面向可靠性优化设计的分布式系统资源分配研究
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摘要
可靠性定义了系统在一段时间内能够持续正常工作的能力，是系统设计中的一个重要指标，而提高系统可靠性往往会造成系统资源消耗的增加。为了在保障系统长时间可靠运行的同时，达到可靠性增长与资源消耗的平衡，自上个世纪六十年代开始，系统可靠性优化设计作为一个热点研究课题吸引了众多的科研工作者的关注。随着系统规模的增大和复杂性的提升，如何优化系统可靠性变得更为重要，难度也逐步增加。
本文研究课题来源于国家自然科学基金重大项目“大型分布式软件系统的行为监控与可信演化”。与传统系统可靠性优化相比，分布式系统可靠性保障措施产生了改变，从而产生了新的可靠性优化问题。首先，分布式系统规模较大，通常采用多层系统结构表示，如何为多层结构系统合理分配冗余资源成为一个新的难题。其次，分布式系统可靠性无法完全通过传统的测试方式保障，为了提高组件的可靠性，分布式系统中常采用监控机制对组件进行动态替换，如何通过资源分配对基于监控的系统进行可靠性优化也是一大难题。针对分布式系统可靠性优化设计中出现的新问题，本文从多层冗余分配和监控资源分配两方面入手，针对优化系统可靠性设计的目标，研究了多层系统冗余分配算法，多目标的监控资源分配方法以及组件保障策略可选的系统资源分配。现将论文的主要研究内容和成果概括如下：
①对系统可靠性的评估方法，基于资源分配的可靠性优化模型及算法进行了综述。总结了系统可靠性的多种表示方法及相应的应用场合，归纳了单个组件可靠性及系统可靠性的多种评估方法。对现有的基于资源分配的可靠性优化问题进行了分类总结，重点对冗余分配问题和测试资源分配问题的研究现状进行了分析，并对常用的优化算法，包括精确方法和各种启发式算法进行了分析比较。
②研究了多层结构系统冗余分配问题，根据多层冗余系统的复杂性，提出了新的系统编码方式，并改进了相应的冗余度分配算法。首先，分析了代价约束下通过多层冗余分配达到可靠性优化的问题模型，研究了该分配问题编码和最优解搜索的难点。然后，针对已有分层编码方式的缺点，采用二维数组的方式对多层冗余系统的结构进行编码。在此基础上，使用改进的模因算法搜索冗余系统的最优解，在模因算法中采用了基于二维数组的交叉变异算子和基于随机漫步策略的局部搜索算子。最后，通过与其它多层冗余分配算法的比较实验验证了该算法的有效性：采用二维编码方式，算法多次运行的稳定性得到了提高；局部搜索策略提高了算法的全局搜索能力，能够获得更好的近优解。
③针对分布式系统松耦合和动态配置的特点，提出采用监控资源分配达到系统可靠性提高和资源优化的目的，研究了多目标监控资源分配问题和相应算法。为了建立监控资源分配模型，首先建立了监控策略下的系统的可靠性模型；其次分析了监控机制的两种不同代价；再次选择了系统可靠性约束下最小化监控代价的多目标监控资源分配模型。针对该模型，采用基于第二代非支配排序方法和随机漫步局部搜索策略的改进模因算法搜索问题的平衡解集。最后，将监控资源分配模型及算法应用于多层系统中。通过实验验证了监控资源分配的必要性和在可靠性优化中的作用，分析了监控资源分配随系统时间变化的规律，并将所采用的模因算法与若干种已有多目标方法进行了比较，解集的覆盖率和超体积指标结果表明：针对监控资源分配问题，改进算法无论在最优解还是解的多样性方面都有更好的效果。
④为了弥补系统中单一的资源配置方案的不足，本文提出了对可选的监控资源和冗余资源同时进行选择分配的资源分配方案，建立了面向可靠性约束的多目标资源分配模型并改进了相应算法。针对单层和多层系统，分别分析了组件保障性措施可选的系统可靠性与代价模型，并建立了面向可靠性约束的多目标资源分配模型。在现有组件冗余策略可选的编码机制基础上，采用了新的三元组编码方式表示组件对保障措施的选择以及相应的冗余度和监控频率，改进了模因算法中的遗传算子和局部搜索算子使其能够对三元数组进行操作。通过实验验证了：策略可选的资源分配方案不仅包含单纯的冗余资源或监控资源分配方案，而且在环境条件变化时能为系统提供了更多的资源配置方法。将改进模因算法与已有三元组编码遗传算法进行了比较，结果显示：改进模因算法在解空间的搜索广度和最优解选择上效果更好。
Referring to the ability of a system to work continuously in a certain period of time,reliability is an important indicator in system design. However, system reliability isoften improved at the expenses of cost increase. To improve the continuous workingability of a system and to achieve the balance between reliability improvement andresources cost increase at the same time, optimal system reliability design has arousedthe attention of many researchers since1960s. With the increase of system scale andcomplexity, it becomes more important and gradually more difficult to optimize systemreliability.
