automatizaci. V práci byla použita empirická analýza pro určení dominantních faktorů ovlivňujících časového chování síťových zařízení a identifikaci parametrů modelů těchto zařízení. Empirická analýza využívá nástroj TestQoS vyvinutý pro tyto účely. Byla navržena drobná rozšíření rámce network calculus, která byla nutná pro modelování časového chování používaných zařízení. Bylo vytvořeno několik typových modelů zařízení jako výsledek klasifikace různých architektur síťových zařízení a empiricky zjištěných dominantních faktorů. U modelovaných zařízení byla využita nová metoda identifikace parametrů. Práce je zakončena validací časových modelů dvou síťových zařízení (přepínače a směrovače) oproti empirickým pozorováním.With the growing scale of control systems and their distributed nature, communication networks have been gaining importance and new research challenges have been appearing. The major problem, contrary to previously used control systems with dedicated communication circuits, is time-varying delay of control and measurement signals introduced by packet-switched networks, such as Ethernet. The real-time issues in these networks have been tackled by proper adaptations. Nevertheless, market trend analyses foresee also future adoptions of IP-based communication networks in industrial automation for time-critical run-time data exchange. IP-based communication has only a limited support from the existing instrumentation in industrial automation. This challenge has recently been technically tackled within the Virtual Automation Networks (VAN) project by adopting the quality of service (QoS) architecture delivering soft-real-time communication behaviour. This dissertation focuses on the real-time performance aspects from the analytical point of view and provides means for applicability assessment of IP-based communication for future industrial applications. The main objective of this dissertation is establishment of a relevant modelling framework based on network calculus which will assist worst-case performance analysis of temporal behaviour of IP-based communication networks and networking devices intended for future use in industrial automation. Empirical analysis was used to identify dominant factors influencing the temporal performance of networking devices and for model parameter identification. The empirical analysis makes use of the TestQoS tool developed for this purpose. Minor extensions to the network calculus framework were proposed enabling to model the required temporal behaviour of networking devices. Several exemplary models were inferred as a result of classification of different networking device architectures and empirically identified dominant factors. A novel method for parameter identification was used with the modelled devices. Finally, two temporal models of networking devices (a switch and a router) were validated against empirical observations.

Maximising microprocessor reliability through game theory and heuristics

PhD ThesisEmbedded Systems are becoming ever more pervasive in our society, with most routine daily tasks now involving their use in some form and the market predicted to be worth USD 220 billion, a rise of 300%, by 2018. Consumers expect more functionality with each design iteration, but for no detriment in perceived performance. These devices can range from simple low-cost chips to expensive and complex systems and are a major cost driver in the equipment design phase. For more than 35 years, designers have kept pace with Moore's Law, but as device size approaches the atomic limit, layouts are becoming so complicated that current scheduling techniques are also reaching their limit, meaning that more resource must be reserved to manage and deliver reliable operation. With the advent of many-core systems and further sources of unpredictability such as changeable power supplies and energy harvesting, this reservation of capability may become so large that systems will not be operating at their peak efficiency. These complex systems can be controlled through many techniques, with jobs scheduled either online prior to execution beginning or online at each time or event change. Increased processing power and job types means that current online scheduling methods that employ exhaustive search techniques will not be suitable to define schedules for such enigmatic task lists and that new techniques using statistic-based methods must be investigated to preserve Quality of Service. A new paradigm of scheduling through complex heuristics is one way to administer these next levels of processor effectively and allow the use of more simple devices in complex systems; thus reducing unit cost while retaining reliability a key goal identified by the International Technology Roadmap for Semi-conductors for Embedded Systems in Critical Environments. These changes would be beneficial in terms of cost reduction and system exibility within the next generation of device. This thesis investigates the use of heuristics and statistical methods in the operation of real-time systems, with the feasibility of Game Theory and Statistical Process Control for the successful supervision of high-load and critical jobs investigated. Heuristics are identified as an effective method of controlling complex real-time issues, with two-person non-cooperative games delivering Nash-optimal solutions where these exist. The simplified algorithms for creating and solving Game Theory events allow for its use within small embedded RISC devices and an increase in reliability for systems operating at the apex of their limits. Within this Thesis, Heuristic and Game Theoretic algorithms for a variety of real-time scenarios are postulated, investigated, refined and tested against existing schedule types; initially through MATLAB simulation before testing on an ARM Cortex M3 architecture functioning as a simplified automotive Electronic Control Unit.Doctoral Teaching Account from the EPSRC