• The Transactions of the Korea Information Processing Society
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• v.5 no.11
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• pp.2823-2834
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• 1998

This paper deals with the problem of one-to-one mapping of $2^n$ task modules of a parallel program to an n-dimensional hypercube multicomputer so as to minimize to total communication cost during the execution of the task. The problem of finding an optimal mapping has been proven to be NP-complete. We first propose a graph modification technique which transfers the mapping problem in a hypercube multicomputer into the problem of finding a set of maximum cutsets on a given task graph. Using the graph modification technique, we then propose a repeated mapping scheme which efficiently finds a one-to-one mapping of task modules to a hypercube multicomputer by repeatedly applying an existing bipartitioning algorithm on the modified graph. The repeated mapping scheme is shown to be highly effective on a number of test task graphs, it increasingly outperforms the greedy and recursive mapping algorithms as the number of processors increase. The proposed algorithm is shown to be very effective for regular graph, such as hypercube-isomorphic or 'almost' isomorphic graphs and meshes; it finds optimal mapping on almost all the regular task graphs considered.

• Journal of KIISE:Software and Applications
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• v.33 no.12
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• pp.1090-1102
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• 2006

This paper suggests a new algorithm for detecting the plagiarism among a set of source codes, constrained to be functionally equivalent, such are submitted for a programming assignment or for a programming contest problem. The typical algorithms largely exploited up to now are based on Greedy-String Tiling, which seeks for a perfect match of substrings, and analysis of similarity between strings based on the local alignment of the two strings. This paper introduces a new method for detecting the similar interval of the given programs based on an adaptive similarity matrix, each entry of which is the logarithm of the probabilities of the keywords based on the frequencies of them in the given set of programs. We experimented this method using a set of programs submitted for more than 10 real programming contests. According to the experimental results, we can find several advantages of this method compared to the previous one which uses fixed similarity matrix(+1 for match, -1 for mismatch, -2 for gap) and also can find that the adaptive similarity matrix can be used for detecting various plagiarism cases.

• KEPCO Journal on Electric Power and Energy
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• v.2 no.3
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• pp.391-395
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• 2016

In the last few decades, global electricity consumption has dramatically increased and has become drastically fluctuating and uncertain causing blackout. Due to the unexpected peak electricity demand, we need significant electricity supply. The solutions to these problems are smart grid system which is envisioned as future power system. Smart grid system can reduce electricity peak demand and induce effective electricity consumption through various price policies, demand response (DR) control methodologies, and state-of-the-art smart equipments in order to optimize electricity resource usage in an intelligent fashion. Demand response (DR) is one of the key technologies to enable smart grid. In this paper, we propose greedy technique for demand response smart grid system. The proposed scheme focuses on minimizing electricity bills, preventing system blackout and sacrificing user convenience.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.2
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• pp.700-713
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• 2015

It is critical to design energy-efficient routing protocols for battery-limited mobile ad hoc networks, especially in which the energy-consuming MIMO techniques are employed. However, there are several challenges in such a design: first, it is difficult to characterize the energy consumption of a MIMO-based link; second, without a careful design, the broadcasted RREP packets, which are used in most energy-efficient routing protocols, could flood over the networks, and the destination node cannot decide when to reply the communication request; third, due to node mobility and persistent channel degradation, the selected route paths would break down frequently and hence the protocol overhead is increased further. To address these issues, in this paper, a novel Greedy Energy-Efficient Routing (GEER) protocol is proposed: (a) a generalized energy consumption model for the MIMO-based link, considering the trade-off between multiplexing and diversity gains, is derived to minimize link energy consumption and obtain the optimal transmit model; (b) a simple greedy route discovery algorithm and a novel adaptive reply strategy are adopted to speed up path setup with a reduced establishment overhead; (c) a lightweight route maintenance mechanism is introduced to adaptively rebuild the broken links. Extensive simulation results show that, in comparison with the conventional solutions, the proposed GEER protocol can significantly reduce the energy consumption by up to 68.74%.

• Journal of KIISE:Computer Systems and Theory
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• v.32 no.2
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• pp.85-94
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• 2005

It has been reported and verified in many design experiences that a judicious utilization of the page and burst access modes supported by DRAMs contributes a great reduction in not only the DRAM access latency but also DRAM's energy consumption. Recently, researchers showed that a careful arrangement of data variables in memory directly leads to a maximum utilization of the page and burst access modes for the variable accesses, but unfortunately, found that the problems are not tractable, consequently, resorting to simple (e.g., greedy) heuristic solutions to the problems. In this parer, to improve the quality of existing solutions, we propose 0-1 ILP-based techniques which produce optimal or near-optimal solution depending on the formulation parameters. It is shown that the proposed techniques use on average 32.2%, l5.1% and 3.5% more page accesses, and 84.0%, 113.5% and 10.1% more burst accesses compared to OFU (the order of first use) and the technique in [l, 2] and the technique in [3], respectively.

