3,702 research outputs found
Workflow Partitioning and Deployment on the Cloud using Orchestra
Orchestrating service-oriented workflows is typically based on a design model
that routes both data and control through a single point - the centralised
workflow engine. This causes scalability problems that include the unnecessary
consumption of the network bandwidth, high latency in transmitting data between
the services, and performance bottlenecks. These problems are highly prominent
when orchestrating workflows that are composed from services dispersed across
distant geographical locations. This paper presents a novel workflow
partitioning approach, which attempts to improve the scalability of
orchestrating large-scale workflows. It permits the workflow computation to be
moved towards the services providing the data in order to garner optimal
performance results. This is achieved by decomposing the workflow into smaller
sub workflows for parallel execution, and determining the most appropriate
network locations to which these sub workflows are transmitted and subsequently
executed. This paper demonstrates the efficiency of our approach using a set of
experimental workflows that are orchestrated over Amazon EC2 and across several
geographic network regions.Comment: To appear in Proceedings of the IEEE/ACM 7th International Conference
on Utility and Cloud Computing (UCC 2014
EbbRT: a framework for building per-application library operating systems
Efficient use of high speed hardware requires operating system components be customized to the application work- load. Our general purpose operating systems are ill-suited for this task. We present EbbRT, a framework for constructing per-application library operating systems for cloud applications. The primary objective of EbbRT is to enable high-performance in a tractable and maintainable fashion. This paper describes the design and implementation of EbbRT, and evaluates its ability to improve the performance of common cloud applications. The evaluation of the EbbRT prototype demonstrates memcached, run within a VM, can outperform memcached run on an unvirtualized Linux. The prototype evaluation also demonstrates an 14% performance improvement of a V8 JavaScript engine benchmark, and a node.js webserver that achieves a 50% reduction in 99th percentile latency compared to it run on Linux
EbbRT: a customizable operating system for cloud applications
Efficient use of hardware requires operating system components be customized to the application workload. Our general purpose operating systems are ill-suited for this task. We present Genesis, a new operating system that enables per-application customizations for cloud applications. Genesis achieves this through a novel heterogeneous distributed structure, a partitioned object model, and an event-driven execution environment. This paper describes the design and prototype implementation of Genesis, and evaluates its ability to improve the performance of common cloud applications. The evaluation of the Genesis prototype demonstrates memcached, run within a VM, can outperform memcached run on an unvirtualized Linux. The prototype evaluation also demonstrates an 14% performance improvement of a V8 JavaScript engine benchmark, and a node.js webserver that achieves a 50% reduction in 99th percentile latency compared to it run on Linux
funcX: A Federated Function Serving Fabric for Science
Exploding data volumes and velocities, new computational methods and
platforms, and ubiquitous connectivity demand new approaches to computation in
the sciences. These new approaches must enable computation to be mobile, so
that, for example, it can occur near data, be triggered by events (e.g.,
arrival of new data), be offloaded to specialized accelerators, or run remotely
where resources are available. They also require new design approaches in which
monolithic applications can be decomposed into smaller components, that may in
turn be executed separately and on the most suitable resources. To address
these needs we present funcX---a distributed function as a service (FaaS)
platform that enables flexible, scalable, and high performance remote function
execution. funcX's endpoint software can transform existing clouds, clusters,
and supercomputers into function serving systems, while funcX's cloud-hosted
service provides transparent, secure, and reliable function execution across a
federated ecosystem of endpoints. We motivate the need for funcX with several
scientific case studies, present our prototype design and implementation, show
optimizations that deliver throughput in excess of 1 million functions per
second, and demonstrate, via experiments on two supercomputers, that funcX can
scale to more than more than 130000 concurrent workers.Comment: Accepted to ACM Symposium on High-Performance Parallel and
Distributed Computing (HPDC 2020). arXiv admin note: substantial text overlap
with arXiv:1908.0490
A deliberative model for self-adaptation middleware using architectural dependency
A crucial prerequisite to externalized adaptation is an understanding of how components are interconnected, or more particularly how and why they depend on one another. Such dependencies can be used to provide an architectural model, which provides a reference point for externalized adaptation. In this paper, it is described how dependencies are used as a basis to systems' self-understanding and subsequent architectural reconfigurations. The approach is based on the combination of: instrumentation services, a dependency meta-model and a system controller. In particular, the latter uses self-healing repair rules (or conflict resolution strategies), based on extensible beliefs, desires and intention (EBDI) model, to reflect reconfiguration changes back to a target application under examination
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