Optimisation of large scale network problems

The Constrained Shortest Path Problem (CSPP) consists of finding the shortest path in a graph or network that satisfies one or more resource constraints. Without these constraints, the shortest path problem can be solved in polynomial time; with them, the CSPP is NP-hard and thus far no polynomial-time algorithms exist for solving it optimally. The problem arises in a number of practical situations. In the case of vehicle path planning, the vehicle may be an aircraft flying through a region with obstacles such as mountains or radar detectors, with an upper bound on the fuel consumption, the travel time or the risk of attack. The vehicle may be a submarine travelling through a region with sonar detectors, with a time or risk budget. These problems all involve a network which is a discrete model of the physical domain. Another example would be the routing of voice and data information in a communications network such as a mobile phone network, where the constraints may include maximum call delays or relay node capacities. This is a problem of current economic importance, and one for which time-sensitive solutions are not always available, especially if the networks are large. We consider the simplest form of the problem, large grid networks with a single side constraint, which have been studied in the literature. This thesis explores the application of Constraint Programming combined with Lagrange Relaxation to achieve optimal or near-optimal solutions of the CSPP. The following is a brief outline of the contribution of this thesis. Lagrange Relaxation may or may not achieve optimal or near-optimal results on its own. Often, large duality gaps are present. We make a simple modification to Dijkstra’s algorithm that does not involve any additional computational work in order to generate an estimate of path time at every node.We then use this information to constrain the network along a bisecting meridian. The combination of Lagrange Relaxation (LR) and a heuristic for filtering along the meridian provide an aggressive method for finding near-optimal solutions in a short time. Two network problems are studied in this work. The first is a Submarine Transit Path problem in which the transit field contains four sonar detectors at known locations, each with the same detection profile. The side constraint is the total transit time, with the submarine capable of 2 speeds. For the single-speed case, the initial LR duality gap may be as high as 30%. The first hybrid method uses a single centre meridian to constrain the network based on the unused time resource, and is able to produce solutions that are generally within 1% of optimal and always below 3%. Using the computation time for the initial Lagrange Relaxation as a baseline, the average computation time for the first hybrid method is about 30% to 50% higher, and the worst case CPU times are 2 to 4 times higher. The second problem is a random valued network from the literature. Edge costs, times, and lengths are uniform, randomly generated integers in a given range. Since the values given in the literature problems do not yield problems with a high duality gap, the values are varied and from a population of approximately 100,000 problems only the worst 200 from each set are chosen for study. These problems have an initial LR duality gap as high as 40%. A second hybrid method is developed, using values for the unused time resource and the lower bound values computed by Dijkstra’s algorithm as part of the LR method. The computed values are then used to position multiple constraining meridians in order to allow LR to find better solutions.This second hybrid method is able to produce solutions that are generally within 0.1% of optimal, with computation times that are on average 2 times the initial Lagrange Relaxation time, and in the worst case only about 5 times higher. The best method for solving the Constrained Shortest Path Problem reported in the literature thus far is the LRE-A method of Carlyle et al. (2007), which uses Lagrange Relaxation for preprocessing followed by a bounded search using aggregate constraints. We replace Lagrange Relaxation with the second hybrid method and show that optimal solutions are produced for both network problems with computation times that are between one and two orders of magnitude faster than LRE-A. In addition, these hybrid methods combined with the bounded search are up to 2 orders of magnitude faster than the commercial CPlex package using a straightforward MILP formulation of the problem. Finally, the second hybrid method is used as a preprocessing step on both network problems, prior to running CPlex. This preprocessing reduces the network size sufficiently to allow CPlex to solve all cases to optimality up to 3 orders of magnitude faster than without this preprocessing, and up to an order of magnitude faster than using Lagrange Relaxation for preprocessing. Chapter 1 provides a review of the thesis and some terminology used. Chapter 2 reviews previous approaches to the CSPP, in particular the two current best methods. Chapter 3 applies Lagrange Relaxation to the Submarine Transit Path problem with 2 speeds, to provide a baseline for comparison. The problem is reduced to a single speed, which demonstrates the large duality gap problem possible with Lagrange Relaxation, and the first hybrid method is introduced.Chapter 4 examines a grid network problem using randomly generated edge costs and weights, and introduces the second hybrid method. Chapter 5 then applies the second hybrid method to both network problems as a preprocessing step, using both CPlex and a bounded search method from the literature to solve to optimality. The conclusion of this thesis and directions for future work are discussed in Chapter 6

