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No / Traffic congestion arising from the shared nature of uplink channels in wireless networks can cause serious problems for the provision of QoS to various services. One approach to overcome these problems is to implement some effective congestion control mechanisms at the downlink buffer at the mobile network link layer or at gateways on the behalf of wireless network access points. Active queue management (AQM) is an effective mechanism to support end-to-end traffic congestion control in modern high-speed networks. Initially developed for Internet routers, AQM is now being also considered as an effective congestion control mechanism to enhance TCP performance over 3G links. This paper proposes an analytical performance model for AQM using various dropping functions. The selection of different dropping functions and threshold values required for this scheme plays a critical role on its effectiveness. The model uses a well-known Markov-modulated Poisson process (MMPP) to capture traffic burstiness and correlations. The validity of the model has been demonstrated through simulation experiments. Extensive analytical results have indicated that exponential dropping function is a good choice for AQM to support efficient congestion control.

Yes / Addressing key management in mobile multicast communication is currently a booming topic due to the convergence of wireless and mobile technologies. With the proliferation of multiple group based services that are possible to co-exist within a single network, mobile subscribers could subscribe to these services concurrently while ubiquitous. However, the existing group key management (GKM) protocols intend to secure group communication for just a single group service. The GKM approaches involve inefficient use of keys and huge rekeying overheads, hence unsuitable for multiple multicast group environments. In this paper, we propose a novel GKM protocol for multiple multicast groups, called slot based multiple group key management (SMGKM) scheme. SMGKM supports the movement of single and multiple members across a homogeneous or heterogeneous wireless network while participating in multiple group services with minimized rekeying transmission overheads. Unlike conventional GKM protocols, SMGKM protocol can mitigate 1-affect-n phenomenon, single point of failure and investment pressure of signaling load caused by rekeying at the core network. Numerical analysis and simulation results of the proposed protocol show significant resource economy in terms of communication bandwidth overhead, storage overheads at the Domain Key Distributor (DKD), mobile receiver and Area Key Distributors while providing intense security.

No / Previous cluster based group key management schemes for wireless mobile multicast communication lack efficiency in rekeying the group key if high mobility users concurrently subscribe to multiple multicast services that co-exist in the same network. This paper proposes an efficient multi-service group key management scheme suitable for high mobility users which perform frequent handoffs while participating seamlessly in multiple multicast services. The users are expected to drop subscriptions after multiple cluster visits hence inducing huge key management overhead due to rekeying the previously visited cluster keys. However we adopt our already proposed SMGKM system with completely decentralised authentication and key management functions to address demands for high mobility environment with same level of security and less overhead. Through comparisons with existing schemes and simulations, SMGKM shows resource economy in terms of rekeying communication overhead in high mobility environment with multi-leaves.

No / Abstract: Mobile multicast is recently becoming a hot research in the convergence of wireless and mobile technologies. With the emergence of various multicast-based services, multiple multicast groups are possible to exist within a single network, and mobile subscribers could subscribe to multiple groups concurrently. However, the existing group key management (GKM) protocols intend to secure group communication for just a single group service. The GKM approaches involve inefficient use of keys and huge rekeying overheads, hence unsuitable for multiple multicast group environments. In this paper, we propose a novel GKM protocol for multiple multicast groups, called slot based multiple group key management (SMGKM) scheme. SMGKM supports the movement of single and multiple members across a homogeneous or heterogeneous wireless network while participating in multiple group services with minimized rekeying transmission overheads. Unlike conventional GKM protocols, SMGKM protocol mitigates 1-affect-n phenomenon, single point of failure and investment pressure of signaling load at the core network. The results of the proposed protocol show resource economy in terms of communication bandwidth and storage overheads.

