MAEER: Mobility aware energy efficient routing protocol for Internet of Things

In many IoT applications, device-to-device communication (i.e. P2P Communication) is required and in some applications these devices are mobile. [14] There are Routing Protocols which support P2P communication but not with mobile nodes. So, there should be a Routing Protocol which support mobility of nodes and also choose optimal paths for less energy consumption as mobile nodes have limited energy. This proposed protocol is an extension of MAEER (Mobility Aware Energy efficient Routing Protocol) which supports mobility of nodes and also offers an additional mechanism of link recovery. Link Recovery technique is very important in device-to-device communication as mobile nodes sometimes can move away from radio range which results in link failure. This link failure affects network performance. It leads to energy depletion and also loss of packet data. So, overall performance degrades and leads to network failure. In this paper, we have proposed a routing technique which can solve the issue of energy depletion and link failure. In addition to that, it also decreases propagation delay.

Objectives: The main objectives of this research endeavor encompass the development of the Adaptive RPL Optimization (ARPLO) model to enhance data transmission efficiency within IoT networks. This includes constructing a grid-based network structure optimized for data transfer, selecting the most suitable nodes as grid head nodes to maximize network lifespan while minimizing energy consumption, implementing an innovative objective function-driven approach to optimize parent node selection, and integrating an Adaptive Deep Neural Network (ADNN) to accurately classify medical data. Methods: The research methodology entails several key steps. A grid-based network structure is established with IoT nodes and root nodes, where a DODAG process incorporating DIO messages is utilized for node ranking. To enhance energy efficiency, the Trickle algorithm is employed for control message optimization. Grid head nodes are chosen based on metrics such as root node fairness, residual energy, and load influence index. The novel Middle Order Optimal Routing (MOOR) objective function is utilized to optimize routing decisions. ADNN is implemented for precise medical data classification. The proposed model's performance is evaluated through simulation in a Python environment. Findings: The research findings demonstrate that the ARPLO model yields notable benefits compared to existing models. It achieves higher energy efficiency, improved throughput, enhanced packet delivery ratio (PDR), and an extended network lifespan. The Trickle algorithm contributes to efficient control message optimization. The MOOR-based routing approach improves multimedia medical data transfer. Moreover, the integration of ADNN enhances the accuracy of data classification, particularly in healthcare applications. The research outcomes align with the broader field's existing values and reports while offering novel insights that contribute to enhancing the existing knowledge base. ARPLO protocol performance reveals that there is increase of throughput of 31.2%, PDR by 7.12%, lifetime of 10.7 % with reduction of energy consumption by 12.72%, control overhead by 31.01% and end-to-end delay by 33.01%. Novelty: The novelty of this research lies in its comprehensive approach that integrates a grid-based network structure, MOOR-based optimization, and ADNN-based classification. The incorporation of the Trickle algorithm for energy-efficient communication is an innovative feature. The introduction of new metrics for grid head node selection, along with the application of the MOOR objective function for multimedia medical data routing, showcases the research's innovative contributions. Keywords: Internet of Things (IoT), RPL (Routing Protocol for Low­Power and Lossy Networks), Optimization, Routing, Multimedia, Healthcare

This paper researches wireless RFID routings in Internet of Things based on the idea of quantization. The researches include the obtaining of routing contexts, the measurement of contexts in evaluating the performance of routing, methods for controlling the quantification of contexts, the realization of a perceptive computational model, the mergence of the security policies. Its goal is to construct a precise lightweight and perceptive model of wireless RFID routing protocols in Internet of Things, and to lay a foundation for accelerating the developments in Internet of Things.

Recently, Roy et al. proposed a physically unclonable function (PUF)-based authentication and key exchange protocol for Internet of Things (IoT) devices. The PUF protocol is efficient, because it integrates both the Node-to-Node (N2N) authentication and the Node-to-Server (N2S) authentication into a standalone protocol. In this paper, we therefore examine the security of the PUF protocol under the assumption of an insider attack. Our cryptanalysis findings are the following. (1) A legitimate but malicious IoT node can monitor the secure communication among the server and any other IoT nodes in both N2N authentication and N2S authentication. (2) A legitimate but malicious IoT node is able to impersonate a target IoT node to cheat the server and any other IoT nodes in N2N authentication and the server in N2S authentication, respectively. (3) A legitimate but malicious IoT node can masquerade as the server to cheat any other target IoT nodes in both N2N authentication and N2S authentication. To the best of our knowledge, our work gives the first non-trivial concrete security analysis for the PUF protocol. In addition, we employ the automatic verification tool of security protocols, i.e., Scyther, to confirm the weaknesses found in the PUF protocol. We finally consider how to prevent weaknesses in the PUF protocol.

