BIECS: A Blockchain-based Intelligent Edge Cooperation System for Latency-Sensitive Services

Although the emerging edge computing paradigm offers a promising approach to overcoming some limitations of conventional cloud computing, the heterogeneous edge nodes with highly diverse system capacities bring new challenges to service provisioning especially for latency-sensitive services. Cooperative edge computing (CEC) has been proposed for facing such challenges through resource sharing among edge nodes. However, some technical issues must be fully addressed to make CEC effective, among which incentive and trust mechanisms and performance optimization are crucial for latency-sensitive service provision. In this paper, we design a novel blockchain-based intelligent edge cooperation system named BIECS to tackle these challenges systematically. BIECS provides incentive to edge nodes for resource sharing and enables trust among cooperative nodes upon a distributed platform leveraging the blockchain technology. In order to optimize system performance for meeting the requirements of latency-sensitive services, we propose a two-stage strategy for node selection in BIECS that chooses the most appropriate edge nodes for executing offloaded tasks and recording related transactions in the blockchain. We also implemented a prototype of BIECS based on Hyperledger Fabric and conducted extensive experiments for evaluating the performance of BIECS. The obtained experiment results verify that the proposed BIECS achieves better performance in system delay and throughput compared to the state-of-the-art methods for edge cooperation.

I. Introduction

With the rapid development of the 5G network and the Internet of Things (IoT), the number and capacity of user devices are growing exponentially. The emerging edge computing paradigm essentially deploys cloud-like computation and storage capabilities on some network devices (referred to as edge nodes) located at network edge in proximity of user devices [1], which may significantly reduce system delay thus facilitating provision of latency-sensitive services. Edge nodes have a wide variety of implementations with different amounts of computing and storage capacities, ranging from 5G network gateways hosted on high-performance servers to IoT access points implemented on a Raspberry-Pi platform with very constrained resources. Therefore, some edge nodes might lack sufficient resources for completing their tasks in time while other edge nodes have under-utilized resources [2]. In order to address this issue for further enhancing edge service performance, cooperative edge computing (CEC) has been proposed to enable multiple edge nodes interconnected through a network to collaborate for resource sharing. As shown in Fig. 1, in CEC, an overloaded edge node may offload some of its tasks to other edge nodes in order to fully utilize the available resources on various edge nodes for meeting service requirements [3].