Posted: Apr 12, 2016
The exponential growth of video conferencing in banking institutions has created unprecedented challenges for network bandwidth management. Financial organizations require robust, secure, and high-quality video communication systems that can handle sensitive transactions, client meetings, and internal collaborations while maintaining strict regulatory compliance. Traditional bandwidth management techniques, while effective in general enterprise environments, prove inadequate for the specialized demands of banking video conferencing where security, privacy, and quality of service must be balanced with exceptional precision. This research addresses the critical gap in current network management approaches by developing a comprehensive framework specifically tailored for banking video conferencing environments. The unique requirements of financial institutions include the need for end-to-end encryption, compliance with financial regulations such as GDPR and SOX, protection against eavesdropping and data interception, and maintenance of high-quality video streams during critical financial operations. Conventional bandwidth management systems fail to adequately address these multifaceted requirements, often sacrificing either security or performance. Our work introduces several novel contributions to the field. First, we develop a quantum-inspired bandwidth allocation algorithm that treats network resources as quantum states, enabling more efficient distribution of bandwidth while maintaining security protocols. Second, we implement a bio-inspired congestion control mechanism based on ant colony optimization principles, which dynamically adapts to network conditions without compromising encrypted data streams. Third, we incorporate federated learning techniques to predict bandwidth requirements across multiple banking branches without centralizing sensitive data, addressing privacy concerns while optimizing network performance.
Downloads: 57
Abstract Views: 1185
Rank: 76415