• International Journal of Computer Science & Network Security
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• v.24 no.4
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• pp.60-66
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• 2024

Host's data during transmission. Data tempering results in loss of host's sensitive information, which includes number of VM, storage availability, and other information. In the distributed cloud environment, each server (computing server (CS)) configured with Local Resource Monitors (LRMs) which runs independently and performs Virtual Machine (VM) migrations to nearby servers. Approaches like predictive VM migration [21] [22] by each server considering nearby server's CPU usage, roatative decision making capacity [21] among the servers in distributed cloud environment has been proposed. This approaches usage underlying server's computing power for predicting own server's future resource utilization and nearby server's resource usage computation. It results in running VM and its running application to remain in waiting state for computing power. In order to reduce this, a decentralized decision making hybrid model for VM migration need to be proposed where servers in decentralized cloud receives, future resource usage by analytical computing system and takes decision for migrating VM to its neighbor servers. Host's in the decentralized cloud shares, their detail with peer servers after fixed interval, this results in chance to tempering messages that would be exchanged in between HC and CH. At the same time, it reduces chance of over utilization of peer servers, caused due to compromised host. This paper discusses, an roatative decisive (RD) approach for VM migration among peer computing servers (CS) in decentralized cloud environment, preserving confidentiality and integrity of the host's data. Experimental result shows that, the proposed predictive VM migration approach reduces extra VM migration caused due over utilization of identified servers and reduces number of active servers in greater extent, and ensures confidentiality and integrity of peer host's data.

• Asia-Pacific Journal of Business
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• v.3 no.2
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• pp.23-33
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• 2012

Sustainable competitive advantage depends on formulation and implementation of appropriate human resource management (HRM) strategies and deployment of their competencies effectively in dynamic and complex environment. Competencies deployment is an approach to make decisions on the intentions and plans of organization concerning employment relationship and its recruitment, training, development, performance appraisal, reward and employee relations policies and practice. The improvement of organizational effectiveness is an overall objective of people management in organizations. In light of these, this study explores the present practices of HRM like: HR departments, HR policies and strategies, HR planning, recruitment selection and placement, training and development, performance appraisal, compensation and benefit, employee relations and communications. Based on the survey in 204 Nepalese organizations as a unit of analysis, the study concludes that HR practices in few organizations have action program for minorities, ethnic group, older employees and people with disabilities. Due to centralized organizational structure, most of HR decisions are taken into central office and line managers being involved highly in planning and implementing HR policies. In a nutshell, though HRM practices are not developed like developed countries, Nepalese organizations are realizing the significance of people management at work and changing their practices in the present dynamic environment.

• ETRI Journal
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• v.42 no.5
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• pp.686-699
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• 2020

In this paper, we propose a supervised-learning-based spatial performance prediction (SLPP) framework for next-generation heterogeneous communication networks (HCNs). Adaptive asset placement, dynamic resource allocation, and load balancing are critical network functions in an HCN to ensure seamless network management and enhance service quality. Although many existing systems use measurement data to react to network performance changes, it is highly beneficial to perform accurate performance prediction for different systems to support various network functions. Recent advancements in complex statistical algorithms and computational efficiency have made machine-learning ubiquitous for accurate data-based prediction. A robust network performance prediction framework for optimizing performance and resource utilization through a linear discriminant analysis-based prediction approach has been proposed in this paper. Comparison results with different machine-learning techniques on real-world data demonstrate that SLPP provides superior accuracy and computational efficiency for both stationary and mobile user conditions.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.9
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• pp.3034-3055
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• 2014

Wireless Sensor Networks have extensively been utilized for ambient data collection from simple linear structures to dense tiered deployments. Issues related to optimal resource allocation still persist for simplistic deployments including linear and hierarchical networks. In this work, we investigate the case of dimensioning parameters for linear and tiered wireless sensor network deployments with notion of providing extended lifetime and reliable data delivery over extensive infrastructures. We provide a single consolidated reference for selection of intrinsic sensor network parameters like number of required nodes for deployment over specified area, network operational lifetime, data aggregation requirements, energy dissipation concerns and communication channel related signal reliability. The dimensioning parameters have been analyzed in a pipeline monitoring scenario using ZigBee communication platform and subsequently referred with analytical models to ensure the dimensioning process is reflected in real world deployment with minimum resource consumption and best network connectivity. Concerns over data aggregation and routing delay minimization have been discussed with possible solutions. Finally, we propose a node placement strategy based on a dynamic programming model for achieving reliable received signals and consistent application in structural health monitoring with multi hop and long distance connectivity.

• Journal of East-Asian Urban History
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• v.2 no.1
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• pp.65-85
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• 2020

Examining how the CCP operated social services in Shanghai neighborhood[linong] in early 1950s, this article reveals the hidden relation between social service and rectification of neighborhood organizations in 1954. One of the main purpose of 1954 rectification was to guarantee provision of grassroots level of the city by recruiting local cadres, the implementers of social services. Though series of social service, such as night patrol, cleaning and public charity were indispensable for residents' life and welfare(fuli)[福利] of neighborhood, the social services was the something most of the Shanghai residents were reluctant to do. The result was the shortage of human resource for social service, triggering the "nominal position(gua ming)[掛名] " phenomenon. During political rectification of neighborhood organizations in 1954 Shanghai Municipal government tried to solve this 'decline of human resource in social services' problem by attracting the unemployed to the position of basic level cadre. To be specific, it demanded jobless person in neighborhood to be registered in time if they want a job placement. And it used that registration as the nominee of cadre in re-election process of the rectification campaign. The government measures were closely related to Shanghai people's inclination to rely on party-state when they try to get a job. Hence political rectification in neighborhood organizations become the strategic tool of city governance to mobilize residents in operating social services. So this article suggests that the CCP's urban governance was a complex and nuanced process to induce urban residents' interest and voluntarism beyond the suppression-oriented totalitarian perspective.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.6
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• pp.447-453
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• 2021

