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As wireless communication grows, so does the need for smart, simple, affordable solutions. The need prompted academics to develop appropriate network solutions ranging from wireless sensor networks (WSNs) to the Internet of Things (IoT). With the innovations of researchers, the necessity for enhancements in existing researchers has increased. Initially, network protocols were the focus of study and development. Regardless, IoT devices are already being employed in different industries and collecting massive amounts of data through complicated applications. This necessitates IoT load-balancing research. Several studies tried to address the communication overheads produced by significant IoT network traffic. These studies intended to control network loads by evenly spreading them across IoT nodes. Eventually, the practitioners decided to migrate the IoT node data and the apps processing it to the cloud. So, the difficulty is to design a cloud-based load balancer algorithm that meets the criteria of IoT network protocols. Defined as a unique method for controlling loads on cloud-integrated IoT networks. The suggested method analyses actual and virtual host machine needs in cloud computing environments. The purpose of the proposed model is to design a load balancer that improves network response time while reducing energy consumption. The proposed load balancer algorithm may be easily integrated with peer-existing IoT frameworks. Handling the load for cloud-based IoT architectures with the above-described methods. Significantly boosts response time for the IoT network by 60 %. The proposed scheme has less energy consumption (31 %), less execution time (24\%), decreased node shutdown time (45 %), and less infrastructure cost (48\%) in comparison to existing frameworks. Based on the simulation results, it is concluded that the proposed framework offers an improved solution for IoT-based cloud load-balancing issues.
RESUMO
INTRODUCTION: A close association exists between oral health and cardiovascular disease. Periodontal disease induces early vascular changes while oral pathogens have been detected in sub gingival and atheromatous plaques. We examined the interrelationship between Periodontal disease, oral bacteria, surrogate sub-clinical markers and coronary artery disease (CAD) in a representative Asian Indian cohort. MATERIALS AND METHODS: 532 Gingivitis cases and 282 Periodontitis cases were assessed for early peripheral vascular changes, namely pulse wave velocity (PWV), arterial stiffness index (ASI) and ankle brachial index (ABI) using computerized oscillometry method. Relative quantitation (RQ) of Porphyromonas gingivalis (Pg) was estimated in saliva samples of 54 Periodontitis, 25 Gingivitis and 51 CAD cases (38 also had oral disease) by Taqman assay by amplifying pathogen-specific gene targets, 16srRNA and IktA, respectively, and 16s universal bacterial rRNA as endogenous control. RESULTS: PWV and ASI were elevated in Periodontitis compared to Gingivitis cases (p<0.0001) and in those with diabetes and hypertension. Cases with Periodontitis showed higher mean expression of Pg than Gingivitis (0.37±0.05 versus 0.15±0.04, p<0.0001), while CAD patients with oral disease (N=38) showed lower mean Pg expression than those without oral disease (N=13) (0.712±0.119 versus 1.526±0.257, p=0.008). Higher Pg expression was recorded in subjects with diabetes and hypertension. CONCLUSION: Oral disease induces early changes in the peripheral blood vessels. Further, common presence of Pg in subjects with oral disease, in those with established cardiovascular risk factors and in patients with symptomatic CAD reflects the importance of oral hygiene in the development of Coronary Artery Disease in Asian Indians.