Energy Efficiency in IoT based on Sensor Node Deployment Pattern

: IoT becomes more complicated due to its large size. The existing techniques of Wireless Sensor Networks (WSN) are not useful directly to the IoT. That’s why the using the energy efficient schemes for the IoT is a challenging issue. Due to battery constrained IoT devices, energy efficiency is of greatest importance. This paper gives overview and broad survey on IoT, WSN in IoT, Challenges in IoT and WSN, energy conserving issues and solutions and different Node Deployment patterns. For green IoT, this paper addresses energy competence issues by proposing an energy efficient heuristic for a regular and particular deployment scheme. QC-MCSC heuristic is implemented for Strip Based Deployment Pattern and analyzed in terms of Energy Efficiency and Life Time of a sensor on Energy Latency Density Design Space, a topology management application that is power efficient. QC-MCSC for Strip based deployment pattern and for random deployment pattern are compared.

Anomaly-Based Intrusion Detection Systems for Mobile Ad Hoc Networks

Ad hoc networks are used in heterogeneous environments like tactical military applications, where no centrally coordinated infrastructure is available. The network is required to perform self-configuration, dynamic topology management, and ensure the self-sustainability of the network. Security is hence of paramount importance. Anomaly-based intrusion detection system (IDS) is a distributed activity carried out by all nodes of the network in a cooperative manner along with other related network activities like routing, etc. Machine learning and its advances have found a promising place in anomaly detection. This paper describes the journey of defining the most suitable routing protocol for implementing IDS for tactical applications, along with the selection of the related suitable data set. The paper also reviews the latest machine learning techniques, implementation capabilities, and limitations.

5G Environment based CLB-AODV Multicast Routing for the Zigbee on Wireless Sensor Heterogeneous

A communication load balanced dynamic topology management algorithm (CLB-AODV) is proposed to extend the wireless sensor network (WSN) lifetime via managing the participation in communication process among all nodes in the network. The idea is that, each time there is a failure in the network topology; the topology is adjusted only on-demand by choosing the best path according to paths weights between source and destination nodes. The path weight reflects the nodes participation in communication process through the lifetime of the nodes. Our algorithm is based on the routing protocol AODV instead of using a separate protocol for dynamic topology control in order to reduce the routing load among nodes. Simulation results show that CLB-AODV can prolong the lifetime of the network, increase the number of alive nodes and reduce the average routing load when compared with some of the most powerful recent algorithms the integration of Wireless Sensor Networks (WSN), new generation networks or 5G, TCP / IP (IPv6) protocols with the Internet of Things (IoT) that aims to exchange information, applying security, QoS (Quality of Service) and configuration, these three aspects are the problems in the construction of a network in which confidentiality, integrity, availability, authentication, reconfiguration of topology, improvement, high quality of service, addressing, infrastructure, Network and node construction, for M2M (Machine to Machine) communication or end to end. Because 5G cellular networks, in particular, are attractive technologies to provide Internet connectivity to equipment (UE). Moreover, an additional routing information collecting method is developed to further improve the routing performance.

Wireless Sensor Network in IoT and Performance Optimization

: A serious problem in Wireless Sensor Networks (WSNs) is to attain high-energy efficiency as battery is used to power and have limited stored energy. They can’t be suitably replaced or recharged. Appearance of renewable energy harvesting techniques and their combination with sensor devices gives Energy Harvesting Wireless Sensor Networks (EHWSNs). IoT is now becoming part of our lives, comforting simplifying our routines and work life. IoT is very popular . It connects together, computes, communicates and performs the required task. IoT is actually a network of physical devices or things that can interact with each other to share information. This paper gives an overview of WSN and IoT, related work, different ways of connecting WSN with internet, development of smart home, challenges for WSN etc. Next a Framework for performance optimization in IoT is given and QC-PC-MCSC heuristic is analyzed in terms of Energy Efficiency and Life Time of a sensor on Energy Latency Density Design Space, a topology management application that is power efficient. QC-PC-MCSC and QC-MCSC are compared for Energy Efficiency and Life Time of a sensor over energy latency density design space, a topology management application.