• Journal of the East Asian Society of Dietary Life
• /
• v.20 no.5
• /
• pp.776-784
• /
• 2010

This study investigated causal relationships between goal orientation, sales and performance towards increasing the effectiveness of up-selling in internal promotion methods in family restaurants and provided implications about the hiring and training of sales people. The subjects were 232 sales people in family restaurants. The data were collected by self-administered questionnaires and analyzed by exploratory factor analysis, reliability analysis, comparative analysis of the average, and regression analysis. Results, showed that variations in goal orientation, sales, and performance depended on the age and experience of salespeople and that goal orientation makes adaptive selling more effective. It turned out that effort selling affects up-selling result than adaptive selling. Long-term workers were better than short-term workers in goal orientation, selling, and up-selling results, so human resource management needs to implement a long-term plan to enhance these effects. And, because effort selling is more effective than adaptive selling in up-selling results in family restaurants, effort selling requires training.

• Journal of KIISE:Computer Systems and Theory
• /
• v.37 no.3
• /
• pp.127-137
• /
• 2010

As large-scale computational applications in various scientific domains have been utilized over many integrated sets of grid computing resources, the difficulty of their execution management and control has been increased. It is beneficial to refer job history generated from many application executions, in order to identify application‘s characteristics and to decide selection policies of grid resource meaningfully. In this paper, we apply a statistical technique, Plackett-Burman design with fold-over (PBDF), for analyzing grid environments and execution history of applications. PBDF design identifies main factors in grid environments and applications, ranks based on how much they affect to their execution time. The effective factors are used for selecting reference job profiles and then preferable resource based on the reference profiles is chosen. An application is performed on the selected resource and its execution result is added to job history. Factor's credit is adjusted according to the actual execution time. For a proof-of-concept, we analyzed job history from an aerospace research grid system to get characteristics of grid resource and applications. We built JARS algorithm and simulated the algorithm with the analyzed job history. The simulation result shows good reliability and considerable performance in grid environment with frequently crashed resources.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.37 no.7B
• /
• pp.505-516
• /
• 2012

According to distribute of resource of macro cell and reduce distance between transmitter and receiver, Femto cell system is promising to provide costeffective strategy for high data traffic and high spectral efficient services in future wireless cellular system environment. However, the co-channel operation with existing Macro networks occurs some severe interference between Macro and Femto cells. Hence, the interference cancellation or management schemes are imperative between Macro and Femto cells in order to avoid the decrease of total cell throughput. First, we briefly investigate the conventional resource allocation and interference cancellation scheme between Macro and Femto cells. So we found that cell throughput and frequency reuse ware decreased Then, we propose an adaptive resource allocation scheme based on the distribution of Femtocell traffic in order to increase the cell throughput and also maximize the spectral efficiency over the FFR (Fractional Frequency Reuse) based conventional resource allocation schemes. Simulation Results show that the proposed scheme attains a bit similar SINR (Signal to Interference Noise Ratio) distribution but achieves much higher total cell throughput performance distribution over the conventional resource allocation schemes for FFR and future IEEE 802.16m based Femtocell network environment.

• Journal of Internet Computing and Services
• /
• v.12 no.3
• /
• pp.37-47
• /
• 2011

Current researches in the Cloud focus on the appropriate interactions of cloud components in a large-scale system implementation. However, the current designs do not include intelligent methods like grouping the similar service providers based on their properties and integrating adaptive schemes for load distribution which can promote effective sharing of resource. This paper proposes an efficient virtualization of services by grouping the cloud providers to improve the service provisioning. The grouping of cloud service providers based on a cluster analysis collects the similar and related services in one group. The adaptive load balancing supports the service provisioning of the cloud system where it manages the load distribution within the group using an adaptive scheme. The proposed virtualization mechanism (GRALB) showed good results in minimizing message overhead and throughput performance compared to other methods.

• KIPS Transactions on Computer and Communication Systems
• /
• v.3 no.7
• /
• pp.219-230
• /
• 2014

In the cloud computing environment, cloud service users purchase and use the virtualized resources from cloud resource providers on a pay as you go manner. Typically, there are two billing plans for computing resource allocation adopted by large cloud resource providers such as Amazon, Gogrid, and Microsoft, on-demand and reserved plans. Reserved Virtual Machine(VM) instance is provided to users based on the lengthy allocation with the cheaper price than the one of on-demand VM instance which is based on shortly allocation. With the proper mixture allocation of reserved and on-demand VM corresponding to users' requests, cloud service providers are able to reduce the resource allocation cost. To do this, prior researches about VM allocation scheme have been focused on the optimization approach with the users' request prediction techniques. However, it is difficult to predict the expected demands exactly because there are various cloud service users and the their request patterns are heavily fluctuated in reality. Moreover, the previous optimization processing techniques might require unacceptable huge time so it is hard to apply them to the current cloud computing system. In this paper, we propose the cloud brokering system with the adaptive VM allocation schemes called A3R(Adaptive 3 Resource allocation schemes) that do not need any optimization processes and kinds of prediction techniques. By using A3R, the VM instances are allocated to users in response to their service demands adaptively. We demonstrate that our proposed schemes are able to reduce the resource use cost significantly while maintaining the acceptable Quality of Service(QoS) of cloud service users through the evaluation results.

