Advanced DSP Techniques for High-Capacity and Energy-Efficient Optical Fiber Communications

The rapid proliferation of the Internet has been driving communication networks closer and closer to their limits, while available bandwidth is disappearing due to an ever-increasing network load. Over the past decade, optical fiber communication technology has increased per fiber data rate from 10 Tb/s to exceeding 10 Pb/s. The major explosion came after the maturity of coherent detection and advanced digital signal processing (DSP). DSP has played a critical role in accommodating channel impairments mitigation, enabling advanced modulation formats for spectral efficiency transmission and realizing flexible bandwidth. This book aims to explore novel, advanced DSP techniques to enable multi-Tb/s/channel optical transmission to address pressing bandwidth and power-efficiency demands. It provides state-of-the-art advances and future perspectives of DSP as well

Energy-efficient routing algorithms based on swarm intelligence for wireless sensor networks

High efficient routing is an important factor to be considered in the design of limited energy resource Wireless Sensor Networks (WSNs). WSN environment has limited resources in terms of on-board energy, transmission power, processing, and storage, and this prompt for careful resource management and new routing protocol so as to counteract the challenges. This work first introduces the concept of wireless sensor networks, routing in WSNs, and its design factors as they affect routing protocols. Next, a comprehensive review of the most prominent routing protocols in WSN, from the classical routing protocols to swarm intelligence based protocols is presented. From the literature study, it was found that comparing routing protocols in WSNs is currently a very challenging task for protocol designers. Often, much time is required to re-create and re-simulate algorithms from descriptions in published papers to perform the comparison. Compounding the difficulty is that some simulation parameters and performance metrics may not be mentioned. We then see a need in the research community to have standard simulation and performance metrics for comparing different protocols. To this end, we re-simulate different protocols using a Matlab based simulator; Routing Modeling Application Simulation Environment (RMASE), and gives simulation results for standard simulation and performance metrics which we hope will serve as a benchmark for future comparisons for the research community. Also, from the literature study, Energy Efficient Ant-Based Routing (EEABR) protocol was found to be the most efficient protocol due to its low energy consumption and low memory usage in WSNs nodes. Following this efficient protocol, an Improved Energy Efficient Ant-Based Routing (IEEABR) Protocol was proposed. Simulation were performed using Network Simulator-2 (NS-2), and from the results, our proposed algorithm performs better in terms of energy utilization efficiency, average energy of network nodes, and minimum energy of nodes. We further improved on the proposed protocol and simulation performed in another well-known WSNs MATLAB-based simulator; Routing Modeling Application Simulation Environment (RMASE), using static, mobile and dynamic scenario. Simulation results show that the proposed algorithm increases energy efficiency by up to 9% and 64% in converge-cast and target-tracking scenarios, respectively, over the original EEABR and also found to out-perform other four Ant-based routing protocols. We further show how this algorithm could be used for energy management in sensor network in the presence of energy harvesters. However, high number of control packets is generated by the IEEABR due to the proactive nature of its path establishment. As such, a new routing protocol for WSNs that has less control packets due to its on-demand (reactive) nature is proposed. This new routing protocol termed Termite-hill is borrowed from the principles behind the termite’s mode of communication. We first study the foraging principles of a termite colony and utilize the inspirational concepts to develop a distributed, simple and energy-efficient routing protocol for WSNs. We perform simulation studies to compare the behavior and performance of the Termite-hill design with an existing classical and on-demand protocol (AODV) and other Swarm Intelligence (SI) based WSN protocols in both static, dynamic and mobility scenarios of WSN. The simulation results demonstrate that Termite-hill outperforms its competitors in most of the assumed scenarios and metrics with less latency. Further studies show that the current practice in modeling and simulation of wireless sensor network (WSN) environments has been towards the development of functional WSN systems for event gathering, and optimization of the necessary performance metrics using heuristics and intuition. The evaluation and validation are mostly done using simulation approaches and practical implementations. Simulation studies, despite their wide use and merits of network systems and algorithm validation, have some drawbacks like long simulation times, and practical implementation might be cost ineffective if the system is not properly studied before the design. We therefore argue that simulation based validation and practical implementation of WSN systems and environments should be further strengthened through mathematical analysis. To conclude this work and to gain more insight on the behavior of the termite-hill routing algorithm, we developed our modeling framework for WSN topology and information extraction in a grid based and line based randomly distributed sensor network. We strengthen the work with a model of the effect of node mobility on energy consumption of Termite-hill routing algorithm as a function of event success rate and occasional change in topology. The results of our mathematical analysis were also compared with the simulation results

