• Journal of KIISE:Computing Practices and Letters
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• v.11 no.6
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• pp.477-487
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• 2005

As embedded system grows in size and complexity, the importance of the technique for dynamic memory allocation has increased. The objective of this paper is to measure the performance of dynamic memory allocation by varying both hardware and software design parameters for embedded systems. Unlike torrent performance evaluation studies that have presumed the single threaded system with single address spate without OS support, our study adopts realistic environment where the embedded system runs on Linux OS. This paper contains the experimental performance analyses of dynamic memory allocation method by investigating the effects of each software layer and some hardware design parameters. Our quantitative results tan be used to help system designers design high performance, low power embedded systems.

• Proceedings of the IEEK Conference
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• 2003.07d
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• pp.1335-1338
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• 2003

Fixed-size memory allocation is one of the most promising way to avoid external fragmentation in dynamic memory allocation problem. This paper presents an experimental result of applying the fixed- size memory allocation strategy to Java virtual machine for embedded system. The result says that although this strategy induces another memory utilization problem caused by internal fragmentation, the effect is not very considerable and this strategy is well-suited for embedded Java system. The experiment has been performed in a real embedded Java system called the simpleRTJ.

• Journal of the Korea Society for Simulation
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• v.11 no.3
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• pp.23-34
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• 2002

Dynamic storage allocation (DSA) is a field fairly well studied for a long time as a basic problem of system software area. Due to memory fragmentation problem of DSA and its unpredictable worst case execution time, real-time system designers have believed that DSA may not be promising for real-time application service. Recently, the need for an efficient DSA algorithm is widely discussed and the algorithm is considered to be very important in the real-time system. This paper proposes an efficient DSA algorithm called QSB (quick semi-buddy) which is designed to be suitable for real-time environment. QSB scheme effectively maintains free lists based on quick-fit approach to quickly accommodate small and frequent memory requests, and the other free lists devised with adaptation upon a typical binary buddy mechanism for bigger requests in harmony for the .improved performance. Comprehensive simulation results show that the proposed scheme outperforms QHF which is known to be effective in terms of memory fragmentation up to about 16%. Furthermore, the memory allocation failure ratio is significantly decreased and the worst case execution time is predictable.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.10B
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• pp.1648-1664
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• 2000

This paper proposes a real-time dynamic storage allocation algorithm QSHF(quick-segregated-half-fit) that provides various memory allocation policies. that manages a free block list per each word size for memory requests of small size good(segregated)-fit policy that manages a free list per proper range size for medium size requests and half-fit policy that manages a free list per proper range size for medium size requests and half-fit policy that manages a free list per each power of 2 size for large size requests. The proposed algorithm has the time complexit O(1) and makes us able to easily estimate the worst case execution time(WCET). This paper also suggests two algorithm that finds the proper free list for the requested memory size in predictable time and if the found list is empty then finds next available non-empty free list in fixed time. In order to confirm efficiency of the proposed algorithm we simulated the memory utilization of each memory allocation policy. The simulation result showed that each policy guarantees the constant WCET regardless of memory size but they have trade-off between memory utilization and list management overhead.

• Journal of Computing Science and Engineering
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• v.9 no.2
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• pp.51-72
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• 2015

Time predictability is crucial in hard real-time and safety-critical systems. Cache memories, while useful for improving the average-case memory performance, are not time predictable, especially when they are shared in multicore processors. To achieve time predictability while minimizing the impact on performance, this paper explores several time-predictable scratch-pad memory (SPM) based architectures for multicore processors. To support these architectures, we propose the dynamic memory objects allocation based partition, the static allocation based partition, and the static allocation based priority L2 SPM strategy to retain the characteristic of time predictability while attempting to maximize the performance and energy efficiency. The SPM based multicore architectural design and the related allocation methods thus form a comprehensive solution to hard real-time multicore based computing. Our experimental results indicate the strengths and weaknesses of each proposed architecture and the allocation method, which offers interesting on-chip memory design options to enable multicore platforms for hard real-time systems.

