Capacity Sharing and Stealing in Dynamic Server-based Real-Time Systems

Nogueira, Luís; Pinho, Luís Miguel

doi:10.1109/ipdps.2007.370349

Cited by 9 publications

(19 citation statements)

References 18 publications

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“…The Capacity Sharing and Stealing (CSS) scheduler [9] proposes to handle overloads with additional capacity that is available from two sources: (i) by reclaiming unused allocated capacity when jobs complete in less than their budgeted execution time; and (ii) by stealing allocated capacities to nonisolated servers used to schedule sporadic best-effort jobs. The integration of the CSS scheduler into the CooperatES framework is discussed in detail in [54].…”

Section: Related Workmentioning

confidence: 99%

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Time-bounded distributed QoS-aware service configuration in heterogeneous cooperative environments

Nogueira

Pinho

2009

Journal of Parallel and Distributed Computing

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The scarcity and diversity of resources among the devices of heterogeneous computing environments may affect their ability to execute services within the users' requested Quality of Service levels, particularly in open real-time environments where the characteristics of the computational load cannot always be predicted in advance but, nevertheless, response to events still has to be provided within precise timing constraints in order to guarantee a desired level of performance. This paper proposes a cooperative service execution, allowing resource constrained devices to collectively execute services with their more powerful neighbours, meeting non-functional requirements that otherwise would not be met by an individual execution. Nodes dynamically group themselves into a new coalition, allocating resources to each new service and establishing an initial service configuration which maximises the satisfaction of the QoS constraints associated with the new service and minimises the impact on the global QoS caused by the new service's arrival.However, the increased complexity of open real-time environments may prevent the possibility of computing optimal local and global resource allocations within a useful and bounded time. As such, the QoS optimisation problem is here reformulated as a heuristic-based anytime optimisation problem that can be interrupted at any time and quickly respond to environmental changes. Extensive simulations demonstrate that the proposed anytime algorithms are able to quickly find a good initial service solution and effectively optimise the rate at which the quality of the current solution improves at each iteration of the algorithms, with an overhead that can be considered negligible when compared against the introduced benefits. AbstractThe scarcity and diversity of resources among the devices of heterogeneous computing environments may affect their ability to execute services within the users' requested Quality of Service levels, particularly in open real-time environments where the characteristics of the computational load cannot always be predicted in advance but, nevertheless, response to events still has to be provided within precise timing constraints in order to guarantee a desired level of performance. This paper proposes a cooperative service execution, allowing resource constrained devices to collectively execute services with their more powerful neighbours, meeting non-functional requirements that otherwise would not be met by an individual execution. Nodes dynamically group themselves into a new coalition, allocating resources to each new service and establishing an initial service configuration which maximises the satisfaction of the QoS constraints associated with the new service and minimises the impact on the global QoS caused by the new service's arrival.However, the increased complexity of open real-time environments may prevent the possibility of computing optimal local and global resource allocations within a useful and bounded time. As such, the QoS optimisat...

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Section: Related Workmentioning

confidence: 99%

“…This paper reformulates the distributed resource allocation problem as an anytime optimisation problem in which there are a range of acceptable solutions with varying qualities, adapting the distributed service allocation is to the available deliberation time that is dynamically imposed as a result of emerging environmental conditions [9].…”

Section: Introductionmentioning

confidence: 99%

Time-bounded distributed QoS-aware service configuration in heterogeneous cooperative environments

Nogueira

Pinho

2009

Journal of Parallel and Distributed Computing

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“…This is strictly related to the capacity of controlling the incoming workload, preventing abrupt and unpredictable degradations and achieving isolation among services, providing service guarantees to critical applications [1]. The Capacity Sharing and Stealing (CSS) scheduler [15] extends the resource reservation approach by proposing to handle overloads with additional capacity that is available from two sources: (i) by reclaiming unused allocated capacity when jobs complete in less than their budgeted execution time; and (ii) by stealing allocated capacities to non-isolated servers used to schedule sporadic besteffort jobs. The integration of the CSS scheduler into the CooperatES framework is discussed in detail in [12].…”

