Smart cars, with the emergence of the Internet of Vehicles (IoV), are expected to generate huge volumes of data at rates that typical data management systems will not be able to handle. Such data can be extremely useful to both analytics and machine learning applications. This paper discusses and demonstrates the process of architecting and building a scalable data management system for the IoV in

The massive data exchange between base stations and network backhaul creates a strong overhead on mobile networks, especially at peak times. This motivates researchers to think about the proactive caching concept which depends mainly on caching some of the expected data items during off-peak times. The caching problem consists of two distinct phases, placement phase and delivery phase. In this

In this paper, we introduce a novel geographic routing with cooperation scheme for 5G Device-to-Device ad hoc networks. The prime focus of our scheme (coined Cooperative Routing for Reliable Paths (CRRP)) is to enhance the routing performance in cooperative communication networks in terms of the path length and reliability. In particular, it introduces novel algorithms for cooperative relay and

In this paper, we exploit tools from stochastic geometry to characterize the average probability of successful content delivery in a cache-enabled device-to-device (D2D) network under Nakagami- m fading. Specifically, we focus on the impact of temporal interference correlation due to erroneous packets retransmissions. The aggregate network interference is characterized under a slotted Aloha scheme

Harnessing information about the user mobility pattern and daily demand can enhance the network capability to improve the quality of experience (QoE) at Vehicular Ad- Hoc Networks (VANETs). Proactive caching, as one of the key features offered by 5G networks, has lately received much interest. However, more research is still needed to convey large-sized multimedia content including video, audio

Caching at Roadside Units (RSUs) is a promising technique to alleviate the load on network backhaul in Vehicular AdHoc Networks (VANETs). It also allows us to minimize communications latency between RSUs and connected vehicles, which are interested in massive multimedia contents. This work proposes novel proactive caching schemes at RSUs for the city mobility environment. We adopt the Manhattan

In this paper, we present an indoor visible light communication (VLC) system to estimate the position of a moving user. This system uses two approaches based on received signal strength, trilateration estimation, and neural network estimation. In the VLC system, each transmitter sends its position information via light. A photo-detector receiver supported with the moving user is used to receive

Recently, emerging vehicular applications are increasing the demand of vehicles which form significant burdens on network backhaul and represents a cause to the quality of experience (QoE) decay of the vehicular users. Proactive caching is a promising technique to mitigate the load on core networks by caching some of the expected data items. This work proposes a hierarchical proactive caching

This paper studies the Multi-Input-Multi-Output (MIMO) interference networks with arbitrary number of transmitters and receivers, where both the transmitters and receivers are equipped with caches. Our objective is to propose content placement and delivery schemes that minimize the worst case normalized delivery time (NDT). First, we design a delivery scheme for the cache-aided Single-Input

Energy efficiency (EE) is one of the main parameters to be considered in recent networks targeting green technology. Our system is based on cloud radio access networks and it consists of a macro base-station and many small remote radio heads (RRHs). We solve an optimization problem to improve the system's EE through resource allocation and power control. We also reduce the power consumption