• KIPS Transactions on Computer and Communication Systems
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• v.4 no.9
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• pp.327-336
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• 2015

Mobile game servers usually execute frequent dynamic memory allocation for generating the buffers that deal with clients requests. It causes to deteriorate the performance of game servers since it increases system workload and memory fragmentation. In this paper, we propose fixed-sized memory pool management method. Memory pool for the proposed method has a sequential memory structure based on circular linked list data structure. It solves memory fragmentation problem and saves time for searching the memory blocks which are required for memory allocation and deallocation. We showed the efficiency of the proposed method by evaluating the performance of dynamic memory allocation, through the proposed method and the memory pool management method based on boost open source library.

• Journal of KIISE:Computer Systems and Theory
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• v.37 no.3
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• pp.147-160
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• 2010

The system virtualization shows interest in the consolidation of servers for the efficient utilization of system resources. There are many various researches to utilize a server machine more efficiently through the system virtualization technique, and improve performance of the virtualization software. These researches have studied with the activity to control the resource allocation of virtual machines dynamically focused on CPU, or to manage resources in the cross-machine using the migration. However, the researches of the memory management have been wholly lacking. In this respect, the use of memory is limited to allocate the memory statically to virtual machine in server consolidation. Unfortunately, the static allocation of the memory causes a great quantity of the idle memory and decreases the memory utilization. The underutilization of the memory makes other side effects such as the load of other system resources or the performance degradation of services in virtual machines. In this paper, we suggest the dynamic allocation of the memory in Xen to control the memory allocation of virtual machines for the utilization without the performance degradation. Using AR model for the prediction of the memory usage and ACO (Ant Colony Optimization) algorithm for optimizing the memory utilization, the system operates more virtual machines without the performance degradation of servers. Accordingly, we have obtained 1.4 times better utilization than the static allocation.

• The Transactions of the Korea Information Processing Society
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• v.7 no.4
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• pp.1082-1091
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• 2000

In Distributed Shared Memory systems, false sharing occurs when two different data items, not shared but accessed by two different processors, are allocated to a single block and is an important factor in degrading system performance. The paper first analyzes shared memory allocation and reference patterns in parallel applications that allocate memory for shared data objects using a dynamic memory allocator. The shared objects are sequentially allocated and generally show different reference patterns. If the objects with the same size are requested successively as many times as the number of processors, each object is referenced by only a particular processor. If the objects with the same size are requested successively much more than the number of processors, two or more successive objects are referenced by only particular processors. On the basis of these analyses, we propose a memory allocation scheme which allocates each object requested by different processors to different pages and evaluate the existing memory allocation techniques for reducing false sharing faults. Our allocation scheme reduces a considerable amount of false sharing faults for some applications with a little additional memory space.

• Journal of KIISE:Computer Systems and Theory
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• v.27 no.6
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• pp.592-598
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• 2000

The locality of data references at the distributed shared memory systems affects the performance significantly. Data allocation methods by considering the locality of data references can improve the performance of DSM systems. This paper evaluates the performance for the dynamic limited directory scheme which data allocation methods can apply very effectively. The information of the data allocation is used by the dynamic limited directory scheme to set the presence bit effectively. And the proper use of the presence bit improves the performance by reducing memory overhead and using directory pool efficiently. Simulations are conducted using three application programs which have various data sharing. The results show that the optimal data allocation method improves the performance up to 3.6 times in the proposed scheme.

• The Transactions of the Korea Information Processing Society
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• v.7 no.7
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• pp.2204-2218
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• 2000

This paper proposes a dynamic storage allocation algorithm, QHF(quick-half-fit) for real-time systems. The proposed algorithm manages a free block list per each worked size for memory requests of small size, and a free block list per each power of 2 size for memory requests of large size. This algorithms uses the exact-fit policy for small sie requests and provides high memory utilization. The proposed algorithm also has the time complexity O(I) and enables us to easily estimate the worst case execution time (WCET). In order to confirm efficiency of the proposed algorithm, we compare he memory utilization of proposed algorithm with that of half-fit and binary buddy system that have also time complexity O(I). The simulation result shows that the proposed algorithm guarantees the constant WCET regardless of the system memory size and provides lower fragmentation ratio and allocation failure ratio thant other two algorithms.