Throughput and Delay Scaling in Supportive Two-Tier Networks

Consider a wireless network that has two tiers with different priorities: a primary tier vs. a secondary tier, which is an emerging network scenario with the advancement of cognitive radio technologies. The primary tier consists of randomly distributed legacy nodes of density $n$, which have an absolute priority to access the spectrum. The secondary tier consists of randomly distributed cognitive nodes of density $m=n^\beta$ with $\beta\geq 2$, which can only access the spectrum opportunistically to limit the interference to the primary tier. Based on the assumption that the secondary tier is allowed to route the packets for the primary tier, we investigate the throughput and delay scaling laws of the two tiers in the following two scenarios: i) the primary and secondary nodes are all static; ii) the primary nodes are static while the secondary nodes are mobile. With the proposed protocols for the two tiers, we show that the primary tier can achieve a per-node throughput scaling of $\lambda_p(n)=\Theta(1/\log n)$ in the above two scenarios. In the associated delay analysis for the first scenario, we show that the primary tier can achieve a delay scaling of $D_p(n)=\Theta(\sqrt{n^\beta\log n}\lambda_p(n))$ with $\lambda_p(n)=O(1/\log n)$. In the second scenario, with two mobility models considered for the secondary nodes: an i.i.d. mobility model and a random walk model, we show that the primary tier can achieve delay scaling laws of $\Theta(1)$ and $\Theta(1/S)$, respectively, where $S$ is the random walk step size. The throughput and delay scaling laws for the secondary tier are also established, which are the same as those for a stand-alone network.Comment: 13 pages, double-column, 6 figures, accepted for publication in JSAC 201

Throughput and Delay Analysis in Cognitive Overlaid Networks

Consider a cognitive overlaid network (CON) that has two tiers with different priorities: a primary tier vs. a secondary tier, which is an emerging network scenario with the advancement of cognitive radio (CR) technologies. The primary tier consists of randomly distributed primary radios (PRs) of density n, which have an absolute priority to access the spectrum. The secondary tier consists of randomly distributed CRs of density m = n^y with y greater than or equal to 1, which can only access the spectrum opportunistically to limit the interference to PRs. In this dissertation, the fundamental limits of such a network are investigated in terms of the asymptotic throughput and packet delay performance when m and n approaches infinity. The following two types of CONs are considered: 1) selfish CONs, in which neither the primary tier nor the secondary tier is willing to route the packets for the other, and 2) supportive CONs, in which the secondary tier is willing to route the packets for the primary tier while the primary tier does not. It is shown that in selfish CONs, both tiers can achieve the same throughput and delay scaling laws as a stand-alone network. In supportive CONs, the throughput and delay scaling laws of the primary tier could be significantly improved with the aid of the secondary tier, while the secondary tier can still achieve the same throughput and delay scaling laws as a stand-alone network. Finally, the throughput and packet delay of a CON with a small number of nodes are investigated. Specifically, we investigate the power and rate control schemes for multiple CR links in the same neighborhood, which operate over multiple channels (frequency bands) in the presence of PRs with a delay constraint imposed on data transmission. By further considering practical limitations in spectrum sensing, an efficient algorithm is proposed to maximize the average sum-rate of the CR links over a finite time horizon under the constraints on the CR-to-PR interference and the average transmit power for each CR link. In the proposed algorithm, the PR occupancy of each channel is modeled as a discrete-time Markov chain (DTMC). Based on such a model, a novel power and rate control strategy based on dynamic programming (DP) is derived, which is a function of the spectrum sensing output, the instantaneous channel gains for the CR links, and the remaining power budget for the CR transmitter. Simulation results show that the proposed algorithm leads to a significant performance improvement over heuristic algorithms

Characterization of the fundamental properties of wireless CSMA multi-hop networks