Human resources play a key role in developing and enhancing the manner in which an organization change. In fact, the role of human resource-related quality management has contributed greatly to the growth of the organization in both the short and long term. The purpose of the current study is to identify factors that influence human resource retention in Hanoi in the backdrop of growing economic performance of Hanoi in Vietnam's economy. Primary data was collected through questionnaires of 280 respondents from the four districts in Hanoi, including 25.2% of respondents working in Cau Giay district, 21.2% in Dong Da district, 34.2% in Ha Dong district, and 19.4% in Thanh Xuan district. After applying Cronbach's Alpha and Explore Factor Analysis (EFA) analysis, Durbin-Watson test, empirical results demonstrate that relationship among co-workers has a significant and positive contribution on the maintenance of human resources in the organization. Additionally, higher welfare facilities for an employee are more likely to impact the maintenance of human resources in the organization. Factors such as working environment, job placement, and leadership relationship have no adverse effect on the maintenance of human resources, although a positive impact could be established in all cases.

• IEMEK Journal of Embedded Systems and Applications
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• v.15 no.3
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• pp.129-137
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• 2020

Kubernetes is one of the most widely used tool in cloud computing environments. It m anages POD as a basic operational unit, providing a isolated environments through container tech nology. Basically, its scheduler properly allocates POD, considering the utilizations of CPUs, mem ories and volumes on hosts. In our work, we develop a customized scheduling framework additio nally considering network resources. In the framework, we can monitor the dynamic variations of resources and make it possible to utilize the resources for the scheduler. This framework offers not only observing necessary information but also visualizing the data to scheduler for providing convenience.

• Journal of the Korean Institute of Educational Facilities
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• v.5 no.3
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• pp.91-97
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• 1998

The purpose of this study is to investigate elementary school landscaping. The landscaping has intrinsic value for educational purpose as well as an open space resource in urban area. Four elementary schools in Taegu were surveyed and analyzed to identify the ratio of greenery, green volume and its maintenance. The result can be summarized as follows: 1. While 58 species of trees were quoted all over the text book, 17 to 52 species were found in each school and only few species were always dominant in each school. 2. The greenery and green volume were insufficient in terms of quantity and inadequate in placement, and there were differences in landscaping quality and quantity between schools. However the differences were not associated with the age of schools. 3. Functional implementations of landscaping technique(for example, environmental control) were needed for future landscaping of elementary schools.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.2
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• pp.312-334
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• 2023

In large-scale computing, cloud computing plays an important role by sharing globally-distributed resources. The evolution of cloud has taken place in the development of data centers and numerous servers across the globe. But the cloud information centers incur huge operational costs, consume high electricity and emit tons of dioxides. It is possible for the cloud suppliers to leverage their resources and decrease the consumption of energy through various methods such as dynamic consolidation of Virtual Machines (VMs), by keeping idle nodes in sleep mode and mistreatment of live migration. But the performance may get affected in case of harsh consolidation of VMs. So, it is a desired trait to have associate degree energy-performance exchange without compromising the quality of service while at the same time reducing the power consumption. This research article details a number of novel algorithms that dynamically consolidate the VMs in cloud information centers. The primary objective of the study is to leverage the computing resources to its best and reduce the energy consumption way behind the Service Level Agreement (SLA)drawbacks relevant to CPU load, RAM capacity and information measure. The proposed VM consolidation Algorithm (PVMCA) is contained of four algorithms: over loaded host detection algorithm, VM selection algorithm, VM placement algorithm, and under loading host detection algorithm. PVMCA is dynamic because it uses dynamic thresholds instead of static thresholds values, which makes it suggestion for real, unpredictable workloads common in cloud data centers. Also, the Algorithms are adaptive because it inevitably adjusts its behavior based on the studies of historical data of host resource utilization for any application with diverse workload patterns. Finally, the proposed algorithm is online because the algorithms are achieved run time and make an action in response to each request. The proposed algorithms' efficiency was validated through different simulations of extensive nature. The output analysis depicts the projected algorithms scaled back the energy consumption up to some considerable level besides ensuring proper SLA. On the basis of the project algorithms, the energy consumption got reduced by 22% while there was an improvement observed in SLA up to 80% compared to other benchmark algorithms.

• Journal of Digital Convergence
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• v.11 no.2
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• pp.205-214
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• 2013

Team collaboration is becoming commonplace and it is spotlighted in agile software development projects as well. More efficient teamwork in terms of effective team operation and project performance is very important. Heuristic software development staffing method has been used, but algorithm approach is needed to compensate for it. In this paper, we propose a mathematical approaches for staffing developers in teamwork-based software development projects. This consist of six process, and activities in each processor is defined as a mathematical function placement, and functional deployment matrix is used. A case study is presented in order to prove the usefulness of this approach. This paper is a significant research because a mathematical approach of work assignment is developed for human resources by quantitative logic and it deviate from intuitive or heuristic methods used previously.