An elastic demand schedule-based multimodal assignment model for the simulation of high speed rail (HSR) systems

HSR represents the future of medium-haul intercity transport. In fact, a number of HSR projects are being developed all over the world despite the financial and economic crisis. Such large investments require reliable demand forecasting models to develop solid business plans aiming at optimizing the fares structure and the timetables (operational level) and, on the other hand, at exploring opportunities for new businesses in the long period (strategic level). In this paper we present a model system developed to forecast the national passenger demand for different macroeconomic, transport supply, and HSR market scenarios. The core of the model is based on the simulation of the competition between transportation modes (i.e. air, auto, rail), railways services (intercity vs. High Speed Rail) and HSR operators using an explicit representation of the timetables of all competing modes\services (schedule-based assignment). This requires, in turn, a diachronic network representation of the transport supply for scheduled services and a nested logit model of mode, service, operator, and run choice. To authors’ knowledge this represents the first case of elastic demand, schedule-based assignment model at national scale to forecast HSR demand. The overall modeling framework has been calibrated based on extensive traffic counts and mixed RP-SP interviews gathered between 2009 and 2011, on the Italian multimodal transportation system. The results of the models estimation are presented, and, some applications to test HSR service options (i.e. fares and timetable) of a new operator entering the HSR market and competing with the national incumbent are discussed

Decision Routing Problems in A Wireless Sensor Network Based on A Neural Mechanism

This article proposes a solution for the routing problem in wireless sensor networks (WSN) based on a neural mechanism. The basic concepts of wireless sensor networks, artificial neural networks (ANNs), and WSN routing protocols are presented. The Kohonen ANN was selected to solve the problem of routing in wireless sensor networks based on a neural mechanism. A radio visibility matrix is proposed, which is a mathematical description of the connectivity of network nodes and the radio visibility of each node with respect to all other network nodes. Based on the Kohonen ANN trained by the constructive method, a method for WSN neural network clustering was developed. Two software-modeling environments are presented that were created to confirm the theory with respect to the logic of the developed methods for WSN clustering, their correction and the verification of their adequacy. Numerical results of modeling the solution of the routing problem in a wireless sensor network based on a neural mechanism by neural network clustering, the WSN matrix clustering method and the energy distance neural clustering protocol (EDNCP) are presented. It was found that the developed EDNCP protocol was 29% more efficient than known analogs

A critical look at power law modelling of the Internet

This paper takes a critical look at the usefulness of power law models of the Internet. The twin focuses of the paper are Internet traffic and topology generation. The aim of the paper is twofold. Firstly it summarises the state of the art in power law modelling particularly giving attention to existing open research questions. Secondly it provides insight into the failings of such models and where progress needs to be made for power law research to feed through to actual improvements in network performance.Comment: To appear Computer Communication

Guaranteed bit rate traffic prioritisation and isolation in multi-tenant radio access networks

©2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Network slicing is a key feature of forthcoming 5G systems to facilitate the partitioning of the network into multiple logical networks customised according to different operation and application needs. Network slicing allows the materialisation of multi-tenant networks, in which the same infrastructure is shared among multiple communication providers, each one using a different slice. The support of multi-tenancy through slicing in the Radio Access Network (RAN) is particularly challenging because it involves the configuration and operation of multiple and diverse RAN behaviour over a common pool of radio resources while guaranteeing a certain Quality of Service (QoS) and isolation to each of the slices. This paper presents a Markovian approach to model different QoS aware Admission Control (AC) policies in a multi-tenant scenario with Guaranteed Bit Rate (GBR) services. From the analytical model, different metrics are defined to later analyse the effect of AC mechanisms on the performance achieved in various scenarios. Results show the impact of priorities for services of different tenants and isolation between tenants when different AC polices are adopted.Peer ReviewedPostprint (author's final draft

Cross-layer design of multi-hop wireless networks

MULTI -hop wireless networks are usually defined as a collection of nodes equipped with radio transmitters, which not only have the capability to communicate each other in a multi-hop fashion, but also to route each others’ data packets. The distributed nature of such networks makes them suitable for a variety of applications where there are no assumed reliable central entities, or controllers, and may significantly improve the scalability issues of conventional single-hop wireless networks. This Ph.D. dissertation mainly investigates two aspects of the research issues related to the efficient multi-hop wireless networks design, namely: (a) network protocols and (b) network management, both in cross-layer design paradigms to ensure the notion of service quality, such as quality of service (QoS) in wireless mesh networks (WMNs) for backhaul applications and quality of information (QoI) in wireless sensor networks (WSNs) for sensing tasks. Throughout the presentation of this Ph.D. dissertation, different network settings are used as illustrative examples, however the proposed algorithms, methodologies, protocols, and models are not restricted in the considered networks, but rather have wide applicability. First, this dissertation proposes a cross-layer design framework integrating a distributed proportional-fair scheduler and a QoS routing algorithm, while using WMNs as an illustrative example. The proposed approach has significant performance gain compared with other network protocols. Second, this dissertation proposes a generic admission control methodology for any packet network, wired and wireless, by modeling the network as a black box, and using a generic mathematical 0. Abstract 3 function and Taylor expansion to capture the admission impact. Third, this dissertation further enhances the previous designs by proposing a negotiation process, to bridge the applications’ service quality demands and the resource management, while using WSNs as an illustrative example. This approach allows the negotiation among different service classes and WSN resource allocations to reach the optimal operational status. Finally, the guarantees of the service quality are extended to the environment of multiple, disconnected, mobile subnetworks, where the question of how to maintain communications using dynamically controlled, unmanned data ferries is investigated