Portable Support for Transparent Thread Migration in Java

Truyen, Eddy; Robben, Bert; Vanhaute, Bart; Coninx, Tim; Joosen, Wouter; Verbaeten, Pierre

doi:10.1007/978-3-540-45347-5_4

Cited by 66 publications

(49 citation statements)

References 8 publications

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“…RELATED WORK MAG [3], Brakes [18] and JavaGoX [19] implement Java thread migration at application level. These systems are designed as mobile agent systems.…”

Section: Migration For Resource Utilizationmentioning

confidence: 99%

“…Computation migration can be implemented at different levels: application level [7,8], middleware level [9,10], Java virtual machine level [11,12] and OS level [13]. The motivation for implementing migration feature at the application level is the portability.…”

Section: Introductionmentioning

confidence: 99%

“…These added codes are mainly used for status-polling, state-capturing, state-restoring, and facilitating the communication among migrating nodes during migration. Several systems [16,17,18,19] follow this preprocessing approach, either working with source code [16,17] or bytecode [18,19].…”

Section: Introductionmentioning

confidence: 99%

“…In some systems [18], the preprocessor inserts a status-polling block after each method invocation. The status-polling is to check whether the execution is in the capturing mode (i.e., the process has decided to migrate and it is now capturing the stack content.)…”

Section: Introductionmentioning

confidence: 99%

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Lightweight Application-Level Task Migration for Mobile Cloud Computing

K.K.

Wang

2012

2012 IEEE 26th International Conference on Advanced Information Networking and Applications

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Abstract-Mobile cloud computing allows mobile applications to use the enormous resources in the clouds. In order to seamlessly utilize the resources, it is common to migrate computation among mobile nodes and cloud nodes. Therefore, a highly portable and transparent migration approach is needed. In terms of portability, application-level migration with code instrumentation is the most portable approach. However, in the existing literature, this approach imposes significant runtime overhead, even when no migration takes place. Most of these works are for mobile agents, and migrations are to be invoked by the programs. Migration points are also restricted to certain locations where migration status is being polled. In this paper, we propose a Java bytecode transformation technique for realizing task migration without imposing significant overhead on normal execution. Asynchronous migration technique is used to allow migrations to take place virtually anywhere in the user codes, and the proposed Twin Method Hierarchy minimizes the overhead resulting from state-restoration codes in normal execution. We have implemented our approach in our middleware. The results show that our approach can allow lightweight computation migration at application level, achieve considerable speedups and utilize the cloud resources from mobile devices.

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“…RELATED WORK MAG [3], Brakes [18] and JavaGoX [19] implement Java thread migration at application level. These systems are designed as mobile agent systems.…”

Section: Migration For Resource Utilizationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Lightweight Application-Level Task Migration for Mobile Cloud Computing

K.K.

Wang

2012

2012 IEEE 26th International Conference on Advanced Information Networking and Applications

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“…The problem with strong mobility is that it is typically complex and costly, especially when agent activity is based on threads (e.g. see work on Java thread migration in [15]). …”

Section: Transparency To Mobilitymentioning

confidence: 99%

Programming and Executing Telecommunication Service Logic with Moorea Reactive Mobile Agents

Dillenseger

Tagant

Hazard

2002

Lecture Notes in Computer Science

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High‐Performance Computing on Clusters: The Distributed JVM Approach

Zhu

Wang

Fang

et al. 2005

High‐Performance Computing

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Machine (DJVM) is a cluster-wide virtual machine that supports parallel execution of a multithreaded Java application on clusters, as if it was executed on a single machine but with improved computation power. The DJVM hides the physical boundaries between the cluster nodes and allows parallelly executed Java threads to access all cluster resources through a unified interface. It is a more user-friendly parallel environment than many other existing parallel languages [8], or libraries for parallel programming such as MPI [13], CORBA [16], and Java RMI [7]. The DJVM research is valuable for high-performance computing as Java has become the dominant language for building the server-side applications, such as enterprise information systems, Web services, and large-scale Grid computing systems, due to its platform independency and built-in multithreading support at language level. This chapter addresses the realization of a distributed Java virtual machine, named JESSICA2, on clusters. Section 1.1 describes Java, Java Virtual Machine, and the main programming paradigms using Java for high-performance computing. We then focus our study on the newly emerging distributed JVM research in Section 1.2. In Section 1.3, we introduce our JESSICA2 Distributed JVM. Section 1.4 gives the performance analysis of JESSICA2. Related work is given in Section 1.5. Section 1.6 concludes this chapter. † This research is supported by Hong Kong RGC Grant HKU-7030/01E and HKU Large Equipment Grant 01021001. i BACKGROUND iii app.java app.class Java compiler Java Virtual Machine Method Area Heap PC PC obj ref Object Thread Scheduler Class Loader Execution Engine obj ref Object Stack Stack

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Portable Support for Transparent Thread Migration in Java

Cited by 66 publications

References 8 publications

Lightweight Application-Level Task Migration for Mobile Cloud Computing

Lightweight Application-Level Task Migration for Mobile Cloud Computing

Programming and Executing Telecommunication Service Logic with Moorea Reactive Mobile Agents

High‐Performance Computing on Clusters: The Distributed JVM Approach

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