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Eduard Ayguade

Universitat Politecnica de Catalunya, Arquitectura de Computadors, Faculty Member

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Papers by Eduard Ayguade

Ayguad e E.(1992) Computed-Aided Synthesis of Data-Path by Using a Simulated-Annealing-Based Approach

2013 Index IEEE Transactions on Network and Service Management Vol. 10

Using sacks to organize registers in VLIW machines

Lecture Notes in Computer Science, 1994

This paper analyses the register requirements of software pipelined inner loops. When the number ... more

POSTER: Profit-aware cloud resource provisioner for ecommerce

2014 IEEE International Conference on Cluster Computing (CLUSTER), 2014

Quantitative analysis of vector code

Proceedings Euromicro Workshop on Parallel and Distributed Processing, 1995

In this paper we present the results of a detailedsimulation study of the execution of vector pro... more In this paper we present the results of a detailedsimulation study of the execution of vector programson a single processor of a Convex C3480 machine,using a subset of the Perfect Club benchmarks. Weare interested in evaluating several cost/performancetradeoffs that the machine designers made in order toasses which features of the architecture severely limitthe performance attainable. We present the detailedusage of

Assessing the impact of network compression on molecular dynamics and finite element methods

Proceedings of the 14th IEEE International Conference on High Performance Computing and Communications, HPCC-2012 - 9th IEEE International Conference on Embedded Software and Systems, ICESS-2012, 2012

Efficient communication in parallel applications is one of the main challenges for the scalabilit... more Efficient communication in parallel applications is one of the main challenges for the scalability of supercomputers, both in weak and strong scaling environments. In the past, several compression techniques have been proposed as a way to improve the performance and scalability of parallel applications. Those works have shown significant speed-ups when applying compressors to the MPI transfers of certain algorithmic kernels. However, these techniques have not seen widespread adoption in current supercomputers.

Enabling resource sharing between transactional and batch workloads using dynamic application placement

by Malgorzata Steinder and Eduard Ayguade

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2008

We present a technique that enables existing middleware to fairly manage mixed workloads: batch j... more We present a technique that enables existing middleware to fairly manage mixed workloads: batch jobs and transactional applications. The technique leverages a generic application placement controller, which dynamically allocates compute resources to application instances. The controller works towards a fairness goal while also trying to maximize individual workload performance. We use relative performance functions to drive the application placement controller. Such functions are derived from workload-specific performance modelsin the case of transactional workloads, we use queuing theory to build the performance model. For batch workloads, we evaluate a candidate placement by calculating long-term estimates of the completion times that are achievable with that placement according to a scheduling policy. In this paper, we propose a lowest relative performancwe first scheduling policy as a way to also achieve fair resource allocation among batch jobs. Our technique permits collocation of the workload types on the same physical hardware, and leverages control mechanisms such as suspension and migration to perform online system reconfiguration. In our experiments we demonstrate that our technique maximizes mixed workload performance while providing service differentiation based on high-level performance goals.

Managing SLAs of heterogeneous workloads using dynamic application placement

by Malgorzata Steinder and Eduard Ayguade

Proceedings of the 17th International Symposium on High Performance Distributed Computing 2008, HPDC'08, 2008

In this paper we address the problem of managing heterogeneous workloads in a virtualized data ce... more In this paper we address the problem of managing heterogeneous workloads in a virtualized data center. We consider two different workloads: transactional applications and long-running jobs. We present a technique that permits collocation of these workload types on the same physical hardware. Our technique dynamically modifies workload placement by leveraging control mechanisms such as suspension and migration, and strives to optimally trade off resource allocation among these workloads in spite of their differing characteristics and performance objectives. Our approach builds upon our previous work on dynamically placing transactional workloads. This paper extends our framework with the capability to manage long-running workloads. We achieve this goal by using utility functions, which permit us to compare the performance of various workloads, and which are used to drive allocation decisions. We demonstrate that our technique maximizes heterogeneous workload performance while providing service differentiation based on high-level performance goals.

Utility-based placement of dynamic web applications with fairness goals

by Malgorzata Steinder and Eduard Ayguade

NOMS 2008 - IEEE/IFIP Network Operations and Management Symposium: Pervasive Management for Ubiquitous Networks and Services, 2008

We study the problem of dynamic resource allocation to clustered Web applications. We extend appl... more We study the problem of dynamic resource allocation 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 allocation 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.

