In-Band Device to Device (D2D) Communication and Device Discovery: A Survey

Hayat, Omar; Ngah, Razali; Zahedi, Yasser

doi:10.1007/s11277-019-06173-9

Cited by 40 publications

(15 citation statements)

References 46 publications

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“…Several surveys have covered the general principles and mechanisms of D2D communications [53]- [59]. Moreover, specific aspects of D2D communication have been surveyed, namely D2D communications architectures [60], device discovery for D2D communications [61], relay assisted D2D [62], and mobility [63]. The interference management for D2D links has been surveyed in [64], [65], while D2D channel models were covered in [66].…”

Section: B Related Surveys On Mec and D2d Communicationmentioning

confidence: 99%

Device-Enhanced MEC: Multi-Access Edge Computing (MEC) Aided by End Device Computation and Caching: A Survey

et al. 2019

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Multi-access edge computing (MEC) has recently been proposed to aid mobile end devices in providing compute-and data-intensive services with low latency. Growing service demands by the end devices may overwhelm MEC installations, while cost constraints limit the increases of the installed MEC computing and data storage capacities. At the same time, the ever increasing computation capabilities and storage capacities of mobile end devices are valuable resources that can be utilized to enhance the MEC. This article comprehensively surveys the topic area of device-enhanced MEC, i.e., mechanisms that jointly utilize the resources of the community of end devices and the installed MEC to provide services to end devices. We classify the device-enhanced MEC mechanisms into mechanisms for computation offloading and mechanisms for caching. We further subclassify the offloading and caching mechanisms according to the targeted performance goals, which include throughput maximization, latency minimization, energy conservation, utility maximization, and enhanced security. We identify the main limitations of the existing device-enhanced MEC mechanisms and outline future research directions. INDEX TERMS Caching, computation offloading, device-to-device (D2D) communication, mobile edge computing (MEC). I. INTRODUCTION A. MOTIVATION

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Section: B Related Surveys On Mec and D2d Communicationmentioning

confidence: 99%

Device-Enhanced MEC: Multi-Access Edge Computing (MEC) Aided by End Device Computation and Caching: A Survey

et al. 2019

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“…DD in the cellular systems and in the dense area is not given attention properly, causing invader attacks and inaccuracy [1]. In [3] authors described that to achieve a capable DD, there are several requirements such as security and privacy, energy-efficient DD, secure proximal DD in the 3GPP network. Cyber security related issues for the vehicleto-everything communications is being surveyed in [16].…”

Section: Sandp Requirements For Ddmentioning

confidence: 99%

“…it is anticipated that cooperative DD architecture will be implemented that will rely upon 5G technologies like Massive MIMO (M-MIMO), small cells, and mm-waves [3]. The 3rd Generation Partnership Project (3GPP) authority focuses on future cellular systems to help connecting 1 trillion devices [4].…”

Section: Introductionmentioning

confidence: 99%

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A Survey on Security and Privacy Challenges in Device Discovery for Next-Generation Systems

et al. 2020

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Device to Device (D2D) communications is a candidate technology for the fifth-generation (5G) and beyond mobile networks and certainly that results in high throughput, less energy consumption, reduce delay, and data traffic offload. Proximity services are the key enablers of D2D communications. A D2D technology boosts the performance and capacity of a conventional cellular system through the proximity services. To initiate the proximity services, Device Discovery (DD) is one of the the primary tasks. A DD makes the decision for effective D2D communications in terms of accuracy, speed, and minimum energy consumption. To discover the neighbor devices, the discovery signal is transmitted directly or through some access points. The discovery signal is affected by invaders during transmission which causes inaccuracy, energy consumption, and latency. Therefore, security and privacy issues must be addressed, especially in discovery signal transmission. In this paper, security and privacy issues in DD are highlighted. It is comprehensive and proves that in-band is much better than out-band with practical and technological reasons. To enhance the scope of the research, network level, and system level Security and Privacy (S&P) issues in the distributed and centralized systems environment with or without central management are surveyed. Along with an extensive survey is provided for the most recent work on DD concerning security and privacy issues, and comparison among in-band and out-band DD is performed. In the end, open issues are identified as future work on DD security and privacy in D2D communications. It is a novel survey in terms of security and privacy aspects of DD with possible suggested solutions for readers' motivation.

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“…In order to describe the random locations of cellular users, V2V users, eavesdroppers, and autopilot floating vehicles in the cellular-V2V heterogeneous system, we model the system and simulate using the Poisson point process of stochastic geometry theory: All users are nodes randomly distributed in a two-dimensional plane [38], and the position satisfies the Poisson point distribution process. There is a 5G base station with N antennas in the center.…”

Section: B Simulation Modelmentioning

confidence: 99%

Simulation of Vehicle Network Communication Security Based on Random Geometry and Data Mining

2020

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Internet of vehicles is a specific application of Internet of things technology in the field of intelligent transportation. The rapid development of 5G communication technology promotes the development of Internet of vehicles. Car for cellular network communication node random distribution and complex multi-source interference and mobile terminal security calculation ability is limited, this article in view of the actual scene, was proposed based on random geometry contains eavesdropper (Eve) honeycomb-V2V heterogeneous physical layer security system model, the introduction of automatic (PB) as artificial floating vehicle noise, the analysis of cellular network users in the system (CU), V2V users (VU) and interference of the eavesdropper, each user letter simulation with dry to noise ratio (SINR) of the cumulative distribution function, and by using the random geometry tools related safety expression deduction, Then, data mining was carried out on the distance between PB and VU receiver, PB transmitting power and other related variables through genetic algorithm, and the value process was visualized to extract valuable information, providing a mathematical analysis framework and theoretical guidance for the future design, deployment and operation of cellular vehicle network. The results show that the proposed system model can significantly improve the security of vehicle-network communication.

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In-Band Device to Device (D2D) Communication and Device Discovery: A Survey

Cited by 40 publications

References 46 publications

Device-Enhanced MEC: Multi-Access Edge Computing (MEC) Aided by End Device Computation and Caching: A Survey

Device-Enhanced MEC: Multi-Access Edge Computing (MEC) Aided by End Device Computation and Caching: A Survey

A Survey on Security and Privacy Challenges in Device Discovery for Next-Generation Systems

Simulation of Vehicle Network Communication Security Based on Random Geometry and Data Mining

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