A new promising approach for wireless network optimization is from a cross-layer perspective. This thesis focuses on exploiting channel state information (CSI) from the physical layer for optimal transmission scheduling at the medium access control (MAC) layer. The first part of the thesis considers exploiting CSI via a distributed channel-aware MAC protocol. The MAC protocol is analysed using a centralized design approach and a non-cooperative game theoretic approach. Structural results are obtained and provably convergent stochastic approximation algorithms that can estimate the optimal transmission policies are proposed. Especially, in the game theoretic MAC formulation, it is proved that the best response transmission policies are threshold in the channel state and there exists a Nash equilibrium at which every user deploys a threshold transmission policy. This threshold result leads to a particularly efficient stochastic-approximation-based adaptive learning algorithm and a simple distributed implementation of the MAC protocol. Simulations show that the channel-aware MAC protocols result in system throughputs that increase with the number of users. The thesis also considers opportunistic transmission scheduling from the perspective of a single user using Markov Decision Process (MDP) approaches. Both channel state information and channel memory are exploited for opportunistic transmission. First, a finite horizon MDP transmission scheduling problem is considered. The finite horizon formulation is suitable for short-term delay constraints. It is proved for the finite horizon opportunistic transmission scheduling problem that the optimal transmission policy is threshold in the buffer occupancy state and the transmission time. This two-dimensional threshold structure substantially reduces the computational complexity required to compute and implement the optimal policy. Second, the opportunistic transmission scheduling problem is formulated as an infinite horizon average cost MDP with a constraint on the average waiting cost. An advantage of the infinite horizon formulation is that the optimal policy is stationary. Using the Lagrange dynamic programming theory and the supermodularity method, it is proved that the stationary optimal transmission scheduling policy is a randomized mixture of two policies that are threshold in the buffer occupancy state. A stochastic approximation algorithm and a Q-learning based algorithm that can adaptively estimate the optimal transmission scheduling policies are then proposed.

The ever-increasing demand on content distribution and media streaming over the Internet has created the need for efficient methods of delivering information. One of the most promising approaches is based on multicasting. However, multicast solutions have to cope with several constraints as well as being able to perform in different environments such as wired, wireless, and ad hoc environments. Additionally, the scale and size of the Internet introduces another dimension of difficulty. Providing scalable multicast for mobile hosts in wireless environment and in mobile ad hoc networks (MANETs) is a challenging problem. In the past few years, several protocols have been proposed to efficient multicast solutions over the Internet, but these protocols did not give efficient solution for the scalability issue. In this thesis, scalable multicast protocols for wired, wireless and wireless ad hoc networks are proposed and evaluated. These protocols share the idea of building up a multicast tree gradually and recursively as join/leave of the multicast group members using a dynamic branching node-based tree (DBT) concept. The DBT uses a pair of branching node messages (BNMs). These messages traverse between a set of dynamically assigned branching node routers (BNRs) to build the multicast tree. In the proposed protocols only the branching node routers (BNRs) carry the state information about their next BNRs rather than the multicast group members, which gives a fixed size of control packet header size as the multicast group size increases, i.e. a good solution to the problem of scalability. Also the process of join/leave of multicast group members is carried out locally which gives low join/leave latency. The proposed protocols include: Scalable Recursive Multicast protocol (SReM) which is proposed using the DBT concepts mentioned above, Mobile Scalable Recursive Multicast protocol (MoSReM) which is an extension for SReM by taking into consideration the mobility feature in the end hosts and performing an efficient roaming process, and finally, a Scalable Ad hoc Recursive Multicast protocol (SARM) to achieve the mobility feature for all nodes and performing an efficient solution for link recovery because of node movement. By cost analysis and an extensive simulation, the proposed protocols show many positive features like fixed size control messages, being scalable, low end to end delay, high packet rate delivery and low normalized routing overhead. The thesis concludes by discussing the contributions of the proposed protocols on scalable multicast in the Internet society.

