基于混合粒度冲突检测的事务工作流调度算法

事务工作流由若干个平面事务组成,其执行满足松弛原子性.由于组成事务工作流的平面事务具有不同的完成特性,为了防止不可串行化的执行,现有的调度算法通常只允许一个活动工作流执行不可补偿事务,这大大限制了并发度.定义了基于事务类型和事务实例两种粒度的冲突关系,并提出了一种基于这两种粒度冲突检测的调度算法,保证了并发事务工作流的可串行化和可恢复执行.该算法从两个方面提高了并发度:一方面通过事务实例之间(细粒度)的冲突检测减少了工作流冲突的概率;另一方面通过事务类型之间(粗粒度)的冲突预测,允许多个将来不冲突的工作流执行不可补偿事务.     

蓝牙自组个人网监听模式下分散网调度算法

蓝牙自组个人区域网络是由具有蓝牙功能的设备组成一个不需额外网络设备,在某个区域内一起自主协调工作,相互间自由通信的独立无线移动网络.网络中的某些节点采用时分复用方式参与多个微微网中并转发网络数据.由于节点在某时刻只能加入其中一个微微网中,这就需要微微网间或者分散网调度算法.监听模式为分散网调度算法提供了一个比较灵活的方式并且无须更改协议.提出了一种基于监听模式的自适应分散网调度算法,有效解决了这个具有挑战性的课题.算法监控各个链路上的流量,并获得流量变化数据,根据这些数据实时改变节点在各个链路上的监听时隙分配比例.通过对算法仿真结果的对比和分析,证明算法能够提高吞吐量,减少传输延迟,改善网络性能.     

Unrelated parallel machine scheduling with setup times and a total weighted tardiness objective

This paper presents several search heuristics and their performance in batch scheduling of parallel, unrelated machines. Identical or similar jobs are typically processed in batches in order to decrease setup times and/or processing times. The problem accounts for allotting batched work parts into unrelated parallel machines, where each batch consists of a fixed number of jobs. Some batches may contain different jobs but all jobs within each batch should have an identical processing time and a common due date. Processing time of each job of a batch is determined according to the machine group as well as the batch group to which the job belongs. Major or minor setup times are required between two subsequent batches depending on batch sequence but are independent of machines. The objective of our study is to minimize the total weighted tardiness for the unrelated parallel machine scheduling. Four search heuristics are proposed to address the problem, namely (1) the earliest weighted due date, (2) the shortest weighted processing time, (3) the two-level batch scheduling heuristic, and (4) the simulated annealing method. These proposed local search heuristics are tested through computational experiments with data from dicing operations of a compound semiconductor manufacturing facility.     

A knowledge-based decision support system for the management of parts and tools in FMS

Flexible manufacturing systems (FMS) are very complex systems with large part, tool, and information flows. The aim of this work is to develop a knowledge-based decision support system (KBDSS) for short-term scheduling in FMS strongly influenced by the tool management concept to provide a significant operational control tool for a wide range of machining cells, where a high level of flexibility is demanded, with benefits of more efficient cell utilization, greater tool flow control, and a dependable way of rapidly adjusting short-term production requirements. Development of a knowledge-based system to support the decision making process is justified by the inability of decision makers to diagnose efficiently many of the malfunctions that arise at machine, cell, and entire system levels during manufacturing. In this context, this paper proposes three knowledge-based models to ease the decision making process: an expert production scheduling system, a knowledge-based tool management decision support systems, and a tool management fault diagnosis system. The entire system has been created in a hierarchical manner and comprises more than 400 rules. The expert system (ES) was implemented in a commercial expert system shell, Knowledge Engineering System (KES) Production System (PS).     

Two-machine open shop scheduling with secondary criteria

This paper considers two-machine open shop problems with secondary criteria where the primary criterion is the minimization of makespan and the secondary criterion is the minimization of the total flow time, total weighted flow time, or total weighted tardiness time. In view of the strongly NP-hard nature of these problems, two polynomially solvable special cases are given and constructive heuristic algorithms based on insertion techniques are developed. A strongly connected neighborhood structure is derived and used to develop effective iterative heuristic algorithms by incorporating iterative improvement, simulated annealing and multi-start procedures. The proposed insertion and iterative heuristic algorithms are empirically evaluated by solving problem instances with up to 80 jobs.     

不同插秧量对东北杂交稻与常规稻产量结构的影响

对东北杂交稻与常规稻的产量形成过程和产量结构进行了分析。结果表明：杂交稻比常规稻增产的主要原因在于杂交稻的经济系数显高于常规稻，这主要得益于杂交稻后期光合产物向籽粒的转移率较高。在产量结构上，杂交稻的穗粒数多、千粒重大，但穗粒数的优势主要来源于二次枝梗，这也造成了杂交稻的结实率偏低，成为限制杂交稻产量潜力发挥的瓶颈。进一步发挥杂交稻的杂种优势，需要从提高后期光合能力和提高结实率两方面人手。杂交稻与常规稻有各自适宜的栽培方式，插单苗有利于提高杂交稻的平均穗重、千粒重、结实率，并最终使产量提高；而插3苗更适于常规稻生产力的发挥。     

大穗型超级杂交粳稻辽优3072产量结构及灌浆特性研究

对北方大穗型超级杂交粳稻辽优3072进行了产量结构和灌浆特性的研究。结果表明：辽优3072在产量结构上表现出了较强的杂交优势，比对照辽粳294增产明显。辽优3072在灌浆上的特点为穗上、中、下各部间干物质充实及灌浆速率差异较小：穗下部灌浆启动早，后期灌浆速率大；整穗表现出较强的持续灌浆能力。辽优3072良好的籽粒灌浆特性是其在产量上表现出超高产的生理基础之一。同时探讨了利用水稻杂交优势选育具有特异灌浆特性的杂交组合的育种思路以及在北方冷凉稻区推广大穗型超级杂交粳稻品种的可能性。     

Odyssey: a high‐performance clustered video server

Video servers are essential in video‐on‐demand and other multimedia applications. In this paper, we present our high‐performance clustered CBR video server, Odyssey. Odyssey is a server connecting PCs with switched Ethernet. It provides efficient support for normal play and interactive browsing functions such as fast‐forward and fast‐backward. We designed a set of algorithms for scheduling, synchronization and admission control, which results in a high utilization of resources. Odyssey is able to deliver a large number of video streams. Copyright © 2003 John Wiley & Sons, Ltd.     

一个基于多Agent的PCB装配调度系统

PCB装配调度是一个job shop调度问题。本文针对这一问题设计了一个基于多agent调度系统模型，系统的最大特点是将任务和优先权机制与基于合同网协议和KQML消息的竞标机制两者相结合。     

一个基于关联规则的Web信息检索模型

针对Web信息检索系统在大数据量下的数据存储，数据调度与工作的效率问题，分析了数据挖掘在Internet信息检索中的运用。提出了一个基于关联规则的Web信息检索模型，并以逻辑层次、服务域与数据路由为中心，输出了这个模型的结构、算法与设计思想。