Backhaul Problem Research Articles

You can’t always get what you want: Protectionist policies with the transport sector

This paper incorporates key stylized facts about the transport sector into the conventional international oligopoly model and explores how protectionist policies perform differently when transport costs are endogenous and subject to the backhaul problem (i.e., the imbalance of shipping volume in outgoing and incoming routes). A country’s protectionist policies, which benefit domestic firms and harm foreign firms in the conventional model, can harm domestic firms and benefit foreign firms if carriers avoid the backhaul problem. Protectionist policies may also lead to a facilitating practice. In the absence of the backhaul problem, both domestic and foreign consumers lose from protectionist policies.

What goes around comes around: Export-enhancing effects of import-tariff reductions

In international trade, transportation requires a round trip for which a transport firm has to commit to shipping capacity that is sufficient to meet the maximum shipping volume. This may cause the “backhaul problem.” Trade theory suggests that, facing the problem, transport firms with market power adjust their freight rates strategically when import tariffs change. As a consequence, a country reducing its import tariffs may experience an increase in exports as well as imports. Using worldwide data covering 1995–2007, we find evidence that supports these predictions: a 1% reduction in an importer's tariffs increases the import freight rates by around 0.8%; decreases the export freight rates by around 1.1%; and increases the export quantity by 0.6% to 1%. These findings indicate a new mechanism through which import-tariff reductions lead to export expansions.

V-Xpress: B2B marketing in the logistics industry

Learning outcomes The learning objectives of this case study are to understand business-to-business (B2B) marketing in a logistics organization; apply go-to-market (GTM) strategy in the logistics industry; design B2B distribution strategy so as to enhance geographic penetration; and develop digital marketing strategies in the logistics industry. Case Overview/Synopsis V-Xpress is a leading B2B player in the express cargo category in the Indian logistics industry. In March 2017, Sachin Nair, Head of V-Xpress Marketing, was presenting three different GTM strategies to the CEO for the new Assured Timely Movement services. He wanted CEO views on each of them so that he can choose the best one. Sachin was also trying to find a solution to backhaul problem in eastern India. The resolution of this problem would have helped V-Xpress to become a truly pan-India B2B logistics company. Sachin was also revamping the digital marketing strategy as part of ambitious V-Xpress marketing strategy. These initiatives were taken as part of CEO’s vision for reaching annual revenue of INR 10bn by 2020. Sachin was thinking about various options so as to implement these changes with least investments. Complexity academic level This case study can be used in B2B marketing, marketing management and marketing strategy course of an MBA program. Supplementary materials Teaching Notes are available for educators only. Please contact your library to gain login details or email support@emeraldinsight.com to request teaching notes. Subject code CSS: 8: Marketing

Resource Efficient Allocation and RRH Placement for Backhaul of Moving Small Cells

Mobile users suffer from deteriorating signal quality due to vehicle penetration losses. To solve this, small cells are deployed within the vehicles to improve the Quality of Service (QoS). These small cells called moving small cell access points (MSAPs), however, suffer from backhaul issues since they would have to send a huge amount of data to the core network. To solve the backhaul problem, cloud radio access network (CRAN) along with the millimeter wave (mmwave) can be a viable solution for moving vehicles. However, in order to realize its potential benefits, an effective remote radio head (RRH) deployment strategy and the resource-efficient allocation are needed. In this paper, we investigate the placement of RRH alongside a railway track; then, for the placed RRH, a joint time slot and power allocation problem are formulated with an objective of maximizing the resource efficiency (RE) of the MSAP backhaul network. An optimal Branch and Bound Algorithm (BnBA) is proposed for the constituted non-linear integer problem, and the effects of changing various model parameters are investigated. The simulation results show that our proposed algorithm deviates 52% of the sub-optimal result.

Backfiring with backhaul problems: Trade and industrial policies with endogenous transport costs

Trade barriers due to transport costs are as large as those due to tariffs. This paper incorporates the transport sector into a standard model of international trade and studies the effects of trade and industrial policies. Transport firms need to commit to a shipping capacity sufficient for a round trip, with a possible imbalance of shipping volumes in two directions. This imbalance is known as the “backhaul problem.” As transport firms attempt to avoid this problem, a tariff in one sector may affect other independent import and/or export sectors. In particular, domestic tariffs may backfire: domestic exports may also decrease, harming domestic export sectors and the domestic economy. This finding contributes to the literature on how import liberalization may generate a positive effect on the liberalizing country's exports by identifying a new channel through endogenous changes in transport costs given the backhaul problem.

