• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제14권9호
• /
• pp.3885-3906
• /
• 2020

Hybrid fuzzing which combines fuzzing and concolic execution, has proved its ability to achieve higher code coverage and therefore find more bugs. However, current hybrid fuzzers usually suffer from inefficiency and poor scalability when applied to complex, real-world program testing. We observed that the performance bottleneck is the inefficient cooperation between the fuzzer and concolic executor and the slow symbolic emulation. In this paper, we propose a novel solution named EPfuzzer to improve hybrid fuzzing. EPfuzzer implements two key ideas: 1) only the hardest-to-reach branch will be prioritized for concolic execution to avoid generating uninteresting inputs; and 2) only input bytes relevant to the target branch to be flipped will be symbolized to reduce the overhead of the symbolic emulation. With these optimizations, EPfuzzer can be efficiently targeted to the hardest-to-reach branch. We evaluated EPfuzzer with three sets of programs: five real-world applications and two popular benchmarks (LAVA-M and the Google Fuzzer Test Suite). The evaluation results showed that EPfuzzer was much more efficient and scalable than the state-of-the-art concolic execution engine (QSYM). EPfuzzer was able to find more bugs and achieve better code coverage. In addition, we discovered seven previously unknown security bugs in five real-world programs and reported them to the vendors.

• 한국지열·수열에너지학회논문집
• /
• 제16권2호
• /
• pp.7-12
• /
• 2020

The battery of an electric vehicle is a key part of the energy supply to operate the vehicles. There are many factors affecting battery life such as charging method, discharge rate, and ambient temperature those are requires systematic monitoring and management. To solve the issues like environmental problems and fuel consumption reduction the battery needs more performance improvement. In this study, it was analyzed the thermal characteristics and securing battery stability for electric vehicle battery cooling system. The simulation test was operated using GT-suite software with several conditions like cooling capacity 1, 2 and 4 kW, cooling flow rate 5, 10, 20 and 30 LPM, and battery initial temperatures 40, 35, and 30℃ at the temperature of ambient 25℃. The results shown that the case of cooling flow rate at 20 LPM was most efficient among all above conditions.

• 대한임베디드공학회논문지
• /
• 제4권2호
• /
• pp.55-62
• /
• 2009

The power consumption of a high-end microprocessor increases very rapidly. High power consumption will lead to a rapid increase in the chip temperature as well. If the temperature reaches beyond a certain level, chip operation becomes either slow or unreliable. Therefore various approaches for Dynamic Thermal Management (DTM) have been proposed. In this paper, we propose a learning based temperature prediction scheme for a multi-core system. In this approach, from repeatedly executing an application, we learn the thermal patterns of the chip, and we control the temperature in advance through DTM. When the predicted temperature may go beyond a threshold value, we reduce the temperature by decreasing the operation frequencies of the corresponding core. We implement our temperature prediction on an Intel's Quad-Core system which has integrated digital thermal sensors. A Dynamic Frequency System (DFS) technique is implemented to have four frequency steps on a Linux kernel. We carried out experiments using Phoronix Test Suite benchmarks for Linux. The peak temperature has been reduced by on average $5^{\circ}C{\sim}7^{\circ}C$. The overall average temperature reduced from $72^{\circ}C$ to $65^{\circ}C$.

• ETRI Journal
• /
• 제38권5호
• /
• pp.922-933
• /
• 2016

IP header compression schemes offer a valuable measure for bandwidth preservation. Such schemes have been practically implemented in infrastructure-based IP networks for point-to-point links. However, minimal research and practical implementation efforts have been conducted in the direction of an IP header compression strategy that can meet the peculiar requirements of multi-hop ad hoc wireless networks. In this paper, we present a practically implemented multi-hop IP header compression scheme using the Robust Header Compression (ROHC) protocol suite. The scheme runs on a novel identifier (ID) based networking architecture, known as an ID-based ad hoc network (IDHOCNET). IDHOCNET additionally solves a number of bottlenecks of pure IP-based ad hoc networks that have emerged owing to IP address auto-configuration service, distributed naming and name resolution, and the role of an IP address as an identifier at the application layer. The proposed scheme was tested on a multi-hop test bed. The results show that the implemented scheme has better gain and requires only O (1) ROHC contexts.

• 국제초고층학회논문집
• /
• 제7권4호
• /
• pp.299-311
• /
• 2018

As engineered timber such as Glulam is seeing increasing use in tall timber buildings, building codes are adapting to allow for this. In order for this material to be used confidently and safely in one of these applications, there is a need to understand the effects that fire can have on an engineered timber structural member. The post-fire resilience aspect of glulam is studied herein. Two sets of experiments are performed to consider the validity of zero strength guidance with respect to short duration fire exposure on thin glulam members. Small scale samples were heated in a cone calorimeter to different fire severities. These samples illustrated significant strength loss but high variability despite controlled quantification of char layers. Large scale samples were heated locally using a controlled fuel fire in shear and moment locations along the length of the beam respectively. Additionally, reduced cross section samples were created by mechanically carving a way an area of cross section equal to the area lost to char on the heated beams. All of the samples were then loaded to failure in four-point (laterally restrained) bending tests. The beams that have been burnt in the shear region were observed as having a reduction in strength of up to 34.5% from the control beams. These test samples displayed relatively little variability, apart from beams that displayed material defects. The suite of testing indicated that zero strength guidance may be under conservative and may require increasing from 7 mm up to as much as 23 mm.

