• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권3호
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• pp.921-940
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• 2015

In this paper, we investigate the multi-resource allocation problem, a unique feature of which is that the multiple resources can compensate each other while achieving the desired system performance. In particular, power and time allocations are jointly optimized with the target of energy efficiency under the resource-limited constraints. Different from previous studies on the power-time tradeoff, we consider a multi-server case where the concurrent serving users are quantitatively restricted. Therefore user selection is investigated accompanying the resource allocation, making the power-time tradeoff occur not only between the users in the same server but also in different servers. The complex multivariate optimization problem can be modeled as a variant of 2-Dimension Bin Packing Problem (V2D-BPP), which is a joint non-linear and integer programming problem. Though we use state decomposition model to transform it into a convex optimization problem, the variables are still coupled. Therefore, we propose an Iterative Dual Optimization (IDO) algorithm to obtain its optimal solution. Simulations show that the joint multi-resource allocation algorithm outperforms two existing non-joint algorithms from the perspective of energy efficiency.

• 한국경영과학회지
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• 제31권1호
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• pp.1-13
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• 2006

In this paper we consider a design problem of a cyclic queueing network with two stages, each with a local buffer of limited capacity. Based on the theory of reversibility and product-form solution, we derive the throughput function of the network as a key performance measure to maximize. Two cases are considered. In case each stage consists of a single server, an optimal allocation policy of a given buffer capacity and work load between stages as well as the optimal number of customers is identified by exploiting the properties of the throughput function. In case each stage consists of multiple servers, the optimal policy developed for the single server case doesn't hold any more and an algorithm is developed to allocate with a small number of computations a given number of servers, buffer capacity as well as total work load and the total number of customers. The differences of the optimal policies between two cases and the implications of the results are also discussed. The results can be applied to support the design of certain manufacturing and computer/communication systems.

• Journal of Information Processing Systems
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• 제18권3호
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• pp.389-401
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• 2022

The business of Internet of Vehicles (IoV) is growing rapidly, and the large amount of data exchange has caused problems of large mobile network communication delay and large energy loss. A strategy for resource allocation of IoV communication based on mobile edge computing (MEC) is thus proposed. First, a model of the cloud-side collaborative cache and resource allocation system for the IoV is designed. Vehicles can offload tasks to MEC servers or neighboring vehicles for communication. Then, the communication model and the calculation model of IoV system are comprehensively analyzed. The optimization objective of minimizing delay and energy consumption is constructed. Finally, the on-board computing task is coded, and the optimization problem is transformed into a knapsack problem. The optimal resource allocation strategy is obtained through genetic algorithm. The simulation results based on the MATLAB platform show that: The proposed strategy offloads tasks to the MEC server or neighboring vehicles, making full use of system resources. In different situations, the energy consumption does not exceed 300 J and 180 J, with an average delay of 210 ms, effectively reducing system overhead and improving response speed.

• 한국시뮬레이션학회논문지
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• 제24권3호
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• pp.37-44
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• 2015

실생활에서 2개의 병렬형 대기행렬 시스템은 흔히 발견된다. 병렬형 대기행렬 시스템에서 각 작업장은 서로 다른 고객 도착패턴과 고객 서비스 시간 분포를 갖는 경우가 많다. 이 논문은 서로 다른 서비스 시간을 갖는 병렬형 대기행렬 시스템에 총 서버 수가 제한되어 있는 상황에서 각각의 작업장에 적절한 수의 서버를 배치하는 문제를 다룬다. 각 작업장은 제한된 수의 서버를 전체 시스템의 가중평균 시스템 시간이 최소가 되는 기준에 따라 배치 받는다. 일반적으로 M/M/c 시스템은 시스템 시간에 대한 해석적 방법의 산출식이 알려져 있다. M/M/c 시스템에 대한 최적 서버 배치 방안을 해석적 방법에 따라 계산한 결과를 컴퓨터 시뮬레이션 실험 결과와 비교해 본 결과, 두 가지 방법에 의한 최적 해가 동일함이 확인되었다. M/M/c 시스템의 최적화 과정에서 발견한, 각 작업장의 유효작업부하가 가장 비슷하거나 같게 되도록 서버를 배치하는 방식인 CETI 규칙에 따라 M/G/c, G/M/c 그리고 G/G/c 시스템에 대한 컴퓨터 시뮬레이션 실험 결과를 제시하였다. 그 결과, 해석적 방법으로는 증명할 수 없지만 일부 G/G/c 시스템을 제외한 나머지 경우에서는 CETI 규칙이 최적의 서버 배치 방식인 것으로 나타났다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권6호
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• pp.2282-2303
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• 2021

To solve the problems of heavy computing load and system transmission pressure in energy internet (EI), we establish a three-tier cloud-edge integrated EI network based on a cloud-edge collaborative computing to achieve the tradeoff between energy consumption and the system delay. A joint optimization problem for resource allocation and task offloading in the threetier cloud-edge integrated EI network is formulated to minimize the total system cost under the constraints of the task scheduling binary variables of each sensor node, the maximum uplink transmit power of each sensor node, the limited computation capability of the sensor node and the maximum computation resource of each edge server, which is a Mixed Integer Non-linear Programming (MINLP) problem. To solve the problem, we propose a joint task offloading and resource allocation algorithm (JTOARA), which is decomposed into three subproblems including the uplink transmission power allocation sub-problem, the computation resource allocation sub-problem, and the offloading scheme selection subproblem. Then, the power allocation of each sensor node is achieved by bisection search algorithm, which has a fast convergence. While the computation resource allocation is derived by line optimization method and convex optimization theory. Finally, to achieve the optimal task offloading, we propose a cloud-edge collaborative computation offloading schemes based on game theory and prove the existence of Nash Equilibrium. The simulation results demonstrate that our proposed algorithm can improve output performance as comparing with the conventional algorithms, and its performance is close to the that of the enumerative algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제18권1호
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• pp.211-232
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• 2024

