Remote evaluation

Stamos, James W.; Gifford, David K.

doi:10.1145/88616.88631

Cited by 155 publications

(67 citation statements)

References 21 publications

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“…In this paper we proposed a mobile computing middleware-framework for handheld devices which is based on the combination of reflection [6], remote evaluation [7] and code mobility [8]. We have implemented a prototype application [9] along with the framework libraries in order to demonstrate the feasibility of the approach.…”

Section: Resultsmentioning

confidence: 99%

“…We propose that a mobile computing system for hand-held devices must be based on the combination of reflection [6], remote evaluation [7] and code mobility [8]. The remote evaluation paradigm not only enables the clients to out-source resource intensive tasks, but also allows more client-side applications (because of their smaller footprint).…”

Section: Introductionmentioning

confidence: 99%

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Framework of an Application-Aware Adaptation Scheme for Disconnected Operations

Kalim

Jameel

Ali

et al. 2009

Active and Programmable Networks

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Abstract. The complex software development scenarios for mobile/ hand-held devices operating in wireless environments require adaptation to the variations in the environment (such as fluctuating bandwidth). This translates to maintenance of service availability in preferably all circumstances. In this paper we propose that a mobile computing system (for hand-held, wireless devices) must be based on the combination of reflection, remote evaluation and code mobility mechanisms such that the communication framework 1 allows developers to design disconnectionaware applications which maintain service availability in case of varying circumstances by automatically redeploying essential components to appropriate locations. This not only allows the application to continue executing in varying conditions, but also in entirely disconnected modes.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Framework of an Application-Aware Adaptation Scheme for Disconnected Operations

Kalim

Jameel

Ali

et al. 2009

Active and Programmable Networks

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“…Rather than streaming large data sets to the clients, the situation is reversed, and clients transfer small pieces of code to the storage nodes, as an instance of remote evaluation [57]. Specifically, a visitor function is transferred and evaluated in parallel on each storage node.…”

Section: Key Design Choicesmentioning

confidence: 99%

Cogset: a high performance MapReduce engine

Valvåg

Johansen

Kvalnes

2012

Concurrency and Computation

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MapReduce has become a widely employed programming model for large-scale data-intensive computations. Traditional MapReduce engines employ dynamic routing of data as a core mechanism for fault tolerance and load balancing. An alternative mechanism is static routing, which reduces the need to store temporary copies of intermediate data, but requires a tighter coupling between the components for storage and processing. The initial intuition motivating our work is that reading and writing less temporary data could improve performance, while the tight coupling of storage and processing could be leveraged to improve data locality.We therefore conjecture that a high-performance MapReduce engine can be based on static routing, while preserving the non-functional properties associated with traditional engines. To investigate this thesis, we design, implement, and experiment with Cogset, a distributed MapReduce engine that deviates considerably from the traditional design.We evaluate the performance of Cogset by comparing it to a widely used traditional MapReduce engine using a previously established benchmark. The results confirm our thesis that a high-performance MapReduce engine can be based on static routing, although analysis indicates that the reasons for Cogset's performance improvements are more subtle than expected. Through our work we develop a better understanding of static routing, its benefits and limitations, and its ramifications for a MapReduce engine.A secondary goal of our work is to explore how higher-level abstractions that are commonly built on top of MapReduce will interact with an execution engine based on static routing. Cogset is therefore designed with a generic, low-level core interface, upon which MapReduce is implemented as a relatively thin layer, as one of several supported programming interfaces.At its core, Cogset provides a few fundamental mechanisms for reliable and distributed storage of data, and parallel processing of statically partitioned data. While this dissertation mainly focuses on how these capabilities are leveraged to implement a distributed MapReduce engine, we also demonstrate how two other higher-level abstractions were built on top of Cogset. These may serve as alternative access points for data-intensive applications, and illustrate how some of the lessons learned from Cogset can be applicable in a broader context.

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“…Remote evaluation (REV) [16] focused on remote execution as an optimization for RPC. REV's execution model is based on a procedure call, and the implementation is tightly integrated with the language and compiler.…”

Section: Placing Code "In" the Networkmentioning

confidence: 99%

Java active extensions: Scalable middleware for performance-isolated remote execution

Newhouse

Pasquale

2005

Computer Communications

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We present the design and implementation of a highly scalable and easily deployed middleware system that provides performance-isolated execution environments for client and server application functionality. The Java Active Extensions system allows clients or servers to "extend" their operation by hosting portions of their codes, called extensions, at network vantage points for improved performance and reliability, and by providing them with qualities of service in the form of rate-based resource reservations. This is especially useful for wireless resource-limited clients, which can remotely locate filters, caches, monitors, buffers, etc., to act on their behalf and improve interactions with servers. Servers also benefit by moving some of their services close to their clients (e.g., those near a common base station) to reduce latency and improve bandwidth. In both cases, the client's or server's extended functionality executes with a specified fraction of the (remote) system's processor. The system design is based on a scalable distributed architecture that allows for incremental hardware growth, and is highly deployable as it runs entirely at user level, including its rate-based scheduling system.

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Remote evaluation

Cited by 155 publications

References 21 publications

Framework of an Application-Aware Adaptation Scheme for Disconnected Operations

Framework of an Application-Aware Adaptation Scheme for Disconnected Operations

Cogset: a high performance MapReduce engine

Java active extensions: Scalable middleware for performance-isolated remote execution

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