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Research papers on Edge computing and IoT

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  2. Internet of Things: A Survey on Enabling Technologies, Protocols, and Applications

    Ala Al‐Fuqaha, Mohsen Guizani, Mehdi Mohammadi, et al. · 2015 · IEEE Communications Surveys & Tutorials · 8,550 citations

    This paper provides an overview of the Internet of Things (IoT) with emphasis on enabling technologies, protocols, and application issues. The IoT is enabled by the latest developments in RFID, smart sensors, communication technologies, and Internet protocols. The basic premise is to have smart sensors collaborate directly without human involvement to deliver a new class of applications. The current revolution in Internet, mobile, and machine-to-machine (M2M) technologies can be seen as the first phase of the IoT. In the coming years, the IoT is expected to bridge diverse technologies to enable new applications by connecting physical objects together in support of intelligent decision making

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  3. Fog computing and its role in the internet of things

    Flavio Bonomi, Rodolfo Milito, Jiang Zhu, et al. · 2012 · 6,059 citations

    Fog Computing extends the Cloud Computing paradigm to the edge of the network, thus enabling a new breed of applications and services. Defining characteristics of the Fog are: a) Low latency and location awareness; b) Wide-spread geographical distribution; c) Mobility; d) Very large number of nodes, e) Predominant role of wireless access, f) Strong presence of streaming and real time applications, g) Heterogeneity. In this paper we argue that the above characteristics make the Fog the appropriate platform for a number of critical Internet of Things (IoT) services and applications, namely, Connected Vehicle, Smart Grid, Smart Cities, and, in general, Wireless Sensors and Actuators Networks (W

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  4. A Survey on Mobile Edge Computing: The Communication Perspective

    Yuyi Mao, Changsheng You, Jun Zhang, et al. · 2017 · IEEE Communications Surveys & Tutorials · 5,648 citations

    Driven by the visions of Internet of Things and 5G communications, recent years have seen a paradigm shift in mobile computing, from the centralized mobile cloud computing toward mobile edge computing (MEC). The main feature of MEC is to push mobile computing, network control and storage to the network edges (e.g., base stations and access points) so as to enable computation-intensive and latency-critical applications at the resource-limited mobile devices. MEC promises dramatic reduction in latency and mobile energy consumption, tackling the key challenges for materializing 5G vision. The promised gains of MEC have motivated extensive efforts in both academia and industry on developing the

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  5. iFogSim: A toolkit for modeling and simulation of resource management techniques in the Internet of Things, Edge and Fog computing environments

    Harshit Gupta, Amir Vahid Dastjerdi, Soumya K. Ghosh, et al. · 2017 · Software Practice and Experience · 1,637 citations

    Summary Internet of Things (IoT) aims to bring every object (eg, smart cameras, wearable, environmental sensors, home appliances, and vehicles) online, hence generating massive volume of data that can overwhelm storage systems and data analytics applications. Cloud computing offers services at the infrastructure level that can scale to IoT storage and processing requirements. However, there are applications such as health monitoring and emergency response that require low latency, and delay that is caused by transferring data to the cloud and then back to the application can seriously impact their performances. To overcome this limitation, Fog computing paradigm has been proposed, where clou

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  6. A Survey on the Edge Computing for the Internet of Things

    Wei Yu, Fan Liang, Xiaofei He, et al. · 2017 · IEEE Access · 1,514 citations

    The Internet of Things (IoT) now permeates our daily lives, providing important measurement and collection tools to inform our every decision. Millions of sensors and devices are continuously producing data and exchanging important messages via complex networks supporting machine-to-machine communications and monitoring and controlling critical smart-world infrastructures. As a strategy to mitigate the escalation in resource congestion, edge computing has emerged as a new paradigm to solve IoT and localized computing needs. Compared with the well-known cloud computing, edge computing will migrate data computation or storage to the network “edge”, near the end users. Thus, a number of computa

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  7. The Promise of Edge Computing

    Weisong Shi, Schahram Dustdar · 2016 · Computer · 1,243 citations

    The success of the Internet of Things and rich cloud services have helped create the need for edge computing, in which data processing occurs in part at the network edge, rather than completely in the cloud. Edge computing could address concerns such as latency, mobile devices' limited battery life, bandwidth costs, security, and privacy.