In this paper, we consider the resource allocation and offloading decisions of device-to-device (D2D) cooperative UAV-assisted mobile edge computing (MEC) system, where the device with task request is served by unmanned aerial vehicle (UAV) equipped with MEC server and D2D device with idle resources. On the one hand, to ensure the fairness of time-delay sensitive devices, when UAV computing resources are relatively sufficient, an optimization model is established to minimize the maximum delay of device computing tasks. The original non-convex objective problem is decomposed into two subproblems, and the suboptimal solution of the optimization problem is obtained by alternate iteration of two subproblems. On the other hand, when the device only needs to complete the task within a tolerable delay, we consider the offloading priorities of task to minimize UAV computing resources. Then we build the model of joint offloading decision and power allocation optimization. Through theoretical analysis based on KKT conditions, we elicit the relationship between the amount of computing task data and the optimal resource allocation. The simulation results show that the D2D cooperation scheme proposed in this paper is effective in reducing the completion delay of computing tasks and saving UAV computing resources.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권11호
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• pp.5234-5251
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• 2018

It is well-known that virtualization technology can bring many benefits not only to users but also to service providers. From the view of system security and resource utility, higher resource sharing degree and higher system reliability can be obtained by the introduction of virtualization technology in distributed cloud. The small size time-sharing multiplexing technology which is based on virtual machine in distributed cloud platform can enhance the resource utilization effectively by server consolidation. In this paper, the concept of memory block and user satisfaction is redefined combined with user requirements. According to the unbalanced memory resource states and user preference requirements in multi-virtual machine environments, a model of proper memory resource allocation is proposed combined with memory block and user satisfaction, and at the same time a memory optimization allocation algorithm is proposed which is based on virtual memory block, makespan and user satisfaction under the premise of an orderly physical nodes states also. In the algorithm, a memory optimal problem can be transformed into a resource workload balance problem. All the virtual machine tasks are simulated in Cloudsim platform. And the experimental results show that the problem of virtual machine memory resource allocation can be solved flexibly and efficiently.

• 한국정보과학회논문지:정보통신
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• 제29권3호
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• pp.265-275
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• 2002

셀룰라 기반의 이동컴퓨팅 환경에서 이동 호스트의 위치 및 상태관리를 위하여 디폴트 서버(default sever)기법이 널리 사용되나 이동 호스트로의 호 요청이 많은 경우나 호를 요청한 클라이언트가 디볼트서버와 멀리 떨어진 경우 통신 오버 헤드가 커지며, 디폴트서버에 결함이 발생할 경우 해당 이동 호스트에 대한 연결이 불가능해 진다. 디폴트 서버를 여러 개로 중복 시키면 위와 같은 문제점을 경감시키고 디폴트 서버와의 통신비용을 줄일 수 있다. 그러나 디폴트 서버를 중복 시킬 경우 전체 통신비용은 이동 호스트의 이동 성향과 질의(query) 요청의 빈도, 중복 디폴트 서버의 할당 위치와 중복 개수에 영향을 받는다. 본 논문에서는 디폴트 서버를 통신 환경에 따라 최적의 위치에 할당 시켰을 때 nn grid네트워크 환경과 이진트리 네트워크 환경에서 각각의 최적 디폴트 서버 중복 개수를 구하는 방법을 제시하였고, 시뮬레이션을 통하여 수학적 방법이 유용함을 보였다.

• 정보처리학회논문지C
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• 제9C권5호
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• pp.679-686
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• 2002

비디오 서버에서 압축된 형태로 저장된 비디오 데이터를 화질의 저하 없이 클라이언트로 전송하기 위해서는 프레임당 대역폭을 일정하게 조절하는 방법이 필요하다. 이에 스무딩 기법은 프레임당 비트수가 다른 가변 비트율(VBR : Variable Bit Rate)을 가진 비디오 스트림을 일련의 고정된 전송률로 전송하는 방법이다. 본 논문에서는 비디오 서버에 저장된 비디오 스트림을 클라이언트측으로 전송할 경우 최소의 대역폭과 전송률 변화 횟수를 가지며 비디오 서버의 CPU 오버헤드를 최소화하는 스무딩 알고리즘을 제시한다. 제시된 알고리즘의 효용성을 증명하기 위해 기존의 다른 스무딩 알고리즘들과 다양한 환경에서 비친 분석하였다.

• Journal of Information Processing Systems
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• 제19권5호
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• pp.702-712
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• 2023

Load balancing plays a crucial role in ensuring the stable operation of information management systems during periods of high user access requests; therefore, load balancing approaches should be reasonably selected. Moreover, appropriate load balancing techniques could also result in an appropriate allocation of system resources, improved system service, and economic benefits. Nginx is one of the most widely used loadbalancing software packages, and its deployment is representative of load-balancing application research. This study introduces Nginx into an educational administration system, builds a server cluster, and compares and sets the optimal cluster working strategy based on the characteristics of the system, Furthermore, it increases the stability of the system when user access is highly concurrent and uses the Nginx reverse proxy service function to improve the cluster's ability to resist illegal attacks. Finally, through concurrent access verification, the system cluster construction becomes stable and reliable, which significantly improves the performance of the information system service. This research could inform the selection and application of load-balancing software in information system services.