• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.4
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• pp.651-669
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• 2013

In this paper, we study a novel routing algorithm based on load balancing for multi-channel wireless mesh networks. In order to increase the network capacity and reduce the interference of transmission streams and the communication delay, on the basis of weighted cumulative expected transmission time (WCETT) routing metric this paper proposes an improved routing metric based on load balancing and channel interference (LBI_WCETT), which considers the channel interference, channel diversity, link load and the latency brought by channel switching. Meanwhile, in order to utilize the multi-channel strategy efficiently in wireless mesh networks, a new channel allocation algorithm is proposed. This channel allocation algorithm utilizes the conflict graph model and considers the initial link load estimation and the potential interference of the link to assign a channel for each link in the wireless mesh network. It also utilizes the channel utilization percentage of the virtual link in its interference range as the channel selection standard. Simulation results show that the LBI_WCETT routing metric can help increase the network capacity effectively, reduce the average end to end delay, and improve the network performance.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.9
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• pp.1538-1544
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• 2006

This paper proposes a non-systolic parallel $AB^2+C$ Computing unit based on irreducible AOP order m of $GF(2^m)$. Proposed circuit have only AND gates and EX-OR gates, composes of cyclic shift operation, multiplication operation power operation power-sum operation and addition operation using a merry irreducible AOP. Suggested operating a method have an advantage high speed data processing, low power and integration because of only needs AND gates and EX-OR gates. $AB^2+C$ computing unit has delay-time of $T_A+(1+[log^m_2])T_X$.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.11
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• pp.831-835
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• 2009

Volunteer computing is a computing paradigm in which the operations of a large-scale application are processed using idle resources of Internet-connected computers. The redundant-work distribution techniques used in the volunteer computing environment cause some problems like delay of the work completion time or inefficiency of the work execution due to continuous requests of the work redistribution because the techniques do not consider the characteristics of works and dynamic resources. To cope with such problems this paper suggests a P2P based regional matchmaking technique which can redistribute works in consideration of the characteristics of the works and the participant resources. The techniques consist of the profiles for works/resources, the module for monitoring the available resources spaces, the protocols for the matching request/reply, the module for match-ratio calculation, and so on.

• The Transactions of the Korea Information Processing Society
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• v.5 no.6
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• pp.1639-1651
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• 1998

In this paper, we present analytical and simulation models for evaluating the operation of a uniprocessor computer which utilizes a time redundant approach (such as recomputation by shilted operands) for lault-tolerant computing. In the proposed approach, all incoming jobs to the uniprocessor are duplicated, thus two versions 01 each job must be processed. Three methods for appropriately scheduling the primary and sL'Condary versions of the jobs are proposed and analyzed. The proposed scheduling methods take into account the load and the fault rate of the uniprocessor to evaluate two figures of merit for cost and profit with respect to a delay in response time due to faults and fault tolerance. Our model utilizes a fault-tolerant schedule according to which it is possible to find an optimal delay (given by $\kappa$) based on empiric parameters such as cost, the load and the fault rate of the uniprocessor.

• Journal of Internet Computing and Services
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• v.10 no.4
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• pp.189-198
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• 2009

Unstructured peer-to-peer systems are most commonly used in today's internet. But file placement is random in these systems and no correlation exists between peers and their contents. There is no guarantee that flooding queries will find the desired data. In this paper, we propose to cluster nodes in unstructured P2P systems using the agglomerative hierarchical clustering algorithm to improve the search method. We compared the delay time of clustering the nodes between our proposed algorithm and the k-means clustering algorithm. We also simulated the delay time of locating data in a network topology and recorded the overhead of the system using our proposed algorithm, k-means clustering, and without clustering. Simulation results show that the delay time of our proposed algorithm is shorter compared to other methods and resource overhead is also reduced.

• Journal of Internet Computing and Services
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• v.9 no.4
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• pp.61-68
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• 2008

Ethernet passive optical network (EPON) is the next-generation technology mitigating the bottleneck between high-capacity local area networks (LANs) and a backbone network. The bottleneck is aggrevated depending on burstiness and long range dependence (LRD) of traffic characteristics as well as amount of outgoing traffic from the high-capacity LANs. The proposed scheme decreases average packet delay for data upstreaming by considering such traffic characteristics to dynamically allocate bandwidth to multiple optical network units (ONUs). In addition, it can appropriately support delay-sensitive traffic such as constant bit ratio (CBR) traffic by making maximum cycle time fix regardless of the number of ONUs. The comprehensive simulation results indicate that the proposed scheme acheives up to 77% and 82% lower than previous schemes in terms of average packet delay and average queue size while it limits the maximum cycle time to twice of the basic cycle time.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.55 no.1
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• pp.13-20
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• 2006