The research work in this thesis is supported by the Major Research Project of theNational Natural Science Foundation of China “Behavior monitoring and dependableevolution of large-scale distributed software systems”. Comparing with reliabilityoptimization in traditional systems, the reliability assurance measures in distributedsystems has changed, resulting in new reliability optimization problems. First of all, adistributed system couldn’t be represented as a single-level system due to its large scaleand multilevel structure is often used instead. It becomes a new problem of how toallocate redundancy appropriately in multilevel systems. Secondly, the reliability ofcomponents in distributed system couldn’t be guaranteed by traditional testing method.To improve the component reliability, monitoring mechanism is often used for dynamiccomponent failover. Thus, it is also a major problem of how to optimize systemreliability through monitoring resources allocation. Aiming at solving the new problemsin optimal distributed system reliability design, this thesis generally concentrates on twoaspects: multilevel redundancy allocation and monitoring resources allocation. Tooptimize the system reliability and resources, we concentrated on three fields includingthe algorithm for multilevel system redundancy allocation, multi-objective monitoringresources allocation and the resources allocation with multiple choices of reliabilityassurance. The detailed research results and the major contributions of this paper aresummarized as follows.
①A survey is conducted on the system reliability evaluation methods, theresources allocation models for reliability optimization and the correspondingalgorithms. The different ways of reliability representation and the correspondingapplication is summarized including various reliability evaluation methods for single component and the overall system. Existing reliability optimization oriented resourcesallocation problems are divided into four categories, among which the redundancyallocation problem and testing resources allocation problems are studied in detail. Thecommon optimization methods including exact methods and heuristic algorithms arealso analyzed and compared.
②The multilevel system redundancy allocation problem has been studied and theallocation algorithm has been improved. Based on the existing multilevel redundancyallocation model, the multilevel system reliability optimization problem under theconstraint of redundancy cost has been analyzed and much attention has been paid onmultilevel optimization algorithm. A two-dimensional array encoding mechanism isemployed to represent the structure of multilevel redundant systems to overcome theshortcomings of existing hierarchical encoding mechanism. A memetic algorithm isdeveloped using this encoding method to search the optimal result for the allocationproblem and a random-walk strategy is used as the local search method to search theneighbors of local best solutions. Experiments are conducted to compare our algorithmwith existing multilevel redundancy allocation algorithms and to prove the effectivenessof our algorithm. The experimental results have shown that the two-dimensionalencoding method could be used in memetic algorithms effectively and the local searchstrategy could improve the global search capabilities of memetic algorithm, resulting inbetter results.
③Multi-objective monitoring resources allocation model and the correspondingalgorithms has been studied oriented at system reliability optimization. First of all, themonitoring and dynamic failover mechanism in distributed systems using serviceoriented architecture is analyzed and a reliability model for components using this kindof mechanism is presented. Secondly, a modified architecture-based reliability analysismodel is used to evaluate the overall system reliability. On the top of that, two differentkinds of monitoring resources cost are analyzed and a monitoring resources allocationmodel is built under the system reliability constraint. This model chooses theappropriate monitoring rate for each component through minimizing the monitoringcost. A random walk strategy based memetic algorithm is also used to solve the problem.Monitoring resources allocation model and the algorithm is also used for multilevelredundant systems. Experimental results prove the necessity and impact of monitoringresources allocation in reliability optimization. After analyzing the changing effect ofmonitoring resources allocation with the increase of time, we compare the memetic algorithm used with some existing multi-objective evolutionary algorithms. Thecoverage rate and hypervolume indicator have both proved the superiority of ouralgorithm in this allocation problem.
④The resources allocation problem for systems with multiple choices ofreliability assurance strategies are researched the corresponding algorithm has beenpresented. Redundancy and monitoring are the two major mechanisms taken intoconsideration. For both single level system and multilevel system, the reliability andcost of systems are analyzed considering multiple choices on each component. Based onthese models, a multi-objective resources allocation model is presented under thereliability constraint. A triple-element encoding mechanism is used for single levelsystem to encode the choice of reliability assurance mechanism and the correspondingparameters. The two-dimensional encoding mechanism is also modified to represent themultiple choices of strategies in multilevel system, which could encode the redundancyvalue in subsystem and the monitoring rate in components. Finally, the memeticalgorithms for both single level system and multilevel systems are improved to copewith the three-element encoding mechanism. Experimental results have proved theeffectiveness of the three-element encoding mechanism. Comparison with existinggenetic algorithms using three-element encoding method has shown the effectivenessand superiority of our algorithm in searching solution spaces. The changing effect ofresources allocation with the increase of time is also discussed through the results.