A fundamental problem in multi-hop wireless networks is to estimate their throughout capacity. The problem can be informally stated as follows: given a multi-hop wireless network and a set of source destination pairs, determine the maximum rate r at which data can be transmitted between each source destination pair. Estimating the capacity of a multi-hop wireless network is practically useful --- it yields insights into the fundamental performance limits of the wireless network and at the same time aids the development of protocols that can utilize the network close to this limit. A goal of this dissertation is to develop rigorous mathematical foundations to compute the capacity of any given multi-hop wireless network with known source-destination pairs. An important factor that affects the capacity of multi-hop wireless networks is radio interference. As a result, researchers have proposed increasingly realistic interference models that aim to capture the physical characteristics of radio signals. Some of the commonly used simple models that capture radio interference are based on geometric disk-graphs. The simplicity of these models facilitate the development of provable and often conceptually simple methods for estimating the capacity of wireless networks. A potential weakness of this class of models is that they oversimplify the physical process by assuming that the signal ends abruptly at the boundary of a geometric region (a disk for omni-directional antennas). A more sophisticated interference model is the physical interference model, also known as the Signal to Interference Plus Noise Ratio (SINR) model. This model is more realistic than disk-graph models as it captures the effects of signal fading and ambient noise. This work considers both disk-graph and SINR interference models. In addition to radio interference, the throughput capacity of a multi-hop wireless network also depends on other factors, including the specific paths selected to route the packets between the source destination pairs (routing), the time at which packets are transmitted (scheduling), the power with which nodes transmit (power control) and the rate at which packets are injected (rate control). In this dissertation, we consider three different problems related to estimating network capacity. We propose an algorithmic approach for solving these problems. We first consider the problem of maximizing throughput with the SINR interference model by jointly considering the effects of routing and scheduling constraints. Second, we consider the problem of maximizing throughput by performing adaptive power control, scheduling and routing for disk-graph interference models. Finally, we examine the problem of minimizing end-to-end latency by performing joint routing, scheduling and power control using the SINR interference model. Recent results have shown that traditional layered networking principles lead to inefficient utilization of resources in multi-hop wireless networks. Motivated by these observations, recent papers have begun investigating cross-layer design approaches. Although our work does not develop new cross-layered protocols, it yields new insights that could contribute to the development of such protocols in the future. Our approach for solving these multi-objective optimization problems is based on combining mathematical programming with randomized rounding to obtain polynomial time approximation algorithms with provable worst case performance ratios. For the problems considered in this work, our results provide the best analytical performance guarantees currently known in the literature. We complement our rigorous theoretical and algorithmic analysis with simulation-based experimental analysis. Our experimental results help us understand the limitations of our approach and assist in identifying certain parameters for improving the performance of our techniques. / Ph. D.

Recently, many new types of wireless networks have emerged for both civil and military applications, such as cognitive radio networks, MIMO networks. There is a strong interest in exploring the optimal performance of these new emerging networks, e.g., maximizing the network throughput, minimizing network energy consumption. Exploring the optimal performance objectives of these new types of wireless networks is both important and intellectual challenging. On one hand, it is important for a network researcher to understand the performance limits of these new wireless networks. Such performance limits are important not only for theoretical understanding, but also in that they can be used as benchmarks for the design of distributed algorithms and protocols. On the other hand, due to some unique characteristics associated with these networks, existing analytic techniques may not be applied directly to obtain the optimal performance. As a result, new theoretical results, along with new mathematical tools, need to be developed. The goal of this dissertation is to make a fundamental advance on network performance optimization via exploring a series of optimization problems. Based on the scale of the underlying wireless network, the works in this dissertation are divided into two parts. In the first part, we study the asymptotic capacity scaling laws of different types of wireless networks. By "asymptotic", we mean that the number of nodes in the network goes to infinity. Such asymptotic capacity scaling laws offer fundamental understandings on the trend of maximum user throughput behavior when the network size increases. In the second part of this dissertation, we study several optimization problems of finite-sized wireless networks. Under a given network size, we accurately characterize some performance limits (e.g., throughput, energy consumption) of wireless networks and provide solutions on how to achieve the optimal objectives. The main contributions of this dissertation can be summarized as follows, where the first three problems are on asymptotic capacity scaling laws and the last three problems are optimization problems of finite-sized wireless networks. <b>1. Capacity Scaling Laws of Cognitive Radio Ad Hoc Networks.