A Self-Adaptive Service Discovery Model for Smart Cities

Cabrera, Christian; Clarke, Siobhán

doi:10.1109/tsc.2019.2944356

Cited by 16 publications

(9 citation statements)

References 31 publications

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“…Smart cities provide services from different domains (e.g., public transport, traffic monitoring, location services, intelligent public spaces, energy-saving, public safety, and emergency services) to support citizens' daily activities [4], [241]. Such services are likely to be deployed in large, dynamic, heterogeneous, and distributed environments that require dynamic service placement to satisfy citizens' needs [42], [242], [243].…”

Section: Smart City Servicesmentioning

confidence: 99%

Dynamic Service Placement in Multi-Access Edge Computing: A Systematic Literature Review

et al. 2022

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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.

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Section: Smart City Servicesmentioning

confidence: 99%

Dynamic Service Placement in Multi-Access Edge Computing: A Systematic Literature Review

et al. 2022

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“…In (Cabrera & Clarke 2022), authors propose a self-adaptive service model for smart cities to support service discovery. The model is based on a Deep Q-Network (DQN) algorithm to proactively adapt the service information according to three types of city events: unforeseen, scheduled, and periodic.…”

Section: Iot and Wotmentioning

confidence: 99%

Reusability and discovery models in software systems: a systematic literature review.

Criado¹,

Iribarne²

2022

JOT

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Software Engineering principles and practices promote the reuse of existing elements to maximize the performance of development and maintenance processes. The core concepts of reusability are aligned with the FAIR (Findability, Accessibility, Interoperability, and Reusability) principles. From our perspective, FAIR principles are not only related to data in a software system, because there are other resources and parts of a system that are related to data indirectly or require data schemas and models for their description and management. Examples of these resources are services, business logic processes, contracts, security policies, architectures, components, deployment resources, execution rules, or interaction alternatives, among other possible examples. Actually, any resource in a system may need to be discovered either internally by a subprocess, or externally by any client that might be interested in finding, accessing, interoperating, or reusing it. This paper addresses a systematic literature review to analyze the current principles, paradigms, and technologies that can be applied to enable discovering and reusing mechanisms in modern software systems, and how traditional and outdated approaches have been adapted to support present issues. From this analysis, we outlined the challenges and open research lines that can be addressed to achieve a suitable reuse strategy.

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“…Discovery mechanisms in IoT cover naming and addressing schemes, which help in identifying and/or locating available devices, understanding what they offer (or consume) as services and how to access them [60], [61]. In complex, heterogeneous and constantly changing environments, such as smart cities, it is crucial to implement efficient discovery mechanisms.…”

Section: Device and Service Discoverymentioning

confidence: 99%

bIoTope: Building an IoT Open Innovation Ecosystem for Smart Cities

et al. 2020

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The Internet of Things (IoT) has led towards a digital world in which everything becomes connected. Unfortunately, most of the currently marketed connected devices feed vertically-oriented closed systems (commonly referred to as vertical silos) which prevent the development of a unified global IoT. This issue is all the more valid in complex environments, such as smart cities, in which exceedingly large amounts of heterogeneous sensor data are collected, and in which platforms and stakeholders should also be able to interact and cooperate. Therefore, it is of utmost importance to move towards the creation of open IoT ecosystems to support efficient smart city service integration, discovery and composition. This paper contributes to the specifications of such an ecosystem, which has been developed as part of the EU's H2020 bIoTope project. The novelty of this ecosystem compared with the current literature is threefold: (i) it is based on the extensive use of open communication and data standards, notably O-MI and O-DF standards, that foster technical, syntactic and semantic interoperability over domains; (ii) it proposes an innovative service marketplace for data/service publication, discovery and incentivization; (iii) it integrates security functionalities at the IoT gateway level. The practicability of our ecosystem has been validated through several smart city proofs-of-concept set up in three distinct cities: Helsinki, Lyon and Brussels. Given the five major themes defined in the CITYKeys (a smart city performance indicator framework), namely People, Planet, Prosperity, Governance and Propagation, bIoTope mainly contributes to Prosperity-related metrics, as discussed in this paper.

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A Self-Adaptive Service Discovery Model for Smart Cities

Cited by 16 publications

References 31 publications

Dynamic Service Placement in Multi-Access Edge Computing: A Systematic Literature Review

Dynamic Service Placement in Multi-Access Edge Computing: A Systematic Literature Review

Reusability and discovery models in software systems: a systematic literature review.

bIoTope: Building an IoT Open Innovation Ecosystem for Smart Cities

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