With advances in the information and communication technology (ICT), connected vehicles are one of the key enablers to unleash intelligent transportation systems (ITS). On the other hand, the envisioned massive number of connected vehicles raises the need for powerful communication and computation capabilities. As an emerging technique, fog computing is expected to be integrated with existing communication infrastructures, giving rise to a concept of fog-enhanced radio access networks (FeRANs). Such architecture brings computation capabilities closer to vehicular users, thereby reducing communication latency to access services, while making users capable of sharing local environment information for advanced vehicular services. In the FeRANs service migration, where the service is migrated from a source fog node to a target fog node following the vehicle's moving trace, it is necessary for users to access service as close as possible in order to maintain the service continuity and satisfy stringent latency requirements of real-time services. Fog servers, however, need to have sufficient computational resources available to support such migration. Indeed, a fog node typically has limited resources and hence can easily become overloaded when a large number of user requests arrive, e.g., during peak traffic, resulting in degraded performance. This paper addresses resource management in FeRANs with a focus on management strategies at each individual fog node to improve quality of service (QoS), particularly for real-time vehicular services. To this end, the paper proposes two resource management schemes, namely fog resource reservation and fog resource reallocation. In both schemes, real-time vehicular services are prioritized over other services so that their respective vehicular users can access the services with only one hop. Simulation results show that the proposed schemes can effectively improve one-hop access probability for real-time vehicular services implying low delay performance, even when the fog resource is under heavy load.

The advent of Internet of Things and 5G applications renders the need for integration of both centralized cloud computing and emerging mobile-edge computing (MEC) with existing network infrastructures to enhance storage, processing, and caching capabilities in not only centralized but also distributed fashions for supporting both delay-tolerant and mission-critical applications. This paper investigates performance gains of centralized cloud and MEC enabled integrated fiber-wireless (FiWi) access networks. A novel unified resource management scheme incorporating both centralized cloud and MEC computation offloading activities into the underlying FiWi dynamic bandwidth allocation process is proposed. Both MEC and cloud traffic are scheduled outside the transmission slot of FiWi traffic by leveraging time division multiple access. An analytical framework is developed to model packet delay, response time efficiency, gain-offload overhead ratio, and communication-to-computation ratio for both cloud and broadband access traffic. In addition, given the importance of reliability in optical backhaul and MEC, this paper develops a probabilistic survivability analysis model to assess the impact of both fiber cuts and MEC server failures. The obtained results demonstrate the feasibility of implementing conventional cloud and MEC in FiWi access networks, without affecting network performance of broadband access traffic.

This paper proposes to enhance capacity-centric fiber-wireless (FiWi) broadband access networks based on data-centric Ethernet technologies with computation- and storage-centric cloudlets to provide reliable cloud services at the edge of FiWi networks and thereby realize the vision of mobile-edge computing (MEC). To reduce offload delay and prolong battery life of edge devices, a novel cloudlet-aware resource management scheme is proposed that incorporates offloading activities into the underlying FiWi dynamic bandwidth allocation process. The whole system is designed in two time division multiple access layers to enhance the network performance. To allow for the efficient coexistence of FiWi and MEC traffic, the offloaded traffic is scheduled outside the FiWi transmission slots. To thoroughly study the scheme's performance, a comprehensive analytical framework is developed that covers a rich set of performance metrics, including packet delay of both FiWi and MEC traffic, response time efficiency, offload gain-overhead ratio, energy efficiency, and battery life. Analytical results demonstrate the feasibility and effectiveness of the cloudlet-enhanced FiWi networks for MEC by employing the proposed solution. Further, we develop an experimental testbed to validate the accuracy of our analytical model via real-world measurements.

This paper deals with resource management in data centre networks that feature optical interconnects. It first proposes an optical resource management framework as a platform to develop different solutions for multipoint-to-multipoint optical communication systems with a centralized controller. The paper takes optical intra-rack communications as an example application scenario of the framework and studies the intra-rack scheduling (IRS) problem using a theoretical approach. The problem is mapped into the classical open-shop scheduling problem, in which the optical interfaces are viewed as the jobs and the wavelengths used for communication among the interfaces are viewed as the machines. The IRS problem can therefore be solved by adopting the existing preemptive and/or non-preemptive open-shop scheduling algorithms. In a realistic intra-rack communication scenario with non-negligible network reconfiguration time, it is important to understand whether the preemptive or non-preemptive strategy provides better performance under given traffic conditions and system configurations. To address the question, this paper presents a performance analysis that allows to quantitatively compare the two scheduling strategies in terms of packet delay and potential energy savings obtained from sleep mode implementation. Analytical results reveal that the non-preemptive strategy outperforms the preemptive one for typical configurations used in data centre networks. In addition, the tuning and wake-up times of optical transceivers are shown to be key performance-determining factors. The proposed framework and obtained findings are not limited to the considered intra-rack communication scenario, but can be applied to any centralized optical switching systems featuring multipoint-to-multipoint transmissions with non-negligible reconfiguration time.