Batch job profiling and adaptive profile enforcement for virtualized environments

Proceedings of the 17th Euromicro International Conference on Parallel, Distributed and Network-Based Processing, PDP 2009, 2009

Data center management is driven by high-level performance goals, and it is the responsibility of... more Data center management is driven by high-level performance goals, and it is the responsibility of a management middleware to ensure that those goals are met using dynamic resource allocation. The performance delivered by the heterogeneous set of applications running in a virtualized enterprise data center must be predicted to make resource allocation decisions. For some of these applications, it is required to produce accurate profiles based on previous executions: that is the case of batch jobs. In this paper we propose a methodology to produce resource consumption profiles for batch applications running inside of virtual machines and a technique to enforce and adapt the profiles to actual execution conditions and application performance. For this purpose we have developed a testing prototype. The enforcement technique observes the fact that management middleware usually run in control cycles in which the system can be reconfigured, what imposes a tradeoff between the accuracy of the profiles and their applicability in real deployments. The novel contribution of this work is the study of the tradeoff between accuracy and applicability of workload profiles, what is a necessary step to enable existing management middleware with the performance prediction mechanisms required to perform effective dynamic resource allocation.

Characterization of workload and resource consumption for an online travel and booking site

IEEE International Symposium on Workload Characterization, IISWC'10, 2010

Online travel and ticket booking is one of the top E-Commerce industries. As they present a mix o... more Online travel and ticket booking is one of the top E-Commerce industries. As they present a mix of products: flights, hotels, tickets, restaurants, activities and vacational packages, they rely on a wide range of technologies to support them: Javascript, AJAX, XML, B2B Web services, Caching, Search Algorithms and Affiliation; resulting in a very rich and heterogeneous workload. Moreover, visits to travel sites present a great variability depending on time of the day, season, promotions, events, and linking; creating bursty traffic, making capacity planning a challenge. It is therefore of great importance to understand how users and crawlers interact on travel sites and their effect on server resources, for devising cost effective infrastructures and improving the Quality of Service for users.

Non-intrusive estimation of QoS degradation impact on e-commerce user satisfaction

Proceedings - 2011 IEEE International Symposium on Network Computing and Applications, NCA 2011, 2011

Abstract With the massification of high speed Internet access, recent industry consumer reports s... more

An Experimental Evaluation of the New OpenMP Tasking Model

Lecture Notes in Computer Science, 2008

Abstract. The OpenMP standard was conceived to parallelize dense array-based applications, and it... more Abstract. The OpenMP standard was conceived to parallelize dense array-based applications, and it has achieved much success with that. Recently, a novel tasking proposal to handle unstructured parallelism in OpenMP has been submitted to the OpenMP 3.0 Language Commit- tee. We tested its expressiveness and flexibility, using it to parallelize a number,of examples from a variety of different application areas.

Adaptive MapReduce Scheduling in Shared Environments

by Malgorzata Steinder and Eduard Ayguade

2014 14th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, 2014

ABSTRACT In this paper we present a MapReduce task scheduler for shared environments in which Map... more ABSTRACT In this paper we present a MapReduce task scheduler for shared environments in which MapReduce is executed along with other resource-consuming workloads, such as transactional applications. All workloads may potentially share the same data store, some of them consuming data for analytics purposes while others acting as data generators. This kind of scenario is becoming increasingly important in data centers where improved resource utilization can be achieved through workload consolidation, and is specially challenging due to the interaction between workloads of different nature that compete for limited resources. The proposed scheduler aims to improve resource utilization across machines while observing completion time goals. Unlike other MapReduce schedulers, our approach also takes into account the resource demands for non-MapReduce workloads, and assumes that the amount of resources made available to the MapReduce applications is variable over time. As shown in our experiments, our proposal improves the management of MapReduce jobs in the presence of variable resource availability, increasing the accuracy of the estimations made by the scheduler, thus improving completion time goals without an impact on the fairness of the scheduler.

