• Journal of the Korea Society of Computer and Information
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• v.12 no.3
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• pp.147-153
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• 2007

Task scheduling is an essential part of any computer system for allocating tasks to a processor of the system among various competitors. As we know, in real-time system, the failure of scheduling a hard real-time task my lead to disastrous consequence. Besides efficiency, resource and speed, real-time system has to take time constraint in serious consideration. This paper proposes a priority-driven scheduling algorithm for real-time multiprocessor system. which is called L-RE coordinates algorithm. L-RE coordinates is a new way of describing the task scheduling problem. In the algorithm, we take both deadline and laxity into consideration for allocating the priority. The simulation result shows that the new algorithm is viable and performance better than EDF and LLF algorithm on schedulability and context switch respectively.

• Journal of the Korean Institute of Intelligent Systems
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• v.27 no.1
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• pp.7-14
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• 2017

Theoretically, it is known that common beliefs and/or common knowledge cannot be attained in asynchronously distributed multiagent environments, however, it show that some propositions with deadlines can be attained as common beliefs among a set of fully trusted agents even when they communicate to each other asynchronously. Generally, in the multiagent environment, the attainment of common beliefs is approached as a problem of communication, and for the common beliefs paradox that the common beliefs is not attained on a system without communication time restriction is applied to loose coarser granularity and it prove that forming common beliefs is possible by relaxing necessary requirements through the KakaoTalk chatting model. I also experimented with the reasoning function that confirms the common beliefs by inquiring about the common belief generated by implementing the inference function in each agent of the KakaoTalk chatting model. Through utilizing metalogic programming, a formalization of the presentation and reasoning of common beliefs has been achieved, and the group chatting model of KakaoTalk was adopted in experiments to show that common beliefs can be formed among distributed agents using asynchronous communication.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.6
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• pp.71-76
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• 2021

Recently, as the size of IoT data grows, the memory power consumption of real-time systems increases rapidly. This is because real-time systems always place entire tasks in memory, which increases the demand of DRAM significantly. In this paper, we adopt emerging fast storage media and move a certain portion of real-time tasks from DRAM to storage. The part of tasks in storage are, then, loaded into memory when they are actually used. We incorporate our memory/storage power-saving into the dynamic voltage/frequency scaling of processors, thereby optimizing power consumptions in CPU and memory simultaneously. Specifically, the proposed technique aims at minimizing the CPU idle time and the DRAM memory size by determining appropriate voltage modes of CPU and the swap ratio of memory, without violating the deadlines of all tasks. Through simulation experiments, we show that the proposed technique significantly reduces the power consumption of real-time systems.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.3
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• pp.43-48
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• 2022

Recently, due to the rapid performance improvement of smartphones and the increase in background executions of mobile apps, multitasking has become common on mobile platforms. Unlike traditional desktop and server apps, response time is important in most mobile apps as they are interactive tasks, and some apps are classified as real-time tasks with deadlines. In this paper, we discuss how to meet the requirements of heterogeneous multitasking in managing memory of real-time and interactive tasks when they are executed together on a smartphone. To do so, we analyze the memory requirement of real-time tasks, and propose a model that has the ability of allocating memory to multitasking tasks on a smartphone. Trace-driven simulations with real-world storage access traces captured by heterogeneous apps show that the proposed model provides reasonable performance for interactive tasks while guaranteeing the requirement of real-time tasks.

• Journal of KIISE:Computer Systems and Theory
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• v.32 no.7
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• pp.377-392
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• 2005

A lot of studies to measure and analyze the system performance have been done in areas such as system modeling, performance measurement, monitoring, and performance prediction since the advent of a computer system. Studies on a framework to unify the performance related areas have rarely been performed although many studies in the various areas have been done, however. In the case of TMO(Time-Triggered Message-Triggered Object), a real-time programming model, it hardly provides tools and frameworks on the performance except a simple run-time monitor. So it is difficult to analyze the performance of the real-time system and the process based on TMO. Thus, in this paper, we propose a framework for the dynamic analysis of the real-time system based on TMO, TDAF(TMO based Dynamic Analysis Framework). TDAF treats all the processes for the performance measurement and analysis, and Provides developers with more reliable information systematically combining a load model, a performance model, and a reporting model. To support this framework, we propose a load model which is extended by applying TMO model to the conventional one, and we provide the load calculation algorithm to compute the load of TMO objects. Additionally, based on TMO model, we propose performance algorithms which implement the conceptual performance metrics, and we present the reporting model and algorithms which can derive the period and deadline for the real-time processes based on the load and performance value. In last, we perform some experiments to validate the reliability of the load calculation algorithm, and provide the experimental result.