Digital Twin is a new concept that consists of creating an up-to-date virtual asset in the cyberspace which mimics the original physical asset in most of its aspects, ultimately to monitor, analyze, test, and optimize the physical asset. In this paper, we investigate and discuss the use of the digital twin concept of the roads as a step towards realizing the dream of smart cities. To this end, we propose the deployment of a Digital Twin Box to the roads that is composed of a 360 • camera and a set of IoT devices connected to a Single Onboard Computer. The Digital Twin Box creates a digital twin of the physical road asset by constantly sending real-time data to the edge/cloud, including the 360 • live stream, GPS location, and measurements of the temperature, humidity. This data will be used for real-time monitoring and other purposes by displaying the live stream via head-mounted devices or using a 360 • web-based player. Additionally, we perform an object detection process to extract all possible objects from the captured stream. For some specific objects (person and vehicle), an identification module and a tracking module are employed to identify the corresponding objects and keep track of all video frames where these objects appeared. The outcome of the latter step would be of outermost importance to many other services and domains such as the national security. To show the viability of the proposed solution, we have implemented and conducted real-world experiments where we focus more on the detection and recognition processes. The achieved results show the effectiveness of the proposed solution in creating a digital twin of the roads, a step forward to enable self-driving vehicles as a crucial component of the smart mobility, using the Digital Twin Box.
The many advantages of Dynamic Adaptive streaming over HTTP (DASH) made it one of the most prevalent video streaming technologies in recent years. Unfortunately, many studies have unveiled the QoE issue of users when multiple DASH clients compete for the bandwidth of a bottleneck link. This issue consists of several aspects, namely the frequent encoding changes, the unfair bandwidth allocation, the inefficient bandwidth utilization, and the relatively long convergence time. These aspects are indeed conflicting each other and resolving them entails tradeoffs. In this paper, we propose a new mathematical model that leverages a score matrix to ensure a fair sharing of the server's bottleneck link between competing clients and satisfies the requests of as many clients as possible and that is for efficient bandwidth utilization. The proposed solution is compared against notable solutions through computer-based simulations, and the results show that the proposed solution achieves high scores in terms of both efficiency and fairness.
Network Function Virtualization (NFV) ecosystem enables the automation of deployment and scaling of softwarized network services (SNSs), thus reducing their operational expenditures. This enables operators to handle workload fluctuations, to keep the desired performance, with great agility and reduced costs. However, to realize the automation of such management practices, it is needed to determine the amount of required resources to allocate the SNS so that its performance requirements are met. This problem is commonly referred to as resources dimensioning problem. In this paper, we address the derivation of a closed-form expression for the optimal resources dimensioning of an SNS in terms of cost or energy efficiency. The performance requirement considered for the SNS is a limit on its mean response time. The performance model considered for the SNS is practical and accurate. The usefulness of the derived closedform expression is successfully validated by means of simulation. The scenario considered for the validation is a video optimization chain located at the SGi-LAN of a mobile network.
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