• 한국지반환경공학회 논문집
• /
• 제22권1호
• /
• pp.13-20
• /
• 2021

A suite of 3D large deformation finite element (FE) analyses was performed to investigate the load transfer mechanism and penetration resistance of spudcan foundations in heterogeneous soil profile consisting of sand and clay. The Elasto-Plastic models following Mohr-Coulomb and Tresca failure criteria were adopted for sand and clay, respectively. The accuracy of the numerical model was validated against centrifuge test measurements. The dense sand behavior with dilation is modeled using the non-associated flow rule. An investigation study consisting of key parameters, which includes variation in soil stratigraphy (sand-clay, sand-clay-sand), strength parameters of sand and clay (��' and su) and normalized height ratio of the sand layer (Hs/D) was conducted to assess the penetration behavior of spudcan. Based on calculated outputs, it was demonstrated that these parameters have a significant influence on the penetration resistance of spudcan. The calculated penetration resistance profiles are compared with the published (sand overlying clay) analytical model. It is confirmed that for the case of two-layer soil, the available theoretical model provides an accurate estimate of peak penetration resistance (qpeak). In the case of three-layer soil, the presence of a third stiff layer affects the penetration resistance profile due to the squeezing of the soil.

• ETRI Journal
• /
• 제44권5호
• /
• pp.805-815
• /
• 2022

The model-based evolutionary algorithms are divided into three groups: estimation of distribution algorithms, inverse modeling, and surrogate modeling. Existing inverse modeling is mainly applied to solve multi-objective optimization problems and is not suitable for many-objective optimization problems. Some inversed-model techniques, such as the inversed-model of multi-objective evolutionary algorithm, constructed from the Pareto front (PF) to the Pareto solution on nondominated solutions using a random grouping method and Gaussian process, were introduced. However, some of the most efficient inverse models might be eliminated during this procedure. Also, there are challenges, such as the presence of many local PFs and developing poor solutions when the population has no evident regularity. This paper proposes inverse modeling using random forest regression and uniform reference points that map all nondominated solutions from the objective space to the decision space to solve many-objective optimization problems. The proposed algorithm is evaluated using the benchmark test suite for evolutionary algorithms. The results show an improvement in diversity and convergence performance (quality indicators).

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제16권9호
• /
• pp.2976-2990
• /
• 2022

The adaptive adjustment of reference or weight vectors in decomposition-based methods has been a hot research topic in the evolutionary community over the past few years. Although various methods have been proposed regarding this issue, most of them aim to diversify solutions in the objective space to cover the true Pareto fronts as much as possible. Different from them, this paper proposes a knee point-based reference vector adaptive adjustment strategy to concurrently balance the convergence and diversity. To be specific, the knee point-based reference vector adaptive adjustment strategy firstly utilizes knee points to construct the adaptive reference vectors. After that, a new fitness function is defined mathematically. Then, this paper further designs a many-objective evolutionary algorithm with knee point-based reference vector adaptive adjustment strategy, where the mating operation and environmental selection are designed accordingly. The proposed method is extensively tested on the WFG test suite with 8, 10 and 12 objectives and MPDMP with state-of-the-art optimizers. Extensive experimental results demonstrate the superiority of the proposed method over state-of-the-art optimizers and the practicability of the proposed method in tackling practical many-objective optimization problems.

• International Journal of Internet, Broadcasting and Communication
• /
• 제14권4호
• /
• pp.121-131
• /
• 2022

We look at the initial stage of Meta (previous Facebook)'s new metaverse platform and investigate its platform design in pre-launch and ignition life stage. From the Rocket Model (RM)'s theoretical logic, the results reveal that Meta firstly focuses on investing in key content developers by acquiring virtual reality (VR), video, music content firms and offering production support platform of the augmented reality (AR) content, 'Spark AR' last three years (2019~2021) for attracting high-potential developers and users. In terms of three matching criteria, Meta develops an Artificial Intelligence (AI) powered translation software, partners with Microsoft (MS) for cloud computing and AI, and develops an AI platform for realistic avatar, MyoSuite. In 'connect' function, Meta curates the game concept submitted by game developers, welcomes other game and SNS based metaverse apps, and expands Horizon Worlds (HW) on VR devices to PCs and mobile devices. In 'transact' function, Meta offers 'HW Creator Funding' program for metaverse, launches the first commercialized Meta Avatar Store on Meta's conventional SNS and Messaging apps by inviting all fashion creators to design and sell clothing in this store. Mata also launches an initial test of non-fungible token (NFT) display on Instagram and expands it to Facebook in the US. Lastly, regarding optimization, especially in the face of recent data privacy issues that have adversely affected corporate key performance indicators (KPIs), Meta assures not to collect any new data and to make its privacy policy easier to understand and update its terms of service more user friendly.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제13권12호
• /
• pp.5785-5804
• /
• 2019

The information of localization is a fundamental requirement in wireless sensor network (WSN). The method of distance vector-hop (DV-Hop), a range-free localization algorithm, can locate the ordinary nodes by utilizing the connectivity and multi-hop transmission. However, the error of the estimated distance between the beacon nodes and ordinary nodes is too large. In order to enhance the positioning precision of DV-Hop, fast triangle flip bat algorithm, which is based on curve strategy and rank transformation (FTBA-TCR) is proposed. The rank is introduced to directly select individuals in the population of each generation, which arranges all individuals according to their merits and a threshold is set to get the better solution. To test the algorithm performance, the CEC2013 test suite is used to check out the algorithm's performance. Meanwhile, there are four other algorithms are compared with the proposed algorithm. The results show that our algorithm is greater than other algorithms. And this algorithm is used to enhance the performance of DV-Hop algorithm. The results show that the proposed algorithm receives the lower average localization error and the best performance by comparing with the other algorithms.