Section: The Cooperates Frameworkmentioning

confidence: 99%

“…The CooperatES (Cooperative Embedded Systems) framework [11,14,15] facilitates the cooperation among neighbours when a service request cannot be satisfyingly answered by a single node. Nodes dynamically group themselves into a new coalition, allocating resources to each new service and establishing an initial Service Level Agreement (SLA) that maximises the satisfaction of the QoS constraints associated with the new service and minimises the impact on the global QoS caused by the new service's arrival [11,14].…”

Section: Introductionmentioning

confidence: 99%

Dynamic QoS adaptation of inter-dependent task sets in cooperative embedded systems

Nogueira¹,

Pinho²

2008

Proceedings of the 2nd International ICST Conference on Autonomic Computing and Communication Systems

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Due to the growing complexity and dynamism of many embedded application domains (including consumer electronics, robotics, automotive and telecommunications), it is increasingly difficult to react to load variations and adapt the system's performance in a controlled fashion within an useful and bounded time. This is particularly noticeable when intending to benefit from the full potential of an open distributed cooperating environment, where service characteristics are not known beforehand and tasks may exhibit unrestricted QoS inter-dependencies. This paper proposes a novel anytime adaptive QoS control policy in which the online search for the best set of QoS levels is combined with each user's personal preferences on their services' adaptation behaviour. Extensive simulations demonstrate that the proposed anytime algorithms are able to quickly find a good initial solution and effectively optimise the rate at which the quality of the current solution improves as the algorithms are given moretime to run, with a minimum overhead when compared against their traditional versions.

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“…Based upon a careful study of the ways in which unused reserved capacities can be more efficiently used to meet deadlines of tasks whose resource usage exceeds their reservations, our previous work [16] proposed the coexistence of the traditional isolated servers with a novel non-isolated type of servers, combining an efficient reclamation of residual capacities with a controlled isolation loss. The goal of the Capacity Sharing and Stealing (CSS) scheduler is to reduce the mean tardiness of periodic guaranteed jobs by handling overloads with additional capacity available from two sources: (i) by reclaiming unused allocated capacity when jobs complete in less than their budgeted execution time; and (ii) by stealing allocated capacities from inactive non-isolated servers used to schedule aperiodic best-effort jobs.…”

Section: Introductionmentioning

confidence: 99%

A capacity sharing and stealing strategy for open real-time systems

Nogueira

Pinho

2010

Journal of Systems Architecture

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,5,. 9$,73,3/$90,3$97,90147 503#0,920$89028 AbstractThis paper focuses on the scheduling of tasks with hard and soft real-time constraints in open and dynamic real-time systems. It starts by presenting a capacity sharing and stealing (CSS) strategy that supports the coexistence of guaranteed and non-guaranteed bandwidth servers to efficiently handle soft-tasks' overloads by making additional capacity available from two sources: (i) reclaiming unused reserved capacity when jobs complete in less than their budgeted execution time and (ii) stealing reserved capacity from inactive non-isolated servers used to schedule best-effort jobs.CSS is then combined with the concept of bandwidth inheritance to efficiently exchange reserved bandwidth among sets of inter-dependent tasks which share resources and exhibit precedence constraints, assuming no previous information on critical sections and computation times is available. The proposed Capacity Exchange Protocol (CXP) has a better performance and a lower overhead when compared against other available solutions and introduces a novel approach to integrate precedence constraints among tasks of open real-time systems.

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Capacity Sharing and Stealing in Dynamic Server-based Real-Time Systems

Abstract: Abstract

Cited by 9 publications

References 18 publications

Time-bounded distributed QoS-aware service configuration in heterogeneous cooperative environments

Time-bounded distributed QoS-aware service configuration in heterogeneous cooperative environments

Dynamic QoS adaptation of inter-dependent task sets in cooperative embedded systems

A capacity sharing and stealing strategy for open real-time systems

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