# PECSA: Practical Edge Computing Service Architecture Applicable to Adaptive IoT-Based Applications
###### Abstract
How to design an efficient cooperation service architecture to provide quick-response service by integrating the resources of 4G and 5G devices is still an open problem. Furthermore, due to the openness of network structure in IoT and edge networks, the security operational costs must be evaluated. To address the above -mentioned problems, we propose a practical edge service architecture including three cost evaluation schemes and a novel trust management mechanism for adaptive IoT-based applications. The proposed service architecture aims to meet the adaptive requirements of IoT-based applications, including minimum time delay, minimum service price, and minimum price within a given time. To be specific, our task offloading scheme includes two parts: (1) Which devices are reliable? That is, it is necessary to decide which devices are suited for task processing according to the available resources and historical behaviors. (2) How can we assign tasks according to the adaptive needs of users (i.e., a resource allocation problem)? How can we then transform this problem into three sub-problems: how can we assign tasks within the minimum service time? How can we assign tasks with the minimum price? Finally, how can we assign tasks with the minimum price within a given time? We transformed these problems into linear programming problems, which can be efficiently solved by the interior point method. In summary, the scientific contributions of the paper are as follows:  
1. We propose a practical edge computing service architecture that integrates a trust management methodology with dynamic cost evaluation schemes. To better allocate online resources and meet the demands of IoT-based applications, all the service requirements are divided into three categories: (1) requirements that need to be handled within the shortest time, (2) requirements that need to be completed using the minimum price, and (3) requirements that need to be handled using the minimum price within a given time. Users are allowed to choose one of the three service types according to the specific situations, while the providers are able to provide various services. 2. Our architecture is robust regardless of the relationship between data volume and computation amount. A scale factor is used to construct the relationship. Our estimation schemes change adaptively with the change in coefficients; thus, the robustness of our architecture is not be undermined by task changes. 3. The available devices are filtered before task allocation based on our trust management scheme. The service provider selects the nodes with a high trust value for data processing, and the nodes with a low trust value are rejected. The convergence time is very small, and the trust bias is acceptable. Moreover, the trust managements in the IoT and the edge networks are distinguished. The former focuses on the legality of behavior, while the latter focuses on the availability of resources. Moreover, the edge platform can monitor the edge network status to dynamically adjust the resource allocation strategies. This paper is organized as follows: Section 2 provides related works. Section 3 presents the basic concept of a novel architecture. Section 4 focuses on the design details of the architecture. Section 5 presents the experiments results and analyses. We discuss some practical issues in Section 6 and conclude this paper in Section 7.