Mobile Edge Computing (original) (raw)
Related papers
A Survey on Mobile Edge Computing
Mobile Edge Computing is an emerging technology that provides cloud and IT services within the close proximity of mobile subscribers. Traditional telecom network operators perform traffic control flow (forwarding and filtering of packets), but in Mobile Edge Computing, cloud servers are also deployed in each base station. Therefore, network operator has a great responsibility in serving mobile subscribers. Mobile Edge Computing platform reduces network latency by enabling computation and storage capacity at the edge network. It also enables application developers and content providers to serve context-aware services (such as collaborative computing) by using real time radio access network information. Mobile and Internet of Things devices perform computation offloading for compute intensive applications, such as image processing, mobile gaming, to leverage the Mobile Edge Computing services. In this paper, some of the promising real time Mobile Edge Computing application scenarios are discussed. Later on, a state-of-the-art research efforts on Mobile Edge Computing domain is presented. The paper also presents taxonomy of Mobile Edge Computing, describing key attributes. Finally, open research challenges in successful deployment of Mobile Edge Computing are identified and discussed.
Towards Mobile Edge Computing: Taxonomy, Challenges, Applications and Future Realms
Towards Mobile Edge Computing: Taxonomy, Challenges, Applications and Future Realms, 2020
The realm of cloud computing has revolutionized access to cloud resources and their utilization and applications over the Internet. However, deploying cloud computing for delay critical applications and reducing the delay in access to the resources are challenging. The Mobile Edge Computing (MEC) paradigm is one of the effective solutions, which brings the cloud computing services to the proximity of the edge network and leverages the available resources. This paper presents a survey of the latest and state-of-the-art algorithms, techniques, and concepts of MEC. The proposed work is unique in that the most novel algorithms are considered, which are not considered by the existing surveys. Moreover, the chosen novel literature of the existing researchers is classified in terms of performance metrics by describing the realms of promising performance and the regions where the margin of improvement exists for future investigation for the future researchers. This also eases the choice of a particular algorithm for a particular application. As compared to the existing surveys, the bibliometric overview is provided, which is further helpful for the researchers, engineers, and scientists for a thorough insight, application selection, and future consideration for improvement. In addition, applications related to the MEC platform are presented. Open research challenges, future directions, and lessons learned in area of the MEC are provided for further future investigation. INDEX TERMS Mobile edge computing, cloud servers, networks, edge device, smart cities, latency, energy. NOMENCLATURE APs Access points BS Base station CCBM Computational capability based matching DRL Deep reinforcement learning D2D Device-to-device E2E End-to-end ECIPs Edge computing infrastructure providers IoT Internet-of-Things IPDC Interior penalty with D.C IA Iterative algorithms JCOS Joint cache offloading solution KKT Karush-Kuhn-Tucker
An Overview of Mobile Edge Computing: Architecture, Technology and Direction
KSII Trans. Internet Inf. Syst., 2019
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.
A Comprehensive Review on Edge Computing
International Journal for Research in Applied Science & Engineering Technology (IJRASET), 2023
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.
Edge Computing: Needs, Concerns and Challenges
— 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) —————————— ——————————
Electronics
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...
Impact of Mobile Edge Computing in Real-World
Today's world is seeing an increasing usage of mobile devices and sensor rich devices such as smartphones, tablets and wearable devices such as smart watches. The volume of data that is generated by these devices is huge. Centralized cloud computing architectures cannot address the problems of network latency and jitter, degrading QoS (Quality of Service) and QoE (Quality of Experience) and other challenges in the world of mobile users. In this paper, we survey the impact of Mobile Edge Computing in the real world, an emerging edge computing technology to bring the cloud computing paradigm beyond the centralized architecture towards the edge of the network, nearer to the devices.
Mobile edge cloud architecture for future low-latency applications
2020
OF THE DISSERTATION Mobile Edge Cloud Architecture for Future Low-latency Applications by Sumit Maheshwari Dissertation Director: Dipankar Raychaudhuri This thesis presents the architecture, design, and evaluation of the mobile edge cloud (MEC) system aimed at supporting future low-latency applications. Mobile edge clouds have emerged as a solution for providing low latency services in future generations (5G and beyond) of mobile networks, which are expected to support a variety of realtime applications such as AR/VR (Augmented/Virtual Reality), autonomous vehicles and robotics. Conventional cloud computing implemented at distant large-scale data centers incurs irreducible propagation delays of the order of 50-100ms or more that may be acceptable for current applications but may not be able to support emerging real-time needs. Edge clouds considered here promise to meet the stringent latency requirements of emerging classes of real-time applications by bringing compute, storage, and...
Location-aware Resource Allocation in Mobile Edge Clouds
2021
Over the last decade, cloud computing has realized the long-held dream of computing as a utility, in which computational and storage services are made available via the Internet to anyone at any time and from anywhere. This has transformed Information Technology (IT) and given rise to new ways of designing and purchasing hardware and software. However, the rapid development of the Internet of Things (IoTs) and mobile technology has brought a new wave of disruptive applications and services whose performance requirements are stretching the limits of current cloud computing systems and platforms. In particular, novel large scale mission-critical IoT systems and latency-intolerant applications strictly require very low latency and strong guarantees of privacy, and can generate massive amounts of data that are only of local interest. These requirements are not readily satisfied using modern application deployment strategies that rely on resources from distant large cloud datacenters bec...