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77
Automatic virtual machine configuration for database workloads
- In SIGMOD
, 2008
"... Virtual machine monitors are becoming popular tools for the deployment of database management systems and other enterprise software applications. In this paper, we consider a common resource consolidation scenario, in which several database management system instances, each running in a virtual mach ..."
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Cited by 53 (3 self)
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Virtual machine monitors are becoming popular tools for the deployment of database management systems and other enterprise software applications. In this paper, we consider a common resource consolidation scenario, in which several database management system instances, each running in a virtual machine, are sharing a common pool of physical computing resources. We address the problem of optimizing the performance of these database management systems by controlling the configurations of the virtual machines in which they run. These virtual machine configurations determine how the shared physical resources will be allocated to the different database instances. We introduce a virtualization design advisor that uses information about the anticipated workloads of each of the database systems to recommend workload-specific configurations offline. Furthermore, runtime information collected after the deployment of the recommended configurations can be used to refine the recommendation. To estimate the effect of a particular resource allocation on workload performance, we use the query optimizer in a new what-if mode. We have implemented our approach using both PostgreSQL and DB2, and we have experimentally evaluated its effectiveness using DSS and OLTP workloads.
Dynamic Resource Allocation Using Virtual Machines for Cloud Computing Environment
"... Abstract—Cloud computing allows business customers to scale up and down their resource usage based on needs. Many of the touted gains in the cloud model come from resource multiplexing through virtualization technology. In this paper, we present a system that uses virtualization technology to alloca ..."
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Cited by 32 (0 self)
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Abstract—Cloud computing allows business customers to scale up and down their resource usage based on needs. Many of the touted gains in the cloud model come from resource multiplexing through virtualization technology. In this paper, we present a system that uses virtualization technology to allocate data center resources dynamically based on application demands and support green computing by optimizing the number of servers in use. We introduce the concept of “skewness ” to measure the unevenness in the multidimensional resource utilization of a server. By minimizing skewness, we can combine different types of workloads nicely and improve the overall utilization of server resources. We develop a set of heuristics that prevent overload in the system effectively while saving energy used. Trace driven simulation and experiment results demonstrate that our algorithm achieves good performance. Index Terms—Cloud computing, resource management, virtualization, green computing Ç 1
Performance Model Driven QoS Guarantees and Optimization in Clouds
- in Proceedings of Workshop on Software Engineering Challenges in Cloud Computing @ ICSE 2009
, 2009
"... This paper presents a method for achieving optimization in clouds by using performance models in the development, deployment and operations of the applications running in the cloud. We show the architecture of the cloud, the services offered by the cloud to support optimization and the methodology u ..."
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Cited by 24 (5 self)
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This paper presents a method for achieving optimization in clouds by using performance models in the development, deployment and operations of the applications running in the cloud. We show the architecture of the cloud, the services offered by the cloud to support optimization and the methodology used by developers to enable runtime optimization of the clouds. An optimization algorithm is presented which accommodates different goals, different scopes and timescales of optimization actions, and different control algorithms. The optimization here maximizes profits in the cloud constrained by QoS and SLAs across a large variety of workloads. 1. Clouds and Optimization
Multi-dimensional SLA-based resource allocation for multi-tier cloud computing systems
- Proc. of the IEEE Cloud
, 2011
"... Abstract—With increasing demand for computing and memory, distributed computing systems have attracted a lot of attention. Resource allocation is one of the most important challenges in the distributed systems specially when the clients have Service Level Agreements (SLAs) and the total profit in th ..."
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Cited by 23 (9 self)
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Abstract—With increasing demand for computing and memory, distributed computing systems have attracted a lot of attention. Resource allocation is one of the most important challenges in the distributed systems specially when the clients have Service Level Agreements (SLAs) and the total profit in the system depends on how the system can meet these SLAs. In this paper, an SLA-based resource allocation problem for multi-tier applications in the cloud computing is considered. An upper bound on the total profit is provided and an algorithm based on force-directed search is proposed to solve the problem. The processing, memory requirement, and communication resources are considered as three dimensions in which optimization is performed. Simulation results demonstrate the effectiveness of the proposed heuristic algorithm. I.