</b> We first study the capacity scaling laws for cognitive radio ad hoc networks (CRNs), i.e., how each individual node's maximum throughput scales as the number of nodes in the network increases. This effort is critical to the fundamental understanding of the scalability of such network. However, due to the heterogeneity in available frequency bands at each node, the asymptotic capacity is much more difficult to develop than prior efforts for other types of wireless networks. To overcome this difficulty, we introduce two auxiliary networks ζ and α to analyze the capacity upper and lower bounds. We derive the capacity results under both the protocol model and the physical model. Further, we show that the seminal results developed by Gupta and Kumar for the simple single-channel single-radio (SC-SR) networks are special cases under the results for CRNs. <b>2. Asymptotic Capacity of Multi-hop MIMO Ad Hoc Networks.</b> Multi-input multi-output (MIMO) is a key technology to increase the capacity of wireless networks. Although there has been extensive work on MIMO at the physical and link layers, there has been limited work on MIMO at the network layer (i.e., multi-hop MIMO ad hoc network), particularly results on capacity scaling laws. In this work, we investigate capacity scaling laws for MIMO ad hoc networks. Our goal is to find the achievable throughput of each node as the number of nodes in the network increases. We employ a MIMO network model that captures spatial multiplexing (SM) and interference cancellation (IC). We show that for a MIMO network with n randomly located nodes, each equipped with γ antennas and a rate of W on each data stream, the achievable throughput of each node is Θ(γW/√<span style="text-decoration:overline;"> n ln n</span></span>). <b>3. Toward Simple Criteria for Establishing Capacity Scaling Laws.</b> Capacity scaling laws offer fundamental understanding on the trend of user throughput behavior when the network size increases. Since the seminal work of Gupta and Kumar, there have been tremendous efforts developing capacity scaling laws for ad hoc networks with various advanced physical layer technologies. These efforts led to different custom-designed approaches, most of which were intellectually challenging and lacked universal properties that can be extended to address scaling laws of ad hoc networks with a different physical layer technology. In this work, we present a set of simple yet powerful general criteria that one can apply to quickly determine the capacity scaling laws for various physical layer technologies under the protocol model. We prove the correctness of our proposed criteria and validate them through a number of case studies, such as ad hoc networks with directional antenna, MIMO, cognitive radio, multi-channel and multi-radio, and multiple packet reception. These simple criteria will serve as powerful tools to networking researchers to obtain throughput scaling laws of ad hoc networks under different physical layer technologies, particularly those to appear in the future. <b>4. Exploiting SIC forMulti-hopWireless Networks.</b> There is a growing interest on exploiting interference (rather than avoiding it) to increase network throughput. In particular, the so-called successive interference cancellation (SIC) scheme appears very promising, due to its ability to enable concurrent receptions from multiple transmitters and interference rejection. However, due to some stringent constraints and limit, SIC alone is inadequate to handle all concurrent interference. We advocate a joint interference exploitation and avoidance approach, which combines the best of interference exploitation and interference avoidance, while avoiding each's pitfalls. We discuss the new challenges of such a new approach in a multi-hop wireless network and propose a formal optimization framework, with cross-layer formulation of physical, link, and network layers. This framework offers a rather complete design space for SIC to squeeze the most out of interference. The goal of this effort is to lay a mathematical foundation for modeling and analysis of a joint interference exploitation and avoidance scheme in a multi-hop wireless network. Through modeling and analysis, we develop a tractable model that is suitable for studying a broad class of network throughput optimization problems. To demonstrate the practical utility of our model, we conduct a case study. Our numerical results affirm the validity of our model and give insights on how SIC can optimally interact with an interference avoidance scheme. <b>5. Throughput Optimization with Network-wide Energy Constraint.</b> Conserving network wide energy consumption is becoming an increasingly important concern for network operators. In this work, we study network-wide energy conservation problem which we hope will offer insights to both network operators and users. Specifically, we study how to maximize network throughput under a network-wide energy constraint for a general multi-hop wireless network. We formulate this problem as a mixed-integer nonlinear program (MINLP). We propose a novel piece-wise linear approximation to transform the nonlinear constraints into linear constraints. We prove that the solution developed under this approach is near optimal with guaranteed performance bound. <b>6. Bicriteria Optimization in Multi-hop Wireless Networks.</b> Network throughput and energy consumption are two important performance metrics for a multi-hop wireless network. Current state-of-the-art is limited to either maximizing throughput under some energy constraint or minimizing energy consumption while satisfying some throughput requirement. However, the important problem of how to optimize both objectives simultaneously remains open. In this work, we take a multicriteria optimization approach to offer a systematic study on the relationship between the two performance objectives. We show that the solution to the multicriteria optimization problem characterizes the envelope of the entire throughput energy region, i.e., the so-called optimal throughput-energy curve. We prove some important properties of the optimal throughput-energy curve. For case study, we consider both linear and nonlinear throughput functions. For the linear case, we characterize the optimal throughput-energy curve precisely through parametric analysis, while for the nonlinear case, we use a piece-wise linear approximation to approximate the optimal throughput-energy curve with arbitrary accuracy. Our results offer important insights on exploiting the trade-off between the two performance metrics. / Ph. D.