Analysis of Biochemical Reaction Networks using Tropical and Polyhedral Geometry Methods

The field of systems biology makes an attempt to realise various biological functions and processes as the emergent properties of the underlying biochemical network model. The area of computational systems biology deals with the computational methods to compute such properties. In this context, the thesis primarily discusses novel computational methods to compute the emergent properties as well as to recognize the essence in complex network models. The computational methods described in the thesis are based on the computer algebra techniques, namely tropical geometry and extreme currents. Tropical geometry is based on ideas of dominance of monomials appearing in a system of differential equations, which are often used to describe the dynamics of the network model. In such differential equation based models, tropical geometry deals with identification of the metastable regimes, defined as low dimensional regions of the phase space close to which the dynamics is much slower compared to the rest of the phase space. The application of such properties in model reduction and symbolic dynamics are demonstrated in the network models obtained from a public database namely Biomodels. Extreme currents are limiting edges of the convex polyhedrons describing the admissible fluxes in biochemical networks, which are helpful to decompose a biochemical network into a set of irreducible pathways. The pathways are shown to be associated with given clinical outcomes thereby providing some mechanistic insights associated with the clinical phenotypes. Similar to the tropical geometry, the method based on extreme currents is evaluated on the network models derived from a public database namely KEGG. Therefore, this thesis makes an attempt to explain the emergent properties of the network model by determining extreme currents or metastable regimes. Additionally, their applicability in the real world network models are discussed

Service quality assurance for the IPTV networks

The objective of the proposed research is to design and evaluate end-to-end solutions to support the Quality of Experience (QoE) for the Internet Protocol Television (IPTV) service. IPTV is a system that integrates voice, video, and data delivery into a single Internet Protocol (IP) framework to enable interactive broadcasting services at the subscribers. It promises significant advantages for both service providers and subscribers. For instance, unlike conventional broadcasting systems, IPTV broadcasts will not be restricted by the limited number of channels in the broadcast/radio spectrum. Furthermore, IPTV will provide its subscribers with the opportunity to access and interact with a wide variety of high-quality on-demand video content over the Internet. However, these advantages come at the expense of stricter quality of service (QoS) requirements than traditional Internet applications. Since IPTV is considered as a real-time broadcast service over the Internet, the success of the IPTV service depends on the QoE perceived by the end-users. The characteristics of the video traffic as well as the high-quality requirements of the IPTV broadcast impose strict requirements on transmission delay. IPTV framework has to provide mechanisms to satisfy the stringent delay, jitter, and packet loss requirements of the IPTV service over lossy transmission channels with varying characteristics. The proposed research focuses on error recovery and channel change latency problems in IPTV networks. Our specific aim is to develop a content delivery framework that integrates content features, IPTV application requirements, and network characteristics in such a way that the network resource utilization can be optimized for the given constraints on the user perceived service quality. To achieve the desired QoE levels, the proposed research focuses on the design of resource optimal server-based and peer-assisted delivery techniques. First, by analyzing the tradeoffs on the use of proactive and reactive repair techniques, a solution that optimizes the error recovery overhead is proposed. Further analysis on the proposed solution is performed by also focusing on the use of multicast error recovery techniques. By investigating the tradeoffs on the use of network-assisted and client-based channel change solutions, distributed content delivery frameworks are proposed to optimize the error recovery performance. Next, bandwidth and latency tradeoffs associated with the use of concurrent delivery streams to support the IPTV channel change are analyzed, and the results are used to develop a resource-optimal channel change framework that greatly improves the latency performance in the network. For both problems studied in this research, scalability concerns for the IPTV service are addressed by properly integrating peer-based delivery techniques into server-based solutions.Ph.D

