Towards Practical Store-Carry-Forward Networking: Examples and Issues

In the evolution of wireless networks such as wireless sensor networks, mobile ad-hoc networks, and delay/disruption tolerant networks, the Store-Carry-Forward (SCF) message relaying paradigm has been commonly featured and studied with much attention. SCF networking is essential for offsetting the deficiencies of intermittent and range limited communication environments because it allows moving wireless communication nodes to act as “mobile relay nodes”. Such relay nodes can store/carry/process messages, wait for a better opportunity for transmission, and finally forward the messages to other nodes. This paper starts with a short overview of SCF routing and then examines two SCF networking scenarios. The first one deals with large content delivery across multiple islands using existing infrastructural transportation networks (e.g., cars and ferries) in which mobility is uncontrollable from an SCF viewpoint. Simulations show how a simple coding technique can improve flooding-based SCF. The other scenario looks at a prototype system of unmanned aerial vehicle (UAV) for high-quality video surveillance from the sky in which mobility is partially controllable from an SCF viewpoint. Three requisite techniques in this scenario are highlighted - fast link setup, millimeter wave communications, and use of multiple links. Through these examples, we discuss the benefits and issues of the practical use of SCF networking-based systems

Caching Techniques in Next Generation Cellular Networks

Content caching will be an essential feature in the next generations of cellular networks. Indeed, a network equipped with caching capabilities allows users to retrieve content with reduced access delays and consequently reduces the traffic passing through the network backhaul. However, the deployment of the caching nodes in the network is hindered by the following two challenges. First, the storage space of a cache is limited as well as expensive. So, it is not possible to store in the cache every content that can be possibly requested by the user. This calls for efficient techniques to determine the contents that must be stored in the cache. Second, efficient ways are needed to implement and control the caching node. In this thesis, we investigate caching techniques focussing to address the above-mentioned challenges, so that the overall system performance is increased. In order to tackle the challenge of the limited storage capacity, smart proactive caching strategies are needed. In the context of vehicular users served by edge nodes, we believe a caching strategy should be adapted to the mobility characteristics of the cars. In this regard, we propose a scheme called RICH (RoadsIde CacHe), which optimally caches content at the edge nodes where connected vehicles require it most. In particular, our scheme is designed to ensure in-order delivery of content chunks to end users. Unlike blind popularity decisions, the probabilistic caching used by RICH considers vehicular trajectory predictions as well as content service time by edge nodes. We evaluate our approach on realistic mobility datasets against a popularity-based edge approach called POP, and a mobility-aware caching strategy known as netPredict. In terms of content availability, our RICH edge caching scheme provides an enhancement of up to 33% and 190% when compared with netPredict and POP respectively. At the same time, the backhaul penalty bandwidth is reduced by a factor ranging between 57% and 70%. Caching node is an also a key component in Named Data Networking (NDN) that is an innovative paradigm to provide content based services in future networks. As compared to legacy networks, naming of network packets and in-network caching of content make NDN more feasible for content dissemination. However, the implementation of NDN requires drastic changes to the existing network infrastructure. One feasible approach is to use Software Defined Networking (SDN), according to which the control of the network is delegated to a centralized controller, which configures the forwarding data plane. This approach leads to large signaling overhead as well as large end-to-end (e2e) delays. In order to overcome these issues, in this work, we provide an efficient way to implement and control the NDN node. We propose to enable NDN using a stateful data plane in the SDN network. In particular, we realize the functionality of an NDN node using a stateful SDN switch attached with a local cache for content storage, and use OpenState to implement such an approach. In our solution, no involvement of the controller is required once the OpenState switch has been configured. We benchmark the performance of our solution against the traditional SDN approach considering several relevant metrics. Experimental results highlight the benefits of a stateful approach and of our implementation, which avoids signaling overhead and significantly reduces e2e delays

Mobile Ad Hoc Networks

Guiding readers through the basics of these rapidly emerging networks to more advanced concepts and future expectations, Mobile Ad hoc Networks: Current Status and Future Trends identifies and examines the most pressing research issues in Mobile Ad hoc Networks (MANETs). Containing the contributions of leading researchers, industry professionals, and academics, this forward-looking reference provides an authoritative perspective of the state of the art in MANETs. The book includes surveys of recent publications that investigate key areas of interest such as limited resources and the mobility of mobile nodes. It considers routing, multicast, energy, security, channel assignment, and ensuring quality of service. Also suitable as a text for graduate students, the book is organized into three sections: Fundamentals of MANET Modeling and Simulation—Describes how MANETs operate and perform through simulations and models Communication Protocols of MANETs—Presents cutting-edge research on key issues, including MAC layer issues and routing in high mobility Future Networks Inspired By MANETs—Tackles open research issues and emerging trends Illustrating the role MANETs are likely to play in future networks, this book supplies the foundation and insight you will need to make your own contributions to the field. It includes coverage of routing protocols, modeling and simulations tools, intelligent optimization techniques to multicriteria routing, security issues in FHAMIPv6, connecting moving smart objects to the Internet, underwater sensor networks, wireless mesh network architecture and protocols, adaptive routing provision using Bayesian inference, and adaptive flow control in transport layer using genetic algorithms

Deep Learning -Powered Computational Intelligence for Cyber-Attacks Detection and Mitigation in 5G-Enabled Electric Vehicle Charging Station