Multipath TCP (MPTCP) is a new modification of TCP protocol which enables a client to transfer data over multiple paths simultaneously under a single TCP connection, for improved throughput and fault resilience. However, MPTCP is susceptible to some major drawbacks when applied in a wireless network. We found several cases where, despite improving individual MPTCP clients throughput, MPTCP reduces the capacity of the overall wireless network due to the mac level fairness and contention-based access schemes. Additionally, even if the bandwidth improves, employing Multipath TCP (MPTCP) in wireless networks can be energy inecient due to additional energy consumption by multiple interfaces. This creates a dilemma between bandwidth improvement and energy efficiency. This thesis research aims to solve these important issues for MPTCP in the wireless environment. We analyzed the root cause of these drawbacks and identified instances where they can arise. Two novel schemes denoted MPWiFi and kMPTCP, are developed to solve the bandwidth degradation and energy efficiency issues respectively, while maintaining the promised benefitts of MPTCP. The MPWiFi assigns dierent priorities to the subflows and aggressively suppresses some of them based on some design logic. Similarly, kMPTCP adds an additional multipath subflow only if the bandwidth requirement can't be fulllled by single path and the new subflow meets the data rate and signal strength condition. Moreover, kMPTCP keeps additional subflows as long as the signal strength remains in good range and this subflow remain mandatory to provide the necessary bandwidth to the application. These two schemes have been implemented along with Linux Kernel MPTCP implementation. Extensive real-world deployment and NS3 simulation show that the proposed schemes can eectively alleviate the adverse impacts of the MPTCP based multipath access in Wireless networks.

abstract: A Fiber-Wireless (FiWi) network integrates a passive optical network (PON) with wireless mesh networks (WMNs) to provide high speed backhaul via the PON while offering the flexibility and mobility of a WMN. Generally, increasing the size of a WMN leads to higher wireless interference and longer packet delays. The partitioning of a large WMN into several smaller WMN clusters, whereby each cluster is served by an Optical Network Unit (ONU) of the PON, is examined. Existing WMN throughput-delay analysis techniques considering the mean load of the nodes at a given hop distance from a gateway (ONU) are unsuitable for the heterogeneous nodal traffic loads arising from clustering. A simple analytical queuing model that considers the individual node loads to accurately characterize the throughput-delay performance of a clustered FiWi network is introduced. The accuracy of the model is verified through extensive simulations. It is found that with sufficient PON bandwidth, clustering substantially improves the FiWi network throughput-delay performance by employing the model to examine the impact of the number of clusters on the network throughput-delay performance. Different traffic models and network designs are also studied to improve the FiWi network performance. / Dissertation/Thesis / Doctoral Dissertation Electrical Engineering 2015

A new promising approach for wireless network optimization is from a cross-layer perspective. This thesis focuses on exploiting channel state information (CSI) from the physical layer for optimal transmission scheduling at the medium access control (MAC) layer. The first part of the thesis considers exploiting CSI via a distributed channel-aware MAC protocol. The MAC protocol is analysed using a centralized design approach and a non-cooperative game theoretic approach. Structural results are obtained and provably convergent stochastic approximation algorithms that can estimate the optimal transmission policies are proposed. Especially, in the game theoretic MAC formulation, it is proved that the best response transmission policies are threshold in the channel state and there exists a Nash equilibrium at which every user deploys a threshold transmission policy. This threshold result leads to a particularly efficient stochastic-approximation-based adaptive learning algorithm and a simple distributed implementation of the MAC protocol. Simulations show that the channel-aware MAC protocols result in system throughputs that increase with the number of users. The thesis also considers opportunistic transmission scheduling from the perspective of a single user using Markov Decision Process (MDP) approaches. Both channel state information and channel memory are exploited for opportunistic transmission. First, a finite horizon MDP transmission scheduling problem is considered. The finite horizon formulation is suitable for short-term delay constraints. It is proved for the finite horizon opportunistic transmission scheduling problem that the optimal transmission policy is threshold in the buffer occupancy state and the transmission time. This two-dimensional threshold structure substantially reduces the computational complexity required to compute and implement the optimal policy. Second, the opportunistic transmission scheduling problem is formulated as an infinite horizon average cost MDP with a constraint on the average waiting cost. An advantage of the infinite horizon formulation is that the optimal policy is stationary. Using the Lagrange dynamic programming theory and the supermodularity method, it is proved that the stationary optimal transmission scheduling policy is a randomized mixture of two policies that are threshold in the buffer occupancy state. A stochastic approximation algorithm and a Q-learning based algorithm that can adaptively estimate the optimal transmission scheduling policies are then proposed. / Applied Science, Faculty of / Electrical and Computer Engineering, Department of / Graduate