Learner autonomy: The complexity of control‐shift

It is generally held that constructing learner autonomy (LA) requires a pedagogical shift of control from teachers to students. It is also understood that the development of learner autonomy relates largely to teacher autonomy (TA), which requires school managers to relinquish some degree of control to teachers. However, from a socio‐political perspective, the construct of autonomy is a right also extended to educational managers (MA). Thus, a problem arises: how can the three levels of controlshifts co‐exist and survive in harmony, and ideally, thrive each in its own way? Based on a recent case study, this paper aims to explore the complexity of the dynamic interaction between these three types of autonomy within an educational hierarchy. The study was conducted in a private Chinese secondary school which was promoting whole‐person development through a comprehensive innovation project involving all its academic staff members. The participants comprised nine English teachers, the principal, and the school’s executive director. Data collection was conducted through interviews, classroom observations followed by post‐lesson discussions, and the researcher’s field notes. Specifically, three questions were addressed in this paper focusing on managers’ perceptions of LA, a classroom instruction model intended to cultivate LA, and an in‐house professional development scheme to facilitate TA, all of which impacted on teachers’ professional decision‐making. The findings display a complex picture of these issues, and imply the importance of a genuine shared understanding of the nature of autonomy and the need to carefully ensure the optimal balance among the three types of autonomy in the design and implementation of curriculum innovations

Spectrum Sharing Methods in Coexisting Wireless Networks

Radio spectrum, the fundamental basis for wireless communication, is a finite resource. The development of the expanding range of radio based devices and services in recent years makes the spectrum scarce and hence more costly under the paradigm of extensive regulation for licensing. However, with mature technologies and with their continuous improvements it becomes apparent that tight licensing might no longer be required for all wireless services. This is from where the concept of utilizing the unlicensed bands for wireless communication originates. As a promising step to reduce the substantial cost for radio spectrum, different wireless technology based networks are being deployed to operate in the same spectrum bands, particularly in the unlicensed bands, resulting in coexistence. However, uncoordinated coexistence often leads to cases where collocated wireless systems experience heavy mutual interference. Hence, the development of spectrum sharing rules to mitigate the interference among wireless systems is a significant challenge considering the uncoordinated, heterogeneous systems. The requirement of spectrum sharing rules is tremendously increasing on the one hand to fulfill the current and future demand for wireless communication by the users, and on the other hand, to utilize the spectrum efficiently. In this thesis, contributions are provided towards dynamic and cognitive spectrum sharing with focus on the medium access control (MAC) layer, for uncoordinated scenarios of homogeneous and heterogeneous wireless networks, in a micro scale level, highlighting the QoS support for the applications. This thesis proposes a generic and novel spectrum sharing method based on a hypothesis: The regular channel occupation by one system can support other systems to predict the spectrum opportunities reliably. These opportunities then can be utilized efficiently, resulting in a fair spectrum sharing as well as an improving aggregated performance compared to the case without having special treatment. The developed method, denoted as Regular Channel Access (RCA), is modeled for systems specified by the wireless local resp. metropolitan area network standards IEEE 802.11 resp. 802.16. In the modeling, both systems are explored according to their respective centrally controlled channel access mechanisms and the adapted models are evaluated through simulation and results analysis. The conceptual model of spectrum sharing based on the distributed channel access mechanism of the IEEE 802.11 system is provided as well. To make the RCA method adaptive, the following enabling techniques are developed and integrated in the design: a RSS-based (Received Signal Strength based) detection method for measuring the channel occupation, a pattern recognition based algorithm for system identification, statistical knowledge based estimation for traffic demand estimation and an inference engine for reconfiguration of resource allocation as a response to traffic dynamics. The advantage of the RCA method is demonstrated, in which each competing collocated system is configured to have a resource allocation based on the estimated traffic demand of the systems. The simulation and the analysis of the results show a significant improvement in aggregated throughput, mean delay and packet loss ratio, compared to the case where legacy wireless systems coexists. The results from adaptive RCA show its resilience characteristics in case of dynamic traffic. The maximum achievable throughput between collocated IEEE 802.11 systems applying RCA is provided by means of mathematical calculation. The results of this thesis provide the basis for the development of resource allocation methods for future wireless networks particularly emphasized to operate in current unlicensed bands and in future models of the Open Spectrum Alliance