The dual network theorem for static flow networks and its application for maximising the throughput flow

The paper discuses a new fundamental result in the theory of flow networks referred to as the ‘dual network theorem forstatic flow networks’. The theorem states that the maximum throughput flow in any static network is equal to the sum ofthe capacities of the edges coming out of the source, minus the total excess flow at all excess nodes, plus the maximumthroughput flow in the dual network. For very few imbalanced nodes in a flow network, determining the throughput flowin the dual network is a task significantly easier than determining the throughput flow in the original network. This createsthe basis of a very efficient algorithm for maximising the throughput flow in a network, by maximising the throughputflow in its dual network.Consequently, a new algorithm for maximising the throughput flow in a network has been proposed. For networks withvery few imbalanced nodes, in the case where only the maximum throughput flow is of interest, the proposed algorithmwill outperform any classical method for determining the maximum throughput flow.In this paper we also raise awareness of a fundamental flaw in classical algorithms for maximising the throughput flow instatic networks with directed edges. Despite the years of intensive research on static flow networks, the classicalalgorithms leave undesirable directed loops of flow in the optimised networks. These directed flow loops are associatedwith wastage of energy and resources and increased levels of congestion in the optimised networks. Consequently, analgorithm is also proposed for discovering and removing directed loops of flow in networks

The throughput flow constraint theorem and its applications

The paper states and proves an important result related to the theory of flow networks with disturbed flows:“the throughput flow constraint in any network is always equal to the throughput flow constraint in its dual network”. After the failure or congestion of several edges in the network, the throughput flow constraint theorem provides the basis of a very efficient algorithm for determining the edge flows which correspond to the optimal throughput flow from sources to destinations which is the throughput flow achieved with the smallest amount of generation shedding from the sources. In the case where a failure of an edge causes a loss of the entire flow through the edge, the throughput flow constraint theorem permits the calculation of the new maximum throughput flow to be done in time, where m is the number of edges in the network.In this case, the new maximum throughput flow is calculated by inspecting the network only locally, in the vicinity of the failed edge, without inspecting the rest of the network. The superior average running time of the presented algorithm, makes it particularly suitable for decongesting overloaded transmission links of telecommunication networks, in real time.In the paper, it is also shown that the deliberate choking of flows along overloaded edges, leading to a generation of momentary excess and deficit flow, provides a very efficient mechanism for decongesting overloaded branches

Closed parasitic flow loops and dominated loops in networks

The paper raises awareness of the presence of closed parasitic flow loops in the solutions of published algorithm for maximising the throughput flow in networks. If the rooted commodity is interchangeable commodity, a closed parasitic loop can effectively be present even if the routed commodity does not physically travel along a closed loop. The closed parasitic flow loops are highly undesirable loops of flow, which effectively never leave the network. Parasitic flow loops increase the cost of transportation of the flow unnecessarily, consume residual capacity from the edges of the network, increase the likelihood of deterioration of perishable products, increase congestion and energy wastage. Accordingly, the paper presents a theoretical framework related to parasitic flow loops in networks. By using the presented framework, it is demonstrated that the probability of existence of closed and dominated flow loops in networks is surprisingly high. The paper also demonstrates that the successive shortest path strategy for minimising the total length of transportation routes from multiple interchangeable origins to multiple destinations fails to minimise the total length of the routes. It is demonstrated that even in a network with multiple origins and a single destination, the successive shortest path strategy could still fail to minimise the total length of the routes. By using the developed theoretical framework, it is shown that a minimum total length of the transportation routes in a network with multiple interchangeable origins, is attained if and only if no closed parasitic flow loops and dominated flow loops exist in the network. Accordingly, an algorithm for minimising the total length of the transportation routes by eliminating all dominated parasitic flow loops is proposed