Modular Approach for Modelling the Hybrid Multi-Hop Backhaul Performance

The backhaul is a cornerstone in the development of future cellular networks and not the least challenging. The difficulty of designing the future backhaul is in the expected range of performance metrics that is increasing in breadth and in rising standards. Novel ideas for solving the heterogeneous backhaul problem are frequently proposed. Tractable analytical models that capture the performance of such backhauls are crucial in order to verify and validate these ideas. We present the first modular and scalable framework for analytically modelling the performance of hybrid multi-hop backhauls, which employs technology-specific models of different performance aspects of each hop.

Green Full-Duplex Self-Backhaul and Energy Harvesting Small Cell Networks With Massive MIMO

With the dense deployment of small cell networks, the powering and backhaul problem of small cell base stations (SBSs) has attracted great attention, and energy harvesting technology and self-backhaul technology have been proposed as promising solutions. Although some excellent works have been done on energy harvesting and self-backhaul in small cell networks, most existing works do not consider them jointly. In this paper, we aim at green small cell networks by jointly achieving self-backhaul and energy harvesting. In addition, full-duplex and massive multiple-input and multiple-output technologies are also exploited to enhance the system performance. In order to improve the energy efficiency (EE) further, a novel precoding scheme is designed to eliminate both the inter-tier and multi-user interference. Based on the proposed precoding scheme, we formulate the cell association and power allocation problem as an optimization problem to optimize the system EE performance, with the energy arrival rate and remaining battery energy in SBSs involved. The formulated optimization problem implies a sleep mechanism to control the ON/OFF of SBSs, which will further reduce the energy consumption of small cell networks. In addition, to reduce the computation complexity to solve this non-convex problem, we propose to transform the original problem into a difference of convex program, which can be efficiently solved via a constrained concave convex procedure-based algorithm. Extensive simulation results are presented to justify the effectiveness of the proposed scheme with different system configurations.

5G Backhaul Challenges and Emerging Research Directions: A Survey

5G is the next cellular generation and is expected to quench the growing thirst for taxing data rates and to enable the Internet of Things. Focused research and standardization work have been addressing the corresponding challenges from the radio perspective while employing advanced features, such as network densification, massive multiple-input-multiple-output antennae, coordinated multi-point processing, inter-cell interference mitigation techniques, carrier aggregation, and new spectrum exploration. Nevertheless, a new bottleneck has emerged: the backhaul. The ultra-dense and heavy traffic cells should be connected to the core network through the backhaul, often with extreme requirements in terms of capacity, latency, availability, energy, and cost efficiency. This pioneering survey explains the 5G backhaul paradigm, presents a critical analysis of legacy, cutting-edge solutions, and new trends in backhauling, and proposes a novel consolidated 5G backhaul framework. A new joint radio access and backhaul perspective is proposed for the evaluation of backhaul technologies which reinforces the belief that no single solution can solve the holistic 5G backhaul problem. This paper also reveals hidden advantages and shortcomings of backhaul solutions, which are not evident when backhaul technologies are inspected as an independent part of the 5G network. This survey is key in identifying essential catalysts that are believed to jointly pave the way to solving the beyond-2020 backhauling challenge. Lessons learned, unsolved challenges, and a new consolidated 5G backhaul vision are thus presented.

Multi-Layer High-Speed Network Design in Mobile Backhaul Using Robust Optimization

The multi-layer network design problem and the mobile backhaul problem are both interesting from the perspective of choosing the correct technology and protocol as well as choosing the appropriate node architecture to meet a wide variety of overlay traffic demands. Network operators encounter two variants of the multi-layer/backhaul problem: 1) For a given set of uncertain traffic demands, which set of technologies would minimize the network cost? 2) Would these technology choices be invariant to the changing traffic demands? This problem of technology choice can essentially be abstracted to a switching and grooming problem with the added complexity of unknown traffic demands, which at best may be approximated to some known statistical parameters. To solve this complex switching and grooming problem, our goal is to make use of the theory of robust optimization with the assumption of known boundary conditions on traffic. We present a comprehensive optimization model that considers technology choices in terms of protocols, physical layer parameters, link boundary conditions, and transmission layer constraints. Validated by simulations, our model shows the stand-off conditions between various technologies and how a network operator must take proactive steps to be able to meet requirements of the next-generation networks and services. Our main result showcases network design using two technology alternatives [1) Multi-Protocol Label Switching (MPLS) + Optical Transport Network (OTN) + Reconfigurable Optical Add–Drop Multiplexer (ROADM) and 2) Carrier Ethernet (CE) + OTN + ROADM] and the effect of robustness on these choices. A heuristic is used for comparative purposes as well as to exhaustively model the dynamic case of brownfield networks.