Validating Heuristics for Virtual Machines Consolidation
"... This paper examines two fundamental issues pertaining to virtual machines (VM) consolidation. Current virtualization management tools, both commercial and academic, enable multiple virtual machines to be consolidated into few servers so that other servers can be turned off, saving power. These tools ..."
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Cited by 20 (0 self)
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This paper examines two fundamental issues pertaining to virtual machines (VM) consolidation. Current virtualization management tools, both commercial and academic, enable multiple virtual machines to be consolidated into few servers so that other servers can be turned off, saving power. These tools determine effective strategies for VM placement with the help of clever optimization algorithms, relying on two inputs: a model of resource utilization vs performance tradeoff when multiple VMs are hosted together and estimates of resource requirements for each VM in terms of CPU, network and storage. This paper investigates the following key questions: What factors govern the performance model that drives VM placement, and how do competing resource demands in multiple dimensions affect VM consolidation? It establishes a few basic insights about these questions through a combination of experiments and empirical analysis. This experimental study points out potential pitfalls in the use of current VM management tools and identifies promising opportunities for more effective performance consolidation algorithms. In addition to providing valuable guidance to practitioners, we believe this paper will serve as a starting point for research into next-generation virtualization platforms and tools. 1
A Scalable Data Platform for a Large Number of Small Applications
"... As a growing number of websites open up their APIs to external application developers (e.g., Facebook, Yahoo! Widgets, Google Gadgets), these websites are facing an intriguing scalability problem: while each user-generated application is by itself quite small (in terms of size and throughput require ..."
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Cited by 20 (0 self)
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As a growing number of websites open up their APIs to external application developers (e.g., Facebook, Yahoo! Widgets, Google Gadgets), these websites are facing an intriguing scalability problem: while each user-generated application is by itself quite small (in terms of size and throughput requirements), there are many many such applications. Unfortunately, existing data-management solutions are not designed to handle this form of scalability in a cost-effective, manageable and/or flexible manner. For instance, large installations of commercial database systems such as Oracle, DB2 and SQL Server are usually very expensive and difficult to manage. At the other extreme, low-cost hosted datamanagement solutions such as Amazon’s SimpleDB do not support sophisticated data-manipulation primitives such as joins that are necessary for developing most Web applications. To address this issue, we explore a new point in the design space whereby we use commodity hardware and free software (MySQL) to scale to a large number of applications while still supporting full SQL functionality, transactional guarantees, high availability and Service Level Agreements (SLAs). We do so by exploiting the key property that each application is “small ” and can fit in a single machine (which can possibly be shared with other applications). Using this property, we design replication strategies, data migration techniques and load balancing operations that automate the tasks that would otherwise contribute to the operational and management complexity of dealing with a large number of applications. Our experiments based on the TPC-W benchmark suggest that the proposed system can scale to a large number of small applications. 1.
A Network-aware Virtual Machine Placement and Migration Approach in Cloud Computing
- In 2010 Ninth International Conference on Grid and Cloud Computing
, 2010
"... Abstract—Cloud computing represents a major step up in computing whereby shared computation resources are provided on demand. In such a scenario, applications and data thereof can be hosted by various networked virtual machines (VMs). As applications, especially data-intensive applications, often ne ..."
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Cited by 20 (0 self)
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Abstract—Cloud computing represents a major step up in computing whereby shared computation resources are provided on demand. In such a scenario, applications and data thereof can be hosted by various networked virtual machines (VMs). As applications, especially data-intensive applications, often need to communicate with data frequently, the network I/O performance would affect the overall application performance significantly. Therefore, placement of virtual machines which host an application and migration of these virtual machines while the unexpected network latency or congestion occurs is critical to achieve and maintain the application performance. To address these issues, this paper proposes a virtual machine placement and migration approach to minimizing the data transfer time consumption. Our simulation studies suggest that the proposed approach is effective in optimizing the data transfer between the virtual machine and data, thus helping optimize the overall application performance. Keywords—cloud computing, virtual machine, placement, migration, network I.
