Radio Resource Management Optimization For Next Generation Wireless Networks

The prominent versatility of today’s mobile broadband services and the rapid advancements in the cellular phones industry have led to a tremendous expansion in the wireless market volume. Despite the continuous progress in the radio-access technologies to cope with that expansion, many challenges still remain that need to be addressed by both the research and industrial sectors. One of the many remaining challenges is the efficient allocation and management of wireless network resources when using the latest cellular radio technologies (e.g., 4G). The importance of the problem stems from the scarcity of the wireless spectral resources, the large number of users sharing these resources, the dynamic behavior of generated traffic, and the stochastic nature of wireless channels. These limitations are further tightened as the provider’s commitment to high quality-of-service (QoS) levels especially data rate, delay and delay jitter besides the system’s spectral and energy efficiencies. In this dissertation, we strive to solve this problem by presenting novel cross-layer resource allocation schemes to address the efficient utilization of available resources versus QoS challenges using various optimization techniques. The main objective of this dissertation is to propose a new predictive resource allocation methodology using an agile ray tracing (RT) channel prediction approach. It is divided into two parts. The first part deals with the theoretical and implementational aspects of the ray tracing prediction model, and its validation. In the second part, a novel RT-based scheduling system within the evolving cloud radio access network (C-RAN) architecture is proposed. The impact of the proposed model on addressing the long term evolution (LTE) network limitations is then rigorously investigated in the form of optimization problems. The main contributions of this dissertation encompass the design of several heuristic solutions based on our novel RT-based scheduling model, developed to meet the aforementioned objectives while considering the co-existing limitations in the context of LTE networks. Both analytical and numerical methods are used within this thesis framework. Theoretical results are validated with numerical simulations. The obtained results demonstrate the effectiveness of our proposed solutions to meet the objectives subject to limitations and constraints compared to other published works

Dynamic bandwidth allocation in multi-class IP networks using utility functions.

PhDAbstact not availableFujitsu Telecommunications Europe Lt

34th Midwest Symposium on Circuits and Systems-Final Program

Organized by the Naval Postgraduate School Monterey California. Cosponsored by the IEEE Circuits and Systems Society. Symposium Organizing Committee: General Chairman-Sherif Michael, Technical Program-Roberto Cristi, Publications-Michael Soderstrand, Special Sessions- Charles W. Therrien, Publicity: Jeffrey Burl, Finance: Ralph Hippenstiel, and Local Arrangements: Barbara Cristi

Performance evaluation of multicast networks and service differentiation mechanisms in IP networks

The performance of a communication network depends on how well the network is designed in terms of delivering the level of service required by a given type of traffic. The field of teletraffic theory is concerned with quantifying the three-way relationship between the network, its level of service and the traffic arriving at the network. In this thesis, we study three different problems concerning this three-way relationship and present models to assist in designing and dimensioning networks to satisfy the different quality of service demands. In the first part of the thesis, we consider service differentiation mechanisms in packet-switched IP networks implementing a Differentiated Services (DiffServ) architecture. We study how bandwidth can be divided in a weighted fair manner between persistent elastic TCP flows, and between these TCP flows and streaming real-time UDP flows. To this end, we model the traffic conditioning and scheduling mechanisms on the packet and the flow level. We also model the interaction of these DiffServ mechanisms with the TCP congestion control mechanism and present closed-loop models for the sending rate of a TCP flow that reacts to congestion signals from the network. In the second part, we concentrate on non-persistent elastic TCP traffic in IP networks and study how flows can be differentiated in terms of mean delay by giving priority to flows based on their age. We study Multi Level Processor Sharing (MLPS) disciplines, where jobs are classified into levels based on their age or attained service. Between levels, a strict priority discipline is applied; the level containing the youngest jobs has the highest priority. Inside a particular level, any scheduling discipline could be used. We present an implementation proposal of a two-level discipline, PS+PS, with the Processor Sharing discipline used inside both levels. We prove that, as long as the hazard rate of the job-size distribution is decreasing, which is the case for Internet traffic, PS+PS, and any MLPS discipline that favors young jobs, is better than PS with respect to overall mean delay. In the final part, we study distribution-type streaming traffic in a multicast network, where there is, at most, one copy of each channel transmission in each network link, and quantify the blocking probability. We derive an exact blocking probability algorithm for multicast traffic in a tree network based on the convolution and truncation algorithm for unicast traffic. We present a new convolution operation, the OR-convolution, to suit the transmission principle of multicast traffic, and a new truncation operator to take into account the case of having both unicast and multicast traffic in the network. We also consider different user models derived from the single-user model.reviewe

