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The growing demand on the performance of transparent computing systems requires good cache schemes in order to overcome the prolonged network latency. However, evaluating cache schemes, especially measuring the performance of a transparent computing system with particular cache scheme remains challenging. This is because neither method is available to evaluate the effectiveness and efficiency of the cache schemes in transparent computing, nor the simulator has been developed to measure the system performance under particular cache schemes. In this paper, we propose TranSim, a full-featured, high-performance simulation framework for transparent computing. For the first time, TranSim introduces a methodology to evaluate the performance of multi-level cache hierarchies in transparent computing under different cache configurations and cache replacement policies. TranSim can also demonstrate the behavior and performance of the entire transparent computing system rather than only the cache miss/hit rate. Using TranSim, the system designer can quickly evaluate the effectiveness of cache schemes along with the system performance. We construct several experiments to evaluate the effectiveness and efficiency of TranSim. Results show that TranSim can accurately output the performance of both the cache hierarchy and the entire transparent computing system. [ABSTRACT FROM AUTHOR]

Abstract: Dynamic balancing of computation and communication load is vital for the execution stability and performance of distributed, parallel simulations deployed on the shared, unreliable resources of large-scale environments. High Level Architecture (HLA) based simulations can experience a decrease in performance due to imbalances that are produced initially and/or during run time. These imbalances are generated by the dynamic load changes of distributed simulations or by unknown, non-managed background processes resulting from the non-dedication of shared resources. Due to the dynamic execution characteristics of elements that compose distributed applications, the computational load and interaction dependencies of each simulation entity change during run time. These dynamic changes lead to an irregular load and communication distribution, which increases overhead of resources and latencies. A static partitioning of load is limited to deterministic applications and is incapable of predicting the dynamic changes caused by distributed applications or by external background processes. Therefore, a scheme for balancing the communication and computational load during the execution of distributed simulations is devised in a scalable hierarchical architecture. The proposed balancing system employs local and cluster monitoring mechanisms in order to observe the distributed load changes and identify imbalances, repartitioning policies to determine a distribution of load and minimize imbalances. A migration technique is also employed by this proposed balancing system to perform reliable and low-latency load transfers. Such a system successfully improves the use of shared resources and increases distributed simulations’ performance by minimizing communication latencies and partitioning the load evenly. Experiments and comparative analyses were conducted in order to identify the gains that the proposed balancing scheme provides to large-scale distributed simulations. [ABSTRACT FROM AUTHOR]