• Journal of applied mathematics & informatics
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• v.26 no.3_4
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• pp.493-500
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• 2008

In this paper, we first construct a mathematical model for tagSNP selection based on LD measure $r^2$, then aiming at this kind of model, we develop an efficient algorithm, which is called approximate greedy algorithm. This algorithm is able to make up the disadvantage of the greedy algorithm for tagSNP selection. The key improvement of our approximate algorithm over greedy algorithm lies in that it adds local replacement(or local search) into the greedy search, tagSNP is replaced with the other SNP having greater similarity degree with it, and the local replacement is performed several times for a tagSNP so that it can improve the tagSNP set of the local precinct, thereby improve tagSNP set of whole precinct. The computational results prove that our approximate greedy algorithm can always find more efficient solutions than greedy algorithm, and improve the tagSNP set of whole precinct indeed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.4
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• pp.529-546
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• 2010

Greedy forwarding is the key mechanism of geographic routing and is one of the protocols used most commonly in wireless sensor networks. Greedy forwarding uses 1-hop local information to forward packets to the destination and does not have to maintain the routing table, and thus it takes small overhead and has excellent scalability. However, the signal intensity reduces exponentially with the distance in realistic wireless sensor network, and greedy forwarding consumes a lot of energy, since it forwards the packets to the neighbor node closest to the destination. Previous proposed greedy forwarding protocols are the sender-based greedy forwarding that a sender selects a neighbor node to forward packets as the forwarding node and hence they cannot guarantee energy efficient forwarding in unpredictable wireless environment. In this paper, we propose the receiver-based greedy forwarding called RGF where one of the neighbor nodes that received the packet forwards it by itself. In RGF, sender selects several energy efficient nodes as candidate forwarding nodes and decides forwarding priority of them in order to prevent unnecessary transmissions. The simulation results show that RGF improves delivery rate up to maximum 66.8% and energy efficiency, 60.9% compared with existing sender-based greedy forwarding.

• The KIPS Transactions:PartB
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• v.14B no.7
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• pp.541-548
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• 2007

Due to the mathematical convergence property, Simulated Annealing (SA) has been one of the most popular optimization algorithms. However, because of its problem of slow convergence in the practical use, many variations of SA like Fast SA (FSA) have been developed for faster convergence. In this paper, we propose and prove that Greedy SA (GSA) also finds the global optimum in probability in the continuous space optimization problems. Because the greedy selection does not allow the cost to become worse, GSA is expected to have faster convergence than the conventional FSA that uses Metropolis selection. In the computer simulation, the proposed method is shown to have as good performance as FSA with Metropolis selection in the viewpoints of the convergence speed and the quality of the found solution. Furthermore, the greedy selection does not concern the cost value itself but uses only dominance of the costs of solutions, which makes GSA invariant to the problem scaling.

• Journal of Korea Society of Digital Industry and Information Management
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• v.13 no.1
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• pp.79-85
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• 2017

Vehicular ad-hoc networks (VANETs) cause link disconnection problems due to the rapid speed and the frequent moving direction change of vehicles. Link disconnection in vehicle-to-vehicle communication is an important issue that must be solved because it decreases the reliability of packet forwarding. From the characteristics of VANETs, greedy forwarding protocols using the position information based on the inter-vehicle distance have gained attention. However, greedy forwarding protocols do not perform well in the urban environment where the direction of the vehicle changes greatly. It is because greedy forwarding protocols select the neighbor vehicle that is closest to the destination vehicle as the next transmission vehicle. In this paper, we propose a greedy anycast forwarding (GAF) protocol to improve the reliability of the inter-vehicle communication. The proposed GAF protocol combines the greedy forwarding scheme and the anycast forwarding method. Simulation results show that the GAF protocol can provide a better packet delivery rate than existing greedy forwarding protocols.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.5
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• pp.753-775
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• 2010

Greedy forwarding is a key mechanism of geographic routing using distance as a metric. As greedy forwarding only uses 1-hop neighbor node information, it minimizes routing overhead and is highly scalable. In existing greedy forwarding schemes, a node selects a next forwarding node based only on the distance. However, the signal strength in a realistic environment reduces exponentially depending on the distance, so that by considering only the distance, it may cause a large number of data packet retransmissions. To solve this problem, many greedy forwarding schemes have been proposed. However, they do not consider the unreliable and asymmetric characteristics of wireless links and thus cause the waste of limited battery resources due to the data packet retransmissions. In this paper, we propose a reliable and energy-efficient opportunistic greedy forwarding scheme for unreliable and asymmetric links (GF-UAL). In order to further improve the energy efficiency, GF-UAL opportunistically uses the path that is expected to have the minimum energy consumption among the 1-hop and 2-hop forwarding paths within the radio range. Comprehensive simulation results show that the packet delivery rate and energy efficiency increase up to about 17% and 18%, respectively, compared with the ones in PRR${\times}$Distance greedy forwarding.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.46 no.11
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• pp.25-31
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• 2009

