МИГРАЦИЯ ДАННЫХ В КОНТЕКСТЕ ERP-СИСТЕМ

At the heart of every ERP is a single database that allows employees of the organization to rely on the same consistent set of information. Data migration is an important component of ERPs upgrade, implementation and integration projects. At the same time, the migration scenario can be complex and lengthy, require a large amount of resources and high competencies of the management staff. Underestimating the required time and effort can lead to a significant increase in costs and delay in the commissioning of the ERP. The accuracy and completeness of the transmitted data is also of great importance, since many aspects of the business – customer satisfaction, decision-making, supply chain and relationships with partners – will depend on the quality of the data. Despite this, the complexity of data migration scenarios is traditionally underestimated. In most existing studies, data migration is considered mainly from the technical side. Aspects related to the conceptual content of data migration, its relationship with business processes and company management, as well as the specific role of data migration in projects of updating, implementing and integrating ERPs, remain insufficiently developed. The aim of the study. The aim of this study is to supplement theoretical ideas about the content, diversity, problems and strategies of data migration in the context of ERPs. Materials and methods. The article summarizes and systematizes the types, stages of the project, key strategies and the most significant problems of data migration. For the purposes of this study, the material from 23 sources on a similar topic was reviewed, revised and supplemented. Results. The paper describes classifications of types of data migration, provides examples related to ERP. The stages of the data migration project are described in detail and supplemented. The comparison of two key data migration strategies is given, their advantages and disadvantages are highlighted, recommendations for the application of a particular strategy are formed. The main problems of data migration in the context of ERPs, the consequences of these problems for the entire migration project are considered. Conclusion. The results obtained suggest that data migration is a complex and time-consuming process that requires serious competencies from management and performers. The migration strategy should be developed in an effective way and take into account all the variety of influencing factors.В основе каждой ERP-системы лежит единая база данных, которая позволяет сотрудникам организации полагаться на один и тот же согласованный набор информации. Миграция данных является важной составляющей проектов обновления, внедрения и интеграции ERP. При этом сценарий миграции может быть сложным и длительным, требовать большого количества ресурсов и высокой компетенции руководящего персонала. Недооценка необходимых времени и усилий может привести к существенному увеличению расходов и затягиванию сроков ввода ERP в эксплуатацию. Точность и полнота передаваемых данных также имеют большое значение, поскольку многие аспекты бизнеса – удовлетворение потребностей клиентов, принятие решений, цепочка поставок и отношения с партнерами – будут зависеть от качества данных. Несмотря на это, сложность сценариев миграции данных традиционно недооценивается. В большинстве существующих исследований миграция данных рассматривается преимущественно с технической стороны. Аспекты, связанные с концептуальным содержанием миграции данных, ее взаимосвязью с бизнес-процессами и управлением компанией, а также специфической ролью миграции данных в проектах обновления, внедрения и интеграции ERP-систем, остаются недостаточно проработанными. Цель исследования. Целью данной работы является дополнение теоретических представлений о содержании, разнообразии, проблемах и стратегиях миграции данных в контексте ERP-систем. Материалы и методы. В статье приведены обобщение и систематизация видов, этапов, ключевых стратегий и наиболее значимых проблем миграции данных. В целях данного исследования был рассмотрен, переработан и дополнен материал из 23 источников на близкую тематику. Результаты. В работе описаны классификации видов миграции данных, приведены примеры, относящиеся к ERP. Детально описаны и дополнены этапы проекта миграции данных. Приведено сравнение двух ключевых стратегий миграции данных, выделены их преимущества и недостатки, сформированы рекомендации для применения той или иной стратегии. Рассмотрены основные проблемы миграции данных в контексте ERP-систем, последствия данных проблем для всего проекта миграции. Заключение. Полученные результаты позволяют утверждать, что миграция данных является сложным и трудоемким процессом, требующим серьезных компетенций от руководства и исполнителей. Стратегия миграции должна быть разработана эффективным образом с учетом всего многообразия влияющих факторов

