A Trust-Aware Task Offloading Framework in Mobile Edge Computing

Abstract

Task offloading in Mobile Edge Computing (MEC) is a solution to augment resource-limited mobile devices' capabilities by migrating tasks to the edge of the network (i.e., edge servers and idle devices). At present, a lot of work is focused on optimizing policies to reduce latency or energy consumption for users. However, they mostly ignore that services are not necessarily trustworthy because the resource providers are complex, dynamic, and unreliable. The trustworthiness of a service in our paper mainly includes two aspects. One is that resource providers will not violate users' privacy. The other is that resource providers will perform well to ensure the effectiveness of services. To solve this problem, we propose a trust-aware task offloading framework. The main purpose of the framework is to select a resource provider for a user to reduce latency or energy consumption and ensure service trustworthiness at the same time. The framework can be divided into three modules (i.e., trust evaluation, filtering and selection). By combining trust evaluation and filtering modules, some resource providers that are not trusted by users are filtered out to ensure that the services provided to users are trustworthy. In the selection module, we select an appropriate provider for a user from the qualified (i.e., left after the filtering process) resource providers based on an offloading policy. The experimental results show that our framework not only reduces latency or energy consumption for users, but also reduces the failure rate of tasks. INDEX TERMS Mobile edge computing (MEC), task offloading, trust evaluation, machine learning, privacy protection.

Trust‐aware task load balancing in multi‐access edge computing based on blockchain and a zero trust security capability framework

“…Calculating the authentication time involves considering the time the UE takes to initiate the authentication process, the time taken for the ZTMM to process the request, and the time taken for the UE to receive the authentication response. Here is a step‐by‐step approach for calculating authentication time 12,36 : Start time measurement . Begin measuring the authentication time when the UE initiates the authentication request. Request transmission time .…”

Threat-modeling-guided Trust-based Task Offloading for Resource-constrained Internet of Things

“…In vehicle and cellular networks the task offloading problem (which we focus on in this article) is referred to as Multi-access Edge Computing (MEC) (previously Mobile Edge Computing) [47]. A variety of solutions have been proposed for trust-based offloading in MEC systems, typically involving machine learning approaches [53,80], linear programming (LP) [20], or game theoretic approaches [63]. However, these solutions are typically unsuitable for use in resource-constrained systems.…”

Trust Trackers for Computation Offloading in Edge-Based IoT Networks

“…One approach is to frame trust evaluation as a classification problem. In [17] support vector machines were trained offline and used to facilitate behavioural trust classification. A downside is that a (potentially) large quality of labelled data may needed to train a model, which may not be available or representative of behaviour that will occur.…”

“…Different works have focused on optimising task offloading for different constraints such as bandwidth [19], latency [20], energy [22] and privacy [17]. Some of these works have framed offloading as a trust evaluation task, with different definitions of what a trustor is evaluating in a trustee.…”