The performance of visible light communication (VLC), as a key technology for next-generation wireless communication networks, can be significantly enhanced in terms of data rate, delay, and fairness, through the integration of optical reconfigurable intelligent surfaces (RISs). This paper introduces a novel channel model for a VLC system incorporating RIS-equipped transmitters, where the RIS is directly integrated with the VLC transmitter. This new design is shown to effectively provide beam steering (BS), enabling the concentration of optical power at desired directions with a typical 9.2dB power gain compared to a scenario without BS capability. To further illustrate the BS capability of the modeled RIS-equipped transmitter, a traffic-aware resource allocation scheme is formulated and efficiently solved using a tailored fractional programming (FP) approach with an affordable computation complexity. This approach allows to jointly optimize user association and power control by decoupling the interference interactions caused by BS. Simulation results reveal that BS-capable VLC through the proposed channel model and optimization scheme, can enhance data rate and fairness considerably while keeping delay within acceptable levels.

Mobile edge computing (MEC) is a promising technology that aims to reduce the total latency of user equipment (UE) by deploying computation resources at the edge of mobile networks. UE mobility is a challenging factor that causes the traditional MEC architecture to suffer from several issues, such as decreased efficiency and frequent service interruptions. One popular method to manage UE mobility is virtual machine (VM) migration, which requires high bandwidth and causes undesirable latency, rendering it impractical for real-time tasks with stringent latency requirements. This paper proposes a hierarchical architecture for MEC networks that facilitates mobility management and mitigates the need for VM migration. In order to utilize this architecture efficiently, a Markov chain-based predictive strategy is introduced to predict UE mobility. Afterward, an optimization problem is formulated to make the optimal long-term offloading decisions for UEs such that their expected cost is minimized subject to latency commitments and resource consumption constraints. Simulation results demonstrate that the proposed scheme reduces the cost of high-mobility UEs by up to 25% compared to traditional schemes. Furthermore, the measures of movement direction predictability and offloading decision popularity are introduced that provide insights into the behavior of the proposed and counterpart schemes.

Dynamic index coding is a practical generalization of conventional index coding that deals with real dynamic traffic streams. We identify the code-constrained capacity region of a dynamic index coding problem with a complete bi-directional side information graph and introduce the performance metric of dynamic index coding gain to measure how dynamic index coding reduces the required data transmissions. A greedy dynamic index coding scheme is proposed that achieves the maximum coding gain almost everywhere in the identified capacity region. Although the greedy scheme attains the maximum coding gain, its selfish nature may unacceptably increase transmission delay. To address this issue, a time-shared friendly dynamic index coding scheme is introduced that achieves the maximum coding gain over the entire capacity region and offers a lower delay than its greedy counterpart. To obtain the minimum delay, a constrained optimization problem is formulated to tune time-sharing weights in the friendly scheme. The closed-form solution of the optimization is derived for the special two-flow case. Furthermore, the results and analysis are extended to dynamic index coding problems with arbitrary side information graphs. We also use analytical and simulation results to provide graphical intuition for the obtained results.

Dynamic reconfigurability in optical and mobile networks can facilitate heterogeneous service provisioning while utilizing minimal resources. This allows cost-efficient service delivery resulting in high revenues for network operators. Deployment of elastic mobile and optical networks is a key driver for enabling reconfigurability in modern networks. Elastic optical networks can be exploited as the fronthaul portion of new generation of mobile networks. Such elastic optical fronthaul networks facilitate joint reconfiguration of flexible radio and optical elements and provide considerable performance improvements. In this paper, we focus on the joint dynamic selection of functional splits and configuration of optical transponders and illustrate that designing a converged network with optical and radio elements improves network power efficiency. A time-averaged stochastic optimization problem is formulated and its solution is derived using a modified version of the Lyapunov drift technique. Simulation results demonstrate that the proposed scheme can reduce the average power consumption by up to 70% compared to a cloud radio access network with a traditional optical fronthaul. Further, the results show that the modified Lyapunov technique can afford stringent fronthaul delays below 250$\mu \text{s}$. We also discuss how future technology upgrades such as increasing the number of radio antenna ports and decreasing the granularity of fiber spectrum grid may influence the results.

Slicing allows 5G networks to accommodate services with different needs over a unified physical network infrastructure. Particularly, in radio access networks (RANs), the baseband processing functions of different slices are treated as virtual applications running on shared compute nodes. Managing this cloud-native network in a cost-effective way requires tightly cou-pled control of connectivity and processing resources. This paper proposes an optimization problem to minimize the overall cost while guaranteeing distinct latency and reliability requirements of different network slices deployed over the infrastructure. This is achieved by choosing for each service, the functional split and transmission parameters that best adapt to the connectivity and processing resources available in the infrastructure. Results demonstrate that the proposed flexible resource allocation scheme provides considerable cost saving (up to 2.4 times) and reduced request blocking (up to 2 times) compared to conventional fixed deployment techniques. The reliability requirements can be guaranteed by packet duplication and/or virtualized forward error correction at the expense of consuming connectivity and/or processing resources, respectively. The flexible assurance of the reliability requirements in the proposed scheme contributes considerably to the achieved improvements on cost saving and request blocking.