The rapid growth of the technologies, high bandwidth applications, and cloud data centers consume heavy internet service. So, the consumer of the internet expects a high capacity medium for communication. The Elastic Optical Network (EON) provides a flexible and reliable transmission service for consumers. The spectrum fragmentation is a key challenge in EON. In simple terms, unaligned Frequency Slots (FSs) in the network are referred to as fragmented spectrum, while in defragmentation, the available FSs need to be rearranged to create room for the new connection requests. The problem in defragmentation occurs due to the lack of a continuous spectrum and it leads to depreciation in spectrum usage and simultaneously increasing the Blocking Probability (BP) which disrupts the majority of the existing connections in the network. Several techniques and approaches were suggested to reduce the possibility of disruption and reconfiguration in the network while defragmenting the frequency slots. This paper proposes a new algorithm to overcome the drawbacks and improvement in the quality of service of the network. The proposed algorithm holds the approach of proactive and reactive along with the meta-heuristic nature-inspired optimization technique called Jellyfish Search Optimization (JSO). The proposed combination, PR-DF-JFSO outperforms well in terms of spectrum utilization, network efficiency, and quality of service offered when compared to the state-of-the-art spectrum defragmentation algorithms according to the results of experiments done using standard quality metrics. The simulation results show the better utilization of spectrum, reduce the spectrum fragmentation complexity, better bandwidth fragmentation ratio, and overall connection blocking reduced.

技术，高带宽应用程序和云数据中心的快速增长消耗了大量的Internet服务。因此，因特网的消费者期望通信的高容量介质。弹性光网络（EON）为消费者提供了灵活而可靠的传输服务。频谱碎片化是EON中的关键挑战。简单来说，网络中未对齐的频率槽（FS）称为碎片频谱，而在进行碎片整理时，需要重新排列可用的FS，以便为新的连接请求腾出空间。碎片整理的问题是由于缺乏连续频谱而发生的，它导致频谱使用量的下降，同时导致阻塞概率（BP）的增加，从而破坏了网络中现有的大多数连接。建议了几种技术和方法以减少对网络碎片进行碎片整理的同时在网络中进行中断和重新配置的可能性。本文提出了一种新的算法来克服网络服务质量的缺点和改进。所提出的算法保留了前摄性和反应性方法以及元启发式自然启发式优化技术，即水母搜索优化（JSO）。根据使用标准质量指标完成的实验结果，与最先进的频谱碎片整理算法相比，PR-DF-JFSO所提出的组合在频谱利用率，网络效率和提供的服务质量方面均表现出色。仿真结果表明，频谱利用率更高，