Enabling Distributed Key-Value Stores with Low Latency-Impact Snapshot Support

2013 IEEE 12th International Symposium on Network Computing and Applications, 2013

ABSTRACT Current distributed key-value stores generally provide greater scalability at the expens... more ABSTRACT Current distributed key-value stores generally provide greater scalability at the expense of weaker consistency and isolation. However, additional isolation support is becoming increasingly important in the environments in which these stores are deployed, where different kinds of applications with different needs are executed, from transactional workloads to data analytics. While fully-fledged ACID support may not be feasible, it is still possible to take advantage of the design of these data stores, which often include the notion of multiversion concurrency control, to enable them with additional features at a much lower performance cost and maintaining its scalability and availability. In this paper we explore the effects that additional consistency guarantees and isolation capabilities may have on a state of the art key-value store: Apache Cassandra. We propose and implement a new multiversioned isolation level that provides stronger guarantees without compromising Cassandra&#39;s scalability and availability. As shown in our experiments, our version of Cassandra allows Snapshot Isolation-like transactions, preserving the overall performance and scalability of the system.

ALOJA: A systematic study of Hadoop deployment variables to enable automated characterization of cost-effectiveness

2014 IEEE International Conference on Big Data (Big Data), 2014

A Hybrid Web Server Architecture for Secure e-Business Web Applications

Lecture Notes in Computer Science, 2005

Nowadays the success of many e-commerce applications, such as on-line banking, depends on their r... more Nowadays the success of many e-commerce applications, such as on-line banking, depends on their reliability, robustness and security. Designing a web server architecture that keeps these properties under high loads is a challenging task because they are the opposite to performance. The industry standard way to provide security on web applications is the use the Secure Socket Layer (SSL) protocol to create a secure communication channel between the clients and the server. Traditionally, the use of data encryption has introduced a negative performance impact over web application servers because it is an extremely CPU consuming task, reducing the throughput achieved by the server as well as increasing its average response time. As far as the revenue obtained by a commercial web application is directly related to the amount of clients that complete business transactions, the performance of such secure applications becomes a mission critical objective for most companies. In this paper we evaluate a novel hybrid web server architecture (implemented over Tomcat 5.5) that combines the best aspects of the two most extended server architectures, the multithreaded and the event-driven, to provide an excellent trade-off between reliability, robustness, security and performance. The obtained results demonstrate the feasibility of the proposed hybrid architecture as well as the performance benefits that this model introduces for secure web applications, providing the same security level than the original Tomcat 5.5 and improved reliability, robustness and performance, according to both technical and business metrics.

Performance Management of Accelerated MapReduce Workloads in Heterogeneous Clusters

2010 39th International Conference on Parallel Processing, 2010

Next generation data centers will be composed of thousands of hybrid systems in an attempt to inc... more Next generation data centers will be composed of thousands of hybrid systems in an attempt to increase overall cluster performance and to minimize energy consumption. New programming models, such as MapReduce, specifically designed to make the most of very large infrastructures will be leveraged to develop massively distributed services. At the same time, data centers will bring an unprecedented degree of workload consolidation, hosting in the same infrastructure distributed services from many different users. In this paper we present our advancements in leveraging the Adaptive MapReduce Scheduler to meet user defined high level performance goals while transparently and efficiently exploiting the capabilities of hybrid systems. While the Adaptive Scheduler was already able to dynamically allocate resources to co-located MapReduce jobs based on their completion time goals, it was completely unaware of specific hardware capabilities. In our work we describe the changes introduced in the Adaptive Scheduler to enable it with hardware awareness and with the ability to co-schedule accelerable and non-accelerable jobs on the same heterogeneous MapReduce cluster, making the most of the underlying hybrid systems. The developed prototype is tested in a cluster of Cell/BE blades and relies on the use of accelerated and non-accelerated versions of the MapReduce tasks of different deployed applications to dynamically select the best version to run on each node. Decisions are made after workload composition and jobs' completion time goals. Results show that the augmented Adaptive Scheduler provides dynamic resource allocation across jobs, hardware affinity when possible, and is even able to spread jobs' tasks across accelerated and non-accelerated nodes in order to meet performance goals in extreme conditions. To our knowledge this is the first MapReduce scheduler and prototype that is able to manage high-level performance goals even in presence of hybrid systems and accelerable jobs.