本文研究课题来源于国家自然科学基金重大项目“大型分布式软件系统的行为监控与可信演化”。与传统系统可靠性优化相比，分布式系统可靠性保障措施产生了改变，从而产生了新的可靠性优化问题。首先，分布式系统规模较大，通常采用多层系统结构表示，如何为多层结构系统合理分配冗余资源成为一个新的难题。其次，分布式系统可靠性无法完全通过传统的测试方式保障，为了提高组件的可靠性，分布式系统中常采用监控机制对组件进行动态替换，如何通过资源分配对基于监控的系统进行可靠性优化也是一大难题。针对分布式系统可靠性优化设计中出现的新问题，本文从多层冗余分配和监控资源分配两方面入手，针对优化系统可靠性设计的目标，研究了多层系统冗余分配算法，多目标的监控资源分配方法以及组件保障策略可选的系统资源分配。现将论文的主要研究内容和成果概括如下：
①对系统可靠性的评估方法，基于资源分配的可靠性优化模型及算法进行了综述。总结了系统可靠性的多种表示方法及相应的应用场合，归纳了单个组件可靠性及系统可靠性的多种评估方法。对现有的基于资源分配的可靠性优化问题进行了分类总结，重点对冗余分配问题和测试资源分配问题的研究现状进行了分析，并对常用的优化算法，包括精确方法和各种启发式算法进行了分析比较。
②研究了多层结构系统冗余分配问题，根据多层冗余系统的复杂性，提出了新的系统编码方式，并改进了相应的冗余度分配算法。首先，分析了代价约束下通过多层冗余分配达到可靠性优化的问题模型，研究了该分配问题编码和最优解搜索的难点。然后，针对已有分层编码方式的缺点，采用二维数组的方式对多层冗余系统的结构进行编码。在此基础上，使用改进的模因算法搜索冗余系统的最优解，在模因算法中采用了基于二维数组的交叉变异算子和基于随机漫步策略的局部搜索算子。最后，通过与其它多层冗余分配算法的比较实验验证了该算法的有效性：采用二维编码方式，算法多次运行的稳定性得到了提高；局部搜索策略提高了算法的全局搜索能力，能够获得更好的近优解。
③针对分布式系统松耦合和动态配置的特点，提出采用监控资源分配达到系统可靠性提高和资源优化的目的，研究了多目标监控资源分配问题和相应算法。为了建立监控资源分配模型，首先建立了监控策略下的系统的可靠性模型；其次分析了监控机制的两种不同代价；再次选择了系统可靠性约束下最小化监控代价的多目标监控资源分配模型。针对该模型，采用基于第二代非支配排序方法和随机漫步局部搜索策略的改进模因算法搜索问题的平衡解集。最后，将监控资源分配模型及算法应用于多层系统中。通过实验验证了监控资源分配的必要性和在可靠性优化中的作用，分析了监控资源分配随系统时间变化的规律，并将所采用的模因算法与若干种已有多目标方法进行了比较，解集的覆盖率和超体积指标结果表明：针对监控资源分配问题，改进算法无论在最优解还是解的多样性方面都有更好的效果。
④为了弥补系统中单一的资源配置方案的不足，本文提出了对可选的监控资源和冗余资源同时进行选择分配的资源分配方案，建立了面向可靠性约束的多目标资源分配模型并改进了相应算法。针对单层和多层系统，分别分析了组件保障性措施可选的系统可靠性与代价模型，并建立了面向可靠性约束的多目标资源分配模型。在现有组件冗余策略可选的编码机制基础上，采用了新的三元组编码方式表示组件对保障措施的选择以及相应的冗余度和监控频率，改进了模因算法中的遗传算子和局部搜索算子使其能够对三元数组进行操作。通过实验验证了：策略可选的资源分配方案不仅包含单纯的冗余资源或监控资源分配方案，而且在环境条件变化时能为系统提供了更多的资源配置方法。将改进模因算法与已有三元组编码遗传算法进行了比较，结果显示：改进模因算法在解空间的搜索广度和最优解选择上效果更好。
Referring to the ability of a system to work continuously in a certain period of time,reliability is an important indicator in system design. However, system reliability isoften improved at the expenses of cost increase. To improve the continuous workingability of a system and to achieve the balance between reliability improvement andresources cost increase at the same time, optimal system reliability design has arousedthe attention of many researchers since1960s. With the increase of system scale andcomplexity, it becomes more important and gradually more difficult to optimize systemreliability.
