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The rapid evolution of wireless communication technologies, particularly the introduction
of Fifth-Generation (5G) networks and the anticipated transition to Sixth-Generation (6G)
systems, ushers in a new era of connectivity, enabling transformative applications across
industrial automation, the Internet of Everything (IoE), and the Industrial Internet of Things
(IIoT). However, the exponential growth in the number of connected devices, stringent reliability
requirements, and increasing security challenges pose significant hurdles for current network
architectures. This dissertation addresses these challenges by proposing innovative frameworks
and mechanisms that enhance reliability, optimize resource utilization, and strengthen security
and trust management in next-generation mobile networks.
The first contribution of this dissertation focuses on reliability enhancements in 5G networks.
While existing mechanisms, such as Dual Connectivity (DC) and Network Function (NF)
redundancy, provide partial solutions, they do not fully resolve application-layer reliability
and dynamic server failover. To bridge this gap, this work introduces the Make-Before-Break-
Reliability (MBBR) and enhanced Make-Before-Break-Reliability (eMBBR) mechanisms. These
frameworks proactively establish redundant communication paths, ensuring seamless failovers
with minimal latency and service disruption. By extending reliability to the application layer
and integrating adaptive path selection and dynamic failover capabilities, these mechanisms
offer robust solutions for latency-sensitive and mission-critical applications.
The second major contribution addresses bandwidth optimization for industrial networks.
The black channel paradigm, widely adopted for industrial safety applications, relies heavily on
cyclic keep-alive messages to detect connection loss, leading to significant signaling overhead.
This dissertation proposes a novel solution leveraging 5G Channel State Information (CSI)
to replace cyclic messaging with real-time connection quality monitoring. By exposing CSI
metrics, such as Signal-to-Noise Ratio (SNR) and Channel Quality Indicator (CQI), to the
application layer, the proposed mechanism reduces bandwidth consumption while maintaining
the safety and reliability requirements of industrial networks.
Addressing the growing complexity of security requirements in IIoT, the third contribution
introduces the AF-based Security Framework (AERO) framework. This framework empowers
application providers to dynamically apply cryptographic mechanisms to the user plane,
overcoming the limitations of legacy protocols and eliminating the need for redundant security
layers. By ensuring backward compatibility and enabling both static and dynamic configuration
of user plane encryption, AERO enhances security while minimizing computational overhead
and reducing transmission delays.
The fourth and final contribution redefines trust management in mobile networks through
the SecUre deleGAtion of tRust (SUGAR) framework. Traditional trust models, which rely
on identity chips for each connected device, are becoming increasingly impractical in the
IoE era, where billions of devices require connectivity. The SUGAR framework introduces a
delegation-based trust model, allowing Parent Devices (PaDs) to delegate trust to multiple
Child Devices (ChDs) securely. This approach eliminates the need for individual identity chips,
significantly reducing costs and enhancing scalability. Integration with System-on-a-Chip
(SoC)-based identity enclaves further strengthens the security of trust credentials.
The findings of this dissertation offer substantial contributions to both academia and
industry. The proposed frameworks effectively address critical gaps in current 5G standards
and provide valuable contributions for developing the 6G framework. By enhancing reliability,
optimizing bandwidth, and redefining security and trust management, this dissertation provides
a comprehensive foundation for the design and deployment of next-generation mobile networks.
Furthermore, the solutions presented are adaptable to a wide range of applications, including
industrial automation, autonomous systems, and smart city infrastructures.
In conclusion, this dissertation represents a significant step toward realizing the full
potential of next-generation mobile networks. By addressing key challenges in reliability,
resource optimization, security, and trust management, the proposed frameworks pave the way
for scalable, secure, and efficient mobile ecosystems that are essential for the dynamic and
interconnected world of the future.