Investigation of an intelligent personalised service recommendation system in an IMS based cellular mobile network

Success or failure of future information and communication services in general and mobile communications in particular is greatly dependent on the level of personalisations they can offer. While the provision of anytime, anywhere, anyhow services has been the focus of wireless telecommunications in recent years, personalisation however has gained more and more attention as the unique selling point of mobile devices. Smart phones should be intelligent enough to match user’s unique needs and preferences to provide a truly personalised service tailored for the individual user. In the first part of this thesis, the importance and role of personalisation in future mobile networks is studied. This is followed, by an agent based futuristic user scenario that addresses the provision of rich data services independent of location. Scenario analysis identifies the requirements and challenges to be solved for the realisation of a personalised service. An architecture based on IP Multimedia Subsystem is proposed for mobility and to provide service continuity whilst roaming between two different access standards. Another aspect of personalisation, which is user preference modelling, is investigated in the context of service selection in a multi 3rd party service provider environment. A model is proposed for the automatic acquisition of user preferences to assist in service selection decision-making. User preferences are modelled based on a two-level Bayesian Metanetwork. Personal agents incorporating the proposed model provide answers to preference related queries such as cost, QoS and service provider reputation. This allows users to have their preferences considered automatically

Mobility-based predictive call admission control and resource reservation for next-generation mobile communications networks.

Recently, the need for wireless and mobile communications has grown tremendously and it is expected that the number of users to be supported will increase with high rates in the next few years. Not only the number of users, but also the required bandwidth to support each user is supposed to increase especially with the deploying of the multimedia and the real time applications. This makes the researchers in the filed of mobile and wireless communications more interested in finding efficient solutions to solve the limitations of the available natural radio resources. One of the important things to be considered in the wireless mobile environment is that the user can move from one location to another when there is an ingoing call. Resource reservation ( RR ) schemes are used to reserve the bandwidth ( BW ) required for the handoff calls. This will enable the user to continue his/her call while he/she is moving. Also, call admission control ( CAC ) schemes are used as a provisioning strategy to limit the number of call connections into the network in order to reduce the network congestion and the call dropping. The problem of CAC and RR is one of the most challenging problems in the wireless mobile networks. Also, in the fourth generation ( 4G ) of mobile communication networks, many types of different mobile systems such as wireless local area networks ( WLAN s) and cellular networks will be integrated. The 4G mobile networks will support a broad range of multimedia services with high quality of service.New Call demission control and resource reservation techniques are needed to support the new 4G systems. Our research aims to solve the problems of Call Admission Control (CAC), and resource reservation (RR) in next-generation cellular networks and in the fourth generation (4G) wireless heterogeneous networks. In this dissertation, the problem of CAC and RR in wireless mobile networks is addressed in detail for two different architectures of mobile networks: (1) cellular networks, and (2) wireless heterogeneous networks (WHNs) which integrate cellular networks and wireless local area networks (WLANs). We have designed, implemented, and evaluated new mobility-based predictive call admission control and resource reservation techniques for the next-generation cellular networks and for the 4G wireless heterogeneous networks. These techniques are based on generating the mobility models of the mobile users using one-dimensional and multidimensional sequence mining techniques that have been designed for the wireless mobile environment. The main goal of our techniques is to reduce the call dropping probability and the call blocking probability, and to maximize the bandwidth utilization n the mobile networks. By analyzing the previous movements of the mobile users, we generate local and global mobility profiles for the mobile users, which are utilized effectively in prediction of the future path of the mobile user. Extensive simulation was used to analyze and study the performance of these techniques and to compare its performance with other techniques. Simulation results show that the proposed techniques have a significantly enhanced performance which is comparable to the benchmark techniques

Network layer access control for context-aware IPv6 applications

As part of the Lancaster GUIDE II project, we have developed a novel wireless access point protocol designed to support the development of next generation mobile context-aware applications in our local environs. Once deployed, this architecture will allow ordinary citizens secure, accountable and convenient access to a set of tailored applications including location, multimedia and context based services, and the public Internet. Our architecture utilises packet marking and network level packet filtering techniques within a modified Mobile IPv6 protocol stack to perform access control over a range of wireless network technologies. In this paper, we describe the rationale for, and components of, our architecture and contrast our approach with other state-of-the- art systems. The paper also contains details of our current implementation work, including preliminary performance measurements

A Survey of Anticipatory Mobile Networking: Context-Based Classification, Prediction Methodologies, and Optimization Techniques

A growing trend for information technology is to not just react to changes, but anticipate them as much as possible. This paradigm made modern solutions, such as recommendation systems, a ubiquitous presence in today's digital transactions. Anticipatory networking extends the idea to communication technologies by studying patterns and periodicity in human behavior and network dynamics to optimize network performance. This survey collects and analyzes recent papers leveraging context information to forecast the evolution of network conditions and, in turn, to improve network performance. In particular, we identify the main prediction and optimization tools adopted in this body of work and link them with objectives and constraints of the typical applications and scenarios. Finally, we consider open challenges and research directions to make anticipatory networking part of next generation networks

Wireless Communications in the Era of Big Data

The rapidly growing wave of wireless data service is pushing against the boundary of our communication network's processing power. The pervasive and exponentially increasing data traffic present imminent challenges to all the aspects of the wireless system design, such as spectrum efficiency, computing capabilities and fronthaul/backhaul link capacity. In this article, we discuss the challenges and opportunities in the design of scalable wireless systems to embrace such a "bigdata" era. On one hand, we review the state-of-the-art networking architectures and signal processing techniques adaptable for managing the bigdata traffic in wireless networks. On the other hand, instead of viewing mobile bigdata as a unwanted burden, we introduce methods to capitalize from the vast data traffic, for building a bigdata-aware wireless network with better wireless service quality and new mobile applications. We highlight several promising future research directions for wireless communications in the mobile bigdata era.Comment: This article is accepted and to appear in IEEE Communications Magazin

Context transfer support for mobility management in all-IP networks.