Distributed control architecture for multiservice networks

The research focuses in devising decentralised and distributed control system architecture for the management of internetworking systems to provide improved service delivery and network control. The theoretical basis, results of simulation and implementation in a real-network are presented. It is demonstrated that better performance, utilisation and fairness can be achieved for network customers as well as network/service operators with a value based control system. A decentralised control system framework for analysing networked and shared resources is developed and demonstrated. This fits in with the fundamental principles of the Internet. It is demonstrated that distributed, multiple control loops can be run on shared resources and achieve proportional fairness in their allocation, without a central control. Some of the specific characteristic behaviours of the service and network layers are identified. The network and service layers are isolated such that each layer can evolve independently to fulfil their functions better. A common architecture pattern is devised to serve the different layers independently. The decision processes require no co-ordination between peers and hence improves scalability of the solution. The proposed architecture can readily fit into a clearinghouse mechanism for integration with business logic. This architecture can provide improved QoS and better revenue from both reservation-less and reservation-based networks. The limits on resource usage for different types of flows are analysed. A method that can sense and modify user utilities and support dynamic price offers is devised. An optimal control system (within the given conditions), automated provisioning, a packet scheduler to enforce the control and a measurement system etc are developed. The model can be extended to enhance the autonomicity of the computer communication networks in both client-server and P2P networks and can be introduced on the Internet in an incremental fashion. The ideas presented in the model built with the model-view-controller and electronic enterprise architecture frameworks are now independently developed elsewhere into common service delivery platforms for converged networks. Four US/EU patents were granted based on the work carried out for this thesis, for the cross-layer architecture, multi-layer scheme, measurement system and scheduler. Four conference papers were published and presented

ADAPTIVE CAPACITY ALLOCATION IN MPLS NETWORKS

Traffic Congestion is one of the salient issues that affect overall network performance. Network traffic has become very dynamic due to a variety of factors, such as, the number of users varies with time of the day, multimedia applications, bursts in traffic due to a failure and so on. Recently, Multi-Protocol Label Switching (MPLS) networks have emerged as a technology with many promising features such as traffic engineering, QoS provisioning, and speeding up the traffic transmission. However, MPLS still suffers from the nonstationary/transient conditions that sometimes cause congestion. Actually, congestion does not always occur when the network is short capacity, but rather, when the network resources are not efficiently utilized. Thus, it is very important to develop an algorithm that efficiently and dynamically adjusts the available capacity. In this thesis, we propose an adaptive capacity allocation scheme. We have started our consideration with a single traffic class system that has dynamic traffic where traffic arrival is considered at the level of connection/call arrival. We assume that the virtual network for this traffic class operates as a loss system; i.e. if a connection does not find bandwidth, the connection is blocked and cleared from the system. Then, we extended our work to include the multiple traffic classes. Two cases have been studied and analyzed; when classes have no coupling and when they are coupled. The capacity allocation scheme is derived from a first-order, differential equation-based, fluid-flow model that captures the traffic dynamics. The scheme aims to maintain the connection blocking probability within a specified range by dynamically adjusting the allocated capacity. A fluid flow differential equation model is developed to model the changing traffic environment. Using the fluid flow model, Lyapunov Stability theory is used to derive a novel adaptive capacity adjustment scheme which guarantees overall system stability while maintaining the target QoS parameters. Numerical results are given which show that the Lyapunov control based scheme successfully provides the desired QoS requirements and performs better than existing schemes in the literature