A wireless multi-hop network consists of a group of decentralized and self-organized wireless devices that collaborate to complete their tasks in a distributed way. Data packets are forwarded collaboratively hop-by-hop from source nodes to their respective destination nodes with other nodes acting as intermediate relays. Existing and future applications in wireless multi-hop networks will greatly benefit from better understanding of the fundamental properties of such networks. In this thesis we explore two fundamental properties of distributed wireless CSMA multi-hop networks, connectivity and capacity. A network is connected if and only if there is at least one (multi-hop) path between any pair of nodes. We investigate the critical transmission power for asymptotic connectivity in large wireless CSMA multi-hop networks under the SINR model. The critical transmission power is the minimum transmission power each node needs to transmit to guarantee that the resulting network is connected aas. Both upper bound and lower bound of the critical transmission power are obtained analytically. The two bounds are tight and differ by a constant factor only. Next we shift focus to the capacity property. First, we develop a distributed routing algorithm where each node makes routing decisions based on local information only. This is compatible with the distributed nature of large wireless CSMA multi-hop networks. Second, we show that by carefully choosing controllable parameters of the CSMA protocols, together with the routing algorithm, a distributed CSMA network can achieve the order-optimal throughput scaling law. Scaling laws are only up to order and most network design choices have a significant effect on the constants preceding the order while not affecting the scaling law. Therefore we further to analyze the pre-constant by giving an upper and a lower bound of throughput. The tightness of the bounds is validated using simulations

Characterization of the fundamental properties of wireless CSMA multi-hop networks

A wireless multi-hop network consists of a group of decentralized and self-organized wireless devices that collaborate to complete their tasks in a distributed way. Data packets are forwarded collaboratively hop-by-hop from source nodes to their respective destination nodes with other nodes acting as intermediate relays. Existing and future applications in wireless multi-hop networks will greatly benefit from better understanding of the fundamental properties of such networks. In this thesis we explore two fundamental properties of distributed wireless CSMA multi-hop networks, connectivity and capacity. A network is connected if and only if there is at least one (multi-hop) path between any pair of nodes. We investigate the critical transmission power for asymptotic connectivity in large wireless CSMA multi-hop networks under the SINR model. The critical transmission power is the minimum transmission power each node needs to transmit to guarantee that the resulting network is connected aas. Both upper bound and lower bound of the critical transmission power are obtained analytically. The two bounds are tight and differ by a constant factor only. Next we shift focus to the capacity property. First, we develop a distributed routing algorithm where each node makes routing decisions based on local information only. This is compatible with the distributed nature of large wireless CSMA multi-hop networks. Second, we show that by carefully choosing controllable parameters of the CSMA protocols, together with the routing algorithm, a distributed CSMA network can achieve the order-optimal throughput scaling law. Scaling laws are only up to order and most network design choices have a significant effect on the constants preceding the order while not affecting the scaling law. Therefore we further to analyze the pre-constant by giving an upper and a lower bound of throughput. The tightness of the bounds is validated using simulations

