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View all- Tay YZong XHe X(2013)An equation-based Heap Sizing RulePerformance Evaluation10.1016/j.peva.2013.05.00970:11(948-964)Online publication date: 1-Nov-2013
Shared heap management for memory-limited java virtual machines
Authors: 
Yoonseo Choi, Hwansoo HanAuthors Info & Claims
Yoonseo Choi, Hwansoo HanAuthors Info & ClaimsArticle No.: 13, Pages 1 - 32
Abstract
One scarce resource in embedded systems is memory. Multitasking makes the lack of memory problem even worse. Most current embedded systems, which do not provide virtual memory, simply divide physical memory and evenly assign contiguous memory chunks to multiple applications. Such simple memory management can frequently cause the lack of available memory for some applications, while others are not using the full amount of assigned memory. To overcome inefficiency in current memory management, we present an efficient heap management scheme that allows multiple applications to share heap space. To reduce overall heap memory usage, applications adaptively acquire subheaps out of shared pool of memory and release surplus subheaps to shared pool. As a result, applications see noncontiguous multiple subheaps as a heap in their address space. We target Java applications to implement our heap-sharing scheme in the KVM from Sun Microsystems. To protect fragmented heap space with a limited number of regions in memory protection unit (MPU), we maintain only a limited number of subheaps. We experimentally evaluate our heap management scheme with J2ME MIDP applications. Our static and dynamic schemes reduce heap memory usage, on average, by 30 and 27%, respectively. For both schemes, overheads are kept low. The execution times in our schemes are increased only by 0.01% for static scheme and 0.35% for dynamic scheme, on average.
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- Shared heap management for memory-limited java virtual machines
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Reviews
Andreas E. Schwald
Multitasking in embedded systems without virtual memory is often done in a very simplistic way: by allocation of a fixed storage segment to a task. A more flexible strategy of heap allocation in a shared storage pool has to deal with the management of multiple fragmented heap areas, and the protection of these areas from undesirable accesses of other programs or tasks. The authors propose a two-level memory management scheme for "sharing and protecting fragmented heaps" to "reduce a considerable amount of memory footprint," with "almost no increase of execution time by carefully triggering garbage collection and live object compaction." The scheme relies on the capabilities of ARM processors (Sun Microsystems). The management of fragmented heap areas uses an adapted form of Kernel-based Virtual Machine (KVM) (portable Java Virtual Machine (JVM) for small, resource-constrained devices) and modified memory allocators/garbage collectors in JVMs. On the global level, subheaps (heap-area fragments) from a shared memory pool are allocated according to an address-ordered first-fit strategy. On the application level, a mark-sweep compact collector in one or more subheaps is used. This includes compaction across noncontiguous regions, and the release of surplus space to the global memory manager. For the selection of the sizes of heap areas, two strategies are discussed: deduction of subheap sizes from profiling information (available before program execution), and adaptive increasing/decreasing of sizes. Experimental results are given for several benchmark examples, showing significant reduction in memory footprints and a marginal increase in execution time. Experiments for other environments/platforms may confirm the value of this approach for heap-memory usage. The performance may largely depend on hardware features, operating system characteristics, and the garbage collection parameters. Though the discussion is rather informal, the paper contains useful information for people dealing with the intricacies of runtime systems for embedded applications. Online Computing Reviews Service
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Publication History
Published: 29 January 2008
Accepted: 01 June 2007
Revised: 01 June 2007
Received: 01 January 2007
Published in TECS Volume 7, Issue 2
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View all- Tay YZong XHe X(2013)An equation-based Heap Sizing RulePerformance Evaluation10.1016/j.peva.2013.05.00970:11(948-964)Online publication date: 1-Nov-2013
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