Data driven SMART intercontinental overlay networks

This paper addresses the use of Big Data and machine learning based analytics to the real-time management of Internet scale Quality-of-Service Route Optimisation with the help of an overlay network. Based on the collection of large amounts of data sampled each $2$ minutes over a large number of source-destinations pairs, we show that intercontinental Internet Protocol (IP) paths are far from optimal with respect to Quality of Service (QoS) metrics such as end-to-end round-trip delay. We therefore develop a machine learning based scheme that exploits large scale data collected from communicating node pairs in a multi-hop overlay network that uses IP between the overlay nodes themselves, to select paths that provide substantially better QoS than IP. The approach inspired from Cognitive Packet Network protocol, uses Random Neural Networks with Reinforcement Learning based on the massive data that is collected, to select intermediate overlay hops resulting in significantly better QoS than IP itself. The routing scheme is illustrated on a $20$-node intercontinental overlay network that collects close to $2\times 10^6$ measurements per week, and makes scalable distributed routing decisions. Experimental results show that this approach improves QoS significantly and efficiently in a scalable manner

Quality of service routing for real-time traffic

Imperial Users onl

Quantifying Potential Energy Efficiency Gain in Green Cellular Wireless Networks

Conventional cellular wireless networks were designed with the purpose of providing high throughput for the user and high capacity for the service provider, without any provisions of energy efficiency. As a result, these networks have an enormous Carbon footprint. In this paper, we describe the sources of the inefficiencies in such networks. First we present results of the studies on how much Carbon footprint such networks generate. We also discuss how much more mobile traffic is expected to increase so that this Carbon footprint will even increase tremendously more. We then discuss specific sources of inefficiency and potential sources of improvement at the physical layer as well as at higher layers of the communication protocol hierarchy. In particular, considering that most of the energy inefficiency in cellular wireless networks is at the base stations, we discuss multi-tier networks and point to the potential of exploiting mobility patterns in order to use base station energy judiciously. We then investigate potential methods to reduce this inefficiency and quantify their individual contributions. By a consideration of the combination of all potential gains, we conclude that an improvement in energy consumption in cellular wireless networks by two orders of magnitude, or even more, is possible.Comment: arXiv admin note: text overlap with arXiv:1210.843

Optimization of the interoperability and dynamic spectrum management in mobile communications systems beyond 3G

The future wireless ecosystem will heterogeneously integrate a number of overlapped Radio Access Technologies (RATs) through a common platform. A major challenge arising from the heterogeneous network is the Radio Resource Management (RRM) strategy. A Common RRM (CRRM) module is needed in order to provide a step toward network convergence. This work aims at implementing HSDPA and IEEE 802.11e CRRM evaluation tools. Innovative enhancements to IEEE 802.11e have been pursued on the application of cross-layer signaling to improve Quality of Service (QoS) delivery, and provide more efficient usage of radio resources by adapting such parameters as arbitrary interframe spacing, a differentiated backoff procedure and transmission opportunities, as well as acknowledgment policies (where the most advised block size was found to be 12). Besides, the proposed cross-layer algorithm dynamically changes the size of the Arbitration Interframe Space (AIFS) and the Contention Window (CW) duration according to a periodically obtained fairness measure based on the Signal to Interference-plus-Noise Ratio (SINR) and transmission time, a delay constraint and the collision rate of a given machine. The throughput was increased in 2 Mb/s for all the values of the load that have been tested whilst satisfying more users than with the original standard. For the ad hoc mode an analytical model was proposed that allows for investigating collision free communications in a distributed environment. The addition of extra frequency spectrum bands and an integrated CRRM that enables spectrum aggregation was also addressed. RAT selection algorithms allow for determining the gains obtained by using WiFi as a backup network for HSDPA. The proposed RAT selection algorithm is based on the load of each system, without the need for a complex management system. Simulation results show that, in such scenario, for high system loads, exploiting localization while applying load suitability optimization based algorithm, can provide a marginal gain of up to 450 kb/s in the goodput. HSDPA was also studied in the context of cognitive radio, by considering two co-located BSs operating at different frequencies (in the 2 and 5 GHz bands) in the same cell. The system automatically chooses the frequency to serve each user with an optimal General Multi-Band Scheduling (GMBS) algorithm. It was shown that enabling the access to a secondary band, by using the proposed Integrated CRRM (iCRRM), an almost constant gain near 30 % was obtained in the throughput with the proposed optimal solution, compared to a system where users are first allocated in one of the two bands and later not able to handover between the bands. In this context, future cognitive radio scenarios where IEEE 802.11e ad hoc modes will be essential for giving access to the mobile users have been proposed

Cognitive radio systems in LTE networks

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University London.The most important fact in the mobile industry at the moment is that demand for wireless services will continue to expand in the coming years. Therefore, it is vital to find more spectrums through cognitive radios for the growing numbers of services and users. However, the spectrum reallocations, enhanced receivers, shared use, or secondary markets-will not likely, by themselves or in combination, meet the real exponential increases in demand for wireless resources. Network operators will also need to re-examine network architecture, and consider integrating the fibre and wireless networks to address this issue. This thesis involves driving fibre deeper into cognitive networks, deploying microcells connected through fibre infrastructure to the backbone LTE networks, and developing the algorithms for diverting calls between the wireless and fibre systems, introducing new coexistence models, and mobility management. This research addresses the network deployment scenarios to a microcell-aided cognitive network, specifically slicing the spectrum spatially and providing reliable coverage at either tier. The goal of this research is to propose new method of decentralized-to-distributed management techniques that overcomes the spectrum unavailability barrier overhead in ongoing and future deployments of multi-tiered cognitive network architectures. Such adjustments will propose new opportunities in cognitive radio-to-fibre systematic investment strategies. Specific contributions include: 1) Identifying the radio access technologies and radio over fibre solution for cognitive network infrastructure to increase the uplink capacity analysis in two-tier networks. 2) Coexistence of macro and microcells are studied to propose a roadmap for optimising the deployment of cognitive microcells inside LTE macrocells in the case of considering radio over fibre access systems. 3) New method for roaming mobiles moving between microcells and macrocell coverage areas is proposed for managing spectrum handover, operator database, authentication and accounting by introducing the channel assigning agent entity. The ultimate goal is to reduce unnecessary channel adaptation

Applications of Repeated Games in Wireless Networks: A Survey

A repeated game is an effective tool to model interactions and conflicts for players aiming to achieve their objectives in a long-term basis. Contrary to static noncooperative games that model an interaction among players in only one period, in repeated games, interactions of players repeat for multiple periods; and thus the players become aware of other players' past behaviors and their future benefits, and will adapt their behavior accordingly. In wireless networks, conflicts among wireless nodes can lead to selfish behaviors, resulting in poor network performances and detrimental individual payoffs. In this paper, we survey the applications of repeated games in different wireless networks. The main goal is to demonstrate the use of repeated games to encourage wireless nodes to cooperate, thereby improving network performances and avoiding network disruption due to selfish behaviors. Furthermore, various problems in wireless networks and variations of repeated game models together with the corresponding solutions are discussed in this survey. Finally, we outline some open issues and future research directions.Comment: 32 pages, 15 figures, 5 tables, 168 reference