• 한국정밀공학회:학술대회논문집
• /
• 한국정밀공학회 1997년도 추계학술대회 논문집
• /
• pp.154-158
• /
• 1997

This paper proposes a new resource allocation system where overall performance can be improved using production smoothing method. In economic point of view, market price is determined by the market mechanism that is subject to the law of demand and supply. Similarly, agents determine whether to allocate tasks to machines by profit and loss or not. In existing resource allocation system, tasks are exclusively allocated to agents with better manufacturing conditions, because they are evaluated by the only currency. But in the proposed resource allocation system, agents are evaluated by not only a currency but also machine specifications. Hereby, the production smoothing is achieved and we expect to improve system performance In this study, we propose a resource allocation system with consideration of Production Smoothing.

• 한국경영과학회:학술대회논문집
• /
• 대한산업공학회/한국경영과학회 2004년도 춘계공동학술대회 논문집
• /
• pp.167-170
• /
• 2004

This paper proposes resource allocation method for achieving investment goals in manufacturing system. In order to align resource allocation and manufacturing system design, the system design decomposition (SDD) approach is used. In this paper, a mathematical formulation for resource allocation based on SDD approach is analyzed and a genetic algorithm application is discussed.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제15권6호
• /
• pp.2282-2303
• /
• 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)
• /
• 제17권4호
• /
• pp.1258-1275
• /
• 2023

Cloud computing is a new technology that has adapted to the traditional way of service providing. Service providers are responsible for managing the allocation of resources. Selecting suitable containers and bandwidth for job scheduling has been a challenging task for the service providers. There are several existing systems that have introduced many algorithms for resource allocation. To overcome these challenges, the proposed system introduces an Optimized Task Scheduling Algorithm with Deep Learning (OTS-DL). When a job is assigned to a Cloud Service Provider (CSP), the containers are allocated automatically. The article segregates the containers as' Long-Term Container (LTC)' and 'Short-Term Container (STC)' for resource allocation. The system leverages an 'Optimized Task Scheduling Algorithm' to maximize the resource utilisation that initially inquires for micro-task and macro-task dependencies. The bottleneck task is chosen and acted upon accordingly. Further, the system initializes a 'Deep Learning' (DL) for implementing all the progressive steps of job scheduling in the cloud. Further, to overcome container attacks and errors, the system formulates a Container Convergence (Fault Tolerance) theory with high-level security. The results demonstrate that the used optimization algorithm is more effective for implementing a complete resource allocation and solving the large-scale optimization problem of resource allocation and security issues.

• 한국전자통신학회논문지
• /
• 제19권4호
• /
• pp.655-660
• /
• 2024

통신시스템에서 중계기는 전체 시스템의 성능을 향상시키는 장점으로 인해 다양한 통신환경에서 적용되어져 왔다. 본 논문에서는 하나의 중계기를 이용하는 듀얼홉 통신시스템에서 비대칭 통신 시나리오를 고려한 시스템의 성능을 분석한다. 성능분석은 비트오류율을 사용한다. 먼저 대칭 환경과 비대칭 환경에서의 전체 성능을 비교하고 자원할당에 따른 성능을 분석한다. 자원할당은 에너지 할당과 중계기 위치 할당을 고려한다. 에너지 할당과 중계기 위치에 따른 성능을 각각 분석하고 두 가지 자원을 동시에 고려했을 경우에 대한 성능 또한 분석한다. 성능분석을 기반으로 하여 대칭 환경과 비대칭 환경에서의 자원할당 효과에 대해 논의한다.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2001년도 ICCAS
• /
• pp.140.3-140
• /
• 2001

This paper analyzes a blocking that is due to shared resource in multiprocessor system. A proposed analysis for shared resource suggests a scalable and amendable scheduling method about task allocation. An equation of shared resource blocking is proposed by a throughput at common bus and a ratio of throughput during time period, it is included a parameter of tasks scheduling. Using this equation, a new guideline for task allocation of multiprocessor is presented. Finally, in proposed system a model simulations for the proposed blocking model is given by a deterministic ratio of shared resource.

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

• 한국멀티미디어학회논문지
• /
• 제16권7호
• /
• pp.862-869
• /
• 2013

In order to support a cell-independent traffic asymmetry, the conventional TDD system cannot avoid crossed time slot (CTS) interference. Moreover, the TDD/FDD hierarchical overlay cellular systems is taken into account as a generally accepted cell model in a heterogeneous radio environment. In this paper, we propose an interference resolving radio resource allocation technique in a TDD-OFDMA cellular system that overlays a FDD-CDMA cell. In our proposed scheme, we exploit under-used FDD-CDMA uplink resource by TDD mobile abiding by a region based time slot(TS) allocation which in turn mitigates CTS interference considerably. It is demonstrated that combined with under-used resource utilization scheme based on mobile's location, the proposed technique can reduce CTS interference considerably and support the asymmetric traffic in TDD system.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제7권10호
• /
• pp.2395-2410
• /
• 2013

Many telecommunication operators around the world have multiple networks. The networks run by each operator are always of different generations, such as 2G and 3G or even 4G systems. Each system has unique characters and specified requirements for optimal operation. It brings about resource allocation problem among these networks for the operator, because the budget of each operator is limited. However, the evaluation of resource allocation among various networks under each operator is missing for long, not to mention resource allocation optimization. The operators are dying for an algorithm to end their blind resource allocation, and the Resource Allocation Optimization Algorithm for Multi-network Operator (RAOAMO) proposed in this paper is what the operators want. RAOAMO evaluates and optimizes resource allocation in the view of overall cost for each operator. It outputs a resource distribution target and corresponding optimization suggestion. Evaluation results show that RAOAMO helps operator save overall cost in various cases.

• 한국통신학회논문지
• /
• 제42권2호
• /
• pp.393-402
• /
• 2017

육상의 셀룰러 네트워크와 같이 수중에서도 기지국을 통해 유입되는 트래픽 양에 따라 적응적으로 기지국의 백홀 자원을 할당하여 전체 네트워크 자원을 효율적으로 관리할 수 있는 수중 셀룰러 통신 네트워크가 필요하다. 본 논문에서는 수중 셀룰러 통신 네트워크에서 기지국에 유입되는 트래픽에 비례하여 기지국의 백홀 자원을 할당하는 자원분배 프로토콜을 제안한다. 자원분배 프로토콜은 자원을 할당하는 주기에 따라 고정주기 방식과 적응주기 방식으로 분류된다. 더 효율적인 자원분배 프로토콜을 결정하기 위해 모의시험을 이용하여 고정주기 방식과 적응주기 방식의 수신율, 메시지 오버헤드, 전송지연 성능을 비교하고 분석하였다. 그 결과, 고정주기 방식이 적응주기 방식에 비해 최대 수백 배 이상의 전송지연이 증가하였으며, 수백 배 이상의 메시지 오버헤드가 더 발생하여 모든 성능 지표에서 적응주기 방식이 고정주기 방식보다 성능이 우수함을 확인하였다.