Unmanned aerial vehicles (UAVs), such as drones, can carry high-performance computing devices (e.g., servers) to provide flexible and on-demand data processing services for the users in the network edge, leading to the so-called mobile edge computing. In mobile edge computing, researchers have already explored how to optimize the computation offloading and the trajectory planning of UAVs, as well as how to perform the service handover when mobile users move from one location to another. However, there is one critical challenge that has been neglected in past research, which is the limited battery life of UAVs. On average, commercial-level drones only have a battery life of around 30 minutes to 2 hours. As a result, during operation, mobile edge computing carriers have to frequently deal with service handovers that require shifting users and their computing jobs from low-battery UAVs to new fully-charged UAVs. This is the first work that focuses on addressing this challenge with the goal of providing continuous and uninterrupted mobile edge computing service. In particular, we propose a seamless service handover system that achieves minimum service downtime when handling the duty shift between low-battery UAVs and new fully-charged UAVs. In addition, we propose a novel UAV dispatch algorithm that provides guidelines about how to dispatch new fully-charged UAVs and where to retrieve low-battery UAVs, with the objective of maximizing UAVs' service time. The effectiveness of the proposed service handover system and the proposed UAV dispatch algorithm is demonstrated through comprehensive simulations using a time-series event-driven simulator.

Empowered by the rapid advancement of fiber optic sensing techniques in recent years, network carriers are able to upgrade their network infrastructure beyond the basic communication services with extra sensing applications and services (e.g., monitoring traffic and road condition, leakage detection, etc.), thus evolving to a new era of Infrastructure-as-a-Sensor (IaaSr) or Network-as-a-Sensor (NaaSr). When network carriers upgrade their network infrastructures with distributed fiber optic sensing (DFOS) technique to provide IaaSr services, there will arise a critical challenge: how to provide survivable (or reliable) IaaSr services against network failures (e.g., fiber cut). In this work, for the first time, we investigate the problem of survivable DFOS placement against single link failure. More specifically, we study where to place the primary and backup sensors and how to assign the primary and backup fiber sensing routes, with the objective of minimizing the number of sensors used. We formulate the problem using Integer Linear Programming (ILP) to facilitate the optimal solution. In addition, we propose a set of efficient heuristic algorithms to solve the problem in a fast manner. In particular, the proposed Shared-one algorithm provides a cost-efficient shared protection, through a one-step global optimization of the assignment of primary and backup DFOS placement. We conduct extensive simulations to evaluate the performance of the proposed solutions. We find out that Shared-one can achieve a close-to-optimal performance, compared to the ILP optimal results, while outperforming the other heuristic solutions with an average performance improvement by at least 16%.

Next generation data centers will have to face an increased amount of network traffic due to emerging applications such as cloud computing. Processing larger data volume leads to higher energy consumption, which in turn causes higher operation expense. Optical interconnects have gained attention recently as a promising solution due to its large bandwidth and high energy efficiency compared to the current networks based on commodity electrical switches. In this paper, we evaluate the energy efficiency of a novel data center network architecture based on optical multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) technology. By utilizing passive optical switch (cyclic arrayed waveguide grating) and parallel signal detection technology to detect multiple optical channels simultaneously with a single photodetector, this architecture offers high energy efficiency. The comparison with a reference design based on commodity electrical switches shows that the proposed architecture can reduce the power consumption and operation cost significantly while providing higher throughput.

As 100-Gb/s digital coherent systems enter commercial deployment, an effort is underway to uncover the technologies that will enable the next-generation optical fiber communication systems. We envisage that future optical transport will be software-defined, enabling flexible allocation of bandwidth resources, with dynamically adjustable per-channel data rates based on instantaneous traffic demand and quality-of-service requirements, leading to unprecedented network agility. Software-defined transponders will have the programmability to adopt various modulation formats, coding rates, and the signal bandwidth based on the transmission distance and type of fiber. Digital signal processing will become increasingly ubiquitous and sophisticated, capable of compensating all types of channel impairments, enabling advanced forward error correction coding, and performing functions previously handled poorly by optical analog hardware such as spectrum shaping and demultiplexing of optical channels.

In this paper, we introduce an electronic traffic grooming (E-Grooming) technique, and propose a novel bit rate and protocol independent optical-layer traffic grooming (O-Grooming) technique for OFDM-based flexible grid WDM networks. We introduce a novel routing, wavelength assignment, subcarrier assignment, and spectrum allocation (RWSSA) problem for the first time. An effective polynomial-time heuristic algorithms is proposed to address the RWSSA problem in OGrooming capable flexible grid networks. The performance of the proposed E-Grooming and O-Grooming techniques are evaluated with transparent flexible grid networks. Simulation results show that traffic grooming in flexible grid networks improve spectral efficiency compared to transparent networks. In addition to bit rate and protocol transparent, the O-Grooming technique is cost and energy efficient compared to the E-Grooming technique while marginally sacrificing the spectral efficiency.