A critical factor affecting the future prospects of wireless networks for wide-scale deployment is network capacity: the end users wish to have their communication experience over wireless networks to be comparable or similar to that for wireline networks. An effective approach to increase network capacity is to increase spectrum efficiency. Such an approach can be achieved by the use of multiple antenna systems (also known as multiple-input multiple-output (MIMO) technology). The benefits of substantial improvements in capacity at no cost of additional spectrum and power have positioned MIMO as one of the breakthrough technologies in modern wireless communications. As expected, research activities on applying MIMO to a variety of wireless networks have soared in recent years. However, compared with the simple point-to-point MIMO channel, which is relatively well-understood nowadays, network design and performance optimization for MIMO-based wireless networks is considerably more challenging. Many fundamental problems remain unsolved. Due to the complex characteristics of MIMO physical layer technology, it is not only desirable but also necessary to consider models and constraints at multiple layers (e.g., physical, link, and network) jointly. The formulations of these cross-layer problems for MIMO wireless networks, however, are usually mathematically challenging. In this dissertation, we aim to develop some novel algorithmic design and optimization techniques that provide optimal or near-optimal solutions. Based on network structure, this dissertation is organized into two parts. In the first part, we focus on single-hop MIMO wireless networks, while in the second part, we focus on multi-hop MIMO networks. The main results and contributions of this dissertation are summarized as follows. Single-hop MIMO Networks. In the first part of this dissertation, we study three different optimization problems for single-hop MIMO networks. The first problem addresses weighted proportional fair (WPF) scheduling associated with MIMO broadcast channels (Chapter 2). For the WPF scheduling problem in MIMO broadcast channels, we develop two algorithms that can efficiently determine the optimal dirty paper encoding order and power allocation to achieve an optimal WPF performance. To our knowledge, our work is the first that provides solutions to the WPF scheduling problem in MIMO broadcast channels. Our next problem concerns single-hop MIMO ad hoc networks (Chapter 3), which are quite different from the MIMO broadcast channels studied in the previous chapter. Single-hop MIMO ad hoc networks can be simply described as "multiple one-to-one," as compared with MIMO broadcast channels, which are "one-to-many." Performance optimization for such networks is known to be challenging due to the non-convex mathematical structure. Indeed, these networks can be viewed as the general case of interference channels in network information theory context, for which the capacity region remains unknown even under the two-user case. In this chapter, we treat the co-channel interference in the network as noise. We consider the maximum weighted sum rate problem under the single-carrier setting. We propose a global optimization approach that combines branch-and-bound (BB) and the reformulation-linearization technique (RLT). This technique is guaranteed to find a global optimal solution Multi-hop MIMO Networks. In addition to managing resources such as power and scheduling in single-hop networks, routing and end-to-end session rate control need to be considered in multi-hop MIMO networks. Thus, performance optimization problems in multi-hop MIMO networks are more interesting and yet challenging. In Chapter 4, we first consider the problem of jointly optimizing power and bandwidth allocation at each node and multihop/multipath routing in a multi-hop MIMO network that employs orthogonal channels. We show that this problem has some special structure that admits a decomposition into a set of subproblems in its dual domain. Based on this finding, we propose both centralized and distributed optimization algorithms to solve this problem optimally. In Chapter 5, we relax the orthogonal channel assumption. More specifically, we exploit the advantage of "dirty paper coding" (DPC) to allow multiple links originated from the same node to share the same channel media simultaneously. However, the formulation of cross-layer optimization problem with DPC has a non-convex structure and an exponentially large search space inherent in enumerating DPC's encoding orders. To address these difficulties, we propose an approach to reformulate and convexify the original problem. Based on the reformulated problem, we design an efficient solution procedure by exploiting decomposable dual structure. One thing in common in Chapters 4 and 5 is that we adopt the classical matrix-based MIMO channel models at the physical layer. Although this approach has its merit, the complex matrix operations in the classical MIMO models may pose a barrier for researchers in networking research community to gain fundamental understanding on MIMO networks. To bridge this gap between communications and networking communities, in Chapter 6, we propose a simple, accurate, and tractable model to enable the networking community to carry out cross-layer research for multi-hop MIMO networks. At the physical layer, we develop an accurate and simple model for MIMO channel capacity computation that captures the essence of spatial multiplexing and transmit power limit without involving complex matrix operations and the water-filling algorithm. At the link layer, we devise a space-time scheduling scheme called order-based interference cancellation (OBIC) that significantly advances the existing zero-forcing beamforming (ZFBF) to handle interference in a multi-hop network setting. The proposed OBIC scheme employs simple algebraic computation on matrix dimensions to simplify ZFBF in a multi-hop network. Finally, we apply both the new physical and link layer models to study a cross-layer optimization problem for a multi-hop MIMO network. / Ph. D.

