Towards Mobile Edge Computing: Taxonomy, Challenges, Applications and Future Realms (original) (raw)
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An Overview of Mobile Edge Computing: Architecture, Technology and Direction
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Modern applications such as augmented reality, connected vehicles, video streaming and gaming have stringent requirements on latency, bandwidth and computation resources. The explosion in data generation by mobile devices has further exacerbated the situation. Mobile Edge Computing (MEC) is a recent addition to the edge computing paradigm that amalgamates the cloud computing capabilities with cellular communications. The concept of MEC is to relocate the cloud capabilities to the edge of the network for yielding ultra-low latency, high computation, high bandwidth, low burden on the core network, enhanced quality of experience (QoE), and efficient resource utilization. In this paper, we provide a comprehensive overview on different traits of MEC including its use cases, architecture, computation offloading, security, economic aspects, research challenges, and potential future directions.
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With the proliferation of the Internet of Things (IoT) and the development of wireless communication technologies such as 5G, new types of services are emerging and mobile data traffic is growing exponentially. The mobile computing model has shifted from traditional cloud computing to mobile edge computing (MEC) to ensure QoS. The main feature of MEC is to “sink” network resources to the edge of the network to meet the needs of delay-sensitive and computation-intensive services, and to provide users with better services. Computation offloading is one of the major research issues in MEC. In this paper, we summarize the state of the art in task offloading in MEC. First, we introduce the basic concepts and typical application scenarios of MEC, and then we formulate the task offloading problem. In this paper, we analyze and summarize the state of research in the industry in terms of key technologies, schemes, scenarios, and objectives. Finally, we provide an outlook on the challenges an...
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— In numerous parts of computing, there has been a continuous issue between the centralization and decentralization aspect which prompted to move from mainframes to PCs and local networks in the past, and union of services and applications in clouds and data centers. The expansion of technological advances such as high capacity mobile end-user devices, powerful dedicated connection boxes deployed in most homes, powerful wireless networks, and IoT (Internet of Things) devices along with developing client worries about protection, trust and independence calls for handling the information at the edge of the network. This requires taking the control of computing applications, information and services away from the core to the other the edge of the Internet. Relevance of cloud computing to mobile networks is on an upward spiral. Edge computing can possibly address the concerns of response time requirement, bandwidth cost saving, elastic scalability, battery life constraint, QoS, etc. MEC additionally offers, high bandwidth environment, ultra-low latency that gives real-time access to radio networks at the edge of the mobile network. Currently, it is being used for enabling on-demand elastic access to, or an interaction with a shared pool of reconfigurable computing resources such as servers, peer devices, storage, applications, and at the edge of the wireless network in close proximity to mobile users. It overcomes obstacles of traditional central clouds by offering wireless network information and local context awareness as well as low latency and bandwidth conservation. In this paper, we introduce edge computing and edge cloud, followed by why do we need edge computing, its classifications, various frameworks, applications and several case studies. Finally, we will present several challenges, concerns and future scope in the field of edge computing. Index Terms— Mobile Edge Computing (MEC), Internet of Things (IoT) —————————— ——————————
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The Edge computing concept has gained traction in academic and corporate circles in recent years. It serves as a key part for many future technologies like 5G, Internet of Things (IoT), augmented reality and vehicle-to-vehicle communications by connecting cloud computing services to the end users. Delay-sensitive applications benefit from the Edge computing paradigm's reduced latency, mobility, and location awareness. Significant research has been carried out in the area of Edge computing, which is reviewed in terms of latest developments such as Cloudlet, and Fog computing, resulting in providing with more insight into the existing solutions and future applications. This article is intended to be an overview of huge progress in Edge computing, with a spotlight on the most important applications.
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The Edge computing paradigm has experienced significant growth in both academic and professional circles in recent years. By linking cloud computing resources and services to the end users, it acts as a crucial enabler for several emerging technologies, including 5G, the Internet of Things (IoT), augmented reality, and vehicle-to-vehicle communications. Applications that require low latency, mobility, and location awareness are supported by the edge computing paradigm. Significant research has been done in the field of edge computing, which is examined in terms of recent advances like mobile edge computing, cloudlets, and fog computing. This has allowed academics to gain a deeper understanding of both current solutions and potential future applications. This article aims to provide a thorough overview of current developments in edge computing while emphasising the key applications. In real-world situations where response time is a crucial need for many applications, it also examines the significance of edge computing. The prerequisites and open research issues in edge computing are discussed in the article's conclusion.