Scaling Laws for Vehicular Networks

Equipping automobiles with wireless communications and networking capabilities is becoming the frontier in the evolution to the next generation intelligent transportation systems (ITS). By means of vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications, information generated by the vehicle-borne computer, vehicle control system, on-board sensors, or roadside infrastructure, can be effectively disseminated among vehicles/infrastructure in proximity or to vehicles/infrastructure multiple hops away, known as vehicular networks (VANETs), to enhance the situational awareness of vehicles and provide motorist/passengers with an information-rich travel environment. Scaling law for throughput capacity and delay in wireless networks has been considered as one of the most fundamental issues, which characterizes the trend of throughput/delay behavior when the network size increases. The study of scaling laws can lead to a better understanding of intrinsic properties of wireless networks and theoretical guidance on network design and deployment. Moreover, the results could also be applied to predict network performance, especially for the large-scale vehicular networks. However, map-restricted mobility and spatio-temporal dynamics of vehicle density dramatically complicate scaling laws studies for VANETs. As an effort to lay a scientific foundation of vehicular networking, my thesis investigates capacity scaling laws for vehicular networks with and without infrastructure, respectively. Firstly, the thesis studies scaling law of throughput capacity and end-to-end delay for a social-proximity vehicular network, where each vehicle has a restricted mobility region around a specific social spot and services are delivered in a store-carry-and-forward paradigm. It has been shown that although the throughput and delay may degrade in a high vehicle density area, it is still possible to achieve almost constant scaling for per vehicle throughput and end-to-end delay. Secondly, in addition to pure ad hoc vehicular networks, the thesis derives the capacity scaling laws for networks with wireless infrastructure, where services are delivered uniformly from infrastructure to all vehicles in the network. The V2V communication is also required to relay the downlink traffic to the vehicles outside the coverage of infrastructure. Three kinds of infrastructures have been considered, i.e., cellular base stations, wireless mesh backbones (a network of mesh nodes, including one mesh gateway), and roadside access points. The downlink capacity scaling is derived for each kind of infrastructure. Considering that the deployment/operation costs of different infrastructure are highly variable, the capacity-cost tradeoffs of different deployments are examined. The results from the thesis demonstrate the feasibility of deploying non-cellular infrastructure for supporting high-bandwidth vehicular applications. Thirdly, the fundamental impact of traffic signals at road intersection on drive-thru Internet access is particularly studied. The thesis analyzes the time-average throughput capacity of a typical vehicle driving through randomly deployed roadside Wi-Fi networks. Interestingly, we show a significant throughput gain for vehicles stopping at intersections due to red signals. The results provide a quick and efficient way of determining the Wi-Fi deployment scale according to required quality of services. In summary, the analysis developed and the scaling laws derived in the thesis provide should be very useful for understanding the fundamental performance of vehicular networks

Advanced Technologies Enabling Unlicensed Spectrum Utilization in Cellular Networks

As the rapid progress and pleasant experience of Internet-based services, there is an increasing demand for high data rate in wireless communications systems. Unlicensed spectrum utilization in Long Term Evolution (LTE) networks is a promising technique to meet the massive traffic demand. There are two effective methods to use unlicensed bands for delivering LTE traffic. One is offloading LTE traffic toWi-Fi. An alternative method is LTE-unlicensed (LTE-U), which aims to directly use LTE protocols and infrastructures over the unlicensed spectrum. It has also been pointed out that addressing the above two methods simultaneously could further improve the system performance. However, how to avoid severe performance degradation of the Wi-Fi network is a challenging issue of utilizing unlicensed spectrum in LTE networks. Specifically, first, the inter-system spectrum sharing, or, more specifically, the coexistence of LTE andWi-Fi in the same unlicensed spectrum is the major challenge of implementing LTE-U. Second, to use the LTE and Wi-Fi integration approach, mobile operators have to manage two disparate networks in licensed and unlicensed spectrum. Third, optimization for joint data offloading to Wi-Fi and LTE-U in multi- cell scenarios poses more challenges because inter-cell interference must be addressed. This thesis focuses on solving problems related to these challenges. First, the effect of bursty traffic in an LTE and Wi-Fi aggregation (LWA)-enabled network has been investigated. To enhance resource efficiency, the Wi-Fi access point (AP) is designed to operate in both the native mode and the LWA mode simultaneously. Specifically, the LWA-modeWi-Fi AP cooperates with the LTE base station (BS) to transmit bearers to the LWA user, which aggregates packets from both LTE and Wi-Fi. The native-mode Wi-Fi AP transmits Wi-Fi packets to those native Wi-Fi users that are not with LWA capability. This thesis proposes a priority-based Wi-Fi transmission scheme with congestion control and studied the throughput of the native Wi-Fi network, as well as the LWA user delay when the native Wi-Fi user is under heavy traffic conditions. The results provide fundamental insights in the throughput and delay behavior of the considered network. Second, the above work has been extended to larger topologies. A stochastic geometry model has been used to model and analyze the performance of an MPTCP Proxy-based LWA network with intra-tier and cross-tier dependence. Under the considered network model and the activation conditions of LWA-mode Wi-Fi, this thesis has obtained three approximations for the density of active LWA-mode Wi-Fi APs through different approaches. Tractable analysis is provided for the downlink (DL) performance evaluation of large-scale LWA networks. The impact of different parameters on the network performance have been analyzed, validating the significant gain of using LWA in terms of boosted data rate and improved spectrum reuse. Third, this thesis also takes a significant step of analyzing joint multi-cell LTE-U and Wi-Fi network, while taking into account different LTE-U and Wi-Fi inter-working schemes. In particular, two technologies enabling data offloading from LTE to Wi-Fi are considered, including LWA and Wi-Fi offloading in the context of the power gain-based user offloading scheme. The LTE cells in this work are subject to load-coupling due to inter-cell interference. New system frameworks for maximizing the demand scaling factor for all users in both Wi-Fi and multi-cell LTE networks have been proposed. The potential of networks is explored in achieving optimal capacity with arbitrary topologies, accounting for both resource limits and inter-cell interference. Theoretical analyses have been proposed for the proposed optimization problems, resulting in algorithms that achieve global optimality. Numerical results show the algorithms’ effectiveness and benefits of joint use of data offloading and the direct use of LTE over the unlicensed band. All the derived results in this thesis have been validated by Monte Carlo simulations in Matlab, and the conclusions observed from the results can provide guidelines for the future unlicensed spectrum utilization in LTE networks