Location Analysis Model for Belgian Intermodal Terminals: Importance of the value of time in the intermodal transport chain

Intermodal transport, the combination and integration of several transport modes, with the use of loading units, is in most cases more environmentally friendly than unimodal road transport for the carriage of goods. The LAMBIT-model (Location Analysis Model for Belgian Intermodal Terminals) has been developed to analyse the market areas of existing and potential intermodal terminals. In the LAMBIT model, barge/road and rail/road intermodal chains can be compared to unimodal road transport within Belgium. In this paper we show how to include, next to market prices, the value of time in the model and how to integrate other factors influencing the cost structure, such as the possibility to use the terminal as an empty depot and implications of the so-called backhaul problem and the distance of the post-haulage section. Different scenarios will be evaluated and compared to the reference scenario.

A matching model for the backhaul problem

The ‘backhaul problem’ is characterized by an imbalance in transport flows between locations. In a perfectly competitive framework with perfect information, the price of transport from low demand locations to high demand locations, the so-called backhaul price, drops to zero when the imbalance is sufficiently large. However, this result is inconsistent with empirical observations for many competitive transport markets (e.g. taxi and inland navigation markets). In this paper, we develop a matching model to show that a deviation from perfect information may address this inconsistency. We argue that carriers’ search time to locate customers plays an important role in the determination of prices. We demonstrate that carriers are compensated for a part of the transport cost and for the time they search for customers. This implies positive backhaul prices. The matching model is numerically applied to the inland navigation shipping market in the Rhine river area in Western-Europe. We find that backhaul prices are substantial.

A Matching Model for the Backhaul Problem

The 'backhaul problem' is characterized by an imbalance in transport flows between locations. This problem is usually studied in a perfectly competitive framework, which essentially predicts that when the imbalance is sufficiently large, the freight price of transport from low demand regions to high demand regions, the so-called backhaul price, drops to zero. This result is inconsistent with empirical observations. In this paper, we develop a matching model to address this inconsistency. We argue that market friction, through search imperfections due to lack of information by carriers on the (future) demand for transport by customers, may play an important role in the determination of backhaul prices. We demonstrate that carriers are at least compensated for the time they search for customers, so the backhaul price is in general positive. The matching model is numerically applied to the inland navigation shipping market in the Rhine river area in Western-Europe. We also analyse the effects of increases in transport costs on transport flows and backhaul prices, e.g. due to climate changes.

Vehicle routing with pick-up and delivery: tour-partitioning heuristics

Many applications of the classical vehicle routing problem involve pick-up and delivery services between the depot and peripheral locations (warehouses, stores, stations). This paper studies an important version of the vehicle routing problem with pick-up and delivery (the so-called delivery and backhaul problem): delivery in our case refers to transportation of goods from the depot to customers, and pick-up (backhaul) refers to shipment from customers to the depot. The objective is to find a set of vehicle routes that service customers such that vehicle capacity is not violated and the total distance traveled is minimized. Tour partitioning heuristics for solving the capacitated vehicle routing problem are based on breaking a basic tour into disjoint segments served by different vehicles. This idea is adapted for solving the delivery and backhaul problem. Two heuristics that focus on efficient utilization of vehicles’ capacities are introduced, analyzed and tested numerically.

On marine engines from 1851 to the present time

Trade barriers due to transport costs are as large as those due to tariffs. This paper incorporates the transport sector into a standard model of international trade and studies the effects of trade and industrial policies. Transport firms need to commit to a shipping capacity sufficient for a round trip, with a possible imbalance of shipping volumes in two directions. This imbalance is known as the “backhaul problem.” As transport firms attempt to avoid this problem, a tariff in one sector may affect other independent import and/or export sectors. In particular, domestic tariffs may backfire: domestic exports may also decrease, harming domestic export sectors and the domestic economy. This finding contributes to the literature on how import liberalization may generate a positive effect on the liberalizing country's exports by identifying a new channel through endogenous changes in transport costs given the backhaul problem.