55 research outputs found

    Stability-Based Topology Control in Wireless Mesh Networks

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    Joint Congestion Control and Scheduling in Wireless Networks with Network Coding

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    Stochastic Security in Wireless Mesh Networks via Saddle Routing Policy

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    Distributed Relay-Assignment Protocols for Coverage Expansion in Cooperative Wireless Networks

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    QoS Routing in Wireless Mesh Networks

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    Wireless Mesh Networking is envisioned as an economically viable paradigm and a promising technology in providing wireless broadband services. The wireless mesh backbone consists of fixed mesh routers that interconnect different mesh clients to themselves and to the wireline backbone network. In order to approach the wireline servicing level and provide same or near QoS guarantees to different traffic flows, the wireless mesh backbone should be quality-of-service (QoS) aware. A key factor in designing protocols for a wireless mesh network (WMN) is to exploit its distinct characteristics, mainly immobility of mesh routers and less-constrained power consumption. In this work, we study the effect of varying the transmission power to achieve the required signal-to-interference noise ratio for each link and, at the same time, to maximize the number of simultaneously active links. We propose a QoS-aware routing framework by using transmission power control. The framework addresses both the link scheduling and QoS routing problems with a cross-layer design taking into consideration the spatial reuse of the network bandwidth. We formulate an optimization problem to find the optimal link schedule and use it as a fitness function in a genetic algorithm to find candidate routes. Using computer simulations, we show that by optimal power allocation the QoS constraints for the different traffic flows are met with more efficient bandwidth utilization than the minimum power allocations

    MAC-PHY Frameworks For LTE And WiFi Networks\u27 Coexistence Over The Unlicensed Band

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    The main focus of this dissertation is to address these issues and to analyze the interactions between LTE and WiFi coexisting on the unlicensed spectrum. This can be done by providing some improvements in the first two communication layers in both technologies. Regarding the physical (PHY) layer, efficient spectrum sensing and data fusion techniques that consider correlated spectrum sensing readings at the LTE/WiFi users (sensors) are needed. Failure to consider such correlation has been a major shortcoming of the literature. This resulted in poorly performing spectrum sensing systems if such correlation is not considered in correlated-measurements environments

    Game-Theoretic Frameworks and Strategies for Defense Against Network Jamming and Collocation Attacks

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    Modern networks are becoming increasingly more complex, heterogeneous, and densely connected. While more diverse services are enabled to an ever-increasing number of users through ubiquitous networking and pervasive computing, several important challenges have emerged. For example, densely connected networks are prone to higher levels of interference, which makes them more vulnerable to jamming attacks. Also, the utilization of software-based protocols to perform routing, load balancing and power management functions in Software-Defined Networks gives rise to more vulnerabilities that could be exploited by malicious users and adversaries. Moreover, the increased reliance on cloud computing services due to a growing demand for communication and computation resources poses formidable security challenges due to the shared nature and virtualization of cloud computing. In this thesis, we study two types of attacks: jamming attacks on wireless networks and side-channel attacks on cloud computing servers. The former attacks disrupt the natural network operation by exploiting the static topology and dynamic channel assignment in wireless networks, while the latter attacks seek to gain access to unauthorized data by co-residing with target virtual machines (VMs) on the same physical node in a cloud server. In both attacks, the adversary faces a static attack surface and achieves her illegitimate goal by exploiting a stationary aspect of the network functionality. Hence, this dissertation proposes and develops counter approaches to both attacks using moving target defense strategies. We study the strategic interactions between the adversary and the network administrator within a game-theoretic framework. First, in the context of jamming attacks, we present and analyze a game-theoretic formulation between the adversary and the network defender. In this problem, the attack surface is the network connectivity (the static topology) as the adversary jams a subset of nodes to increase the level of interference in the network. On the other side, the defender makes judicious adjustments of the transmission footprint of the various nodes, thereby continuously adapting the underlying network topology to reduce the impact of the attack. The defender\u27s strategy is based on playing Nash equilibrium strategies securing a worst-case network utility. Moreover, scalable decomposition-based approaches are developed yielding a scalable defense strategy whose performance closely approaches that of the non-decomposed game for large-scale and dense networks. We study a class of games considering discrete as well as continuous power levels. In the second problem, we consider multi-tenant clouds, where a number of VMs are typically collocated on the same physical machine to optimize performance and power consumption and maximize profit. This increases the risk of a malicious virtual machine performing side-channel attacks and leaking sensitive information from neighboring VMs. The attack surface, in this case, is the static residency of VMs on a set of physical nodes, hence we develop a timed migration defense approach. Specifically, we analyze a timing game in which the cloud provider decides when to migrate a VM to a different physical machine to mitigate the risk of being compromised by a collocated malicious VM. The adversary decides the rate at which she launches new VMs to collocate with the victim VMs. Our formulation captures a data leakage model in which the cost incurred by the cloud provider depends on the duration of collocation with malicious VMs. It also captures costs incurred by the adversary in launching new VMs and by the defender in migrating VMs. We establish sufficient conditions for the existence of Nash equilibria for general cost functions, as well as for specific instantiations, and characterize the best response for both players. Furthermore, we extend our model to characterize its impact on the attacker\u27s payoff when the cloud utilizes intrusion detection systems that detect side-channel attacks. Our theoretical findings are corroborated with extensive numerical results in various settings as well as a proof-of-concept implementation in a realistic cloud setting
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