Tailoring Resources: The Energy Efficient Consolidation Strategy Goes Beyond Virtualization

2008 International Conference on Autonomic Computing, 2008

Virtualization and consolidation are two complementary techniques widely adopted in a global stra... more Virtualization and consolidation are two complementary techniques widely adopted in a global strategy to reduce system management complexity. In this paper we show how two simple and well-known techniques can be combined to dramatically increase the energy efficiency of a virtualized and consolidated data center. This result is obtained by introducing a new approach to the consolidation strategy that allows an important reduction in the amount of active nodes required to process a web workload without degrading the offered service level. Furthermore, when the system eventually gets overloaded and no energy can be saved without loosing performance, we show how these techniques can still improve the overall value obtained from the workload. The two techniques are memory compression and request discrimination, and were separately studied and validated in a previous work to be now combined in a joint effort. Memory compression is used to convert CPU power into extra memory capacity to overcome system underutilization scenarios caused by memory constraints. Request discrimination is used to identify web clients according to the value they have to the system. We study the combined use of these two techniques by describing a simple but still representative scenario and also by considering the dramatic impact they would have for a real workload obtained from a top national travel website. Our results indicate that an important improvement can be achieved by deciding not only how resources are allocated, but also how they are used. Moreover, we believe that this serves as an illustrative example of a new way of management: tailoring the resources to meet high level energy efficiency goals.

Session-Based Adaptive Overload Control for Secure Dynamic Web Applications

2005 International Conference on Parallel Processing (ICPP'05), 2005

As dynamic web content and security capabilities are becoming popular in current web sites, the p... more As dynamic web content and security capabilities are becoming popular in current web sites, the performance demand on application servers that host the sites is increasing, leading sometimes these servers to overload. As a result, response times may grow to unacceptable levels and the server may saturate or even crash. In this paper we present a session-based adaptive overload control mechanism based on SSL (Secure Socket Layer) connections differentiation and admission control. The SSL connections differentiation is a key factor because the cost of establishing a new SSL connection is much greater than establishing a resumed SSL connection (it reuses an existing SSL session on server). Considering this big difference, we have implemented an admission control algorithm that prioritizes the resumed SSL connections to maximize performance on session-based environments and limits dynamically the number of new SSL connections accepted depending on the available resources and the current number of connections in the system to avoid server overload. In order to allow the differentiation of resumed SSL connections from new SSL connections we propose a possible extension of the Java Secure Sockets Extension (JSSE) API. Our evaluation on Tomcat server demonstrates the benefit of our proposal for preventing server overload.

Ayguad e E.(1992) Computed-Aided Synthesis of Data-Path by Using a Simulated-Annealing-Based Approach

2013 Index IEEE Transactions on Network and Service Management Vol. 10

Using sacks to organize registers in VLIW machines

Lecture Notes in Computer Science, 1994

This paper analyses the register requirements of software pipelined inner loops. When the number ... more

POSTER: Profit-aware cloud resource provisioner for ecommerce

2014 IEEE International Conference on Cluster Computing (CLUSTER), 2014

Quantitative analysis of vector code

Proceedings Euromicro Workshop on Parallel and Distributed Processing, 1995

In this paper we present the results of a detailedsimulation study of the execution of vector pro... more In this paper we present the results of a detailedsimulation study of the execution of vector programson a single processor of a Convex C3480 machine,using a subset of the Perfect Club benchmarks. Weare interested in evaluating several cost/performancetradeoffs that the machine designers made in order toasses which features of the architecture severely limitthe performance attainable. We present the detailedusage of

Assessing the impact of network compression on molecular dynamics and finite element methods

Proceedings of the 14th IEEE International Conference on High Performance Computing and Communications, HPCC-2012 - 9th IEEE International Conference on Embedded Software and Systems, ICESS-2012, 2012

Efficient communication in parallel applications is one of the main challenges for the scalabilit... more Efficient communication in parallel applications is one of the main challenges for the scalability of supercomputers, both in weak and strong scaling environments. In the past, several compression techniques have been proposed as a way to improve the performance and scalability of parallel applications. Those works have shown significant speed-ups when applying compressors to the MPI transfers of certain algorithmic kernels. However, these techniques have not seen widespread adoption in current supercomputers.