Utilitybased Placement of Dynamic Web Applications with Fairness Goals
- in Proceedings of 11th IEEE/IFIP Network Ops and Management Symp. (NOMS
, 2008
"... Abstract—We study the problem of dynamic resource allo-cation to clustered Web applications. We extend application server middleware with the ability to automatically decide the size of application clusters and their placement on physical machines. Unlike existing solutions, which focus on maximizin ..."
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Cited by 18 (3 self)
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Abstract—We study the problem of dynamic resource allo-cation to clustered Web applications. We extend application server middleware with the ability to automatically decide the size of application clusters and their placement on physical machines. Unlike existing solutions, which focus on maximizing resource utilization and may unfairly treat some applications, the approach introduced in this paper considers the satisfaction of each application with a particular resource allocation and attempts to at least equally satisfy all applications. We model satisfaction using utility functions, mapping CPU resource al-location to the performance of an application relative to its objective. The demonstrated online placement technique aims at equalizing the utility value across all applications while also satisfying operational constraints, preventing the over-allocation of memory, and minimizing the number of placement changes. We have implemented our technique in a leading commercial middleware product. Using this real-life testbed and a simulation we demonstrate the benefit of the utility-driven technique as compared to other state-of-the-art techniques. I.
Doloto: Code Splitting for Network-Bound Web 2.0 Applications
"... others, use a combination of Dynamic HTML, JavaScript and other Web browser technologies commonly referred as AJAX to push page generation and content manipulation to the client web browser. This approach improves the responsiveness of these network-bound applications, but the shift of application e ..."
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Cited by 16 (5 self)
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others, use a combination of Dynamic HTML, JavaScript and other Web browser technologies commonly referred as AJAX to push page generation and content manipulation to the client web browser. This approach improves the responsiveness of these network-bound applications, but the shift of application execution from a back-end server to the client also often dramatically increases the amount of code that must first be downloaded to the browser. This creates an unfortunate Catch-22: to create responsive distributed Web 2.0 applications developers move code to the client, but for an application to be responsive, the code must first be transferred there, which takes time. In this paper, we present DOLOTO, a system that analyzes application workloads and automatically performs code splitting of existing large Web 2.0 applications. After being processed by DOLOTO, an application will initially transfer only the portion of code necessary for application initialization. The rest of the application’s code is replaced by short stubs—their actual function code is transfered lazily in the background or, at the latest, on-demand on first execution. Since code download is interleaved with application execution, users can start interacting with the Web application much sooner, without waiting for the code that implements extra, unused features. To demonstrate the effectiveness of DOLOTO in practice, we have performed experiments on five large widely-used Web 2.0 applications. DOLOTO reduces the size of initial application code download by hundreds of kilobytes or as much as 50 % of the original download size. The time to download and begin interacting with large applications is reduced by 20-40 % depending on the application and wide-area network conditions. 1
Energy-Aware Service Execution
"... Abstract—The energy consumption of ICT infrastructures has increased considerably in the recent years. This has resulted in extensive research on dynamic power management strategies as well as data centre design and placement. The main problem with most of the proposed or existing approaches is that ..."
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Cited by 12 (10 self)
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Abstract—The energy consumption of ICT infrastructures has increased considerably in the recent years. This has resulted in extensive research on dynamic power management strategies as well as data centre design and placement. The main problem with most of the proposed or existing approaches is that they do not fully take the distributed nature of and strong logical dependencies between executed services into account. However, without a comprehensive knowledge of the wider relationships between services, local power management strategies may be ineffectual or can even result in high aggregate energy cost. Understanding this relationship is useful for fine-grained energyaware computing. For example, services that run on underutilised servers can be stopped or seamlessly migrated to other servers, so that the underutilised servers can be turned off. Alternatively, a re-binding process can be used if the cost of service migration is high. Such advantages can be fully exploited if the dependency between services is properly understood and meaningfully modelled. This paper introduces a conceptual architecture for an energy-aware service execution platform and compares three optimisation mechanisms to support dynamic service migration and rebinding. Index Terms—Context-awareness, dynamic power management, energy-efficient servers, power consumption estimation, service execution, service oriented architecture I.
