Optimal Spectrum Utilization and Flow Controlling In Heterogeneous Network with Reconfigurable Devices

Fairness provisioning in heterogeneous networks is a prime issue for high-rate data flow, wherein the inter-connectivity property among different communication devices provides higher throughput. In Hetnet, optimal resource utilization is required for efficient resource usage. Proper resource allocation in such a network led to higher data flow performance for real-time applications. In view of optimal resource allocation, a resource utilization approach for a reconfigurable cognitive device with spectrum sensing capability is proposed in this paper.  The allocation of the data flow rate at device level is proposed for optimization of network fairness in a heterogeneous network.  A dynamic approach of rate-inference optimization is proposed to provide fairness in dynamic data traffic conditions. The simulation results validate the improvement in offered quality in comparison to multi-attribute optimization

ENERGY EFFICIENT INTRUSION DETECTION SYSTEM FOR WSN

ABSTRACT Recently many new algorithms of wireless sensor networks have been developed which are mainly designed for wireless sensor networks where energy efficiency is an essential criteria. This paper describes a novel intrusion detection scheme which is a lightweight intrusion detection framework for clustered sensor networks. Since WSN nodes are typically battery equipped the primary design goal is to optimize the amount of energy used for transmission. The main idea behind using this approach is its communication and computation overheads are reasonably low and it performs better than other schemes in terms of energy efficiency and high detection rate

SARS-CoV-2 vaccination modelling for safe surgery to save lives: data from an international prospective cohort study

Background Preoperative SARS-CoV-2 vaccination could support safer elective surgery. Vaccine numbers are limited so this study aimed to inform their prioritization by modelling. Methods The primary outcome was the number needed to vaccinate (NNV) to prevent one COVID-19-related death in 1 year. NNVs were based on postoperative SARS-CoV-2 rates and mortality in an international cohort study (surgical patients), and community SARS-CoV-2 incidence and case fatality data (general population). NNV estimates were stratified by age (18-49, 50-69, 70 or more years) and type of surgery. Best- and worst-case scenarios were used to describe uncertainty. Results NNVs were more favourable in surgical patients than the general population. The most favourable NNVs were in patients aged 70 years or more needing cancer surgery (351; best case 196, worst case 816) or non-cancer surgery (733; best case 407, worst case 1664). Both exceeded the NNV in the general population (1840; best case 1196, worst case 3066). NNVs for surgical patients remained favourable at a range of SARS-CoV-2 incidence rates in sensitivity analysis modelling. Globally, prioritizing preoperative vaccination of patients needing elective surgery ahead of the general population could prevent an additional 58 687 (best case 115 007, worst case 20 177) COVID-19-related deaths in 1 year. Conclusion As global roll out of SARS-CoV-2 vaccination proceeds, patients needing elective surgery should be prioritized ahead of the general population.The aim of this study was to inform vaccination prioritization by modelling the impact of vaccination on elective inpatient surgery. The study found that patients aged at least 70 years needing elective surgery should be prioritized alongside other high-risk groups during early vaccination programmes. Once vaccines are rolled out to younger populations, prioritizing surgical patients is advantageous