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Mixed Reality (MR) applications are becoming very popular in different sectors such as communication, education and entertainment for its extensive application areas and also for the wide adoption of mobile and especially wearable devices. Due to weak computational efficiency and short battery life of these devices, MR applications performance can be hampered. Offloading the MR application burden to the cloud server can be a solution to this problem but this approach also creates high communication latency. Mobile Edge Computing (MEC) is an emerging technology which brings cloud close to the user proximity at the base station and utilizes radio access network for maintaining communication with the users. This paper presents a MEC based MR application for assisting blind and visually impaired people. In the proposed scheme, the computational task is offloaded to the nearest MEC server in order to prolong the battery life of the MR devices. Finally, experimental results based on latency and energy consumption are discussed in order to demonstrate the feasibility of the proposed scheme.
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... Therefore, MR is not considered and no decentralized data sharing technique has been proposed in their paper. Authors in  proposed MR based application to assist the blind and visually defected person with the support of MEC server. However, they have not investigated the security issues of their proposed system. ...
Internet of Things (IoT) established the foundation of the smart world via its diverse functionalities (e.g., remote data acquisition, automated task execution). This trend continues to military applications too by introducing internet of military things (IoMT). Due to being at infancy level, new technologies require to move forward and assist IoMT to gain maturity. Mixed reality (MR) can be a potential technology which fuses the virtual and actual world. MR can improve the quality of service (QoS) in terms of inventory management, remote mission handling, battlefield assistance, etc. However, data among these applications is surrounded by cyber threats (e.g., illegal data modification, unauthorised data access). Blockchain is another promising technology which brings security in the distributed world. A content sharing scheme for MR application is proposed on the top of blockchain to bring security in the multi-user environment in IoMT. A smart contract is employed to manage security in accessing data by different users. Moreover, an experimental environment is set to observe the performance of the proposed scheme. The analysis manifests that proposed scheme maintains security without affecting the regular performance.
... HoloLens and multiple parrot bebop 2 has been used for the implementation of this system. HoloLens has IMU display and depth camera that help the visual overlay to be displayed properly . 3D map building process using video stream has been done in ground control station. ...
Natural disasters are increasing day by day as the climate crisis becomes more serious. In a disastrous situation, search and rescue missions are very risky, time-consuming, and resource constraints. A hybrid drone-assisted mixed reality-based system (termed as "MR-Drone") is proposed for conducting search and rescue operations very quickly and efficiently in a disastrous situation like an earthquake, floods, fire breakout, etc. In our proposed system, we use drone’s real-time steaming for generating a 3D map of the target area and this map can be shown in mixed reality device like HoloLens for monitoring the rescue mission. Multiple users can monitor the emergency together in a mixed reality environment using MR-Drone thus reduce the rescue time.
The augmented reality (AR) applications have been widely used in the field of Internet of Things (IoT) because of good immersion experience for users, but their ultralow delay demand and high energy consumption bring a huge challenge to the current communication system and terminal power. The emergence of mobile-edge computing (MEC) provides a good thinking to solve this challenge. In this article, we study an energy-efficient task offloading and resource allocation scheme for AR in both the single-MEC and multi-MEC systems. First, a more specific and detailed AR application model is established as a directed acyclic graph according to its internal functionality. Second, based on this AR model, a joint optimization problem of task offloading and resource allocation is formulated to minimize the energy consumption of each user subject to the latency requirement and the limited resources. The problem is a mixed multiuser competition and cooperation problem, which involves the task offloading decision, uplink/downlink transmission resources allocation, and computing resources allocation of users and MEC server. Since it is an NP-hard problem and the communication environment is dynamic, it is difficult for genetic algorithms or heuristic algorithms to solve. Therefore, we propose an intelligent and efficient resource allocation and task offloading algorithm based on the deep reinforcement learning framework of multiagent deep deterministic policy gradient (MADDPG) in a dynamic communication environment. Finally, simulation results show that the proposed algorithm can greatly reduce the energy consumption of each user terminal.
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 towards 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 technology. A main thrust of MEC research is to seamlessly merge the two disciplines of wireless communications and mobile computing, resulting in a wide-range of new designs ranging from techniques for computation offloading to network architectures. This paper provides a comprehensive survey of the state-of-the-art MEC research with a focus on joint radio-and-computational resource management. We also discuss a set of issues, challenges and future research directions for MEC research, including MEC system deployment, cache-enabled MEC, mobility management for MEC, green MEC, as well as privacy-aware MEC. Advancements in these directions will facilitate the transformation of MEC from theory to practice. Finally, we introduce recent standardization efforts on MEC as well as some typical MEC application scenarios.
Mobile augmented reality (MAR) applications are
gaining popularity due to the wide adoption of mobile and
especially wearable devices. Such devices often present limited
hardware capabilities while MAR applications often rely on computationally
intensive computer vision algorithms with extreme
latency requirements. To compensate for the lack of computing
power, offloading data processing to a distant machine is often
desired. However, if this process introduces new constrains in
the application, especially in terms of latency and bandwidth. If
current network infrastructures are not ready for such traffic,
we envision that future wireless networks such as 5G will rapidly
be saturated by resource hungry MAR applications. Moreover,
due to the high variance of wireless networks, MAR applications
should not rely only on the evolution of infrastructures. In this
article we analyze MAR applications and justify their need for
accessing external infrastructure. After a review of the existing
network infrastructures and protocols, we define guidelines for
future real-time and multimedia transport protocols, with a focus
on MAR offloading.