• The KIPS Transactions:PartB
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• v.11B no.1
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• pp.77-82
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• 2004

Reinforcement learning takes reward about selecting action when agent chooses some action and did state transition in Present state. this can be the important subject in reinforcement learning as temporal-credit assignment problems. In this paper, by new meta heuristic method to solve hard combinational optimization problem, examine Ant-Q learning method that is proposed to solve Traveling Salesman Problem (TSP) to approach that is based for population that use positive feedback as well as greedy search. And, suggest Ant-TD reinforcement learning method that apply state transition through diversification strategy to this method and TD-error. We can show through experiments that the reinforcement learning method proposed in this Paper can find out an optimal solution faster than other reinforcement learning method like ACS and Ant-Q learning.

• Journal of Korea Multimedia Society
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• v.12 no.9
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• pp.1273-1287
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• 2009

PEGASIS, a chain-based protocol, forms chains from sensor nodes so that each node transmits and receives from a neighbor. In this way, only one node (known as a HEAD) is selected from that chain to transmit to the sink. Although PEGASIS is able to balance the workload among all of the nodes by selecting the HEAD node in turn, a considerable amount of energy may be wasted when nodes which are far away from sink node act as the HEAD. In this study, DERP (Distance-based Energy-efficient Routing Protocol) is proposed to address this problem. DERP is a chain-based protocol that improves the greedy-algorithm in PEGASIS by taking into account the distance from the HEAD to the sink node. The main idea of DERP is to adopt a pre-HEAD (P-HD) to distribute the energy load evenly among sensor nodes. In addition, to scale DERP to a large network, it can be extended to a multi-hop clustering protocol by selecting a "relay node" according to the distance between the P-HD and SINK. Analysis and simulation studies of DERP show that it consumes up to 80% less energy, and has less of a transmission delay compared to PEGASIS.

• Journal of KIISE
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• v.44 no.1
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• pp.63-70
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• 2017

This paper considers the problem of combining multiple strategies for solving sleeping bandit problems with stochastic rewards and stochastic availability. It also proposes an algorithm, called sleepComb(${\Phi}$), the idea of which is to select an appropriate strategy for each time step based on ${\epsilon}_t$-probabilistic switching. ${\epsilon}_t$-probabilistic switching is used in a well-known parameter-based heuristic ${\epsilon}_t$-greedy strategy. The algorithm also converges to the "best" strategy properly defined on the sleeping bandit problem. In the experimental results, it is shown that sleepComb(${\Phi}$) has convergence, and it converges to the "best" strategy rapidly compared to other combining algorithms. Also, we can see that it chooses the "best" strategy more frequently.

• Journal of the Korea Institute of Military Science and Technology
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• v.19 no.4
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• pp.508-516
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• 2016

When GPS signals are not available, a relative localization can be alternatively used to represent the topological relationship between mobile nodes. A relative location map of a network can be constructed by using the distance information between all the pairs of nodes in the network. If a network is large, a number of small local maps are individually constructed and are merged to obtain the whole map. However, this approach may result in a high computation and communication overhead. In this paper, we propose a reference-node selection scheme for relative localization map construction, which chooses a subset of nodes as a reference node that is supposed to construct local maps. The scheme is a greedy algorithm that iteratively chooses nodes with high degree as a reference node until the chosen local maps are successfully merged with a sufficient number of common nodes between nearby local maps. The simulation results indicate that the proposed scheme achieves higher localization accuracy with a reduced computational overhead.

• Journal of KIISE:Software and Applications
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• v.28 no.9
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• pp.662-668
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• 2001

Since the problem of disproving a tautology is as hard as the problem of proving it, no polynomial time algorithm for falsification(or testing invalidity) is feasible. Previous algorithms are mostly based on either divide-and-conquer or graph representation. Most of them demonstrated satisfactory results on a variety of input under certain constraints. However, they have experienced difficulties dealing with big input. We propose a new falsification algorithm using a Merge Rule to produce a counterexample by constructing a minterm which is not satisfied by an input expression in DNF(Disjunctive Normal Form). We also show that the algorithm is consistent and sound. The algorithm is based on a greedy method which would seek to maximize the number or terms falsified by the assignment made at each step of the falsification process. Empirical results show practical performance on big input to falsify randomized nontautological problem instances, consuming O(nm$^2$) time, where n is the number of variables and m is number of terms.