A Collaborative Approach for Secured Routing in Mobile Ad-Hoc Network

Mobile computing is the most powerful application for network com-munication and connectivity,given recent breakthroughs in thefield of wireless networks or Mobile Ad-hoc networks(MANETs).There are several obstacles that effective networks confront and the networks must be able to transport data from one system to another with adequate precision.For most applications,a frame-work must ensure that the retrieved data reflects the transmitted data.Before driv-ing to other nodes,if the frame between the two nodes is deformed in the data-link layer,it must be repaired.Most link-layer protocols immediately disregard the frame and enable the high-layer protocols to transmit it down.In other words,because of asset information must be secured from threats,information is a valu-able resource.In MANETs,some applications necessitate the use of a network method for detecting and blocking these assaults.Building a secure intrusion detection system in the network,which provides security to the nodes and route paths in the network,is a major difficulty in MANET.Attacks on the network can jeopardize security issues discovered by the intrusion detection system engine,which are then blocked by the network’s intrusion prevention engine.By bringing the Secure Intrusion Detection System(S-IDS)into the network,a new technique for implementing security goals and preventing attacks will be developed.The Secure Energy Routing(SER)protocol for MANETs is introduced in this study.The protocol addresses the issue of network security by detecting and preventing attacks in the network.The data transmission in the MANET is forwarded using Elliptical Curve Cryptography(ECC)with an objective to improve the level of security.Network Simulator–2 is used to simulate the network and experiments are compared with existing methods.

Energy Based Random Repeat Trust Computation in Delay Tolerant Network

As the use of mobile devices continues to rise,trust administration will significantly improve security in routing the guaranteed quality of service(QoS)supply in Mobile Ad Hoc Networks(MANET)due to the mobility of the nodes.There is no continuance of network communication between nodes in a delay-tolerant network(DTN).DTN is designed to complete recurring connections between nodes.This approach proposes a dynamic source routing protocol(DSR)based on a feed-forward neural network(FFNN)and energybased random repetition trust calculation in DTN.If another node is looking for a node that swerved off of its path in this situation,routing will fail since it won’t recognize it.However,in the suggested strategy,nodes do not stray from their pathways for routing.It is only likely that the message will reach the destination node if the nodes encounter their destination or an appropriate transitional node on their default mobility route,based on their pattern of mobility.The EBRRTC-DTN algorithm(Energy based random repeat trust computation)is based on the time that has passed since nodes last encountered the destination node.Compared to other existing techniques,simulation results show that this process makes the best decision and expertly determines the best and most appropriate route to send messages to the destination node,which improves routing performance,increases the number of delivered messages,and decreases delivery delay.Therefore,the suggested method is better at providing better QoS(Quality of Service)and increasing network lifetime,tolerating network system latency.

Robust Cluster-Based Routing Protocol for IoT-Assisted Smart Devices in WSN

The Internet of Things(IoT)is gaining attention because of its broad applicability,especially by integrating smart devices for massive communication during sensing tasks.IoT-assisted Wireless Sensor Networks(WSN)are suitable for various applications like industrial monitoring,agriculture,and transportation.In this regard,routing is challenging to nd an efcient path using smart devices for transmitting the packets towards big data repositories while ensuring efcient energy utilization.This paper presents the Robust Cluster Based Routing Protocol(RCBRP)to identify the routing paths where less energy is consumed to enhances the network lifespan.The scheme is presented in six phases to explore ow and communication.We propose the two algorithms:(i)energy-efcient clustering and routing algorithm and (ii)distance and energy consumption calculation algorithm.The scheme consumes less energy and balances the load by clustering the smart devices.Our work is validated through extensive simulation using Matlab.Results elucidate the dominance of the proposed scheme is compared to counterparts in terms of energy consumption,the number of packets received at BS and the number of active and dead nodes.In the future,we shall consider edge computing to analyze the performance of robust clustering.

Energy Balance Routing Protocol for Wireless Sensor Networks Based on Fuzzy Next-Hop Selection

The implementation of energy balanced routing is an effective way to prolong the lifetime of wireless sensor networks （WSNs）. To balance energy consumption, fuzzy next-hop selecting strategy was designed： nodes of different gradients are fuzzily classified into relevant levels; each level has a chance to provide a node with maximum residual energy as the next-hop. Based on the above strategy and directed diffusion （DD）, fuzzy next-hop selection based energy balance （FNSEB） routing protocol was proposed. The simulation results showed that FNSEB utilized the limited energy more thoroughly and rationally, decreased the average energy consumption and prolonged the lifetime of WSNs.

Energy aware hierarchical cluster-based routing protocol for WSNs

Wireless sensor networks（WSNs） are emerging as essential and popular ways of providing pervasive computing environments for various applications. Unbalanced energy consumption is an inherent problem in WSNs, characterized by multi-hop routing and a many-to-one traffic pattern. This uneven energy dissipation can significantly reduce network lifetime. In multi-hop sensor networks, information obtained by the monitoring nodes need to be routed to the sinks, the energy consumption rate per unit information transmission depends on the choice of the next hop node. In an energy-aware routing approach, most proposed algorithms aim at minimizing the total energy consumption or maximizing network lifetime. In this paper, we propose a novel energy aware hierarchical cluster-based（NEAHC） routing protocol with two goals： minimizing the total energy consumption and ensuring fairness of energy consumption between nodes. We model the relay node choosing problem as a nonlinear programming problem and use the property of convex function to find the optimal solution. We also evaluate the proposed algorithm via simulations at the end of this paper.

Issues and Challenges in Node Connectivity in Mobile Ad Hoc Networks: A Holistic Review

One of the fundamental properties of an ad hoc network is its connectivity. Maintaining connectivity in wireless networks is extremely difficult due to dynamic changing topology of MANETs. There are several techniques to understand the connectivity level for a given network topology. In this paper, we examine the existing methods and discuss the issues and challenges that are still insurmountable in order to enhance the connectivity properties of wireless multi hop networks.

Deep Learning Convolutional Neural Network for ECG Signal Classification Aggregated Using IoT

Much attention has been given to the Internet of Things (IoT) by citizens, industries, governments, and universities for applications like smart buildings, environmental monitoring, health care and so on. With IoT, networkconnectivity is facilitated between smart devices from anyplace and anytime.IoT-based health monitoring systems are gaining popularity and acceptance forcontinuous monitoring and detect health abnormalities from the data collected.Electrocardiographic (ECG) signals are widely used for heart diseases detection.A novel method has been proposed in this work for ECG monitoring using IoTtechniques. In this work, a two-stage approach is employed. In the first stage, arouting protocol based on Dynamic Source Routing (DSR) and Routing byEnergy and Link quality (REL) for IoT healthcare platform is proposed for effi-cient data collection, and in the second stage, classification of ECG for Arrhythmia. Furthermore, this work has evaluated Support Vector Machine (SVM),Artificial Neural Network (ANN), and Convolution Neural Networks (CNNs)-based approach for ECG signals classification. Deep-ECG will use a deep CNNto extract critical features and then compare through evaluation of simple and fastdistance functions in order to obtain an efficient classification of heart abnormalities. For the identification of abnormal data, this work has proposed techniquesfor the classification of ECG data, which has been obtained from mobile watchusers. For experimental verification of the proposed methods, the Beth Israel Hospital (MIT/BIH) Arrhythmia and Massachusetts Institute of Technology (MIT)Database was used for evaluation. Results confirm the presented method’s superior performance with regards to the accuracy of classification. The CNN achievedan accuracy of 91.92% and has a higher accuracy of 4.98% for the SVM and2.68% for the ANN.