Knowledge based scheduling of distributed systems

Priorities are used to control the execution of systems to meet given requirements for optimal use of resources, e.g., by using scheduling policies. For distributed systems it is hard to find efficient implementations for priorities; because they express constraints on global states, their implementation may incur considerable overhead. Our method is based on performing model checking for knowledge properties. It allows identifying where the local information of a process is sufficient to schedule the execution of a high priority transition. As a result of the model checking, the program is transformed to react upon the knowledge it has at each point. The transformed version has no priorities, and uses the gathered information and its knowledge to limit the enabledness of transitions so that it matches or approximates the original specification of priorities. © 2010 Springer-Verlag Berlin Heidelberg

Replica determinism and flexible scheduling in hard real-time dependable systems

Fault-tolerant real-time systems are typically based on active replication where replicated entities are required to deliver their outputs in an identical order within a given time interval. Distributed scheduling of replicated tasks, however, violates this requirement if on-line scheduling, preemptive scheduling, or scheduling of dissimilar replicated task sets is employed. This problem of inconsistent task outputs has been solved previously by coordinating the decisions of the local schedulers such that replicated tasks are executed in an identical order. Global coordination results either in an extremely high communication effort to agree on each schedule decision or in an overly restrictive execution model where on-line scheduling, arbitrary preemptions, and nonidentically replicated task sets are not allowed. To overcome these restrictions, a new method, called timed messages, is introduced. Timed messages guarantee deterministic operation by presenting consistent message versions to the replicated tasks. This approach is based on simulated common knowledge and a sparse time base. Timed messages are very effective since they neither require communication between the local scheduler nor do they restrict usage of on-line flexible scheduling, preemptions and nonidentically replicated task sets

P2P Web service based system for supporting decision-making in cellular manufacturing scheduling

With the increase of the Internet and Virtual Enterprises (VEs), interfaces for web systems and automated services are becoming an emergent necessity. In this paper we propose a Peer-to-peer (P2P) web-based decision-support system for enabling access to different manufacturing scheduling methods, which can be remotely available and accessible from a distributed knowledge base. The XML-based modeling and communication is applied to manufacturing scheduling. Therefore, manufacturing scheduling problems and methods are modeled using XML. The proposed P2P web-based system works as web services, under the SOAP protocol. The system’s distributed knowledge base enables sharing information about scheduling problems and corresponding solving methods in a widened search space, through a scheduling community, integrating a VE. Running several methods enables different results for a given problem, consequently, contributing for a better decision-making. An important aspect is that this knowledge base can be easily and continuously updated by any contributor through the VE. Moreover, through this system once suitable available methods, for a given problem, are identified, it enables running one or more of them, for enabling a better manufacturing scheduling support, enhanced though incorporated fuzzy decision-making proceduresAichi Science and Technology Foundation(PTDC/EME-GIN/102143/2008)info:eu-repo/semantics/publishedVersio

CRI planning and scheduling for space

Computer Resources International (CRI) has many years of experience in developing space planning and scheduling systems for the European Space Agency. Activities range from AIT/AIV planning over mission planning to research in on-board autonomy using advanced planning and scheduling technologies in conjunction with model based diagnostics. This article presents four projects carried out for ESA by CRI with various subcontractors: (1) DI, Distributed Intelligence for Ground/Space Systems is an on-going research project; (2) GMPT, Generic Mission Planning Toolset, a feasibility study concluded in 1993; (3) OPTIMUM-AIV, Open Planning Tool for AIV, development of a knowledge based AIV planning and scheduling tool ended in 1992; and (4) PlanERS-1, development of an AI and knowledge-based mission planning prototype for the ERS-1 earth observation spacecraft ended in 1991

Autonomous power expert system

The goal of the Autonomous Power System (APS) program is to develop and apply intelligent problem solving and control technologies to the Space Station Freedom Electrical Power Systems (SSF/EPS). The objectives of the program are to establish artificial intelligence/expert system technology paths, to create knowledge based tools with advanced human-operator interfaces, and to integrate and interface knowledge-based and conventional control schemes. This program is being developed at the NASA-Lewis. The APS Brassboard represents a subset of a 20 KHz Space Station Power Management And Distribution (PMAD) testbed. A distributed control scheme is used to manage multiple levels of computers and switchgear. The brassboard is comprised of a set of intelligent switchgear used to effectively switch power from the sources to the loads. The Autonomous Power Expert System (APEX) portion of the APS program integrates a knowledge based fault diagnostic system, a power resource scheduler, and an interface to the APS Brassboard. The system includes knowledge bases for system diagnostics, fault detection and isolation, and recommended actions. The scheduler autonomously assigns start times to the attached loads based on temporal and power constraints. The scheduler is able to work in a near real time environment for both scheduling and dynamic replanning

Scheduling in Transactional Memory Systems: Models, Algorithms, and Evaluations

Transactional memory provides an alternative synchronization mechanism that removes many limitations of traditional lock-based synchronization so that concurrent program writing is easier than lock-based code in modern multicore architectures. The fundamental module in a transactional memory system is the transaction which represents a sequence of read and write operations that are performed atomically to a set of shared resources; transactions may conflict if they access the same shared resources. A transaction scheduling algorithm is used to handle these transaction conflicts and schedule appropriately the transactions. In this dissertation, we study transaction scheduling problem in several systems that differ through the variation of the intra-core communication cost in accessing shared resources. Symmetric communication costs imply tightly-coupled systems, asymmetric communication costs imply large-scale distributed systems, and partially asymmetric communication costs imply non-uniform memory access systems. We made several theoretical contributions providing tight, near-tight, and/or impossibility results on three different performance evaluation metrics: execution time, communication cost, and load, for any transaction scheduling algorithm. We then complement these theoretical results by experimental evaluations, whenever possible, showing their benefits in practical scenarios. To the best of our knowledge, the contributions of this dissertation are either the first of their kind or significant improvements over the best previously known results

Cyber Physical System Based Proactive Collaborative Maintenance

The aim of the MANTIS project is to provide a proactive maintenance service platform architecture based on Cyber Physical Systems. The platform will allow estimating future performance, predicting and preventing imminent failures and scheduling proactive maintenance. Maintenance is an important element that creates added value in the business processes and it also creates new business models with a stronger service orientation. Physical systems and the environment they work in are continuously monitored by a range of intelligent sensors, resulting in massive amounts of data, which characterise the usage history, working condition, location, movement and other physical properties of the systems. These systems are part of a larger network of heterogeneous and collaborative systems (e.g. vehicle fleets) connected via robust communication mechanisms able to operate in challenging environments. MANTIS consists of distributed processing chains that efficiently transform raw data into knowledge, while minimising the need for bandwidth. Sophisticated distributed sensing and decision-making functions are performed at different levels collaboratively, ranging from local nodes to locally optimise performance, bandwidth and maintenance; to cloud-based platforms that integrate information from diverse systems and execute distributed processing and analytics algorithms for global decision-making