The research work in this thesis is supported by the Major Research Project of theNational Natural Science Foundation of China “Behavior monitoring and dependableevolution of large-scale distributed software systems”. Comparing with reliabilityoptimization in traditional systems, the reliability assurance measures in distributedsystems has changed, resulting in new reliability optimization problems. First of all, adistributed system couldn’t be represented as a single-level system due to its large scaleand multilevel structure is often used instead. It becomes a new problem of how toallocate redundancy appropriately in multilevel systems. Secondly, the reliability ofcomponents in distributed system couldn’t be guaranteed by traditional testing method.To improve the component reliability, monitoring mechanism is often used for dynamiccomponent failover. Thus, it is also a major problem of how to optimize systemreliability through monitoring resources allocation. Aiming at solving the new problemsin optimal distributed system reliability design, this thesis generally concentrates on twoaspects: multilevel redundancy allocation and monitoring resources allocation. Tooptimize the system reliability and resources, we concentrated on three fields includingthe algorithm for multilevel system redundancy allocation, multi-objective monitoringresources allocation and the resources allocation with multiple choices of reliabilityassurance. The detailed research results and the major contributions of this paper aresummarized as follows.
①A survey is conducted on the system reliability evaluation methods, theresources allocation models for reliability optimization and the correspondingalgorithms. The different ways of reliability representation and the correspondingapplication is summarized including various reliability evaluation methods for single component and the overall system. Existing reliability optimization oriented resourcesallocation problems are divided into four categories, among which the redundancyallocation problem and testing resources allocation problems are studied in detail. Thecommon optimization methods including exact methods and heuristic algorithms arealso analyzed and compared.
②The multilevel system redundancy allocation problem has been studied and theallocation algorithm has been improved. Based on the existing multilevel redundancyallocation model, the multilevel system reliability optimization problem under theconstraint of redundancy cost has been analyzed and much attention has been paid onmultilevel optimization algorithm. A two-dimensional array encoding mechanism isemployed to represent the structure of multilevel redundant systems to overcome theshortcomings of existing hierarchical encoding mechanism. A memetic algorithm isdeveloped using this encoding method to search the optimal result for the allocationproblem and a random-walk strategy is used as the local search method to search theneighbors of local best solutions. Experiments are conducted to compare our algorithmwith existing multilevel redundancy allocation algorithms and to prove the effectivenessof our algorithm. The experimental results have shown that the two-dimensionalencoding method could be used in memetic algorithms effectively and the local searchstrategy could improve the global search capabilities of memetic algorithm, resulting inbetter results.
③Multi-objective monitoring resources allocation model and the correspondingalgorithms has been studied oriented at system reliability optimization. First of all, themonitoring and dynamic failover mechanism in distributed systems using serviceoriented architecture is analyzed and a reliability model for components using this kindof mechanism is presented. Secondly, a modified architecture-based reliability analysismodel is used to evaluate the overall system reliability. On the top of that, two differentkinds of monitoring resources cost are analyzed and a monitoring resources allocationmodel is built under the system reliability constraint. This model chooses theappropriate monitoring rate for each component through minimizing the monitoringcost. A random walk strategy based memetic algorithm is also used to solve the problem.Monitoring resources allocation model and the algorithm is also used for multilevelredundant systems. Experimental results prove the necessity and impact of monitoringresources allocation in reliability optimization. After analyzing the changing effect ofmonitoring resources allocation with the increase of time, we compare the memetic algorithm used with some existing multi-objective evolutionary algorithms. Thecoverage rate and hypervolume indicator have both proved the superiority of ouralgorithm in this allocation problem.
④The resources allocation problem for systems with multiple choices ofreliability assurance strategies are researched the corresponding algorithm has beenpresented. Redundancy and monitoring are the two major mechanisms taken intoconsideration. For both single level system and multilevel system, the reliability andcost of systems are analyzed considering multiple choices on each component. Based onthese models, a multi-objective resources allocation model is presented under thereliability constraint. A triple-element encoding mechanism is used for single levelsystem to encode the choice of reliability assurance mechanism and the correspondingparameters. The two-dimensional encoding mechanism is also modified to represent themultiple choices of strategies in multilevel system, which could encode the redundancyvalue in subsystem and the monitoring rate in components. Finally, the memeticalgorithms for both single level system and multilevel systems are improved to copewith the three-element encoding mechanism. Experimental results have proved theeffectiveness of the three-element encoding mechanism. Comparison with existinggenetic algorithms using three-element encoding method has shown the effectivenessand superiority of our algorithm in searching solution spaces. The changing effect ofresources allocation with the increase of time is also discussed through the results.
引文
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