• Ocean Systems Engineering
• /
• v.10 no.2
• /
• pp.131-161
• /
• 2020

The objective of this study was to evaluate the downtime cost of side-by-side offloading operations in Malaysian waters. With the help of a numerical time domain tool, the structure and cable response of moored FPSO vessel was simulated for heading and beam sea-states under irregular waves. The weather downtime was assessed by comparing the response under operational wave condition with the pre defined industrial safe offloading criteria. Additionally, two cases of cable failure were simulated for each sea-state. The novel study on downtime cost was presented for three different location of Malaysia subcontinent for which the location specific wave scatter diagram facilitated to estimate the probability of occurrence of operational wave condition. It was concluded that an unpredictable increment in wave height by 0.5 m can significantly impact the production cost.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2012.04a
• /
• pp.37-40
• /
• 2012

Process Offloading 기술은 동작 중인 어플리케이션의 일부를 보다 강력한 성능을 가진 다른 기기로 옮겨 실행하는 기술로써, 스마트폰과 같은 모바일 기기에 적용될 경우 어플리케이션의 수행속도를 향상시키고 배터리 소모 및 발열을 크게 줄일 수 있다. 본 논문에서는 기존의 연구를 조사 및 고찰하여 보다 효과적인 Process Offloading 아카텍처를 제시하고자 한다.

• Journal of Korea Multimedia Society
• /
• v.25 no.8
• /
• pp.1136-1140
• /
• 2022

This paper is a method for efficient traffic prediction in mobile edge computing, where many studies have recently been conducted. For distributed processing in mobile edge computing, tasks offloading from each mobile edge must be processed within the limited computing power of the edge. As a result, in the mobile nodes, it is necessary to efficiently select the surrounding edge server in consideration of performance dynamically. This paper aims to suggest the efficient clustering method by selecting edges in a cloud environment and predicting mobile traffic. Then, our dynamic clustering method is to reduce offloading overload to the edge server when offloading required by mobile terminals affects the performance of the edge server compared with the existing offloading schemes.

• Proceedings of the Korean Institute of Building Construction Conference
• /
• 2023.05a
• /
• pp.75-76
• /
• 2023

The construction industry's lack of experience and expertise makes it difficult for projects to realize the full benefits of implementing modular construction. Such project performance-hindering elements are often labeled as modular challenges. The added requirement for the transportation of the finished volumetric module is one aspect of the 'module transportation logistics,' the under-researched modular challenge that can prevent projects from incurring maximum cost and productivity benefits. The typical module transportation phases include lifting, transporting, and offloading. From conducting a literature review, this paper aims to investigate the equipment commonly adopted to lift and offload the module and validate its economic efficiency by comparing it with the alternative lifting/offloading equipment used in the two case projects. The results showed that hydraulic jacks are an economic alternative to the crane for lifting/offloading the module. The increase in single-module projects with smaller budgets made crane usage economically undesirable, and this study suggested a viable option for a more economical alternative.

• KIPS Transactions on Computer and Communication Systems
• /
• v.2 no.5
• /
• pp.203-208
• /
• 2013

As smartphones are rapidly and widely spread, their applications request gradually larger computation power. Recently, in the personal computer, computing power of hardware has exceeded performance requirement of software sometimes. Computing power of smartphone, however, will not grow at the same pace as demand of applications because of form factor to seek thinner devices and power limitation by relatively slow technical progress of battery. Computation offloading is getting huge attention as one of solution for the problem. It has not commonly used technology in spite of advantages for performance and power consumption since the existing offloading frameworks are difficult for application developer to utilize. This paper presents an application developer-friendly offloading framework, named SorMob. Based on Aspect Oriented Programming model, SorMob provides a convenient environment for application development, and its performance was verified by comparing with the existing offloading framework.

• Journal of KIISE
• /
• v.42 no.6
• /
• pp.707-712
• /
• 2015

Mobile cloud computing is a technology that uses cloud services to overcome resource constrains of a mobile device, and it applies the computation offloading scheme to transfer a portion of a task which should be executed from a mobile device to the cloud. If the communication cost of the computation offloading is less than the computation cost of a mobile device, the mobile device commits a certain task to the cloud. The previous cost analysis models, which were used for separating functions running on a mobile device and functions transferring to the cloud, only considered the amount of data transfer and response time as the offloading cost. In this paper, we proposed a new task partitioning scheme that considers the frequency of function calls and data synchronization, during the cost estimation of the computation offloading. We also verified the energy efficiency of the proposed scheme by using experimental results.

