Secure Routing in Wireless Mesh Networks

Wireless mesh networks (WMNs) have emerged as a promising concept to meet the challenges in next-generation networks such as providing flexible, adaptive, and reconfigurable architecture while offering cost-effective solutions to the service providers. Unlike traditional Wi-Fi networks, with each access point (AP) connected to the wired network, in WMNs only a subset of the APs are required to be connected to the wired network. The APs that are connected to the wired network are called the Internet gateways (IGWs), while the APs that do not have wired connections are called the mesh routers (MRs). The MRs are connected to the IGWs using multi-hop communication. The IGWs provide access to conventional clients and interconnect ad hoc, sensor, cellular, and other networks to the Internet. However, most of the existing routing protocols for WMNs are extensions of protocols originally designed for mobile ad hoc networks (MANETs) and thus they perform sub-optimally. Moreover, most routing protocols for WMNs are designed without security issues in mind, where the nodes are all assumed to be honest. In practical deployment scenarios, this assumption does not hold. This chapter provides a comprehensive overview of security issues in WMNs and then particularly focuses on secure routing in these networks. First, it identifies security vulnerabilities in the medium access control (MAC) and the network layers. Various possibilities of compromising data confidentiality, data integrity, replay attacks and offline cryptanalysis are also discussed. Then various types of attacks in the MAC and the network layers are discussed. After enumerating the various types of attacks on the MAC and the network layer, the chapter briefly discusses on some of the preventive mechanisms for these attacks.Comment: 44 pages, 17 figures, 5 table

Stable dynamic feedback-based predictive clustering protocol for vehicular ad hoc networks

Scalability presents a significant challenge in vehicular communication, particularly when there is no hierarchical structure in place to manage the increasing number of vehicles. As the number of vehicles increases, they may encounter the broadcast storm problem, which can cause network congestion and reduce communication efficiency. Clustering can solve these issues, but due to high vehicle mobility, clustering in vehicular ad hoc networks (VANET) suffers from stability issues. Existing clustering algorithms are optimized for either cluster head or member, and for highways or intersections. The lack of intelligent use of mobility parameters like velocity, acceleration, direction, position, distance, degree of vehicles, and movement at intersections, also contributes to cluster stability problems. A dynamic clustering algorithm that efficiently utilizes all mobility parameters can resolve these issues in VANETs. To provide higher stability in VANET clustering, a novel robust and dynamic mobility-based clustering algorithm called junction-based clustering protocol for VANET (JCV) is proposed in this dissertation. Unlike previous studies, JCV takes into account position, distance, movement at the junction, degree of a vehicle, and time spent on the road to select the cluster head (CH). JCV considers transmission range, the moving direction of the vehicle at the next junction, and vehicle density in the creation of a cluster. JCV's performance is compared with two existing VANET clustering protocols in terms of the average cluster head duration, the average cluster member (CM) duration, the average number of cluster head changes, and the percentage of vehicles participating in the clustering process, etc. To evaluate the performance of JCV, we developed a new cloud-based VANET simulator (CVANETSIM). The simulation results show that JCV outperforms the existing algorithms and achieves better stability in terms of the average CH duration (4%), the average CM duration (8%), the number of CM (6%), the ratio of CM (22%), the average CH change rate (14%), the number of CH (10%), the number of non-cluster vehicles (7%), and clustering overhead (35%). The dissertation also introduced a stable dynamic feedback-based predictive clustering (SDPC) protocol for VANET, which ensures cluster stability in both highway and intersection scenarios, irrespective of the road topology. SDPC considers vehicle relative velocity, acceleration, position, distance, transmission range, moving direction at the intersection, and vehicle density to create a cluster. The cluster head is selected based on the future construction of the road, considering relative distance, movement at the intersection, degree of vehicles, majority-vehicle, and probable cluster head duration. The performance of SDPC is compared with four existing VANET clustering algorithms in various road topologies, in terms of the average cluster head change rate, duration of the cluster head, duration of the cluster member, and the clustering overhead. The simulation results show that SDPC outperforms existing algorithms, achieving better clustering stability in terms of the average CH change rate (50%), the average CH duration (15%), the average CM duration (6%), and the clustering overhead (35%)

VIRTUALIZED BASEBAND UNITS CONSOLIDATION IN ADVANCED LTE NETWORKS USING MOBILITY- AND POWER-AWARE ALGORITHMS

Virtualization of baseband units in Advanced Long-Term Evolution networks and a rapid performance growth of general purpose processors naturally raise the interest in resource multiplexing. The concept of resource sharing and management between virtualized instances is not new and extensively used in data centers. We adopt some of the resource management techniques to organize virtualized baseband units on a pool of hosts and investigate the behavior of the system in order to identify features which are particularly relevant to mobile environment. Subsequently, we introduce our own resource management algorithm specifically targeted to address some of the peculiarities identified by experimental results

Resilience and Controllability of Dynamic Collective Behaviors

The network paradigm is used to gain insight into the structural root causes of the resilience of consensus in dynamic collective behaviors, and to analyze the controllability of the swarm dynamics. Here we devise the dynamic signaling network which is the information transfer channel underpinning the swarm dynamics of the directed interagent connectivity based on a topological neighborhood of interactions. The study of the connectedness of the swarm signaling network reveals the profound relationship between group size and number of interacting neighbors, which is found to be in good agreement with field observations on flock of starlings [Ballerini et al. (2008) Proc. Natl. Acad. Sci. USA, 105: 1232]. Using a dynamical model, we generate dynamic collective behaviors enabling us to uncover that the swarm signaling network is a homogeneous clustered small-world network, thus facilitating emergent outcomes if connectedness is maintained. Resilience of the emergent consensus is tested by introducing exogenous environmental noise, which ultimately stresses how deeply intertwined are the swarm dynamics in the physical and network spaces. The availability of the signaling network allows us to analytically establish for the first time the number of driver agents necessary to fully control the swarm dynamics