A framework for (re)deploying components in distributed real-time and embedded systems

Shankaran, N.; Balasubramanian, Jaiganesh; Schmidt, Douglas C.; Biswas, Gautam; Lardieri, Patrick; Mulholland, E.; Damiano, Thomas

doi:10.1145/1141277.1141446

Cited by 11 publications

(7 citation statements)

References 4 publications

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“…Examples of other middleware that support some aspects of these capabilities include the Resource Allocation and Control Engine (RACE) [19] and Swap-CIAO [20] for DRE systems, as well as WS-DIAMOND [21] for self-healing web services.…”

Section: Planned Enhancements To Le-dancementioning

confidence: 99%

Efficient and deterministic application deployment in component-based enterprise distributed real-time and embedded systems

Otte

Gokhale

Schmidt

2013

Information and Software Technology

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Context: Component-based middleware, such as the Lightweight COR-BA Component Model, is increasingly used to implement enterprise distributed real-time and embedded (DRE) systems. In addition to supporting the quality-of-service (QoS) requirements of individual DRE systems, component technologies must also support bounded latencies when effecting deployment changes to DRE systems in response to changing environmental conditions and operational requirements.Objective: The goals of this paper are to (1) study sources of inefficiencies and non-deterministic performance in deployment capabilities for DRE systems and (2) devise solutions to overcome these performance problems.Method: The paper makes two contributions to the study of the deployment and configuration of distributed component based applications. First, we analyze how conventional implementations of the OMG's Deployment and Configuration (D&C) specification for component-based systems can significantly degrade deployment latencies. Second, we describe architectural changes and performance optimizations implemented within the LocalityEnhanced Deployment and Configuration Engine (LE-DAnCE) implementation of the D&C specification to obtain efficient and deterministic deployment latencies.Results: We analyze the performance of LE-DAnCE in the context of component deployments on 10 nodes for a representative DRE system consisting of 1,000 components and in a cluster environment with up to 100 nodes. Our results show LE-DAnCE's optimizations provide a bounded dePreprint submitted to Information and Software Technology July 27, 2012 ployment latency of less than 2 seconds for the 1,000 component scenario with just a 4 percent jitter. Conclusion:The improvements contained in the LE-DAnCE infrastructure provide an efficient and scaleable standards-based deployment system for component-based enterprise DRE systems. In particular, deployment time parallelism can improve deployment latency significantly, both during pre-deployment analysis of the deployment plan and during the process of installing and activating components.

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Section: Planned Enhancements To Le-dancementioning

confidence: 99%

Efficient and deterministic application deployment in component-based enterprise distributed real-time and embedded systems

Otte

Gokhale

Schmidt

2013

Information and Software Technology

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“…In the tool category, ArcheOpterix should be compared with thye tools DeSi [27], ArchE [8], DAnCE [7] and the RACE framework [32]. The DeSi tool, developed by MikicRakic et al [27] presents an tailorable environment for specification, manipulation, visualization and attribute evaluation of deployment architectures.…”

Section: Related Workmentioning

confidence: 99%

“…To allow the support of other quality domains ArchE provides a well defined interface to also generate reasoning frameworks for other quality attributes [8]. The RACE framework presented by Shankaran et al [32] and the DAnCE implementation by Deng et al [7] addresses the needs of deployment decisions at real-time. Both the above approaches have been well succeeded in industry, but limitations exist for applicability for static architecture optimization domain such as they require implementations of specific system models and lack of support for complex model analysis.…”

Section: Related Workmentioning

confidence: 99%

ArcheOpterix: An extendable tool for architecture optimization of AADL models

Aleti

Björnander

Grunske

et al. 2009

2009 ICSE Workshop on Model-Based Methodologies for Pervasive and Embedded Software

139

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“…Bulls-Eye does not enforce any resource partitioning itself. RACE [26] is the RT-Corba component that implements the resource allocation and monitoring algorithms. Tasks are mapped to nodes in the distributed system, and if the performance monitoring is not satisfactory, the allocation algorithm is tuned or replaced by another one.…”

Section: Related Workmentioning

confidence: 99%

Weighted fair share scheduling for loosely controlled concurrent event systems

Rooney

Garcés-Erice

Dragicevic

et al. 2010

SOCA

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In asynchronous event systems, the production of an event is decoupled from its consumption via an event queue. The loose coupling of such systems allows great flexibility as to where and when within the system the event handler of a given event is actually executed, allowing them to scale with increasing number of processors on a given node or across multiple nodes in a distributed system. Although this flexibility is useful in heterogeneous distributed systems, such as SOA, it may appear not to be well suited for real-time systems, which require an upper bound on how long an event can remain unhandled in a queue. However, we show how the weighted fair scheduling algorithms developed for QoS (quality of service) routing can be adapted to event queues to bound the delay between production and consumption. We achieve this, despite the fact that the underlying execution environment is only weakly controlled, through the use of predictive techniques on a calibrated model of the event system. Our choice of algorithms and data structures is driven in part by the highly concurrent nature of the system. We show how a weighted fair scheduler can be built on a lockfree concurrent priority queue. We analyze the performance of various such queues proposed in the literature and show that a very simple linear quantizing queue yields the best performance.

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A framework for (re)deploying components in distributed real-time and embedded systems

Cited by 11 publications

References 4 publications

Efficient and deterministic application deployment in component-based enterprise distributed real-time and embedded systems

Efficient and deterministic application deployment in component-based enterprise distributed real-time and embedded systems

ArcheOpterix: An extendable tool for architecture optimization of AADL models

Weighted fair share scheduling for loosely controlled concurrent event systems

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