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Computation offloading services in Fog/Edge Computing (FEC) environments are an interesting technique for solving resource constraints on mobile devices through low latency and proximity capabilities, requiring a cost model for their commercialization. In this paper, we constructs a three-stage cooperative system prototype between mobile devices and fog/edge layers and cloud data centers, and proposes matching algorithm based on communication, offloading mechanism, and cost between them. The matching algorithm for offloading uses the basic configuration information required by the MD based on the preference rating of MD and resource specifications of ES, and it is implemented to suit the characteristics of the application service through correction of the matching context. In addition, this paper demonstrates the validity and justification of cost-based offloading services through 1:N and N:M matching experiments of MD and ES, providing great potential for application service processing in mobile devices. [ABSTRACT FROM AUTHOR]

Computation offloading technology in an FEC (Fog/Edge Computing) environment requires the process of transmitting code/data and execution results from a mobile device (MD) to an edge server (ES). In this case, a mobile agent may be used for efficient transmission of code/data. However, the mobile agent migrates with task processing commands and execution results at the time of migration, which can cause time delays and reliability degradation problems due to increased size. This paper proposes a method of securing the applicability and reliability of the mobile agent system by implementing migration algorithm and a method of reducing the weight of the mobile agent for computation offloading. In addition, we demonstrate the legitimacy of the proposed method based on the results of the migration and mounting module execution experiment of the mobile agent equipped with code/data in the FEC environment and the comparative analysis experiment of the migration time according to the size of the mobile agent. [ABSTRACT FROM AUTHOR]

We propose a two-tier cooperative computing system comprised of a mobile device and an edge server for partial offloading of multi-branch structures in Fog/Edge Computing environments in this paper. The proposed system includes an algorithm for splitting up application service processing by using reconstructive linearization techniques for multi-branch structures, as well as an optimal collaboration algorithm based on partial offloading between mobile device and edge server. Furthermore, we formulate computation offloading and CNN layer scheduling as latency minimization problems and simulate the effectiveness of the proposed system. As a result of the experiment, the proposed algorithm is suitable for both DAG and chain topology, adapts well to different network conditions, and provides efficient task processing strategies and processing time when compared to local or edge-only executions. Furthermore, the proposed system can be used to conduct research on the optimization of the model for the optimal execution of application services on mobile devices and the efficient distribution of edge resource workloads. [ABSTRACT FROM AUTHOR]

The paradigm of Internet-of-things(IoT) systems is changing from a cloud-based system to an edge-based system to solve delays caused by network congestion, server overload and security issues due to data transmission. However, edge-based IoT systems have fatal weaknesses such as lack of performance and flexibility due to various limitations. To improve performance, application-specific hardware can be implemented in the edge device, but performance cannot be improved except for specific applications due to a fixed function. This paper introduces a edge-centric metamorphic IoT(mIoT) platform that can use a variety of hardware through on-demand partial reconfiguration despite the limited hardware resources of the edge device, so we can increase the performance and flexibility of the edge device. According to the experimental results, the edge-centric mIoT platform that executes the reconfiguration algorithm at the edge was able to reduce the number of server accesses by up to 82.2% compared to previous studies in which the reconfiguration algorithm was executed on the server. [ABSTRACT FROM AUTHOR]

In the cloud computing environment, there has been a lot of research into the Fog/Edge Computing (FEC) paradigm for securing user proximity of application services and computation offloading to alleviate service delay difficulties. The method of predicting dynamic location change patterns of edge devices (moving objects) requesting application services is critical in this FEC environment for efficient computing resource distribution and deployment. This paper proposes an optimal moving pattern extraction algorithm in which variable weights (distance, time, congestion) are applied to selected paths in addition to a support factor threshold for frequency patterns (moving objects) of edge devices. The proposed algorithm is compared to the OPE_freq [8] algorithm, which just applies frequency, as well as the A* and Dijkstra algorithms, and it can be shown that the execution time and number of nodes accessed are reduced, and a more accurate path is extracted through experiments. [ABSTRACT FROM AUTHOR]