Pro-collaborative mobile systems in next generation IP networks

Computing system designs of today take on either the interactive or the proactive form. Motivated by the user’s desire to make his/her computing experience more intelligent and personalised, the progression from interactive (human-centred) to proactive (human-supervised) is evident. It can be observed that current research mainly emphasises the user as the dominant focus of a user-system interaction. Consider a model that we called the opponent-process model. It contains two processes, one representing the user and the other the system, where both processes are capable of dominating each other, though working collaboratively towards a predefined task. We argue the necessity to design computing systems which are balanced in this model, such that the system process, at times, becomes the dominant process. We refer to this as the pro-collaborative design form. We dissect mobility into the notion of a nomadic user and the notion of a nomadic system. The examination into the nomadic user problem space reveals the potential for applying the pro-collaborative approach in optimising handoff management. Significant performance advantages can be obtained with our proposed S-MIP framework, based on the pro-collaborative design, when compared with established handoff latency optimisation schemes. The key differentiator lies in its indicative approach in addressing handoff ambiguity. Instead of passively anticipating through prediction as to when a mobile user might cross network boundaries (user-dominant), the system actively indicates to the user when, where and how to handoff (system-dominant). This eliminates the handoff ambiguity. Regarding the notion of a nomadic system, that is, the ability to move services offered by computing systems to arbitrary points in the Internet, we explore the idea of the dynamic extension of network services to a mobile user on-demand. Based on the pro-collaborative form, we develop the METAMORPHOSE architecture which facilitates such a dynamic service extension. By assuming the proliferation of programmable network switches and computational resources within the Internet, we re-examine how ‘loose’ service agreements between network services providers can be, to achieve such borderless moving-service offerings. The viability of the pro-collaborative form is reflected through our design and implementation of protocols and architectures which address the notion of nomadic user and nomadic system

Congestion control in multi-serviced heterogeneous wireless networks using dynamic pricing

Includes bibliographical references.Service providers, (or operators) employ pricing schemes to help provide desired QoS to subscribers and to maintain profitability among competitors. An economically efficient pricing scheme, which will seamlessly integrate users’ preferences as well as service providers’ preferences, is therefore needed. Else, pricing schemes can be viewed as promoting social unfairness in the dynamically priced network. However, earlier investigations have shown that the existing dynamic pricing schemes do not consider the users’ willingness to pay (WTP) before the price of services is determined. WTP is the amount a user is willing to pay based on the worth attached to the service requested. There are different WTP levels for different subscribers due to the differences in the value attached to the services requested and demographics. This research has addressed congestion control in the heterogeneous wireless network (HWN) by developing a dynamic pricing scheme that efficiently incentivises users to utilize radio resources. The proposed Collaborative Dynamic Pricing Scheme (CDPS), which identifies the users and operators’ preference in determining the price of services, uses an intelligent approach for controlling congestion and enhancing both the users’ and operators’ utility. Thus, the CDPS addresses the congestion problem by firstly obtaining the users WTP from users’ historical response to price changes and incorporating the WTP factor to evaluate the service price. Secondly, it uses a reinforcement learning technique to illustrate how a price policy can be obtained for the enhancement of both users and operators’ utility, as total utility reward obtained increases towards a defined ‘goal state’

Performance Evaluation of v-eNodeB using Virtualized Radio Resource Management

With the demand upsurge for high bandwidth services, continuous increase in the number of cellular subscriptions, adoption of Internet of Things (IoT), and marked growth in Machine-to-Machine (M2M) traffic, there is great stress exerted on cellular network infrastructure. The present wireline and wireless networking technologies are rigid in nature and heavily hardware-dependent, as a result of which the process of infrastructure upgrade to keep up with future demand is cumbersome and expensive. Software-defined networks (SDN) hold the promise to decrease network rigidity by providing central control and flow abstraction, which in current network setups are hardware-based. The embrace of SDN in traditional cellular networks has led to the implementation of vital network functions in the form of software that are deployed in virtualized environments. This approach to move crucial and hardware intensive network functions to virtual environments is collectively referred to as network function virtualization (NFV). Our work evaluates the cost reduction and energy savings that can be achieved by the application of SDN and NFV technologies in cellular networks. In this thesis, we implement a virtualized eNodeB component (Radio Resource Management) to add agility to the network setup and improve performance, which we compare with a traditional resource manager. When combined with dynamic network resource allocation techniques proposed in Elastic Handoff, our hardware agnostic approach can achieve a greater reduction in capital and operational expenses through optimal use of network resources and efficient energy utilization. Advisor: Jitender S. Deogu