The diploma thesis is focused on exploring the possibility of VoIP service in a wireless network of University of Economics, Prague. This thesis describes the basic principles of VoIP and related wireless technologies necessary for its quality and stable operation. Subsequently, different configurations of wireless network and end clients are tested and compared, including its impact on ordinary users, in a laboratory environment with idle and fully utilized frequency band. Finally, a roaming operation with the use of several advanced 802.11 standards is tested in the real environment of the Old building in Žižkov. In conclusion, the ideal settings for all telecommunication devices are recommended in order to maximize the quality of VoIP operation and to minimize the negative impact on ordinary users.

abstract: This dissertation studies the scheduling in two stochastic networks, a co-located wireless network and an outpatient healthcare network, both of which have a cyclic planning horizon and a deadline-related performance metric. For the co-located wireless network, a time-slotted system is considered. A cycle of planning horizon is called a frame, which consists of a fixed number of time slots. The size of the frame is determined by the upper-layer applications. Packets with deadlines arrive at the beginning of each frame and will be discarded if missing their deadlines, which are in the same frame. Each link of the network is associated with a quality of service constraint and an average transmit power constraint. For this system, a MaxWeight-type problem for which the solutions achieve the throughput optimality is formulated. Since the computational complexity of solving the MaxWeight-type problem with exhaustive search is exponential even for a single-link system, a greedy algorithm with complexity O(nlog(n)) is proposed, which is also throughput optimal. The outpatient healthcare network is modeled as a discrete-time queueing network, in which patients receive diagnosis and treatment planning that involves collaboration between multiple service stations. For each patient, only the root (first) appointment can be scheduled as the following appointments evolve stochastically. The cyclic planing horizon is a week. The root appointment is optimized to maximize the proportion of patients that can complete their care by a class-dependent deadline. In the optimization algorithm, the sojourn time of patients in the healthcare network is approximated with a doubly-stochastic phase-type distribution. To address the computational intractability, a mean-field model with convergence guarantees is proposed. A linear programming-based policy improvement framework is developed, which can approximately solve the original large-scale stochastic optimization in queueing networks of realistic sizes. / Dissertation/Thesis / Doctoral Dissertation Electrical Engineering 2020

The purpose of the thesis is to design and physically implement a system for location of devices in a Wi-Fi based networks deployed in the interior of small and medium-sized enterprises. First of all, the attention is given to the survey of commonly available technologies suitable for determination of the object position. Then, based on these findings, architecture of a location system comprising an array of sensor nodes and central processing unit is proposed. In conclusion, the results are presented and the fulfillment of the requirements is evaluated.

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In this paper, we introduce a clean-slate architecture for improving the delivery of data packets in IEEE 802.11 wireless mesh networks. Opposed to the rigid TCP/IP layer architecture which exhibits serious deficiencies in such networks, we propose a unitary layer approach that combines both routing and transport functionalities in a single layer. The new Mesh Transmission Layer (MTL) incorporates cross-interacting routing and transport modules for a reliable data delivery based on the loss probabilities of wireless links. Due to the significant drawbacks of standard TCP over IEEE 802.11, we particularly focus on the transport module, proposing a pure rate-based approach for transmitting data packets according to the current contention in the network. By considering the IEEE 802.11 spatial reuse constraint and employing a novel acknowledgment scheme, the new transport module improves both goodput and fairness in wireless mesh networks. In a comparative performance study, we show that MTL achieves up to 48% more goodput and up to 100% less packet drops than TCP/IP, while maintaining excellent fairness results.