Multi-Dimensional Resource Orchestration in Vehicular Edge Networks

In the era of autonomous vehicles, the advanced technologies of connected vehicle lead to the development of driving-related applications to meet the stringent safety requirements and the infotainment applications to improve passenger experience. Newly developed vehicular applications require high-volume data transmission, accurate sensing data collection, and reliable interaction, imposing substantial constrains on vehicular networks that solely rely on cellular networks to fetch data from the Internet and on-board processors to make driving decisions. To enhance multifarious vehicular applications, Heterogeneous Vehicular Networks (HVNets) have been proposed, in which edge nodes, including base stations and roadside units, can provide network connections, resulting in significantly reduced vehicular communication cost. In addition, caching servers are equipped at the edge nodes, to further alleviate the communication load for backhaul links and reduce data downloading delay. Hence, we aim to orchestrate the multi-dimensional resources, including communication, caching, and sensing resources, in the complex and dynamic vehicular environment to enhance vehicular edge network performance. The main technical issues are: 1) to accommodate the delivery services for both location-based and popular contents, the scheme of caching contents at edge servers should be devised, considering the cooperation of caching servers at different edge nodes, the mobility of vehicles, and the differential requirements of content downloading services; 2) to support the safety message exchange and collective perception services for vehicles, communication and sensing resources are jointly allocated, the decisions of which are coupled due to the resource sharing among different services and neighboring vehicles; and 3) for interaction-intensive service provisioning, e.g., trajectory design, the forwarding resources in core networks are allocated to achieve delay-sensitive packet transmissions between vehicles and management controllers, ensuring the high-quality interactivity. In this thesis, we design the multi-dimensional resource orchestration schemes in the edge assisted HVNets to address the three technical issues. Firstly, we design a cooperative edge caching scheme to support various vehicular content downloading services, which allows vehicles to fetch one content from multiple caching servers cooperatively. In particular, we consider two types of vehicular content requests, i.e., location-based and popular contents, with different delay requirements. Both types of contents are encoded according to fountain code and cooperatively cached at multiple servers. The proposed scheme can be optimized by finding an optimal cooperative content placement that determines the placing locations and proportions for all contents. To this end, we analyze the upper bound proportion of content caching at a single server and provide the respective theoretical analysis of transmission delay and service cost (including content caching and transmission cost) for both types of contents. We then formulate an optimization problem of cooperative content placement to minimize the overall transmission delay and service cost. As the problem is a multi-objective multi-dimensional multi-choice knapsack one, which is proved to be NP-hard, we devise an ant colony optimization-based scheme to solve the problem and achieve a near-optimal solution. Simulation results are provided to validate the performance of the proposed scheme, including its convergence and optimality of caching, while guaranteeing low transmission delay and service cost. Secondly, to support the vehicular safety message transmissions, we propose a two-level adaptive resource allocation (TARA) framework. In particular, three types of safety message are considered in urban vehicular networks, i.e., the event-triggered message for urgent condition warning, the periodic message for vehicular status notification, and the message for environmental perception. Roadside units are deployed for network management, and thus messages can be transmitted through either vehicle-to-infrastructure or vehicle-to-vehicle connections. To satisfy the requirements of different message transmissions, the proposed TARA framework consists of a group-level resource reservation module and a vehicle-level resource allocation module. Particularly, the resource reservation module is designed to allocate resources to support different types of message transmission for each vehicle group at the first level, and the group is formed by a set of neighboring vehicles. To learn the implicit relation between the resource demand and message transmission requests, a supervised learning model is devised in the resource reservation module, where to obtain the training data we further propose a sequential resource allocation (SRA) scheme. Based on historical network information, the SRA scheme offline optimizes the allocation of sensing resources (i.e., choosing vehicles to provide perception data) and communication resources. With the resource reservation result for each group, the vehicle-level resource allocation module is then devised to distribute specific resources for each vehicle to satisfy the differential requirements in real time. Extensive simulation results are provided to demonstrate the effectiveness of the proposed TARA framework in terms of the high successful reception ratio and low latency for message transmissions, and the high quality of collective environmental perception. Thirdly, we investigate forwarding resource sharing scheme to support interaction intensive services in HVNets, especially for the delay-sensitive packet transmission between vehicles and management controllers. A learning-based proactive resource sharing scheme is proposed for core communication networks, where the available forwarding resources at a switch are proactively allocated to the traffic flows in order to maximize the efficiency of resource utilization with delay satisfaction. The resource sharing scheme consists of two joint modules: estimation of resource demands and allocation of available resources. For service provisioning, resource demand of each traffic flow is estimated based on the predicted packet arrival rate. Considering the distinct features of each traffic flow, a linear regression scheme is developed for resource demand estimation, utilizing the mapping relation between traffic flow status and required resources, upon which a network switch makes decision on allocating available resources for delay satisfaction and efficient resource utilization. To learn the implicit relation between the allocated resources and delay, a multi-armed bandit learning-based resource sharing scheme is proposed, which enables fast resource sharing adjustment to traffic arrival dynamics. The proposed scheme is proved to be asymptotically approaching the optimal strategy, with polynomial time complexity. Extensive simulation results are presented to demonstrate the effectiveness of the proposed resource sharing scheme in terms of delay satisfaction, traffic adaptiveness, and resource sharing gain. In summary, we have investigated the cooperative caching placement for content downloading services, joint communication and sensing resource allocation for safety message transmissions, and forwarding resource sharing scheme in core networks for interaction intensive services. The schemes developed in the thesis should provide practical and efficient solutions to manage the multi-dimensional resources in vehicular networks