Minimizing queueing delays in computer networks

Ph.DDOCTOR OF PHILOSOPH

Learning algorithms for the control of routing in integrated service communication networks

There is a high degree of uncertainty regarding the nature of traffic on future integrated service networks. This uncertainty motivates the use of adaptive resource allocation policies that can take advantage of the statistical fluctuations in the traffic demands. The adaptive control mechanisms must be 'lightweight', in terms of their overheads, and scale to potentially large networks with many traffic flows. Adaptive routing is one form of adaptive resource allocation, and this thesis considers the application of Stochastic Learning Automata (SLA) for distributed, lightweight adaptive routing in future integrated service communication networks. The thesis begins with a broad critical review of the use of Artificial Intelligence (AI) techniques applied to the control of communication networks. Detailed simulation models of integrated service networks are then constructed, and learning automata based routing is compared with traditional techniques on large scale networks. Learning automata are examined for the 'Quality-of-Service' (QoS) routing problem in realistic network topologies, where flows may be routed in the network subject to multiple QoS metrics, such as bandwidth and delay. It is found that learning automata based routing gives considerable blocking probability improvements over shortest path routing, despite only using local connectivity information and a simple probabilistic updating strategy. Furthermore, automata are considered for routing in more complex environments spanning issues such as multi-rate traffic, trunk reservation, routing over multiple domains, routing in high bandwidth-delay product networks and the use of learning automata as a background learning process. Automata are also examined for routing of both 'real-time' and 'non-real-time' traffics in an integrated traffic environment, where the non-real-time traffic has access to the bandwidth 'left over' by the real-time traffic. It is found that adopting learning automata for the routing of the real-time traffic may improve the performance to both real and non-real-time traffics under certain conditions. In addition, it is found that one set of learning automata may route both traffic types satisfactorily. Automata are considered for the routing of multicast connections in receiver-oriented, dynamic environments, where receivers may join and leave the multicast sessions dynamically. Automata are shown to be able to minimise the average delay or the total cost of the resulting trees using the appropriate feedback from the environment. Automata provide a distributed solution to the dynamic multicast problem, requiring purely local connectivity information and a simple updating strategy. Finally, automata are considered for the routing of multicast connections that require QoS guarantees, again in receiver-oriented dynamic environments. It is found that the distributed application of learning automata leads to considerably lower blocking probabilities than a shortest path tree approach, due to a combination of load balancing and minimum cost behaviour

Soft Handoff in MC-CDMA Cellular Networks Supporting Multimedia Services

An adaptive resource reservation and handoff priority scheme, which jointly considers the characteristics from the physical, link and network layers, is proposed for a packet switching Multicode (MC)-CDMA cellular network supporting multimedia applications. A call admission region is derived for call admission control (CAC) and handoff management with the satisfaction of quality of service (QoS) requirements for all kinds of multimedia traffic, where the QoS parameters include the wireless transmission bit error rate (BER), the packet loss rate (PLR) and delay requirement. The BER requirement is guaranteed by properly arranging simultaneous packet transmissions, whereas the PLR and delay requirements are guaranteed by the proposed packet scheduling and partial packet integration scheme. To give service priority to handoff calls, a threshold-based adaptive resource reservation scheme is proposed on the basis of a practical user mobility model and a proper handoff request prediction scheme. The resource reservation scheme gives handoff calls a higher admission priority over new calls, and is designed to adjust the reservation-request time threshold adaptively according to the varying traffic load. The individual reservation requests form a common reservation pool, and handoff calls are served on a first-come-first-serve basis. By exploiting the transmission rate adaptability of video calls to the available radio resources, the resources freed from rate-adaptive high-quality video calls by service degradation can be further used to prioritize handoff calls. With the proposed resource reservation and handoff priority scheme, the dynamic properties of the system can be closely captured and a better grade of service (GoS) in terms of new call blocking and handoff call dropping probabilities(rates) can be achieved compared to other schemes in literature. Numerical results are presented to show the improvement of the GoS performance and the efficient utilization of the radio resources