An electric vehicle charging station (EVCS) infrastructure is the backbone of transportation electrification. However, the EVCS has various cyber-attack vulnerabilities in software, hardware, supply chain, and incumbent legacy technologies such as network, communication, and control. Therefore, proactively monitoring, detecting, and defending against these attacks is very important. The state-of-the-art approaches are not agile and intelligent enough to detect, mitigate, and defend against various cyber-physical attacks in the EVCS system. To overcome these limitations, this dissertation primarily designs, develops, implements, and tests the data-driven deep learning-powered computational intelligence to detect and mitigate cyber-physical attacks at the network and physical layers of 5G-enabled EVCS infrastructure. Also, the 5G slicing application to ensure the security and service level agreement (SLA) in the EVCS ecosystem has been studied. Various cyber-attacks such as distributed denial of services (DDoS), False data injection (FDI), advanced persistent threats (APT), and ransomware attacks on the network in a standalone 5G-enabled EVCS environment have been considered. Mathematical models for the mentioned cyber-attacks have been developed. The impact of cyber-attacks on the EVCS operation has been analyzed. Various deep learning-powered intrusion detection systems have been proposed to detect attacks using local electrical and network fingerprints. Furthermore, a novel detection framework has been designed and developed to deal with ransomware threats in high-speed, high-dimensional, multimodal data and assets from eccentric stakeholders of the connected automated vehicle (CAV) ecosystem. To mitigate the adverse effects of cyber-attacks on EVCS controllers, novel data-driven digital clones based on Twin Delayed Deep Deterministic Policy Gradient (TD3) Deep Reinforcement Learning (DRL) has been developed. Also, various Bruteforce, Controller clones-based methods have been devised and tested to aid the defense and mitigation of the impact of the attacks of the EVCS operation. The performance of the proposed mitigation method has been compared with that of a benchmark Deep Deterministic Policy Gradient (DDPG)-based digital clones approach. Simulation results obtained from the Python, Matlab/Simulink, and NetSim software demonstrate that the cyber-attacks are disruptive and detrimental to the operation of EVCS. The proposed detection and mitigation methods are effective and perform better than the conventional and benchmark techniques for the 5G-enabled EVCS

Mobile Ad Hoc Networks

Guiding readers through the basics of these rapidly emerging networks to more advanced concepts and future expectations, Mobile Ad hoc Networks: Current Status and Future Trends identifies and examines the most pressing research issues in Mobile Ad hoc Networks (MANETs). Containing the contributions of leading researchers, industry professionals, and academics, this forward-looking reference provides an authoritative perspective of the state of the art in MANETs. The book includes surveys of recent publications that investigate key areas of interest such as limited resources and the mobility of mobile nodes. It considers routing, multicast, energy, security, channel assignment, and ensuring quality of service. Also suitable as a text for graduate students, the book is organized into three sections: Fundamentals of MANET Modeling and Simulation—Describes how MANETs operate and perform through simulations and models Communication Protocols of MANETs—Presents cutting-edge research on key issues, including MAC layer issues and routing in high mobility Future Networks Inspired By MANETs—Tackles open research issues and emerging trends Illustrating the role MANETs are likely to play in future networks, this book supplies the foundation and insight you will need to make your own contributions to the field. It includes coverage of routing protocols, modeling and simulations tools, intelligent optimization techniques to multicriteria routing, security issues in FHAMIPv6, connecting moving smart objects to the Internet, underwater sensor networks, wireless mesh network architecture and protocols, adaptive routing provision using Bayesian inference, and adaptive flow control in transport layer using genetic algorithms

Mobility-aware Software-Defined Service-Centric Networking for Service Provisioning in Urban Environments

Disruptive applications for mobile devices, such as the Internet of Things, Connected and Autonomous Vehicles, Immersive Media, and others, have requirements that the current Cloud Computing paradigm cannot meet. These unmet requirements bring the necessity to deploy geographically distributed computing architectures, such as Fog and Mobile Edge Computing. However, bringing computing close to users has its costs. One example of cost is the complexity introduced by the management of the mobility of the devices at the edge. This mobility may lead to issues, such as interruption of the communication with service instances hosted at the edge or an increase in communication latency during mobility events, e.g., handover. These issues, caused by the lack of mobility-aware service management solutions, result in degradation in service provisioning. The present thesis proposes a series of protocols and algorithms to handle user and service mobility at the edge of the network. User mobility is characterized when user change access points of wireless networks, while service mobility happens when services have to be provisioned from different hosts. It assembles them in a solution for mobility-aware service orchestration based on Information-Centric Networking (ICN) and runs on top of Software-Defined Networking (SDN). This solution addresses three issues related to handling user mobility at the edge: (i) proactive support for user mobility events, (ii) service instance addressing management, and (iii) distributed application state data management. For (i), we propose a proactive SDN-based handover scheme. For (ii), we propose an ICN addressing strategy to remove the necessity of updating addresses after service mobility events. For (iii), we propose a graph-based framework for state data placement in the network nodes that accounts for user mobility and latency requirements. The protocols and algorithms proposed in this thesis were compared with different approaches from the literature through simulation. Our results show that the proposed solution can reduce service interruption and latency in the presence of user and service mobility events while maintaining reasonable overhead costs regarding control messages sent in the network by the SDN controller

Markov Decision Processes with Applications in Wireless Sensor Networks: A Survey

Wireless sensor networks (WSNs) consist of autonomous and resource-limited devices. The devices cooperate to monitor one or more physical phenomena within an area of interest. WSNs operate as stochastic systems because of randomness in the monitored environments. For long service time and low maintenance cost, WSNs require adaptive and robust methods to address data exchange, topology formulation, resource and power optimization, sensing coverage and object detection, and security challenges. In these problems, sensor nodes are to make optimized decisions from a set of accessible strategies to achieve design goals. This survey reviews numerous applications of the Markov decision process (MDP) framework, a powerful decision-making tool to develop adaptive algorithms and protocols for WSNs. Furthermore, various solution methods are discussed and compared to serve as a guide for using MDPs in WSNs