A Novel Resource Allocation and Spectrum Defragmentation Mechanism for IoT-Based Big Data in Smart Cities

Area of Science:

• Optical network engineering
• Telecommunications
• Smart city infrastructure

Background:

• Smart cities generate massive, diverse data from high-traffic applications and the Internet of Things (IoT).
• Reliable transmission and efficient resource allocation in optical backbone networks are critical for accommodating this data surge.

Purpose of the Study:

• To present a novel resource allocation and spectrum defragmentation mechanism for massive IoT traffic in smart city optical backbone networks.
• To ensure reliable data transmission and optimize resource utilization.

Main Methods:

• Proposed a routing and spectrum allocation algorithm using the distance-adaptive sharing protection mechanism (DASP).
• Designed a protection path spectrum defragmentation algorithm based on OpenFlow.
• Employed the lowest starting slot-index first (LSSF) algorithm for optical path management.

Main Results:

• The proposed mechanism effectively alleviates spectrum fragmentation in optical networks.
• Achieved a 44.68% reduction in bandwidth-blocking probability compared to traditional schemes.
• Demonstrated improved spectrum utilization through shared protection.

Conclusions:

• The novel mechanism provides a reliable solution for massive IoT traffic in smart city optical networks.
• The DASP and OpenFlow-based algorithms enhance network performance and resource efficiency.
• The findings are crucial for the development of scalable and robust smart city infrastructures.