Colocation as a Service

By colocating with other tenants of an Infrastructure as a Service (IaaS) offering, IaaS users could reap significant cost savings by judiciously sharing their use of the fixed-size instances offered by IaaS providers. This paper presents the blueprints of a Colocation as a Service (CaaS) framework. CaaS strategic services identify coalitions of self-interested users that would benefit from colocation on shared instances. CaaS operational services provide the information necessary for, and carry out the reconfigurations mandated by strategic services. CaaS could be incorporated into an IaaS offering by providers; it could be implemented as a value-added proposition by IaaS resellers; or it could be directly leveraged in a peer-to-peer fashion by IaaS users. To establish the practicality of such offerings, this paper presents XCS – a prototype implementation of CaaS on top of the Xen hypervisor. XCS makes specific choices with respect to the various elements of the CaaS framework: it implements strategic services based on a game-theoretic formulation of colocation; it features novel concurrent migration heuristics which are shown to be efficient; and it offers monitoring and accounting services at both the hypervisor and VM layers. Extensive experimental results obtained by running PlanetLab trace-driven workloads on the XCS prototype confirm the premise of CaaS – by demonstrating the efficiency and scalability of XCS, and by quantifying the potential cost savings accrued through the use of XCS

Strategic and operational services for workload management in the cloud

In hosting environments such as Infrastructure as a Service (IaaS) clouds, desirable application performance is typically guaranteed through the use of Service Level Agreements (SLAs), which specify minimal fractions of resource capacities that must be allocated by a service provider for unencumbered use by customers to ensure proper operation of their workloads. Most IaaS offerings are presented to customers as fixed-size and fixed-price SLAs, that do not match well the needs of specific applications. Furthermore, arbitrary colocation of applications with different SLAs may result in inefficient utilization of hosts' resources, resulting in economically undesirable customer behavior. In this thesis, we propose the design and architecture of a Colocation as a Service (CaaS) framework: a set of strategic and operational services that allow the efficient colocation of customer workloads. CaaS strategic services provide customers the means to specify their application workload using an SLA language that provides them the opportunity and incentive to take advantage of any tolerances they may have regarding the scheduling of their workloads. CaaS operational services provide the information necessary for, and carry out the reconfigurations mandated by strategic services. We recognize that it could be the case that there are multiple, yet functionally equivalent ways to express an SLA. Thus, towards that end, we present a service that allows the provably-safe transformation of SLAs from one form to another for the purpose of achieving more efficient colocation. Our CaaS framework could be incorporated into an IaaS offering by providers or it could be implemented as a value added proposition by IaaS resellers. To establish the practicality of such offerings, we present a prototype implementation of our proposed CaaS framework

Data Management Strategies for Relative Quality of Service in Virtualised Storage Systems

The amount of data managed by organisations continues to grow relentlessly. Driven by the high costs of maintaining multiple local storage systems, there is a well established trend towards storage consolidation using multi-tier Virtualised Storage Systems (VSSs). At the same time, storage infrastructures are increasingly subject to stringent Quality of Service (QoS) demands. Within a VSS, it is challenging to match desired QoS with delivered QoS, considering the latter can vary dramatically both across and within tiers. Manual efforts to achieve this match require extensive and ongoing human intervention. Automated efforts are based on workload analysis, which ignores the business importance of infrequently accessed data. This thesis presents our design, implementation and evaluation of data maintenance strategies in an enhanced version of the popular Linux Extended 3 Filesystem which features support for the elegant specification of QoS metadata while maintaining compatibility with stock kernels. Users and applications specify QoS requirements using a chmod-like interface. System administrators are provided with a character device kernel interface that allows for profiling of the QoS delivered by the underlying storage. We propose a novel score-based metric, together with associated visualisation resources, to evaluate the degree of QoS matching achieved by any given data layout. We also design and implement new inode and datablock allocation and migration strategies which exploit this metric in seeking to match the QoS attributes set by users and/or applications on files and directories with the QoS actually delivered by each of the filesystem’s block groups. To create realistic test filesystems we have included QoS metadata support in the Impressions benchmarking framework. The effectiveness of the resulting data layout in terms of QoS matching is evaluated using a special kernel module that is capable of inspecting detailed filesystem data on-the-fly. We show that our implementations of the proposed inode and datablock allocation strategies are capable of dramatically improving data placement with respect to QoS requirements when compared to the default allocators