This paper aims at designing an ecoconscious future-proof sensor enhanced fiber-wireless (SFiWi) network based on EPON, WLAN, wireless sensor (WS), and fiber optic sensor (FOS) technologies as a shared communications infrastructure for broadband access and smart grids. A total cost of ownership (TCO) model is developed to help utilities decide whether to deploy WSs or FOSs in different scenarios and estimate sensor-related costs. To prolong battery life of wireless devices and maximize the overall energy efficiency, a novel energy conservation scheme for SFiWi networks (ECO-SFiWi) is proposed. ECO-SFiWi designs the whole network in three TDMA layers to enhance network performance, while scheduling network components to sleep outside their transmission slots. A comprehensive energy saving model accounting for both optical backhaul and wireless front-end components and a delay analysis based on M/G/1 queuing are presented. Results reveal that with their extremely long lifetime and ability to sustain in harsh environments, FOSs are superior to WSs when advanced interrogation techniques are deployed to reduce their total cost. ECO-SFiWi achieves more than 89% of energy savings, while maintaining low delay for both broadband and smart grid traffic in typical scenarios. FPGA hardware emulation and analytical results match well verifying the effectiveness of ECO-SFiWi.

Fiber-wireless sensor networks (Fi-WSNs) composed of a hybrid fiber-wireless (FiWi) network enhanced with sensors will play a key role in supporting machine-to-machine (M2M) communications to enable a wide range of Internet of Things (IoT) applications, of which smart grids represent an important real-world example. This paper explores opportunities of designing an energy-efficient Fi-WSN based on EPON/10G-EPON, WLAN, wireless sensors, and passive fiber optic sensors as a shared communications infrastructure for broadband services and smart grids. A novel energy conservation scheme for sensor enhanced FiWi networks (ECO-SFiWi) is proposed to reduce the overall energy consumption. ECO-SFiWi maximizes energy efficiency by leveraging TDMA to schedule power-saving modes of EPON's optical network units, wireless stations, and wireless sensors and incorporate them into EPON's bandwidth allocation algorithm. To study the performance, a comprehensive energy saving model and a delay analysis of both FiWi traffic and sensor data based on M/G/1 queue modeling are presented. FPGA-based hardware emulation and demonstration are performed to verify the effectiveness of the proposed solution. Results provide deep insights into the tradeoff between energy savings and frame delays. Noticeably, ECO-SFiWi achieves significant amounts of energy saving, while maintaining low delay for FiWi traffic and sensor data under typical deployment scenarios.

Integrated fiber-wireless (FiWi) access networks aim at taking full advantage of the reliability and high capacity of the optical backhaul along with the flexibility, ubiquity, and cost savings of the wireless/cellular front-end to provide broadband services for both mobile and fixed users. In FiWi access networks, energy efficiency issues must be addressed in a comprehensive fashion that takes into account not only wireless front-end but also optical backhaul segments to extend the battery life of wireless devices and allow operators to reduce their OPEX, while not compromising quality of service (QoS). This paper proposes an energy conservation scheme for FiWi networks (ECO-FiWi) that jointly schedules power-saving modes of wireless stations and access points and optical network units to reduce their energy consumption. ECO-FiWi maximizes the overall network performance by leveraging TDMA to synchronize the power-saving modes and incorporate them into the dynamic bandwidth allocation (DBA) process. A comprehensive energy saving model and an M/G/1 queuing-based analysis of downstream and upstream end-to-end frame delays are presented accounting for both backhaul and front-end network segments. Analytical results show that ECO-FiWi achieves significant amounts of energy saving, while preserving upstream delay and incurring a low delay for downstream traffic.

We previously proposed and numerically analyzed a theoretical framework of an energy-efficient offline dynamic wavelength and bandwidth allocation (DWBA) algorithm designed for a delay-constrained time and wavelength division multiplexed passive optical network (TWDM-PON). This DWBA algorithm exploits the tunability and the sleep/doze capabilities of a 10 Gbps vertical-cavity surface-emitting optical network unit (10G-VCSEL-ONU) to improve the energy-savings at the OLT and the ONUs, respectively. In this work, using simulation results on the number of active wavelengths and the percentage of energy-savings, we verify the theoretical framework proposed in our previous study. Most importantly, we show that the average delay of upstream packets are not adversely affected by the proposed energy-saving mechanism and is kept below the specified maximum.

This paper proposes an advanced sleep-aware dynamic bandwidth allocation (ASDBA) scheme for 10G-EPONs that aims to maximize ONU energy efficiency with sleep mode. In the proposed ASDBA scheme, both upstream (US) and downstream (DS) transmissions are scheduled in the same transmission slot whose duration is minimized based on both DS and US bandwidth requests and the ONU transceiver is switched off outside the slot for saving energy. The ASDBA swaps the conventional order of control message exchange utilized in legacy 10G-EPON to convert the ONU idle time between a REPORT message and its replying GATE message into ONU sleep time. This enables the ONU to sleep continuously after sending a REPORT message until the beginning of the next transmission slot, further improving ONU energy-savings. Results show that the proposed scheme significantly saves ONU energy whilst incurring acceptable frame queuing delays.

This paper presents the experimental evaluation of an energy-efficient TDMA PON utilizing cyclic sleep technique. In particular, two methods for deciding when to trigger ONU sleep mode are evaluated: downstream (DS)-based triggering and Cooperative triggering. In the former method, the decision whether the ONU is switched to sleep is taken based on the DS traffic only. In the latter one, the decision is taken by considering both DS and upstream (US) traffic. The performance is assessed with constant sleep time as well as variable sleep time for different DS/US traffic ratios. Experimental results show that both triggering methods achieve significant energy savings. The Cooperative saves slightly less energy than the DS-based while providing better network performance, in terms of frame loss rate and frame delay, for both DS and US traffic.