1,540 research outputs found

    METHOD AND SYSTEM TO AUTOMATICALLY SYNTHESIZE SMART CONTRACTS USING TRANSACTION TRACES

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    The present disclosure relates to a method and system to automatically synthesize smart contracts using transaction traces. The present disclosure suggests collecting transaction trace raw data from a blockchain network and transmitting the transaction trace raw data obtained to a transaction decoder system for initial data preprocessing. Thereafter, call frames are extracted from the transaction trace raw data and a Depth-First Search (DFS) traversal is performed on the extracted call frames. Subsequently, at each step of the DFS traversal, the contract address associated (that is, “to” address) with the extracted call frame is verified to determine if it is known or unknown to Etherscan data. Further, the present disclosure suggests collecting top-level calls within the child call frames when the contract address is unknown in the call frame and adding them to the contract as function definitions

    A Co-Simulation Study to Assess the Impacts of Connected and Autonomous Vehicles on Traffic Flow Stability during Hurricane Evacuation

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    Hurricane evacuation has become a major problem for the coastal residents of the United States. Devastating hurricanes have threatened the lives and infrastructure of coastal communities and caused billions of dollars in damage. There is a need for better traffic management strategies to improve the safety and mobility of evacuation traffic. In this study hurricane evacuation traffic was simulated using SUMO a microscopic traffic simulation model. The effects of Connected and Autonomous Vehicles (CAVs) and Autonomous Vehicles (AVs) were evaluated using two approaches. (i) Using the state-of-the-art car-following models available in SUMO and (ii) a co-simulation study by integrating the microscopic traffic simulation model with a separate communication simulator to find the realistic effect of CAVs on evacuation traffic. A road network of I-75 in Florida was created to represent real-world evacuation traffic observed in Hurricane Irma s evacuation periods. Simulation experiments were performed by creating mixed traffic scenarios with 25, 50, 75 and 100 percentages of different vehicle technologies including CAVs or AVs and human-driven vehicles. HDV Simulation results suggest that the CACC car-following model, implemented in SUMO and commonly used in the literature to represent CAVs, produces highly unstable results On the other hand the ACC car following model, used to represent AVs, produces better and more stable results. However, in a co-simulation study, to evaluate the effect of CAVs in the same evacuation traffic scenario, results indicate that with 25 percentage of CAVs the number of potential collisions decrease up to 42.5 percentage

    Plastic Optical Fibers as Passive Optical Front-Ends for Visible Light Communication

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    Plastic Optical Fibers as Passive Optical Front-Ends for Visible Light Communication

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    Performance Evaluation of Wireless Medium Access Control Protocols for Internet of Things

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    The Internet of Things makes the residents in Smart Cities enjoy a more efficient and high-quality lifestyle by wirelessly interconnecting the physical and visual world. However, the performance of wireless networks is challenged by the ever-growing wireless traffic data, the complexity of the network structures, and various requirements of Quality of Service (QoS), especially on the Internet of Vehicle and wireless sensor networks. Consequently, the IEEE 802.11p and 802.11ah standards were designed to support effective inter-vehicle communications and large-scale sensor networks, respectively. Although their Medium Access Control protocols have attracted much research interest, they have yet to fully consider the influences of channel errors and buffer sizes on the performance evaluation of these Medium Access Control (MAC) protocols. Therefore, this thesis first proposed a new analytical model based on a Markov chain and Queuing analysis to evaluate the performance of IEEE 802.11p under imperfect channels with both saturated and unsaturated traffic. All influential factors of the Enhanced Distributed Channel Access (EDCA) mechanism in IEEE 802.11p are considered, including the backoff counter freezing, Arbitration Inter-Frame Spacing (AIFS) defers, the internal collision, and finite MAC buffer sizes. Furthermore, this proposed model considers more common and actual conditions with the influence of channel errors and finite MAC buffer sizes. The effectiveness and accuracy of the developed model have been validated through extensive ns-3 simulation experiments. Second, this thesis proposes a developed analytical model based on Advanced Queuing Analysis and the Gilbert-Elliot model to analyse the performance of IEEE 802.11p with burst error transmissions. This proposed analytical model simultaneously describes transmission queues for all four Access Categories (AC) queues with the influence of burst errors. Similarly, this presented model can analyse QoS performance, including throughputs and end-to-end delays with the unsaturated or saturated load traffics. Furthermore, this model operates under more actual bursty error channels in vehicular environments. In addition, a series of simulation experiments with a natural urban environment is designed to validate the efficiency and accuracy of the presented model. The simulation results reflect the reliability and effectiveness of the presented model in terms of throughput and end-to-end delays under various channel conditions. Third, this thesis designed and implemented a simulation experiment to analyse the performance of IEEE 802.11ah. These simulation experiments are based on ns-3 and an extension. These simulation experiments' results indicate the Restricted Access Window (RAW) mechanism's influence on the throughputs, end-to-end delays, and packet loss rates. Furthermore, the influences of channel errors and bursty errors are considered in the simulations. The results also show the strong impact of channel errors on the performance of IEEE 802.11ah due to urban environments. Finally, the potential future work based on the proposed models and simulations is analysed in this thesis. The proposed models of IEEE 802.11p can be an excellent fundamental to optimise the QoS due to the precise evaluation of the influence of factors on the performance of IEEE 802.11p. Moreover, it is possible to migrate the analytical models of IEEE 802.11p to evaluate the performance of IEEE 802.11ah

    Implementasi Algoritma Penjadwalan Multilevel Feedback Queue pada Aplikasi Berbasis Flutter

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    Application development has experienced a shift towards a cross-platform approach, where developers can write code once for multiple platforms. Flutter, as a fast-growing cross-platform framework with a wide community is one of the most popular cross-platform frameworks today. However, along with that, there is an increase in application complexity which makes the concept of multitasking very important. This article proposes the implementation of the Multilevel Feedback Queue (MLQ) scheduling algorithm in Flutter applications, which can help manage tasks and improve application efficiency. This research aims to examine the changes in application efficiency after the implementation of MLQ, as well as examine whether the changes remain relevant on different operating systems, namely Windows and Android. The implemented MLQ algorithm is an algorithm with adjustments to the calculation of time quantum and integration with the Shortest Job First (SJF) algorithm based on previous research. Tests were conducted using the Flutter benchmarking feature to measure the application frame rate before and after MLQ implementation on Windows and Android. The results of this study found that the implementation of MLQ increased application efficiency by 269% on the Windows operating system and 155% on the Android operating system
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