• Journal of Internet Computing and Services
• /
• v.12 no.6
• /
• pp.53-62
• /
• 2011

In this paper, we introduce a method of graphic offloading computing using a GPU virtualization technology in order to provide high demanding software like 3D software as an on-line software service. When the offloading software is executed on server's software virtualization environment, its graphic works are processed on a client's GPU using GPU virtualization, while on the other its data works are processed on server's CPU. To do that, we propose a method of rendering graphics information on client side GPU using API Remoting method. Also, we show the better performance than server based rendering method when we serve offloading software which include dynamical 3D graphics that display images are frequently changed through on-line. Moreover, we describe a method to virtualize offloading software by a process level and manage client's configuration information in order to decrease server's load when we provide software service to multiple clients.

• KIPS Transactions on Software and Data Engineering
• /
• v.9 no.11
• /
• pp.377-386
• /
• 2020

Mobile cloud computing involves mobile or embedded devices as clients, and features small devices with constrained resource and low availability. Due to the fast expansion of smart phones and smart peripheral devices, researches on mobile cloud computing attract academia's interest more than ever. Computation offloading, or code offloading, enhances the performance of computation by migrating a part of computation of a mobile system to nearby cloud servers with more computational resources through wired or wireless networks. Code offloading is considered as one of the best approaches overcoming the limited resources of mobile systems. In this paper, we analyze the factors and the performance of code offloading, especially focusing on static program partitioning and data protection. We survey state-of-the-art researches on analyzed topics. We also describe directions for future research.

• KIPS Transactions on Computer and Communication Systems
• /
• v.12 no.9
• /
• pp.263-272
• /
• 2023

Industrial Internet of Things (IIoT) is an important factor in increasing production efficiency in industrial sectors, along with data collection, exchange and analysis through large-scale connectivity. However, as traffic increases explosively due to the recent spread of IIoT, an allocation method that can efficiently process traffic is required. In this thesis, I propose a two-stage task offloading decision method to increase successful task throughput in an IIoT environment. In addition, I consider a hybrid offloading system that can offload compute-intensive tasks to a mobile edge computing server via a cellular link or to a nearby IIoT device via a Device to Device (D2D) link. The first stage is to design an incentive mechanism to prevent devices participating in task offloading from acting selfishly and giving difficulties in improving task throughput. Among the mechanism design, McAfee's mechanism is used to control the selfish behavior of the devices that process the task and to increase the overall system throughput. After that, in stage 2, I propose a multi-armed bandit (MAB)-based task offloading decision method in a non-stationary environment by considering the irregular movement of the IIoT device. Experimental results show that the proposed method can obtain better performance in terms of overall system throughput, communication failure rate and regret compared to other existing methods.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.11 no.6
• /
• pp.2811-2830
• /
• 2017

In this paper, we study the problem of mobile data offloading for a network that contains multiple mobile network operators (MNOs), multiple WiFi or femtocell access points (APs) and multiple mobile users (MUs). MNOs offload their subscribed MUs' data traffic by leasing the unused Internet connection bandwidth of third party APs. We propose a combinatorial auction-based two-stage matching mechanism comprised of MU-AP matching and AP-MNO matching. The MU-AP matching is designed to match the MUs to APs in order to maximize the total offloading data traffic and achieve better MU satisfaction. Conversely, for AP-MNO matching, MNOs compete for APs' service using the Nash bargaining solution (NBS) and the Vickrey auction theories and, in turn, APs will receive monetary compensation. We demonstrated that the proposed mechanism converges to a distributed stable matching result. Numerical results demonstrate that the proposed algorithm well capture the tradeoff among the total data traffic, social welfare and the QoS of MUs compared to other schemes. Moreover, the proposed mechanism can considerably offload the total data traffic and improve the network social welfare with less computation complexity and communication overhead.