• Journal of the Institute of Electronics Engineers of Korea TC
• /
• v.47 no.7
• /
• pp.72-79
• /
• 2010

Device-to-device(D2D) links which share resources in a cellular network present a challenge in radio resource management due to the potentially severe interference they may cause to the cellular network. In this paper, a resource allocation scheme based on subset reuse methods is proposed to minimize the interference from the D2D links. We consider an adaptive group-wise subset reuse method to enhance the efficiency of frequency resource allocation for cellular and D2D links. A power optimization scheme is also proposed for D2D links if cellular links are interfered by adjacent D2D transmissions. The computer simulation results show that performance gain is obtained in link SINR, and total cell throughput increases as nearby traffic becomes more dominant.

• Journal of Advanced Navigation Technology
• /
• v.13 no.2
• /
• pp.201-207
• /
• 2009

Recently effective spectrum resource technologies have been studied using a game theorectical approach for cognitive radio networks. Radio resource management is required an effective scheme because the performance of a radio communication system much depends on it's effectiveness. In this paper, we suggest a game theoretical algorithm for adaptive power control which is required an effect scheme in cognitive radio networks. It will be a distributed network. In the network distributed cognitive radio secondary users require an adaptive power control. There are many results which are suggested some possibility of game theoretical approaches for communication resource sharing. However, we suggest a practical game algorithm to achieve Nash equilibrium of all secondary users using a Nash equilibrium theorem in this paper. Particularly, a game model was analyzed for adaptive power control of a cognitive radio network, which is involved in DSSS (Direct Sequence Spread Spectrum) techniques. In case of K=63 and N=12 in the DSSS network, the number of iteration was less than maximum 200 using the suggested algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.36 no.7B
• /
• pp.771-779
• /
• 2011

It is expected that many heterogeneous wireless systems, such as 3GPP LTE systems, WiMAX systems and WLAN systems, will coexist in the next generation wireless communication environments. Integrated radio resource management and seamless vertical handoff (VHO) should be supported to provide integrated communication services over multi-radio access networks. A new class of adaptive VHO system that views the handoff problem as a pattern recognition problem is proposed. In this paper, we propose a unified radio resource management (URRM) architecture and Support Vector Machine (SVM) based vertical handoff decision system. Extensive simulation studies show the proposed VHO algorithm outperforms RSS based VHO algorithms in terms of throughput and service cost.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.13 no.9
• /
• pp.4349-4371
• /
• 2019

Moldable parallel tasks are widely used in different areas, such as weather forecast, biocomputing, mechanical calculation, and so on. Considering the deadline and the speedup, scheduling moldable parallel tasks becomes a difficulty. Past work majorly focuses on the LA (List Algorithms) or OMA (Optimizing the Middle Algorithms). Different from prior work, our work normalizes execution time and makes all tasks have the same scope in normalized execution time: [0,1], and then according to the normalized execution time, a method is used to search for the reference execution time without considering the deadline of tasks. According to the reference execution time, we get an initial scheduling result based on AFCFS (Adaptive First Comes First Served) policy. Finally, a heuristic approach is used to improve the performance of the initial scheduling result. We call our method HSRET (a Heuristic Scheduling method based on Reference Execution Time). Comparisons to other methods show that HSRET has good performance in AWT (Average Waiting Time), AET (Average Execution Time), and PUT (Percentages of Unfinished Tasks).

• Journal of Internet Computing and Services
• /
• v.18 no.4
• /
• pp.51-59
• /
• 2017

With the growth of Cloud computing, it is important to consider resource management techniques to minimize the overall costs of management. In cloud environments, each host's utilization and virtual machine's request based on user preferences are dynamic in nature. To solve this problem, efficient allocation method of virtual machines to hosts where the classification of virtual machines and hosts is undetermined should be studied. In reducing the number of active hosts to reduce energy consumption, thresholds can be implemented to migrate VMs to other hosts. By using Fuzzy logic in classifying resource requests of virtual machines and resource utilization of hosts, we proposed an adaptive VM allocation and migration approach. The allocation strategy classifies the VMs according to their resource request, then assigns it to the host with the lowest resource utilization. In migrating VMs from overutilized hosts, the resource utilization of each host was used to create an upper threshold. In selecting candidate VMs for migration, virtual machines that contributed to the high resource utilization in the host were chosen to be migrated. We evaluated our work through simulations and results show that our approach was significantly better compared to other VM allocation and Migration strategies.