Expressing meaningful processing requirements among heterogeneous nodes in an active network

Galtier, Virginie; Mills, Kevin L.; Carlinet, Yannick; Leigh, Stefan D.; Rukhin, Andrew L.

doi:10.1145/350391.350398

Cited by 16 publications

(6 citation statements)

References 25 publications

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“…In terms of processing performance, it is difficult to compare different system implementations [15]. Enforcing resource reservations for processing is further complicated by the fact that computation that is terminated due to excessive resource usage may leave the system (or at least the data service for one particular information transfer) in an inconsistent state.…”

Section: B Data Servicesmentioning

confidence: 99%

Service-Centric End-to-End Abstractions in Next-Generation Networks

Wolf

2006

Proceedings of 15th International Conference on Computer Communications and Networks

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Next-generation network architectures will be governed by the need for flexibility. Heterogeneous end-systems, novel communication abstractions, and security and manageability challenges will require networks to provide a broad range of services that go beyond the simple store-and-forward capabilities of today's Internet. This paper introduces new abstractions for information transfer and data services in the network, which overcome the constraints of the end-to-end argument that has dominated current network designs. The explicit separation of communication and processing allows the composition of a variety of information transfer patterns that expand the capabilities of the network to meet its next-generation challenges. We discuss implementation issues that arise in this network architecture and present several examples of how applications can utilize the proposed abstractions. This present a first step towards a unified view of the convergence of networking, processing, and their distributed applications.

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Section: B Data Servicesmentioning

confidence: 99%

Service-Centric End-to-End Abstractions in Next-Generation Networks

Wolf

2006

Proceedings of 15th International Conference on Computer Communications and Networks

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“…This is done to simplify the description of the scheduling algorithm and its analysis. In a realistic network, processing cost should be translated to processor cycles per second and then adapted to the partic-ular router system, where the packets get processed, as described in [11].…”

Section: Measurementsmentioning

confidence: 99%

Predictive scheduling of network processors

2003

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To provide flexibility in deploying new protocols and services, general-purpose processing engines are being placed in the datapath of routers. Such network processors (NPs) are typically simple RISC multiprocessors that perform forwarding and custom application processing of packets. The inherent unpredictability of execution time of arbitrary instruction code poses a significant challenge in providing service guarantees for data flows that compete for such processing resources in the network. However, we show that network processing workloads are highly regular and predictable, which can be exploited for scheduling purposes. We present two such predictive processor scheduling algorithms that aim at providing service guarantees as well as improving the performance of the NP by increasing the instruction data locality. Simulation results show that these algorithms provide significantly better performance than processor scheduling algorithms that do not take packet processing times into consideration.

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“…Fourth, we outline an experiment where we used AVNMP to predict resource consumption by an active audio application. Our results suggest that adaptive CPU models [3], which accommodate variations in node capabilities, can improve the accuracy of AVNMP predictions, and reduce prediction overhead. Fifth, we suggest some additional applications for AVNMP, and similar prediction systems.…”

Section: Introductionmentioning

confidence: 81%

“…These problems motivated us to investigate adaptive models to represent the CPU use of active applications in a form that can be scaled among heterogeneous nodes [3]. We suspected that such adaptive models might improve the ability of AVNMP to predict CPU usage in heterogeneous active networks, while also reducing the number of simulation rollbacks.…”

Section: Predicting Cpu Usagementioning

confidence: 99%

“…Each event identifies the previous and current system call, and includes the amount of CPU time used in the current call, as well as the CPU time used in the execution environment between the two calls. Elsewhere, we explain how this execution trace can be used to model CPU-time use as a function of application behavior, specifically transitions between system calls and the execution environment [3].…”

Section: As Shown Inmentioning

confidence: 99%

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Predicting resource demand in heterogeneous active networks

Galtier

Mills²,

Carlinet³

et al.

2001 MILCOM Proceedings Communications for Network-Centric Operations: Creating the Information Force (Cat. No.01CH37277)

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Recent research, such as the Active Virtual Network Management Prediction (AVNMP) system, aims to use simulation models running ahead of real time to predict resource demand among network nodes. If accurate, such predictions can be used to allocate network capacity and to estimate quality of service. Future deployment of active-network technology promises to complicate prediction algorithms because each "active" message can convey its own processing logic, which introduces variable demand for processor (CPU) cycles. This paper describes a means to augment AVNMP, which predicts message load among active-network nodes, with adaptive models that can predict the CPU time required for each "active" message at any activenetwork node. Typical CPU models cannot adapt to heterogeneity among nodes. This paper shows improvement in AVNMP performance when adaptive CPU models replace more traditional non-adaptive CPU models. Incorporating adaptive CPU models can enable AVNMP to predict active-network resource usage farther into the future, and lowers prediction overhead. INTRODUCTIONGrowing availability of processing power and bandwidth in communication networks encourages innovative approaches to network management. One specific innovative idea envisions injecting simulation models into network nodes, and then running those models in parallel with the operational network, but ahead in time, in order to predict traffic and resource use. If the models predict accurately, then network management systems can better allocate capacity in anticipation of varying demands and network operators can better estimate the quality of service (QoS) that customers can expect. This paper describes one approach, the Active Virtual Network Management Prediction (AVNMP) system [1], which aims to predict network traffic. AVNMP uses active-network technology [2] to inject simulation models into network nodes, and to run those models concurrently with corresponding applications. AVNMP then compares estimated performance against measured

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Expressing meaningful processing requirements among heterogeneous nodes in an active network

Cited by 16 publications

References 25 publications

Service-Centric End-to-End Abstractions in Next-Generation Networks

Service-Centric End-to-End Abstractions in Next-Generation Networks

Predictive scheduling of network processors

Predicting resource demand in heterogeneous active networks

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