PhD Thesis Final Defense to be held on October 30, 2019, at 12:00

Photo Credit: Adamantia Stamou

The examination is open to anyone who wishes to attend (Teleteaching Room, Central Library of NTUA).

Thesis Title: Connectivity Management for HetNets based on the Principles of Autonomicity and Context-Awareness

Abstract: Within the Future Internet (FI) ecosystem, the Fifth Generation (5G) networks are already underway. These exploit higher frequency bands with wider available bandwidths and consider extreme base station and device densities, forming a Heterogeneous Network (HetNet) environment, aiming to meet the performance requirements of the lowest possible end-to-end latency and energy consumption. Efficient connectivity management in such a diverse networking environment is an open issue, towards attending user mobility between multiple Radio Access Technologies (RATs) and network tiers, confronting complexity and interoperability issues, accommodating application demands and user preferences and exploiting the capability of handling multiple active network interfaces concurrently. Collection, modeling, reasoning, and distribution of context in relation to sensor data would play a critical role in this challenge.

To this goal, the exploitation of the principles of context-awareness and autonomicity, should be exploited, as they enable the network entities to be aware of themselves and their environment, towards self-governing their behavior to achieve specific goals. Furthermore, proper assessment of the various VHO management approaches that present alternative context acquisition strategies, is needed, requiring a sufficiently comprehensive and generally applicable performance evaluation methodology, as the available methodologies for evaluating the performance of these proposals and for comparing alternatives are still limited.

Therefore, the contributions of this dissertation are twofold. The first part of the dissertation sheds new light to Vertical Handover (VHO) operations from an Autonomic Network Management (ANM) point of view, investigating the role of context-awareness and self-x capabilities, by identifying the main concepts and providing a taxonomy of relevant architectural components and features, extending the current literature. Furthermore, representative state-of-the-art handover management solutions with context-aware and autonomic characteristics are presented, analyzed and correlated according to the proposed taxonomy and criteria, ultimately considering the overall enhancement of the VHO operations, culminating to conclusions that provide useful insights towards future, further enhanced solutions.

The second part of the dissertation provides a versatile modeling methodology, incorporating all significant effects that have an impact on performance, including signaling, processing and congestion (queuing theory). The resulting model is comprehensive, yet capable of admitting closed form solutions and can be flexibly tailored to different VHO architectures. To demonstrate the latter, we apply the modeling methodology in two context-aware VHO approaches that differ in the way of acquiring dynamically varying context (i.e. on-demand and proactively). For both approaches, the model-based results are validated against simulations, confirming the effectiveness and the accuracy of the modeling methodology, demonstrating that the proactive approach can provide significant delay and processing efficiency gains, leading in accordance, to potential energy consumption savings and lower OPEX and CAPEX costs.

Supervisor: Symeon Papavassiliou, Professor

PhD student: Adamantia Stamou