Analytical Performance Evaluation of Cooperative and Multi-Radio Concepts in Emerging Wireless Networks

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Discovering Network Control Vulnerabilities and Policies in Evolving Networks

The range and number of new applications and services are growing at an unprecedented rate. Computer networks need to be able to provide connectivity for these services and meet their constantly changing demands. This requires not only support of new network protocols and security requirements, but often architectural redesigns for long-term improvements to efficiency, speed, throughput, cost, and security. Networks are now facing a drastic increase in size and are required to carry a constantly growing amount of heterogeneous traffic. Unfortunately such dynamism greatly complicates security of not only the end nodes in the network, but also of the nodes of the network itself. To make matters worse, just as applications are being developed at faster and faster rates, attacks are becoming more pervasive and complex. Networks need to be able to understand the impact of these attacks and protect against them. Network control devices, such as routers, firewalls, censorship devices, and base stations, are elements of the network that make decisions on how traffic is handled. Although network control devices are expected to act according to specifications, there can be various reasons why they do not in practice. Protocols could be flawed, ambiguous or incomplete, developers could introduce unintended bugs, or attackers may find vulnerabilities in the devices and exploit them. Malfunction could intentionally or unintentionally threaten the confidentiality, integrity, and availability of end nodes and the data that passes through the network. It can also impact the availability and performance of the control devices themselves and the security policies of the network. The fast-paced evolution and scalability of current and future networks create a dynamic environment for which it is difficult to develop automated tools for testing new protocols and components. At the same time, they make the function of such tools vital for discovering implementation flaws and protocol vulnerabilities as networks become larger and more complex, and as new and potentially unrefined architectures become adopted. This thesis will present the design, implementation, and evaluation of a set of tools designed for understanding implementation of network control nodes and how they react to changes in traffic characteristics as networks evolve. We will first introduce Firecycle, a test bed for analyzing the impact of large-scale attacks and Machine-to-Machine (M2M) traffic on the Long Term Evolution (LTE) network. We will then discuss Autosonda, a tool for automatically discovering rule implementation and finding triggering traffic features in censorship devices. This thesis provides the following contributions: 1. The design, implementation, and evaluation of two tools to discover models of network control nodes in two scenarios of evolving networks, mobile network and censored internet 2. First existing test bed for analysis of large-scale attacks and impact of traffic scalability on LTE mobile networks 3. First existing test bed for LTE networks that can be scaled to arbitrary size and that deploys traffic models based on real traffic traces taken from a tier-1 operator 4. An analysis of traffic models of various categories of Internet of Things (IoT) devices 5. First study demonstrating the impact of M2M scalability and signaling overload on the packet core of LTE mobile networks 6. A specification for modeling of censorship device decision models 7. A means for automating the discovery of features utilized in censorship device decision models, comparison of these models, and their rule discover