Insights in the cost of continuous broadband Internet on trains for multi-service deployments by multiple actors with resource sharing

The economic viability of broadband Internet services on trains has always been proved difficult, mainly due to a high investment cost and low willingness to pay by train passengers, but also due to unused opportunities such as non-passenger services (e.g. train performance monitoring, crew services) and optimization of the resources consumed to offer Internet services. Evaluating opportunities to improve the return on investment is therefore essential towards profitability of the business case. By efficiently sharing resources amongst services, costs can be pooled over several services in order to reduce the investment cost per service. Current techno-economic evaluation models are hard to apply to cost allocation in a multi-service deployment with multiple actors and resource sharing. We therefore propose a new evaluation model and apply it to a deployment of Internet services on trains. We start with a detailed analysis of the technical architecture required to provide Internet access on trains. For each component, we investigate the impact by the different services on resource consumption. The proposed techno-economic evaluation model is then applied in order to calculate the total cost and allocate the used and unused resources to the appropriate services. In a final step, we calculate the business case for each stakeholder involved in the offering of these services. This paper details the proposed model and reports on our findings for a multi-service deployment by multiple actors. Results show important benefits for the case that considers the application of resource sharing in a multi-service, multi-actor scenario and the proposed model produces insights in the contributors to the cost per service and the unused amount of a resource. In addition, ex-ante insights in the cost flows per involved actor are obtained and the model can easily be extended to include revenue flows to evaluate the profitability per actor. As a consequence, the proposed model should be considered to support and stimulate upcoming multi-actor investment decisions for Internet-based multi-service offerings on-board trains with resource sharing

Hybrid Satellite-Terrestrial Communication Networks for the Maritime Internet of Things: Key Technologies, Opportunities, and Challenges

With the rapid development of marine activities, there has been an increasing number of maritime mobile terminals, as well as a growing demand for high-speed and ultra-reliable maritime communications to keep them connected. Traditionally, the maritime Internet of Things (IoT) is enabled by maritime satellites. However, satellites are seriously restricted by their high latency and relatively low data rate. As an alternative, shore & island-based base stations (BSs) can be built to extend the coverage of terrestrial networks using fourth-generation (4G), fifth-generation (5G), and beyond 5G services. Unmanned aerial vehicles can also be exploited to serve as aerial maritime BSs. Despite of all these approaches, there are still open issues for an efficient maritime communication network (MCN). For example, due to the complicated electromagnetic propagation environment, the limited geometrically available BS sites, and rigorous service demands from mission-critical applications, conventional communication and networking theories and methods should be tailored for maritime scenarios. Towards this end, we provide a survey on the demand for maritime communications, the state-of-the-art MCNs, and key technologies for enhancing transmission efficiency, extending network coverage, and provisioning maritime-specific services. Future challenges in developing an environment-aware, service-driven, and integrated satellite-air-ground MCN to be smart enough to utilize external auxiliary information, e.g., sea state and atmosphere conditions, are also discussed

Applications of Soft Computing in Mobile and Wireless Communications

Soft computing is a synergistic combination of artificial intelligence methodologies to model and solve real world problems that are either impossible or too difficult to model mathematically. Furthermore, the use of conventional modeling techniques demands rigor, precision and certainty, which carry computational cost. On the other hand, soft computing utilizes computation, reasoning and inference to reduce computational cost by exploiting tolerance for imprecision, uncertainty, partial truth and approximation. In addition to computational cost savings, soft computing is an excellent platform for autonomic computing, owing to its roots in artificial intelligence. Wireless communication networks are associated with much uncertainty and imprecision due to a number of stochastic processes such as escalating number of access points, constantly changing propagation channels, sudden variations in network load and random mobility of users. This reality has fuelled numerous applications of soft computing techniques in mobile and wireless communications. This paper reviews various applications of the core soft computing methodologies in mobile and wireless communications

Service oriented networking for multimedia applications in broadband wireless networks

Extensive efforts have been focused on deploying broadband wireless networks. Providing mobile users with high speed network connectivity will let them run various multimedia applications on their wireless devices. In order to successfully deploy and operate broadband wireless networks, it is crucial to design efficient methods for supporting various services and applications in broadband wireless networks. Moreover, the existing access-oriented networking solutions are not able to fully address all the issues of supporting various applications with different quality of service requirements. Thus, service-oriented networking has been recently proposed and has gained much attention. This dissertation discusses the challenges and possible solutions for supporting multimedia applications in broadband wireless networks. The service requirements of different multimedia applications such as video streaming and Voice over IP (VoIP) are studied and some novel service-oriented networking solutions for supporting these applications in broadband wireless networks are proposed. The performance of these solutions is examined in WiMAX networks which are the promising technology for broadband wireless access in the near future. WiMAX networks are based on the IEEE 802.16 standards which have defined different Quality of Service (QoS) classes to support a broad range of applications with varying service requirements to mobile and stationary users. The growth of multimedia traffic that requires special quality of service from the network will impose new constraints on network designers who should wisely allocate the limited resources to users based on their required quality of service. An efficient resource management and network design depends upon gaining accurate information about the traffic profile of user applications. In this dissertation, the access level traffic profile of VoIP applications are studied first, and then a realistic distribution model for VoIP traffic is proposed. Based on this model, an algorithm to allocate resources for VoIP applications in WiMAX networks is investigated. Later, the challenges and possible solutions for transmitting MPEG video streams in wireless networks are discussed. The MPEG traffic model adopted by the WiMAX Forum is introduced and different application-oriented solutions for enhancing the performance of wireless networks with respect to MPEG video streaming applications are explained. An analytical framework to verify the performance of the proposed solutions is discoursed, and it is shown that the proposed solutions will improve the efficiency of VoIP applications and the quality of streaming applications over wireless networks. Finally, conclusions are drawn and future works are discussed

Modeling And Dynamic Resource Allocation For High Definition And Mobile Video Streams

Video streaming traffic has been surging in the last few years, which has resulted in an increase of its Internet traffic share on a daily basis. The importance of video streaming management has been emphasized with the advent of High Definition: HD) video streaming, as it requires by its nature more network resources. In this dissertation, we provide a better support for managing HD video traffic over both wireless and wired networks through several contributions. We present a simple, general and accurate video source model: Simplified Seasonal ARIMA Model: SAM). SAM is capable of capturing the statistical characteristics of video traces with less than 5% difference from their calculated optimal models. SAM is shown to be capable of modeling video traces encoded with MPEG-4 Part2, MPEG-4 Part10, and Scalable Video Codec: SVC) standards, using various encoding settings. We also provide a large and publicly-available collection of HD video traces along with their analyses results. These analyses include a full statistical analysis of HD videos, in addition to modeling, factor and cluster analyses. These results show that by using SAM, we can achieve up to 50% improvement in video traffic prediction accuracy. In addition, we developed several video tools, including an HD video traffic generator based on our model. Finally, to improve HD video streaming resource management, we present a SAM-based delay-guaranteed dynamic resource allocation: DRA) scheme that can provide up to 32.4% improvement in bandwidth utilization