Augmented Reality (AR) introduces vast opportunities to the industry in terms of time and therefore cost
reduction when utilized in various tasks. The biggest obstacle for a comprehensive deployment of mobile AR is that current devices still leave much to be desired concerning computational and graphical performance.
To improve this situation in this paper we introduce an AR Edge Computing architecture with the aim to
offload the demanding AR algorithms over the local network to a high-end PC considering the real-time requirements of AR. As an example use case we implemented an AR Remote Live Support
application. Applications like this on the one hand are strongly demanded in the industry at present, on the other hand by now mostly do not implement a satisfying tracking algorithm lacking computational resources.
In our work we lay the focus on both, the possibilities our architecture offers regarding improvements
of tracking and the challenges it implies in respect of real-time. We found that offloading AR algorithms in real-time is possible with available WiFi making use of standard compression techniques
like JPEG. However it can be improved by future radio solutions offering higher bandwidth to avoid additional latency
contributed by the coding.
The emergence of several new computing applications, such as virtual reality and smart environments, has become possible due to availability of large pool of cloud resources and services. However, the delay-sensitive applications pose strict delay requirements that transforms euphoria into a problem. The cloud computing paradigm is unable to meet the requirements of low latency, location awareness, and mobility support. In this context, Mobile Edge Computing (MEC) was introduced to bring the cloud services and resources closer to the user proximity by leveraging the available resources in the edge networks. In this paper, we present the definitions of the MEC given by researchers. Further, motivation of the MEC is highlighted by discussing various applications. We also discuss the opportunities brought by the MEC and some of the important research challenges are highlighted in MEC environment. A brief overview of accepted papers in our Special Issue on MEC is presented. Finally we conclude this paper by highlighting the key points and summarizing the paper.
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.
This research investigates which uses of AR have emerged so far in marketing and proposes classification schemas for them, based on the intensity of the augmentation, different contexts of consumption and on marketing functions. Such differentiation is needed in order to better understand the dynamics of augmentation of physical surroundings for commercial purposes and consequently to distinguish between consumer experiences.
In this paper, we present an innovative Augmented Reality prototype designed for industrial education and training applications. The system uses an Optical See-Through HMD integrating a calibrated camera and a laser pointer to interactively augment an industrial object with virtual sequences designed to train a user for specific maintenance tasks. The training leverages user interactions by simply pointing on a specific object component. The architecture of our prototype involves two main vision-based modules : camera localization and user-interaction handling. The first module includes markerless trackers for camera localization, which can deal with partial occlusions and specular reflections on the metallic object surfaces. In the second module, we developed fast image processing methods for red laser dot tracking. By combining these processing elements, the proposed system is able to interactively augment in real time an industrial object making the learning process more interesting and intuitive.
Usage of augmented reality technology in daily life
is becoming more widespread. This technology is also being
applied in the field of tourism. In this study, a prototype
of mobile application for smart tourism has been developed
by using augmented reality technology. The requirements, the
competences and incompleteness of the methods is described.
The prototype application is developed in the pilot region of
Gökova Mu˘gla. This application aims to introduce important
centers, touristic places, restaurants, hotels and sightseeing places
to domestic and foreign tourists. The intensity, ratings, comments,
current social media data and price information about these
areas will be provided simultaneously on the mobile application.
Image processing techniques and location data will be used for
implementing augmented reality technology.
Mobile Edge Computing (MEC) is an emergent architecture where cloud computing services are extended to the edge of networks leveraging mobile base stations. As a promising edge technology, it can be applied to mobile, wireless and wireline scenarios, using software and hardware platforms, located at the network edge in the vicinity of end-users. MEC provides seamless integration of multiple application service providers and vendors towards mobile subscribers, enterprises and other vertical segments. It is an important component in the 5G architecture which supports variety of innovative applications and services where ultra low latency is required. This paper is aimed to present a comprehensive survey of relevant research and technological developments in the area of MEC. It provides the definition of MEC, its advantages, architectures, and application areas; where we in particular highlight related research and future directions. Finally, security and privacy issues and related existing solutions are also discussed.
To ensure continued competitiveness of 3G technology for the next decade, 3GPP is establishing evolution plans that are following introduction of HSDPA and Enhanced Uplink. The new major step is known as 3G Long Term Evolution (LTE) and is based on several promising technologies, like OFDM and MIMO, involving also the System Architecture Evolution (SAE). Major performance goals addressed by LTE are significantly increased peak data rates, reduced latency, spectrum efficiency, together with lower cost and complexity. This paper presents main mechanisms applied for improving latency in new, evolved system, both in control and user plane.
[poster] classifications of augmented reality uses in marketing