This thesis is a description of the research undertaken in the course of the PhD and evolves around a context transfer protocol which aims to complement and support mobility management in next generation mobile networks. Based on the literature review, it was identified that there is more to mobility management than handover management and the successful change of routing paths. Supportive mechanisms like fast handover, candidate access router discovery and context transfer can significantly contribute towards achieving seamless handover which is especially important in the case of real time services. The work focused on context transfer motivated by the fact that it could offer great benefits to session re-establishment during the handover operation of a mobile user and preliminary testbed observations illustrated the need for achieving this. Context transfer aims to minimize the impact of certain transport, routing, security-related services on the handover performance. When a mobile node (MN) moves to a new subnet it needs to continue such services that have already been established at the previous subnet. Examples of such services include AAA profile, IPsec state, header compression, QoS policy etc. Re-establishing these services at the new subnet will require a considerable amount of time for the protocol exchanges and as a result time- sensitive real-time traffic will suffer during this time. By transferring state to the new domain candidate services will be quickly re-established. This would also contribute to the seamless operation of application streams and could reduce susceptibility to errors. Furthermore, re-initiation to and from the mobile node will be avoided hence wireless bandwidth efficiency will be conserved. In this research an extension to mobility protocols was proposed for supporting state forwarding capabilities. The idea of forwarding states was also explored for remotely reconfiguring middleboxes to avoid any interruption of a mobile users' sessions or services. Finally a context transfer module was proposed to facilitate the integration of such a mechanism in next generation architectures. The proposals were evaluated analytically, via simulations or via testbed implementation depending on the scenario investigated. The results demonstrated that the proposed solutions can minimize the impact of security services like authentication, authorization and firewalls on a mobile user's multimedia sessions and thus improving the overall handover performance

Mobility management across converged IP-based heterogeneous access networks

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University, 8/2/2010.In order to satisfy customer demand for a high performance “global” mobility service, network operators (ISPs, carriers, mobile operators, etc.) are facing the need to evolve to a converged “all-IP” centric heterogeneous access infrastructure. However, the integration of such heterogeneous access networks (e.g. 802.11, 802.16e, UMTS etc) brings major mobility issues. This thesis tackles issues plaguing existing mobility management solutions in converged IP-based heterogeneous networks. In order to do so, the thesis firstly proposes a cross-layer mechanism using the upcoming IEEE802.21 MIH services to make intelligent and optimized handovers. In this respect, FMIPv6 is integrated with the IEEE802.21 mechanism to provide seamless mobility during the overall handover process. The proposed solution is then applied in a simulated vehicular environment to optimize the NEMO handover process. It is shown through analysis and simulations of the signalling process that the overall expected handover (both L2 and L3) latency in FMIPv6 can be reduced by the proposed mechanism by 69%. Secondly, it is expected that the operator of a Next Generation Network will provide mobility as a service that will generate significant revenues. As a result, dynamic service bootstrapping and authorization mechanisms must be in place to efficiently deploy a mobility service (without static provisioning), which will allow only legitimate users to access the service. A GNU Linux based test-bed has been implemented to demonstrate this. The experiments presented show the handover performance of the secured FMIPv6 over the implemented test-bed compared to plain FMIPv6 and MIPv6 by providing quantitative measurements and results on the quality of experience perceived by the users of IPv6 multimedia applications. The results show the inclusion of the additional signalling of the proposed architecture for the purpose of authorization and bootstrapping (i.e. key distribution using HOKEY) has no adverse effect on the overall handover process. Also, using a formal security analysis tool, it is shown that the proposed mechanism is safe/secure from the induced security threats. Lastly, a novel IEEE802.21 assisted EAP based re-authentication scheme over a service authorization and bootstrapping framework is presented. AAA based authentication mechanisms like EAP incur signalling overheads due to large RTTs. As a result, overall handover latency also increases. Therefore, a fast re-authentication scheme is presented which utilizes IEEE802.21 MIH services to minimize the EAP authentication process delays and as a result reduce the overall handover latency. Analysis of the signalling process based on analytical results shows that the overall handover latency for mobility protocols will be approximately reduced by 70% by the proposed scheme

A survey of machine learning techniques applied to self organizing cellular networks

In this paper, a survey of the literature of the past fifteen years involving Machine Learning (ML) algorithms applied to self organizing cellular networks is performed. In order for future networks to overcome the current limitations and address the issues of current cellular systems, it is clear that more intelligence needs to be deployed, so that a fully autonomous and flexible network can be enabled. This paper focuses on the learning perspective of Self Organizing Networks (SON) solutions and provides, not only an overview of the most common ML techniques encountered in cellular networks, but also manages to classify each paper in terms of its learning solution, while also giving some examples. The authors also classify each paper in terms of its self-organizing use-case and discuss how each proposed solution performed. In addition, a comparison between the most commonly found ML algorithms in terms of certain SON metrics is performed and general guidelines on when to choose each ML algorithm for each SON function are proposed. Lastly, this work also provides future research directions and new paradigms that the use of more robust and intelligent algorithms, together with data gathered by operators, can bring to the cellular networks domain and fully enable the concept of SON in the near future