In this paper, a control method of ozone generator for a tiny deodorizer is proposed, and also a cooling technique is described which is cooling down the flowing air gap into a silent discharger to $2[^{\circ}C]$ to generate ozone of high density and diffusing power. As the digital control system for this method, a double feedback loop is designed which detects the voltage and current of equivalent capacitor of the discharger and compensates for the poor power waveform caused by the noise at high discharging frequency. During the plant modeling of this system, computing time factor is considered as a unique parameter of the power system to improve the respond characteristics with regard to fluctuating load and to replenish the computing time delay of the controller. Through the experiment, sinusoidal input current for discharger can be acquired and all the effectiveness of this accurate control system over unstable ozone discharger are proved.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.3
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• pp.874-890
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• 2021

With the widespread deployment of the fifth-generation (5G) communication networks, various real-time applications are rapidly increasing and generating massive traffic on backhaul network environments. In this scenario, network congestion will occur when the communication and computation resources exceed the maximum available capacity, which severely degrades the network performance. To alleviate this problem, this paper proposed an intelligent resource allocation (IRA) to integrate with the extant resource adjustment (ERA) approach mainly based on the convergence of support vector machine (SVM) algorithm, software-defined networking (SDN), and mobile edge computing (MEC) paradigms. The proposed scheme acquires predictable schedules to adapt the downlink (DL) transmission towards off-peak hour intervals as a predominant priority. Accordingly, the peak hour bandwidth resources for serving real-time uplink (UL) transmission enlarge its capacity for a variety of mission-critical applications. Furthermore, to advance and boost gateway computation resources, MEC servers are implemented and integrated with the proposed scheme in this study. In the conclusive simulation results, the performance evaluation analyzes and compares the proposed scheme with the conventional approach over a variety of QoS metrics including network delay, jitter, packet drop ratio, packet delivery ratio, and throughput.

• Nuclear Medicine and Molecular Imaging
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• v.43 no.5
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• pp.459-467
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• 2009

Purpose: The maximum likelihood-expectation maximization (ML-EM) is the statistical reconstruction algorithm derived from probabilistic model of the emission and detection processes. Although the ML-EM has many advantages in accuracy and utility, the use of the ML-EM is limited due to the computational burden of iterating processing on a CPU (central processing unit). In this study, we developed a parallel computing technique on GPU (graphic processing unit) for ML-EM algorithm. Materials and Methods: Using Geforce 9800 GTX+ graphic card and CUDA (compute unified device architecture) the projection and backprojection in ML-EM algorithm were parallelized by NVIDIA's technology. The time delay on computations for projection, errors between measured and estimated data and backprojection in an iteration were measured. Total time included the latency in data transmission between RAM and GPU memory. Results: The total computation time of the CPU- and GPU-based ML-EM with 32 iterations were 3.83 and 0.26 see, respectively. In this case, the computing speed was improved about 15 times on GPU. When the number of iterations increased into 1024, the CPU- and GPU-based computing took totally 18 min and 8 see, respectively. The improvement was about 135 times and was caused by delay on CPU-based computing after certain iterations. On the other hand, the GPU-based computation provided very small variation on time delay per iteration due to use of shared memory. Conclusion: The GPU-based parallel computation for ML-EM improved significantly the computing speed and stability. The developed GPU-based ML-EM algorithm could be easily modified for some other imaging geometries.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.1
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• pp.188-210
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• 2022

As a promising technique to support tremendous numbers of Internet of Things devices and a variety of applications efficiently, mobile edge computing (MEC) has attracted extensive studies recently. In this paper, we consider a MEC-assisted peer-to-peer (P2P) mobile communication system where MEC servers are deployed at access points to accelerate the communication process between mobile terminals. To capture the tradeoff between the time delay and the energy consumption of the system, a cost function is introduced to facilitate the optimization of the computation and communication resources. The formulated optimization problem is non-convex and is tackled by an iterative block coordinate descent algorithm that decouples the original optimization problem into two subproblems and alternately optimizes the computation and communication resources. Moreover, the MEC-assisted P2P communication system is compared with the conventional P2P communication system, then a condition is provided in closed-form expression when the MEC-assisted P2P communication system performs better. Simulation results show that the advantage of this system is enhanced when the computing capability of the receiver increases whereas it is reduced when the computing capability of the transmitter increases. In addition, the performance of this system is significantly improved when the signal-to-noise ratio of hop-1 exceeds that of hop-2.