Enabling resource sharing between transactional and batch workloads using dynamic application placement

by Malgorzata Steinder and Eduard Ayguade

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2008

We present a technique that enables existing middleware to fairly manage mixed workloads: batch j... more We present a technique that enables existing middleware to fairly manage mixed workloads: batch jobs and transactional applications. The technique leverages a generic application placement controller, which dynamically allocates compute resources to application instances. The controller works towards a fairness goal while also trying to maximize individual workload performance. We use relative performance functions to drive the application placement controller. Such functions are derived from workload-specific performance modelsin the case of transactional workloads, we use queuing theory to build the performance model. For batch workloads, we evaluate a candidate placement by calculating long-term estimates of the completion times that are achievable with that placement according to a scheduling policy. In this paper, we propose a lowest relative performancwe first scheduling policy as a way to also achieve fair resource allocation among batch jobs. Our technique permits collocation of the workload types on the same physical hardware, and leverages control mechanisms such as suspension and migration to perform online system reconfiguration. In our experiments we demonstrate that our technique maximizes mixed workload performance while providing service differentiation based on high-level performance goals.

Managing SLAs of heterogeneous workloads using dynamic application placement

by Malgorzata Steinder and Eduard Ayguade

Proceedings of the 17th International Symposium on High Performance Distributed Computing 2008, HPDC'08, 2008

In this paper we address the problem of managing heterogeneous workloads in a virtualized data ce... more In this paper we address the problem of managing heterogeneous workloads in a virtualized data center. We consider two different workloads: transactional applications and long-running jobs. We present a technique that permits collocation of these workload types on the same physical hardware. Our technique dynamically modifies workload placement by leveraging control mechanisms such as suspension and migration, and strives to optimally trade off resource allocation among these workloads in spite of their differing characteristics and performance objectives. Our approach builds upon our previous work on dynamically placing transactional workloads. This paper extends our framework with the capability to manage long-running workloads. We achieve this goal by using utility functions, which permit us to compare the performance of various workloads, and which are used to drive allocation decisions. We demonstrate that our technique maximizes heterogeneous workload performance while providing service differentiation based on high-level performance goals.

Utility-based placement of dynamic web applications with fairness goals

by Malgorzata Steinder and Eduard Ayguade

NOMS 2008 - IEEE/IFIP Network Operations and Management Symposium: Pervasive Management for Ubiquitous Networks and Services, 2008

We study the problem of dynamic resource allocation to clustered Web applications. We extend appl... more We study the problem of dynamic resource allocation 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 allocation 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.

Batch job profiling and adaptive profile enforcement for virtualized environments

Proceedings of the 17th Euromicro International Conference on Parallel, Distributed and Network-Based Processing, PDP 2009, 2009

Data center management is driven by high-level performance goals, and it is the responsibility of... more Data center management is driven by high-level performance goals, and it is the responsibility of a management middleware to ensure that those goals are met using dynamic resource allocation. The performance delivered by the heterogeneous set of applications running in a virtualized enterprise data center must be predicted to make resource allocation decisions. For some of these applications, it is required to produce accurate profiles based on previous executions: that is the case of batch jobs. In this paper we propose a methodology to produce resource consumption profiles for batch applications running inside of virtual machines and a technique to enforce and adapt the profiles to actual execution conditions and application performance. For this purpose we have developed a testing prototype. The enforcement technique observes the fact that management middleware usually run in control cycles in which the system can be reconfigured, what imposes a tradeoff between the accuracy of the profiles and their applicability in real deployments. The novel contribution of this work is the study of the tradeoff between accuracy and applicability of workload profiles, what is a necessary step to enable existing management middleware with the performance prediction mechanisms required to perform effective dynamic resource allocation.

Characterization of workload and resource consumption for an online travel and booking site

IEEE International Symposium on Workload Characterization, IISWC'10, 2010

Online travel and ticket booking is one of the top E-Commerce industries. As they present a mix o... more Online travel and ticket booking is one of the top E-Commerce industries. As they present a mix of products: flights, hotels, tickets, restaurants, activities and vacational packages, they rely on a wide range of technologies to support them: Javascript, AJAX, XML, B2B Web services, Caching, Search Algorithms and Affiliation; resulting in a very rich and heterogeneous workload. Moreover, visits to travel sites present a great variability depending on time of the day, season, promotions, events, and linking; creating bursty traffic, making capacity planning a challenge. It is therefore of great importance to understand how users and crawlers interact on travel sites and their effect on server resources, for devising cost effective infrastructures and improving the Quality of Service for users.