Performance controls for distributed telecommunication services

As the Internet and Telecommunications domains merge, open telecommunication service architectures such as TINA, PARLAY and PINT are becoming prevalent. Distributed Computing is a common engineering component in these technologies and promises to bring improvements to the scalability, reliability and flexibility of telecommunications service delivery systems. This distributed approach to service delivery introduces new performance concerns. As service logic is decomposed into software components and distnbuted across network resources, significant additional resource loading is incurred due to inter-node communications. This fact makes the choice of distribution of components in the network and the distribution of load between these components critical design and operational issues which must be resolved to guarantee a high level of service for the customer and a profitable network for the service operator. Previous research in the computer science domain has addressed optimal placement of components from the perspectives of minimising run time, minimising communications costs or balancing of load between network resources. This thesis proposes a more extensive optimisation model, which we argue, is more useful for addressing concerns pertinent to the telecommunications domain. The model focuses on providing optimal throughput and profitability of network resources and on overload protection whilst allowing flexibility in terms of the cost of installation of component copies and differentiation in the treatment of service types, in terms of fairness to the customer and profitability to the operator. Both static (design-time) component distribution and dynamic (run-time) load distribution algorithms are developed using Linear and Mixed Integer Programming techniques. An efficient, but sub-optimal, run-time solution, employing Market-based control, is also proposed. The performance of these algorithms is investigated using a simulation model of a distributed service platform, which is based on TINA service components interacting with the Intelligent Network through gateways. Simulation results are verified using Layered Queuing Network analytic modelling Results show significant performance gains over simpler methods of performance control and demonstrate how trade-offs in network profitability, fairness and network cost are possible

Resource Allocation for Next Generation Radio Access Networks

Driven by data hungry applications, the architecture of mobile networks is moving towards that of densely deployed cells where each cell may use a different access technology as well as a different frequency band. Next generation networks (NGNs) are essentially identified by their dramatically increased data rates and their sustainable deployment. Motivated by these requirements, in this thesis we focus on (i) capacity maximisation, (ii) energy efficient configuration of different classes of radio access networks (RANs). To fairly allocate the available resources, we consider proportional fair rate allocations. We first consider capacity maximisation in co-channel 4G (LTE) networks, then we proceed to capacity maximisation in mixed LTE (including licensed LTE small cells) and 802.11 (WiFi) networks. And finally we study energy efficient capacity maximisation of dense 3G/4G co-channel small cell networks. In each chapter we provide a network model and a scalable resource allocation approach which may be implemented in a centralised or distributed manner depending on the objective and network constraints

Novel Internet of Vehicles Approaches for Smart Cities

Smart cities are the domain where many electronic devices and sensors transmit data via the Internet of Vehicles concept. The purpose of deploying many sensors in cities is to provide an intelligent environment and a good quality of life. However, different challenges still appear in smart cities such as vehicular traffic congestion, air pollution, and wireless channel communication aspects. Therefore, in order to address these challenges, this thesis develops approaches for vehicular routing, wireless channel congestion alleviation, and traffic estimation. A new traffic congestion avoidance approach has been developed in this thesis based on the simulated annealing and TOPSIS cost function. This approach utilizes data such as the traffic average travel speed from the Internet of Vehicles. Simulation results show that the developed approach improves the traffic performance for the Sheffield the scenario in the presence of congestion by an overall average of 19.22% in terms of travel time, fuel consumption and CO2 emissions as compared to other algorithms. In contrast, transmitting a large amount of data among the sensors leads to a wireless channel congestion problem. This affects the accuracy of transmitted information due to the packets loss and delays time. This thesis proposes two approaches based on a non-cooperative game theory to alleviate the channel congestion problem. Therefore, the congestion control problem is formulated as a non-cooperative game. A proof of the existence of a unique Nash equilibrium is given. The performance of the proposed approaches is evaluated on the highway and urban testing scenarios. This thesis also addresses the problem of missing data when sensors are not available or when the Internet of Vehicles connection fails to provide measurements in smart cities. Two approaches based on l1 norm minimization and a relevance vector machine type optimization are proposed. The performance of the developed approaches has been tested involving simulated and real data scenarios