In this paper we propose an improved energy aware greedy perimeter stateless routing protocol (EAGPSR) for wireless ad hoc network. The existing greedy perimeter stateless routine (GPSR) has some problems with overloaded node and void situation. The improved EAGPSR protocol is proposed to remedy these problems. It also gives the solution for the fundamental problem in geographical routine called void communication. It considers two parameters (Residual Energy of battery and distance to the destination) for the next hop selection. In order to use efficiently limited-energy of node in wireless ad hoc network, network lifetime is focused. To evaluate the performance of our protocol we simulated EAGPSR in ns-2. The simulation results show that the proposed protocol achieves longer network lifetime compared with greedy perimeter stateless routing (GPSR) and the existing Energy aware greedy perimeter stateless routing protocol (EAGPSR).

• Journal of the Korea Society for Simulation
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• v.28 no.1
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• pp.67-79
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• 2019

A warship equipped with Multi Function Radar(MFR) performs operations by evaluating the degree of threats based on threats' symptom and allocating the resource of MFR to the corresponding threats. This study suggests a simulation-based approach and greedy algorithm in order to effectively allocate the resource of an MFR for warships, and compares these two approaches. As a detection probability function depending on the amount of allocations to each threat, we consider linear and exponential functions. Experimental results show that both the simulation-based approach and greedy algorithm allocate resource similarly to the randomly generated threats, and the greedy algorithm outperforms the simulation-based approach in terms of computational perspective. For a various cases of threats, we analyze the results of MFR resource allocation using the greedy algorithm.

• MALSORI
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• no.66
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• pp.105-116
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• 2008

In this research, we propose a speaker identification system using a kernel method which is expected to model the non-linearity of speech features well. We have been using principal component analysis (PCA) successfully, and extended to kernel PCA, which is used for many pattern recognition tasks such as face recognition. However, we cannot use kernel PCA for speaker identification directly because the storage required for the kernel matrix grows quadratically, and the computational cost grows linearly (computing eigenvector of $l{\times}l$ matrix) with the number of training vectors I. Therefore, we use greedy kernel PCA which can approximate kernel PCA with small representation error. In the experiments, we compare the accuracy of the greedy kernel PCA with the baseline Gaussian mixture models using MFCCs and PCA. As the results with limited enrollment data show, the greedy kernel PCA outperforms conventional methods.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.47 no.4
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• pp.43-50
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• 2010

Vehicle-to-Vehicle (V2V) is a special type of vehicle ad-hoc network (VANET), and known as a solution to provide communication among vehicles and reduce vehicle accidents. Geographical routing protocols as Greedy Perimeter Sateless Routing (GPSR) are very suitable for the V2V communication due to special characters of highway and device for vehicles. However, the GPSR has problem that appears local maximum by some stale neighbor nodes in the greedy mode of the GPSR. It can lose transmission data in recovery mode, even if the problem is can be solved by the recovery mode of the GPSR. We therefore propose a Greedy Perimeter Reliable Routing (GPRR), can provide more reliable data transmission, to resolve the GPSR problem in the V2V environment. Simulation results using ns-2 shown that the GPRR reveals much better performance than the GPSR by remarkably reducing the local maximum rate in the greedy mode.

• Convergence Security Journal
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• v.10 no.1
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• pp.41-48
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• 2010

Greedy protocols show good performance in Vehicular Ad-hoc Networks (VANETs) environment in general. But they make longer routes causing by surroundings or turn out routing failures in some cases when there are many traffic signals which generate empty streets temporary, or there is no merge roads after a road divide into two roads. When a node selects the next node simply using the distance to the destination node, the longer route is made by traditional greedy protocols in some cases and sometimes the route ends up routing failure. Most of traditional greedy protocols just take into account the distance to the destination to select a next node. Each node needs to consider not only the distance to the destination node but also the direction to the destination while routing a packet because of geographical environment. The proposed routing scheme considers both of the distance and the direction for forwarding packets to make a stable route. And the protocol can configure as the surrounding environment. We evaluate the performance of the protocol using two mobility models and network simulations. Most of network performances are improved rather than in compared with traditional greedy protocols.