Non-intrusive estimation of QoS degradation impact on e-commerce user satisfaction

Proceedings - 2011 IEEE International Symposium on Network Computing and Applications, NCA 2011, 2011

Abstract With the massification of high speed Internet access, recent industry consumer reports s... more

An Experimental Evaluation of the New OpenMP Tasking Model

Lecture Notes in Computer Science, 2008

Abstract. The OpenMP standard was conceived to parallelize dense array-based applications, and it... more Abstract. The OpenMP standard was conceived to parallelize dense array-based applications, and it has achieved much success with that. Recently, a novel tasking proposal to handle unstructured parallelism in OpenMP has been submitted to the OpenMP 3.0 Language Commit- tee. We tested its expressiveness and flexibility, using it to parallelize a number,of examples from a variety of different application areas.

Adaptive MapReduce Scheduling in Shared Environments

by Malgorzata Steinder and Eduard Ayguade

2014 14th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, 2014

ABSTRACT In this paper we present a MapReduce task scheduler for shared environments in which Map... more ABSTRACT In this paper we present a MapReduce task scheduler for shared environments in which MapReduce is executed along with other resource-consuming workloads, such as transactional applications. All workloads may potentially share the same data store, some of them consuming data for analytics purposes while others acting as data generators. This kind of scenario is becoming increasingly important in data centers where improved resource utilization can be achieved through workload consolidation, and is specially challenging due to the interaction between workloads of different nature that compete for limited resources. The proposed scheduler aims to improve resource utilization across machines while observing completion time goals. Unlike other MapReduce schedulers, our approach also takes into account the resource demands for non-MapReduce workloads, and assumes that the amount of resources made available to the MapReduce applications is variable over time. As shown in our experiments, our proposal improves the management of MapReduce jobs in the presence of variable resource availability, increasing the accuracy of the estimations made by the scheduler, thus improving completion time goals without an impact on the fairness of the scheduler.

Enabling Distributed Key-Value Stores with Low Latency-Impact Snapshot Support

2013 IEEE 12th International Symposium on Network Computing and Applications, 2013

ABSTRACT Current distributed key-value stores generally provide greater scalability at the expens... more ABSTRACT Current distributed key-value stores generally provide greater scalability at the expense of weaker consistency and isolation. However, additional isolation support is becoming increasingly important in the environments in which these stores are deployed, where different kinds of applications with different needs are executed, from transactional workloads to data analytics. While fully-fledged ACID support may not be feasible, it is still possible to take advantage of the design of these data stores, which often include the notion of multiversion concurrency control, to enable them with additional features at a much lower performance cost and maintaining its scalability and availability. In this paper we explore the effects that additional consistency guarantees and isolation capabilities may have on a state of the art key-value store: Apache Cassandra. We propose and implement a new multiversioned isolation level that provides stronger guarantees without compromising Cassandra&#39;s scalability and availability. As shown in our experiments, our version of Cassandra allows Snapshot Isolation-like transactions, preserving the overall performance and scalability of the system.

ALOJA: A systematic study of Hadoop deployment variables to enable automated characterization of cost-effectiveness

2014 IEEE International Conference on Big Data (Big Data), 2014

A Hybrid Web Server Architecture for Secure e-Business Web Applications

Lecture Notes in Computer Science, 2005

Nowadays the success of many e-commerce applications, such as on-line banking, depends on their r... more Nowadays the success of many e-commerce applications, such as on-line banking, depends on their reliability, robustness and security. Designing a web server architecture that keeps these properties under high loads is a challenging task because they are the opposite to performance. The industry standard way to provide security on web applications is the use the Secure Socket Layer (SSL) protocol to create a secure communication channel between the clients and the server. Traditionally, the use of data encryption has introduced a negative performance impact over web application servers because it is an extremely CPU consuming task, reducing the throughput achieved by the server as well as increasing its average response time. As far as the revenue obtained by a commercial web application is directly related to the amount of clients that complete business transactions, the performance of such secure applications becomes a mission critical objective for most companies. In this paper we evaluate a novel hybrid web server architecture (implemented over Tomcat 5.5) that combines the best aspects of the two most extended server architectures, the multithreaded and the event-driven, to provide an excellent trade-off between reliability, robustness, security and performance. The obtained results demonstrate the feasibility of the proposed hybrid architecture as well as the performance benefits that this model introduces for secure web applications, providing the same security level than the original Tomcat 5.5 and improved reliability, robustness and performance, according to both technical and business metrics.

