Orthogonal Array Experiment in Systems

This paper espouses the application of orthogonal array experiment to solve a class of engineering optimization problems encountered in systems engineering and architecting. It also illustrates the applicability of orthogonal array experiment in systems engineering and architecting with two examples: verification and validation of the performance of a bandwidth allocation algorithm and architecting of a system of systems to respond to small boat attacks by terrorists. The orthogonal array experiment approach does not call for linearization of nonlinear engineering optimization problems; using orthogonal arrays, it solves them directly by carrying out the smallest possible number of experiments and determining their solutions from the results of the experiments. The orthogonal array experiment method has been found to be effective and efficient for these problems. The feasibility of applying the orthogonal array experiment approach to these problems suggests its potential application to other optimization problems encountered in systems engineering and architecting

Proton exchange membrane fuel cell stack design optimization using an improved Jaya algorithm

Fuel cell stack configuration optimization is known to be a problem that, in addition to presenting engineering challenges, is computationally hard. This paper presents an improved computational heuristic for solving the problem. The problem addressed in this paper is one of constrained optimization, where the goal is to seek optimal (or near-optimal) values of (i) the number of proton exchange membrane fuel cells (PEMFCs) to be connected in series to form a group, (ii) the number of such groups to be connected in parallel, and (iii) the cell area, such that the PEMFC assembly delivers the rated voltage at the rated power while the cost of building the assembly is as low as possible. Simulation results show that the proposed method outperforms four of the best-known methods in the literature. The improvement in performance afforded by the proposed algorithm is validated with statistical tests of significance

Renegotiation based dynamic bandwidth allocation for selfsimilar VBR traffic

The provision of QoS to applications traffic depends heavily on how different traffic types are categorized and classified, and how the prioritization of these applications are managed. Bandwidth is the most scarce network resource. Therefore, there is a need for a method or system that distributes an available bandwidth in a network among different applications in such a way that each class or type of traffic receives their constraint QoS requirements. In this dissertation, a new renegotiation based dynamic resource allocation method for variable bit rate (VBR) traffic is presented. First, pros and cons of available off-line methods that are used to estimate selfsimilarity level (represented by Hurst parameter) of a VBR traffic trace are empirically investigated, and criteria to select measurement parameters for online resource management are developed. It is shown that wavelet analysis based methods are the strongest tools in estimation of Hurst parameter with their low computational complexities, compared to the variance-time method and R/S pox plot. Therefore, a temporal energy distribution of a traffic data arrival counting process among different frequency sub-bands is considered as a traffic descriptor, and then a robust traffic rate predictor is developed by using the Haar wavelet analysis. The empirical results show that the new on-line dynamic bandwidth allocation scheme for VBR traffic is superior to traditional dynamic bandwidth allocation methods that are based on adaptive algorithms such as Least Mean Square, Recursive Least Square, and Mean Square Error etc. in terms of high utilization and low queuing delay. Also a method is developed to minimize the number of bandwidth renegotiations to decrease signaling costs on traffic schedulers (e.g. WFQ) and networks (e.g. ATM). It is also quantified that the introduced renegotiation based bandwidth management scheme decreases heavytailedness of queue size distributions, which is an inherent impact of traffic self similarity. The new design increases the achieved utilization levels in the literature, provisions given queue size constraints and minimizes the number of renegotiations simultaneously. This renegotiation -based design is online and practically embeddable into QoS management blocks, edge routers and Digital Subscriber Lines Access Multiplexers (DSLAM) and rate adaptive DSL modems

Location management and fault tolerance issues in mobile networks

Mobile networks has become ubiqutous in todays life. The number of people using this technology is rapidly growing each day. The mobile population is expected to reach the figure of nearly 1 billion in the near future. Several research efforts are being undertaken to address various issues in the design and operation of mobile networks. Some of the active research issues in mobile networking include channel allocation, mobility management, signal processing, fault tolerance, routing protocols and interoperability between different mobile networking protocols. In this dissertation we focus on a couple of these research issues namely mobility management and fault tolerance. Mobility management deals with managing the mobile nodes when they move. The network has to maintain connection to the mobile node inspite of the nodes changing location. We develop fundamental bounds for load balanced location management. We develop novel algorithms for load balanced location management in mobile networks. We later derive fundamental bounds satisfied by any load balanced location management algorithm in the presence of failures in the network. We then present a fast recovery protocol to recover from failures in the network. The salient feature of this protocol being the removal of the use of wireless bandwidth in the recovery process. We conclude the thesis by discussing some of the future issues in the area of mobile networks

Topological Design of Multiple Virtual Private Networks UTILIZING SINK-TREE PATHS

With the deployment of MultiProtocol Label Switching (MPLS) over a core backbone networks, it is possible for a service provider to built Virtual Private Networks (VPNs) supporting various classes of services with QoS guarantees. Efficiently mapping the logical layout of multiple VPNs over a service provider network is a challenging traffic engineering problem. The use of sink-tree (multipoint-to-point) routing paths in a MPLS network makes the VPN design problem different from traditional design approaches where a full-mesh of point-to-point paths is often the choice. The clear benefits of using sink-tree paths are the reduction in the number of label switch paths and bandwidth savings due to larger granularities of bandwidth aggregation within the network. In this thesis, the design of multiple VPNs over a MPLS-like infrastructure network, using sink-tree routing, is formulated as a mixed integer programming problem to simultaneously find a set of VPN logical topologies and their dimensions to carry multi-service, multi-hour traffic from various customers. Such a problem formulation yields a NP-hard complexity. A heuristic path selection algorithm is proposed here to scale the VPN design problem by choosing a small-but-good candidate set of feasible sink-tree paths over which the optimal routes and capacity assignments are determined. The proposed heuristic has clearly shown to speed up the optimization process and the solution can be obtained within a reasonable time for a realistic-size network. Nevertheless, when a large number of VPNs are being layout simultaneously, a standard optimization approach has a limited scalability. Here, the heuristics termed the Minimum-Capacity Sink-Tree Assignment (MCSTA) algorithm proposed to approximate the optimal bandwidth and sink-tree route assignment for multiple VPNs within a polynomial computational time. Numerical results demonstrate the MCSTA algorithm yields a good solution within a small error and sometimes yields the exact solution. Lastly, the proposed VPN design models and solution algorithms are extended for multipoint traffic demand including multipoint-to-point and broadcasting connections

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