The Internet of Things (IoT) is getting important and interconnected technologies of the world, consisting of sensor devices. The internet is smoothly changing from an internet of people towards an Internet of Things, which permits various objects to connect to another wirelessly. The energy consumption of the IoT routing protocol can affect the network life span. In addition, the high volume of data produced by IoT will result in transmission collision, security issues, and energy dissipation due to increased data redundancy because tiny sensors are usually hard to recharge after they are deployed. Generally, to save energy, data aggregation reduces data redundancy at each node by turning some nodes into sleep mode and others into wake mode. Therefore, it is important to group the nodes with high data similarity using the fuzzy matrix. Then, the data received from the member nodes at the Cluster Head (CH) are analyzed using a fuzzy similarity matrix for clustering. In the next step, after clustering, some nodes are chosen from all groups as redundant nodes. The sleep scheduling mechanism is then applied to reduce data redundancy, network traffic jamming, and transmission costs. We have proposed an Energy-Efficient Data Aggregation Mechanism (EEDAM) secured by blockchain, which uses a data aggregation mechanism at the cluster level to save energy. As edge computing is used to provide on-demand trusted services to IoT with minimum delay, blockchain is integrated inside a cloud server, so the edge is validated by the blockchain to provide secure services to IoT. Finally, we performed simulations to calculate the performance of the proposed mechanism and compared it with the conventional energy-efficient algorithms. The simulation results show that the proposed structural design can successfully reduce the amount of data, provide proper security to the IoT, and extend the wireless sensor network (WSN).

The Internet of Things (IoT) is one of the highly influencing and promising technologies of today's world, consisting of sensor devices. The internet smoothly changes from an internet of people towards an Internet of Things (IoT), which allows different things and objects to connect wirelessly. Things and objects are grouped into IoT subgroups in the IoT system, which are called clusters, and each cluster is controlled by a central authority and checked by the broker's help. A concept of keeping backup data is used to increase the lifespan of IoT subgroups by avoiding re-clustering overhead for smooth transmission of packets and increasing availability concerns. A novel approach is used for the selection of cluster head/broker and backup nodes simultaneously. Cluster head and Backup Storage Point node (BSP) remain the same unless and until the residual power of the broker/cluster head is greater than the threshold energy. A novel Energy Efficient Message scheduling algorithm EAAFTMS (An Energy-Aware Available and Fault-Tolerant System with Message Scheduling in IoT) is incorporated at broker node for smooth transmission of messages. This proposed approach is not only solving availability issues over the wireless network but also proved to be energy efficient by prolonging the battery-powered network lifetime. Simulation results prove EAAFTMS, many folds better than benchmark protocols. This system ensures fault-tolerant and available schemes for IoT systems while stabilizing the energy of the overall system. The results shown prove the effectiveness and efficiency of the proposed system.

Rapid growth of Internet of Things (IoT), and other intelligent devices, introduced different applications which offer real-time latency features; however, it is difficult to handle the large volumes of data produced during the computational process, to adequately complete tasks. The decentralized edge computing process handles the task at the user's end to accomplish latency applications, but recent research adopted centralized methodologies for computing in the edge network, placing additional overhead for cluster management and grouping. In this paper, we formulate an edge nodes group on task arrivals with a decentralized technique to process jobs, in a parallel mode, to complete execution. In addition, high availability will be added to promise effective processing of IoT based applications executed in the edge computing system. In the edge node environment, where resources are restricted, there is a requirement for high availability methods, which can deliver system reliability according to the local device information, without the data of network topology. In this paper, our technique is to enhance network reliability with the help of the edge node's local information, which is executed in the distributed edge computing network, while also proposing a high availability technique to enhance the overall IoT environment. Our proposed Latency Aware Algorithm for Edge Computing with High Availability (LAAECHA) detects edge nodes faults, repairs edge nodes and replaces edge nodes with backups, using a new algorithm in a decentralized mode. Our research results show that the proposed LAAECHA method is more effective than existing methods, ensuring latency-aware IoT applications achieve their deadlines, while significantly reducing network traffic as well as guaranteeing system availability and reliability of the IoT network.

Recently researchers and companies have shown significant interest in merging blockchain and the Internet of Things (IoT) to create a safe, reliable, and resilient communication platform. However, determining the proper role of blockchain in existing IoT contexts with minimum implications is a challenge. This work suggests a message schedule for a blockchain-based architecture with two access-level setting filters for incoming messages: critical and non-critical. The proposed work of the researchers divides the fog layer into two parts: action clusters and blockchain fog clusters. Similar to the three-layered IoT architecture, the action cluster and the main cloud data center work together for critical message requests. The blockchain fog cluster is dedicated to only the blockchain application's requirements. In the fog layer, a fog broker is used to schedule critical and non-critical messages in the action and blockchain fog clusters, respectively. The proposed technique is compared to the existing Dual Fog-IoT architecture. The solution is also tested for fog and cloud computing resource utilization. The findings demonstrate that this architecture is feasible for varying percentages of receiving critical and non-critical messages. In addition to the inherent benefits of blockchain, the suggested paradigm reduces the system loss rate and offloads the cloud data center with minimal changes to the existing IoT ecosystem.INDEX TERMS Internet of Things (IoT), Message Scheduling, Wireless Sensor Networks, Fog Computing.

Peripartum cardiomyopathy is a relatively rare but life threatening disease. The etiology and pathogenesis of peripartum cardiomyopathy remains largely theoretical and is generally centered upon viral and autoimmune mechanism. This case report describe the anaesthetic management of a patient suffering from dilated peripartum cardiomyopathy, successfully managed with epidural anaesthesia.