Performance Management of Accelerated MapReduce Workloads in Heterogeneous Clusters

2010 39th International Conference on Parallel Processing, 2010

Next generation data centers will be composed of thousands of hybrid systems in an attempt to inc... more Next generation data centers will be composed of thousands of hybrid systems in an attempt to increase overall cluster performance and to minimize energy consumption. New programming models, such as MapReduce, specifically designed to make the most of very large infrastructures will be leveraged to develop massively distributed services. At the same time, data centers will bring an unprecedented degree of workload consolidation, hosting in the same infrastructure distributed services from many different users. In this paper we present our advancements in leveraging the Adaptive MapReduce Scheduler to meet user defined high level performance goals while transparently and efficiently exploiting the capabilities of hybrid systems. While the Adaptive Scheduler was already able to dynamically allocate resources to co-located MapReduce jobs based on their completion time goals, it was completely unaware of specific hardware capabilities. In our work we describe the changes introduced in the Adaptive Scheduler to enable it with hardware awareness and with the ability to co-schedule accelerable and non-accelerable jobs on the same heterogeneous MapReduce cluster, making the most of the underlying hybrid systems. The developed prototype is tested in a cluster of Cell/BE blades and relies on the use of accelerated and non-accelerated versions of the MapReduce tasks of different deployed applications to dynamically select the best version to run on each node. Decisions are made after workload composition and jobs' completion time goals. Results show that the augmented Adaptive Scheduler provides dynamic resource allocation across jobs, hardware affinity when possible, and is even able to spread jobs' tasks across accelerated and non-accelerated nodes in order to meet performance goals in extreme conditions. To our knowledge this is the first MapReduce scheduler and prototype that is able to manage high-level performance goals even in presence of hybrid systems and accelerable jobs.

Tailoring Resources: The Energy Efficient Consolidation Strategy Goes Beyond Virtualization

2008 International Conference on Autonomic Computing, 2008

Virtualization and consolidation are two complementary techniques widely adopted in a global stra... more Virtualization and consolidation are two complementary techniques widely adopted in a global strategy to reduce system management complexity. In this paper we show how two simple and well-known techniques can be combined to dramatically increase the energy efficiency of a virtualized and consolidated data center. This result is obtained by introducing a new approach to the consolidation strategy that allows an important reduction in the amount of active nodes required to process a web workload without degrading the offered service level. Furthermore, when the system eventually gets overloaded and no energy can be saved without loosing performance, we show how these techniques can still improve the overall value obtained from the workload. The two techniques are memory compression and request discrimination, and were separately studied and validated in a previous work to be now combined in a joint effort. Memory compression is used to convert CPU power into extra memory capacity to overcome system underutilization scenarios caused by memory constraints. Request discrimination is used to identify web clients according to the value they have to the system. We study the combined use of these two techniques by describing a simple but still representative scenario and also by considering the dramatic impact they would have for a real workload obtained from a top national travel website. Our results indicate that an important improvement can be achieved by deciding not only how resources are allocated, but also how they are used. Moreover, we believe that this serves as an illustrative example of a new way of management: tailoring the resources to meet high level energy efficiency goals.

Session-Based Adaptive Overload Control for Secure Dynamic Web Applications

2005 International Conference on Parallel Processing (ICPP'05), 2005

As dynamic web content and security capabilities are becoming popular in current web sites, the p... more As dynamic web content and security capabilities are becoming popular in current web sites, the performance demand on application servers that host the sites is increasing, leading sometimes these servers to overload. As a result, response times may grow to unacceptable levels and the server may saturate or even crash. In this paper we present a session-based adaptive overload control mechanism based on SSL (Secure Socket Layer) connections differentiation and admission control. The SSL connections differentiation is a key factor because the cost of establishing a new SSL connection is much greater than establishing a resumed SSL connection (it reuses an existing SSL session on server). Considering this big difference, we have implemented an admission control algorithm that prioritizes the resumed SSL connections to maximize performance on session-based environments and limits dynamically the number of new SSL connections accepted depending on the available resources and the current number of connections in the system to avoid server overload. In order to allow the differentiation of resumed SSL connections from new SSL connections we propose a possible extension of the Java Secure Sockets Extension (JSSE) API. Our evaluation on Tomcat server demonstrates the benefit of our proposal for preventing server overload.