Service placement in the continuum: A systematic literature review

Despite the importance of resource allocation issues, there is no systematic, comprehensive and detailed survey on resource allocation approaches in the fog-computing context. In this article, we provide a Systematic Literature Review (SLR) on the resource allocation approaches in fog environments in the form of a classical taxonomy to recognize the state-of-the-art mechanisms on this important topic and provide open issues. The presented taxonomy is categorized into three main fields: centralized allocation, decentralized allocation, and integrated allocation (published between 2017 and March 2022). According to what is known in fog computing, load balancing and service placement are among the most important basic parameters that ensure service quality. These fields are classified into four methods, approximate, exact, fundamental, and hybrid. In addition, this article investigates resource allocation metrics with all advantages and limitations related to chosen resource allocation mechanisms in networks.

The advent of new cloud-based applications such as mixed reality, online gaming, autonomous driving, and healthcare has introduced infrastructure management challenges to the underlying service network. Multi-access edge computing (MEC) extends the cloud computing paradigm and leverages servers near end-users at the network edge to provide a cloud-like environment. The optimum placement of services on edge servers plays a crucial role in the performance of such service-based applications. Dynamic service placement problem addresses the adaptive configuration of application services at edge servers to facilitate end-users and those devices that need to offload computation tasks. While reported approaches in the literature shed light on this problem from a particular perspective, a panoramic study of this problem reveals the research gaps in the big picture. This paper introduces the dynamic service placement problem and outline its relations with other problems such as task scheduling, resource management, and caching at the edge. We also present a systematic literature review of existing dynamic service placement methods for MEC environments from networking, middleware, applications, and evaluation perspectives. In the first step, we review different MEC architectures and their enabling technologies from a networking point of view. We also introduce different cache deployment solutions in network architectures and discuss their design considerations. The second step investigates dynamic service placement methods from a middleware viewpoint. We review different service packaging technologies and discuss their trade-offs. We also survey the methods and identify eight research directions that researchers follow. Our study categorises the research objectives into six main classes, proposing a taxonomy of design objectives for the dynamic service placement problem. We also investigate the reported methods and devise a solutions taxonomy comprising six criteria. In the third step, we concentrate on the application layer and introduce the applications that can take advantage of dynamic service placement. The fourth step investigates evaluation environments used to validate the solutions, including simulators and testbeds. We introduce real-world datasets such as edge server locations, mobility traces, and service requests used to evaluate the methods. We compile a list of open issues and challenges categorised by various viewpoints in the last step.