• Journal of Communications and Networks
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• v.17 no.3
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• pp.306-320
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• 2015

Due to an explosive growth in services running in different datacenters, there is need for service selection and routing to deliver user requests to the best service instance. In current solutions, it is generally the client that must first select a datacenter to forward the request to before an internal load-balancer of the selected datacenter can select the optimal instance. An optimal selection requires knowledge of both network and server characteristics, making clients less suitable to make this decision. Information-Centric Networking (ICN) research solved a similar selection problem for static data retrieval by integrating content delivery as a native network feature. We address the selection problem for services by extending the ICN-principles for services. In this paper we present Queue and Latency, a network-driven service selection algorithm which maps user demand to service instances, taking into account both network and server metrics. To reduce the size of service router forwarding tables, we present a statistical method to approximate an optimal load distribution with minimized router state required. Simulation results show that our statistical routing approach approximates the average system response time of source-based routing with minimized state in forwarding tables.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.7
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• pp.1252-1273
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• 2011

In Web Service Composition (WSC) area, services selection aims at selecting an appropriate candidate from a set of functionally-equivalent services to execute the function of each task in an abstract WSC according to their different QoS values. In despite of many related works, few of previous studies consider transactional constraints in QoS-aware WSC, which guarantee reliable execution of Composite Web Service (CWS) that is composed by a number of unpredictable web services. In this paper, we propose a novel global selection-optimal approach in WSC by considering both transactional constraints and end-to-end QoS constraints. With this approach, we firstly identify building rules and the reduction method to build layer-based Directed Acyclic Graph (DAG) model which can model transactional relationships among candidate services. As such, the problem of solving global optimal QoS utility with transactional constraints in WSC can be regarded as a problem of solving single-source shortest path in DAG. After that, we present Graph-building algorithms and an optimal selection algorithm to explain the specific execution procedures. Finally, comprehensive experiments are conducted based on a real-world web service QoS dataset. The experimental results show that our approach has better performance over other competing selection approaches on success ratio and efficiency.

• Journal of the Korean Mathematical Society
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• v.44 no.1
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• pp.139-150
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• 2007

We investigate an optimal portfolio selection problem with transaction costs when an illiquid asset pays cash dividends and there are constraints on the illiquid asset holding. We provide closed form solutions for the problem, and by using these solutions we illustrate interesting features of optimal policies.

• Current Photovoltaic Research
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• v.11 no.2
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• pp.58-65
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• 2023

The expanding significance of energy storage (ES) technology is increasing the acceptability of power systems by augmenting renewable energy supply. To deploy such ES technologies, we must select the optimal technology that meets the requirements of the system and confirm the technical and economic feasibility of the business model based on it. Herein, we propose a method and tool for selecting the optimal ES technology and service suitable for meeting the requirements of the system, based on its performance characteristics. The method described in this study can be used to discover and apply various ES technologies and develop business models with excellent economic feasibility.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.7
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• pp.1802-1814
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• 2012

In order to guide users to select the most optimal access network in heterogeneous wireless networks, a network selection algorithm is proposed which is designed based on multi-objective discrete particle swarm optimization (Multi-Objective Discrete Particle Swarm Optimization, MODPSO). The proposed algorithm keeps fast convergence speed and strong adaptability features of the particle swarm optimization. In addition, it updates an elite set to achieve multi-objective decision-making. Meanwhile, a mutation operator is adopted to make the algorithm converge to the global optimal. Simulation results show that compared to the single-objective algorithm, the proposed algorithm can obtain the optimal combination performance and take into account both the network state and the user preferences.

• Journal of Information Processing Systems
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• v.2 no.2
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• pp.130-134
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• 2006

In the distributed replicating server model, the provision of replicated services will improve the performance of the providing service and efficiency for clients. Efficiently composing the server selection algorithm decreases the retrieval time for replicated data. In this paper, we define the system model that selects and connects the replicated server that provides an optimal service using the server-side downstream measurement and propose a server selection algorithm.

• ETRI Journal
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• v.28 no.1
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• pp.77-83
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• 2006

In order to improve the accuracy of cell selection in heterogeneous cellular systems, this paper proposes a fuzzy multiple-objective decision-based cell selection (FMDCS) strategy. Since heterogeneous cellular systems have different access technologies and multiple traffic classes, the strategy adopts cell type, data rate, coverage, transmission delay, and call arrival rate as evaluation indices, and uses different weight vectors according to the traffic classes of the mobile host. Then, a fuzzy multiple-objective decision algorithm is applied to select the optimal cell from all candidates. This paper also gives an instance analysis and simulation. The instance analysis shows FMDCS makes different selections for different traffic classes. Simulation results of the after-handoff quality-of-service (QoS) show the selected cell can provide MH optimal service.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.10
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• pp.3945-3964
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• 2015

Since the decentralized structure and the blindness of a large-scale wireless network make it difficult to collect the real-time channel state or other information from random distributed relays, a fundamental question is whether it is feasible to perform the relay selection without this knowledge. In this paper, a Slotted ALOHA based Greedy Relay Selection (SAGRS) scheme is presented. The proposed scheme allows the relays satisfying the user's minimum transmission request to compete for selection by randomly accessing the channel through the slotted ALOHA protocol without the need for the information collection procedure. Moreover, a greedy selection mechanism is introduced with which a user can wait for an even better relay when a suitable one is successfully stored. The optimal access probability of a relay is determined through the utilization of the available relay region, a geographical region consisting of all the relays that satisfy the minimum transmission demand of the user. The average number of the selection slots and the failure probability of the scheme are analyzed in this paper. By simulations, the validation and the effectiveness of the SAGRS scheme are confirmed. With a balance between the selection slots and the instantaneous rate of the selected relay, the proposed scheme outperforms other random access selection schemes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.2
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• pp.647-669
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• 2016

Multiple attribute for decision making including user preference will increase the complexity of route selection process. Various approaches have been proposed to solve the optimal route selection problem. In this paper, multi attribute decision making (MADM) algorithms such as Simple Additive Weighting (SAW), Weighted Product Method (WPM), Analytic Hierarchy Process (AHP) method and Total Order Preference by Similarity to the Ideal Solution (TOPSIS) methods have been proposed for acoustic signature based optimal route selection to facilitate user with better quality of service. The traffic density state conditions (very low, low, below medium, medium, above medium, high and very high) on the road segment is the occurrence and mixture weightings of traffic noise signals (Tyre, Engine, Air Turbulence, Exhaust, and Honks etc) is considered as one of the attribute in decision making process. The short-term spectral envelope features of the cumulative acoustic signals are extracted using Mel-Frequency Cepstral Coefficients (MFCC) and Adaptive Neuro-Fuzzy Classifier (ANFC) is used to model seven traffic density states. Simple point method and AHP has been used for calculation of weights of decision parameters. Numerical results show that WPM, AHP and TOPSIS provide similar performance.

• Journal of IKEEE
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• v.22 no.3
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• pp.570-577
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• 2018

With the increasing number of network nodes, traditional client/server node selection mechanisms are under tremendous pressure. In order to select efficient cooperative nodes in a highly dynamic P2P network topology, this article uses greedy algorithm to translate the overall optimization into multiple local optimal problems, and to quickly select service nodes. Therefore, the service node with the largest comprehensive capacity is selected to reduce the transmission delay and improve the throughput of the service node. The final simulation results show that the node selection strategy based on greedy algorithm can effectively improve the overall performance of P2P streaming media system.