• Journal of Internet Computing and Services
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• v.22 no.5
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• pp.27-33
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• 2021

With the broad adoption of the Internet of Things (IoT) in a variety of scenarios and application services, management and orchestration entities require upgrading the traditional architecture and develop intelligent models with ultra-reliable methods. In a heterogeneous network environment, mission-critical IoT applications are significant to consider. With erroneous priorities and high failure rates, catastrophic losses in terms of human lives, great business assets, and privacy leakage will occur in emergent scenarios. In this paper, an efficient resource slicing scheme for optimizing federated learning in software-defined IoT (SDIoT) is proposed. The decentralized support vector regression (SVR) based controllers predict the IoT slices via packet inspection data during peak hour central congestion to achieve a time-sensitive condition. In off-peak hour intervals, a centralized deep neural networks (DNN) model is used within computation-intensive aspects on fine-grained slicing and remodified decentralized controller outputs. With known slice and prioritization, federated learning communications iteratively process through the adjusted resources by virtual network functions forwarding graph (VNFFG) descriptor set up in software-defined networking (SDN) and network functions virtualization (NFV) enabled architecture. To demonstrate the theoretical approach, Mininet emulator was conducted to evaluate between reference and proposed schemes by capturing the key Quality of Service (QoS) performance metrics.

• KIEAE Journal
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• v.16 no.6
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• pp.51-56
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• 2016

Purpose: As declines in the quality of residential environments occur, such as urban heat island effect, tropical night phenomenon, and violations of right to light and privacy due to urban densification and high rise building, these problems are emerging as social issues. In order to improve these issues, design factors which consider environmental aspects must be selected when planning apartment complexes, and ways to reflect them in the planning phase must be explored. Method: In this study, the analytical hierarchy process(AHP) was used to deduce design factors that considered environmental elements during the planning of apartment complexes. Furthermore, the priority and weight for each evaluation index were assessed. The objective was to propose a guideline for planning apartment complexes by finding the best solution for each evaluation index using complex weight values. Result: Floor area ratio was selected as the most important evaluation criterion in the environmentally conscious evaluation index for apartment complex planning. The shape and placement of skylights were selected as the most important evaluation criteria in the sunshine environment for a pleasant residential environment. Ground surface cover design was selected as the most important criterion in the outdoor thermal environment index for improving the microclimate within cities and apartment complexes. Thus, the results of this study can serve as an investigation guideline that concerns policy and regulations, and as reference data that can be used in planning apartment complexes.

• KIEAE Journal
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• v.8 no.6
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• pp.11-20
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• 2008

Modern society is an era that demands higher standards of living, and accordingly healthier living conditions due to fast economic growth. This society is being confronted by the necessity to find strategies to promote and manage health condition in everyday living environment. The current 'wellbeing' trend which pursues holistic health including physical, psychological and social health has accelerated the demand for healthy environment. In this context, this study intended to identify health friendly planning features based on consumer's demand. Web survey technique was used as main research methodology. Stratified random sampling was used with age being used as the strata valuable. Two hundred and eleven data were analyzed using SPSS statistical package. As results, awareness about health housing and hierarchy of important planning features were empirically identified. Furthermore, significant differences in some planning features according to the age were scrutinized. Major health friendly features demanded by consumers were found ventilation, non-toxic material, view of nature, space in which family can gather, protection of their privacy. Consumers' recognitions and demands varied according to age. The older the resident was, the higher the demands appeared. The results are expected to be used as a reference to explore and develop strategies for future healthy housing.