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  8. Future Edge Cloud and Edge Computing for Internet of Things Applications

    Jianli Pan, James McElhannon · 2017 · IEEE Internet of Things Journal · 882 citations

    The Internet is evolving rapidly toward the future Internet of Things (IoT) which will potentially connect billions or even trillions of edge devices which could generate huge amount of data at a very high speed and some of the applications may require very low latency. The traditional cloud infrastructure will run into a series of difficulties due to centralized computation, storage, and networking in a small number of datacenters, and due to the relative long distance between the edge devices and the remote datacenters. To tackle this challenge, edge cloud and edge computing seem to be a promising possibility which provides resources closer to the resource-poor edge IoT devices and potenti

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  9. Edge Computing in Industrial Internet of Things: Architecture, Advances and Challenges

    Tie Qiu, Jiancheng Chi, Xiaobo Zhou, et al. · 2020 · IEEE Communications Surveys & Tutorials · 854 citations

    The Industrial Internet of Things (IIoT) is a crucial research field spawned by the Internet of Things (IoT). IIoT links all types of industrial equipment through the network; establishes data acquisition, exchange, and analysis systems; and optimizes processes and services, so as to reduce cost and enhance productivity. The introduction of edge computing in IIoT can significantly reduce the decision-making latency, save bandwidth resources, and to some extent, protect privacy. This paper outlines the research progress concerning edge computing in IIoT. First, the concepts of IIoT and edge computing are discussed, and subsequently, the research progress of edge computing is discussed and sum

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  10. Edge Computing for the Internet of Things: A Case Study

    Gopika Premsankar, Mario Di Francesco, Tarik Taleb · 2018 · IEEE Internet of Things Journal · 707 citations

    The amount of data generated by sensors, actuators, and other devices in the Internet of Things (IoT) has substantially increased in the last few years. IoT data are currently processed in the cloud, mostly through computing resources located in distant data centers. As a consequence, network bandwidth and communication latency become serious bottlenecks. This paper advocates edge computing for emerging IoT applications that leverage sensor streams to augment interactive applications. First, we classify and survey current edge computing architectures and platforms, then describe key IoT application scenarios that benefit from edge computing. Second, we carry out an experimental evaluation of

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  11. Mobile Edge Computing and Networking for Green and Low-Latency Internet of Things

    Ke Zhang, Supeng Leng, Yejun He, et al. · 2018 · IEEE Communications Magazine · 257 citations

    IoT, a heterogeneous interconnection of smart devices, is a great platform to develop novel mobile applications. Resource constrained smart devices, however, often become the bottlenecks to fully realize such developments, especially when it comes to intensive-computation-oriented and low-latency-demanding applications. MEC is a promising approach to address such challenges. In this article, we focus on MEC applications for IoT, and address energy efficiency as well as offloading performance of such applications in terms of end-user experience. In this regard, we present a mobility-aware hierarchical MEC framework for green and low-latency IoT. We deploy a game theoretic approach for computa

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  12. Joint Optimization of Energy Consumption and Latency in Mobile Edge Computing for Internet of Things

    Laizhong Cui, Chong Xu, Shu Yang, et al. · 2018 · IEEE Internet of Things Journal · 184 citations

    With wide adoption of Internet of Things (IoT) across the world, the IoT devices are facing more and more intensive computation task nowadays. However, the IoT devices are usually limited by their computing capability and battery lifetime. Mobile edge computing provides new opportunities for developments of IoT, since edge computing servers which are close to devices can provide more powerful computing resources. The IoT devices can offload the intensive computing tasks to edge computing servers, while saving their own computing resources and reducing energy consumption. However, the benefits come at the cost of higher latency, mainly due to additional transmission time, and it may be unacce

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  22. Fine-grained latency analysis of real-world 5G-enabled multi-tier edge computing for school zone traffic safety

    Ahmed Chebaane, Dominic Scholze, Yassine Rezgui, et al. · 2025 · Discover Internet of Things · 2 citations

    Abstract This article presents a real-world evaluation of 5-Safe, an innovative multi-tier 5G edge computing system designed to enhance traffic safety in school zones. The study addresses the critical challenge of implementing reliable and low-latency communication, data processing, and decision-making in complex urban environments. We employ a diverse methodology, including User Datagram Protocol (UDP) transmission analysis, Graphic Processing Unit (GPU) evaluation, and comparative studies of the messaging protocol Message Queueing Telemetry Transport (MQTT) and the Apache Kafka streaming platform. Our research revealed significant insights into syst

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  23. Optimization of Mobile Edge Computing and Networking for Ultra-Low Latency and Green Internet of Things Applications

    Prasidhee Koli · 2026 · International Journal for Research in Applied Science and Engineering Technology

    IoT growth has quietly outpaced what cloud-centric network architectures were built to handle. When billions of sensors, actuators, and embedded controllers started producing continuous data streams, the assumption that round-trip latency toadistantserverwasanacceptablecoststoppedholding.In industrial automation lines, hospital monitoring loops, and vehicle-tovehicle coordination, tens of milliseconds separate a correctly functioning system from a failed one. This paper examines Mobile Edge Computing (MEC) as a structural fix: computation moves physically closer to wheredataoriginates,cuttingpropagationdelayandrelievingbackhaul pressureatthesametime.Welookathowtaskoffloading,energy budgeting

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