Centralized and partial decentralized design for the Fog Radio Access Network

Fog Radio Access Network (F-RAN) has been shown to be a promising network architecture for the 5G network. With F-RAN, certain amount of signal processing functionalities are pushed from the Base Station (BS) on the network edge to the BaseBand Units (BBU) pool located remotely in the cloud. Hence, partially centralized network operation and management can be achieved, which can greatly improve the energy and spectral efficiency of the network, in order to meet the requirements of 5G. In this work, the optimal design for both uplink and downlink of F-RAN are intensively investigated

Mobile Oriented Future Internet (MOFI)

This Special Issue consists of seven papers that discuss how to enhance mobility management and its associated performance in the mobile-oriented future Internet (MOFI) environment. The first two papers deal with the architectural design and experimentation of mobility management schemes, in which new schemes are proposed and real-world testbed experimentations are performed. The subsequent three papers focus on the use of software-defined networks (SDN) for effective service provisioning in the MOFI environment, together with real-world practices and testbed experimentations. The remaining two papers discuss the network engineering issues in newly emerging mobile networks, such as flying ad-hoc networks (FANET) and connected vehicular networks

Research routing and MAC based on LEACH and S-MAC for energy efficiency and QoS in wireless sensor network

The wireless sensor is a micro-embedded device with weak data processing capability and small storage space. These nodes need to complete complex jobs, including data monitoring, acquisition and conversion, and data processing. Energy efficiency should be considered as one of the important aspects of the Wireless Sensor Network (WSN) throughout architecture and protocol design. At the same time, supporting Quality of Service (QoS) in WSNs is a research field, because the time-sensitive and important information is expected for the transmitting to to the sink node immediately. The thesis is supported by the projects entitled “The information and control system for preventing forest fires”, and “The Erhai information management system”, funded by the Chinese Government. Energy consumption and QoS are two main objectives of the projects. The thesis discusses the two aspects in route and Media Access Control (MAC). For energy efficiency, the research is based on Low Energy Adaptive Clustering Hierarchy (LEACH) protocol. LEACH is a benchmark clustering routing protocol which imposes upon cluster heads to complete a lot of aggregation and relay of messages to the base-station. However, there are limitations in LEACH. LEACH does not suit a wide area in clustering strategy and multi-hop routing. Moreover, routing protocols only focus on one factor, combining the clustering strategy and multi-hop routing mechanism were not considered in routing protocol for performance of network. QoS is supported by the MAC and routing protocol. Sensor MAC(S-MAC) makes the use of the periodically monitoring / sleeping mechanism, as well as collision and crosstalk avoidance mechanism. The mechanism reduces energy costs. Meanwhile, it supports good scalability and avoids the collision. However, the protocols do not take the differentiated services. For supporting QoS,A new route protocol needs to be designed and realized on embed platforms, which has WIFI mode and a Linux operation system to apply on the actual system. This research project was conducted as following the steps: A new protocol called RBLEACH is proposed to solve cluster on a widely scale based on LEACH. The area is divided into a few areas, where LEACH is improved to alter the selecting function in each area. RBLEACH creates routes selected by using a new algorithm to optimize the performance of the network. A new clustering method that has been developed to use several factors is PS-ACO-LEACH. The factors include the residual energy of the cluster head and Euclidean distances between cluster members and a cluster head. It can optimally solve fitness function and maintain a load balance in between the cluster head nodes, a cluster head and the base station. Based on the “Ant Colony” algorithm and transition of probability, a new routing protocol was created by “Pheromone” to find the optimal path of cluster heads to the base station. This protocol can reduce energy consumption of cluster heads and unbalanced energy consumption. Simulations prove that the improved protocol can enhance the performance of the network, including lifetime and energy conservation. Additionally, Multi Index Adaptive Routing Algorithm (MIA-QR) was designed based on network delay, packet loss rate and signal strength for QoS. The protocol is achieved by VC on an embedded Linux system. The MIA-QR is tested and verified by experiment and the protocol is to support QoS. Finally, an improved protocol (SMAC -SD) for wireless sensor networks is proposed, in order to solve the problem of S-MAC protocol that consider either service differentiation or ensure quality of service. According to service differentiation, SMAC-SD adopts an access mechanism based on different priorities including the adjustment of priority mechanisms of channel access probability, channel multi-request mechanisms and the configuring of waiting queues with different priorities and RTS backoff for different service, which makes the important service receive high channel access probability, ensuring the transmission quality of the important service. The simulation results show that the improved protocol is able to gain amount of important service and shortens the delay at the same time. Meanwhile, it improves the performance of the network effectivel

Mobile Ad-Hoc Networks

Being infrastructure-less and without central administration control, wireless ad-hoc networking is playing a more and more important role in extending the coverage of traditional wireless infrastructure (cellular networks, wireless LAN, etc). This book includes state-of the-art techniques and solutions for wireless ad-hoc networks. It focuses on the following topics in ad-hoc networks: vehicular ad-hoc networks, security and caching, TCP in ad-hoc networks and emerging applications. It is targeted to provide network engineers and researchers with design guidelines for large scale wireless ad hoc networks