The explosion in growth of smart wireless devices has increased the ubiquitous presence of computational resources and location-based data. This new reality of numerous wireless devices capable of collecting, sharing, and processing information, makes possible an avenue for new enhanced applications. Multiple radio nodes with diverse functionalities can form a wireless cloud computing network (WCCN) and collaborate on executing complex applications using wireless distributed computing (WDC). Such a dynamically composed virtual cloud environment can offer services and resources hosted by individual nodes for consumption by user applications. This dissertation proposes an architectural framework for WCCNs and presents the different phases of its development, namely, development of a mathematical system model of WCCNs, simulation analysis of the performance benefits offered by WCCNs, design of decision-making mechanisms in the architecture, and development of a prototype to validate the proposed architecture. The dissertation presents a system model that captures power consumption, energy consumption, and latency experienced by computational and communication activities in a typical WCCN. In addition, it derives a stochastic model of the response time experienced by a user application when executed in a WCCN. Decision-making and resource allocation play a critical role in the proposed architecture. Two adaptive algorithms are presented, namely, a workload allocation algorithm and a task allocation - scheduling algorithm. The proposed algorithms are analyzed for power efficiency, energy efficiency, and improvement in the execution time of user applications that are achieved by workload distribution. Experimental results gathered from a software-defined radio network prototype of the proposed architecture validate the theoretical analysis and show that it is possible to achieve 80 % improvement in execution time with the help of just three nodes in the network. / Ph. D.

The rapid growth of the Internet of Things (IoT) introduces an additional challenge to the existing spectrum under-utilisation problem as large scale deployments of thousands devices are expected to require wireless connectivity. Dynamic Spectrum Access (DSA) has been proposed as a means of improving the spectrum utilisation of wireless systems. Based on the Cognitive Radio (CR) paradigm, DSA enables unlicensed spectrum users to sense their spectral environment and adapt their operational parameters to opportunistically access any temporally unoccupied bands without causing interference to the primary spectrum users. In the same context, CR inspired Machine-to-Machine (M2M) communications have recently been proposed as a potential solution to the spectrum utilisation problem, which has been driven by the ever increasing number of interconnected devices. M2M communications introduce new challenges for CR in terms of operational environments and design requirements. With spectrum sensing being the key function for CR, this thesis investigates the performance of spectrum sensing and proposes novel sensing approaches and models to address the sensing problem for cognitive M2M deployments. In this thesis, the behaviour of Energy Detection (ED) spectrum sensing for cognitive M2M nodes is modelled using the two-wave with dffi use power fading model. This channel model can describe a variety of realistic fading conditions including worse than Rayleigh scenarios that are expected to occur within the operational environments of cognitive M2M communication systems. The results suggest that ED based spectrum sensing fails to meet the sensing requirements over worse than Rayleigh conditions and consequently requires the signal-to-noise ratio (SNR) to be increased by up to 137%. However, by employing appropriate diversity and node cooperation techniques, the sensing performance can be improved by up to 11.5dB in terms of the required SNR. These results are particularly useful in analysing the eff ects of severe fading in cognitive M2M systems and thus they can be used to design effi cient CR transceivers and to quantify the trade-o s between detection performance and energy e fficiency. A novel predictive spectrum sensing scheme that exploits historical data of past sensing events to predict channel occupancy is proposed and analysed. This approach allows CR terminals to sense only the channels that are predicted to be unoccupied rather than the whole band of interest. Based on this approach, a spectrum occupancy predictor is developed and experimentally validated. The proposed scheme achieves a prediction accuracy of up to 93% which in turn can lead to up to 84% reduction of the spectrum sensing cost. Furthermore, a novel probabilistic model for describing the channel availability in both the vertical and horizontal polarisations is developed. The proposed model is validated based on a measurement campaign for operational scenarios where CR terminals may change their polarisation during their operation. A Gaussian approximation is used to model the empirical channel availability data with more than 95% confi dence bounds. The proposed model can be used as a means of improving spectrum sensing performance by using statistical knowledge on the primary users occupancy pattern.