Embedding Games

Large scale distributed computing infrastructures pose challenging resource management problems, which could be addressed by adopting one of two perspectives. On the one hand, the problem could be framed as a global optimization that aims to minimize some notion of system-wide (social) cost. On the other hand, the problem could be framed in a game-theoretic setting whereby rational, selfish users compete for a share of the resources so as to maximize their private utilities with little or no regard for system-wide objectives. This game-theoretic setting is particularly applicable to emerging cloud and grid environments, testbed platforms, and many networking applications. By adopting the first, global optimization perspective, this thesis presents NetEmbed: a framework, associated mechanisms, and implementations that enable the mapping of requested configurations to available infrastructure resources. By adopting the second, game-theoretic perspective, this thesis defines and establishes the premises of two resource acquisition mechanisms: Colocation Games and Trade and Cap. Colocation Games enable the modeling and analysis of the dynamics that result when rational, selfish parties interact in an attempt to minimize the individual costs they incur to secure shared resources necessary to support their application QoS or SLA requirements. Trade and Cap is a market-based scheduling and load-balancing mechanism that facilitates the trading of resources when users have a mixture of rigid and fluid jobs, and incentivizes users to behave in ways that result in better load-balancing of shared resources. In addition to developing their analytical underpinnings, this thesis establishes the viability of NetEmbed, Colocation Games, and Trade and Cap by presenting implementation blueprints and experimental results for many variants of these mechanisms. The results presented in this thesis pave the way for the development of economically-sound resource acquisition and management solutions in two emerging, and increasingly important settings. In pay-as-you-go settings, where pricing is based on usage, this thesis anticipates new service offerings that enable efficient marketplaces in the presence of non-cooperative, selfish agents. In settings where pricing is not a function of usage, this thesis anticipates the development of service offerings that enable trading of usage rights to maximize the utility of a shared infrastructure to its tenants

Strategic and operational services for workload management in the cloud (PhD thesis)

In hosting environments such as Infrastructure as a Service (IaaS) clouds, desirable application performance is typically guaranteed through the use of Service Level Agreements (SLAs), which specify minimal fractions of resource capacities that must be allocated by a service provider for unencumbered use by customers to ensure proper operation of their workloads. Most IaaS offerings are presented to customers as fixed-size and fixed-price SLAs, that do not match well the needs of specific applications. Furthermore, arbitrary colocation of applications with different SLAs may result in inefficient utilization of hosts’ resources, resulting in economically undesirable customer behavior. In this thesis, we propose the design and architecture of a Colocation as a Service (CaaS) framework: a set of strategic and operational services that allow the efficient colocation of customer workloads. CaaS strategic services provide customers the means to specify their application workload using an SLA language that provides them the opportunity and incentive to take advantage of any tolerances they may have regarding the scheduling of their workloads. CaaS operational services provide the information necessary for, and carry out the reconfigurations mandated by strategic services. We recognize that it could be the case that there are multiple, yet functionally equivalent ways to express an SLA. Thus, towards that end, we present a service that allows the provably-safe transformation of SLAs from one form to another for the purpose of achieving more efficient colocation. Our CaaS framework could be incorporated into an IaaS offering by providers or it could be implemented as a value added proposition by IaaS resellers. To establish the practicality of such offerings, we present a prototype implementation of our proposed CaaS framework. (Major Advisor: Azer Bestavros

ADAM: A Decentralized Parallel Computer Architecture Featuring Fast Thread and Data Migration and a Uniform Hardware Abstraction

The furious pace of Moore's Law is driving computer architecture into a realm where the the speed of light is the dominant factor in system latencies. The number of clock cycles to span a chip are increasing, while the number of bits that can be accessed within a clock cycle is decreasing. Hence, it is becoming more difficult to hide latency. One alternative solution is to reduce latency by migrating threads and data, but the overhead of existing implementations has previously made migration an unserviceable solution so far. I present an architecture, implementation, and mechanisms that reduces the overhead of migration to the point where migration is a viable supplement to other latency hiding mechanisms, such as multithreading. The architecture is abstract, and presents programmers with a simple, uniform fine-grained multithreaded parallel programming model with implicit memory management. In other words, the spatial nature and implementation details (such as the number of processors) of a parallel machine are entirely hidden from the programmer. Compiler writers are encouraged to devise programming languages for the machine that guide a programmer to express their ideas in terms of objects, since objects exhibit an inherent physical locality of data and code. The machine implementation can then leverage this locality to automatically distribute data and threads across the physical machine by using a set of high performance migration mechanisms. An implementation of this architecture could migrate a null thread in 66 cycles -- over a factor of 1000 improvement over previous work. Performance also scales well; the time required to move a typical thread is only 4 to 5 times that of a null thread. Data migration performance is similar, and scales linearly with data block size. Since the performance of the migration mechanism is on par with that of an L2 cache, the implementation simulated in my work has no data caches and relies instead on multithreading and the migration mechanism to hide and reduce access latencies