In recent times, different routing protocols have been proposed in the Internet of Things enabled Underwater Wireless Sensor Networks (IoT-UWSNs) to explore the underwater environment for different purposes, i.e., scientific and military purposes. However, high Energy Consumption (EC), End to End (E2E) delay, low Packet Delivery Ratio (PDR) and minimum network lifetime make the energy efficient communication a challenging task in Underwater Wireless Sensor Network (UWSN). The high E2E delay, EC and reliable data delivery are the critical issues, which play an important role to enhance the network throughput. So, this paper presents two energy efficient routing protocols namely: Shortest Path-Collision avoidance Based Energy Efficient Routing (SP-CBE2R) protocol and Improved-Collision avoidance Based Energy Efficient Routing (Im-CBE2R) protocol. At this end, both routing protocols minimize the probability of void hole occurrence and in return minimizes the EC and E2E delay. In both routing protocols, courier nodes are positioned at different strategic locations to keep the greedy forwarding continuous. The proposed routing protocols are also analyzed by varying the Packet Size (PS) and Data Rate (DR). Additionally, various simulations have been performed to authenticate the proposed routing protocols. Simulation results show that the proposed routing protocols outperform the baseline routing protocols in counterparts.

In order to solve the problem that the energy consumption of nodes in ad hoc networks with dedicated frequency points in the Internet of things is easy to lose street, and the link failure is easy to occur when the number of nodes increases, an improved ad hoc network driver routing protocol algorithm with dedicated frequency points in the Internet of things is designed. The network model of Internet of things dedicated frequency point ad hoc network is constructed with the main structure of sensing site, sink node and Internet. Through the improved algorithm of network routing protocol, the minimum coverage set is used to repair the link failure of ad hoc network with dedicated frequency points in the Internet of things. It has good throughput performance for routing link information forwarding, which can improve the network data transmission and connectivity, increase the node survival time, and ultimately improve the packet arrival rate and data control.KeywordsInternet of thingsDedicated frequency pointAd hoc networkRouting protocol

In Mobile Adhoc Networks (MANETs), resilient optimization is based on the least energy utilization as well as privacy. The crucial concerns for the productive design to provide multi-hop routing are security and energy consumption. Concerning these problems, we present in this paper an author proposed routing protocol called Protected Quality of Service (QoS) aware Energy Efficient Routing protocol. It is developed on trust along with energy efficiency and points to improve MANET security. The proposed work utilizes an identification methodology in the company of a key based safety feature for assigning trust ratings. This study also determines three categories of trust ratings, including direct, indirect, and overall trust scores, beneficial to increase communication security. The head of a cluster is selected among the nodes based on QoS metrics and scores of the trust which is referred to as a cluster based secured routing approach. Finally, to carry out the safe routing procedure as efficiently as possible, the required final path that is picked depends on path trust, energy consumption, and hop number. The suggested work was evaluated via simulations using the Ns2 simulator. The proposed strategy beats others in the matter of enhanced delivery rate of the packets, lifetime of a network, and security according to the simulation findings. Further, the proposed safe routing technique saves time and energy as compared to current relevant secure routing methods.

Internet enabled computing devices are increasingly at risk of misuse by individuals or malware. Initially such misuse was targeted mainly at computers, however there is increasing targeting of tablet and smartphone devices. In this paper we examine an access control management protocol for Internet of things devices in order to attempt to provide some protection against misuse of such devices. Although anti-malware software is commonly used in computers, and is increasingly being used for tablets and smartphones, this may be a less practicable approach for Internet of things devices. The access control management protocol for Internet of things devices examined in this paper involves the use of physical proximity ‘registration’ for remote control of such devices, encryption of communications, verification of geo-location of the mobile device used to control the IoT device, safe operation controls, and exception reporting as a means of providing a tiered security approach for such devices.

Recently, Internet Engineering Task Force (IETF) standardized a powerful and flexible routing protocol for Low Power and Lossy Networks (RPL). RPL is a routing protocol for low power and lossy networks in the Internet of Things. It is an extensible distance vector protocol, which has been proposed for low power and lossy networks in the global realm of IPv6 networks, so it selects the routes from a source to a destination node based on certain metrics injected into the objective function (OF). There has been an investigation of the performance of RPL in the lighter density network. This study investigates the performance of RPL in medium density using of two objective function in various topologies (e.g. grid, random). The performance of RPL is studied using various metrics. For example, Packet Delivery Ratio (PDR), Power Consumption and Packet Reception Ratio (RX) using a fixed Packet Reception Ratio (RX) values.

Chapter 5 - IP Routing

Energy systems are now incorporating Internet of Things technology to make better monitoring and management of energy possible. This research study analyzes the design and implementation of a secure and smart monitoring network for hybrid energy systems using two of the most widely known Internet of Things protocols and AI, MQTT (Message Queuing Telemetry Transport) and CoAP (Constrained Application Protocol). Traditional energy monitoring has latency issues, low scalability. This paper discusses an enhancement over this with MQTT and CoAP, aiming at increasing overall performance and scalability within hybrid energy frameworks. Methodologies are developed to implement the application with IoT sensors and to collect data from MQTT and CoAP protocols for further processing in the Python programming language. To demonstrate these improvements in efficiency and reliability, the results are compared against those obtained from traditional systems. This work investigates how Internet of Things (IoT) and AI can be deployed in hybrid energy systems with advanced communication protocols to enhance observability as well as control. A total of many enhancements have been added to this system: latency by 35% has been minimized, data transmission efficiency of 96.87%, a reliability increase of 28%, 25% enhancement in scalability, and 20% reduction in energy consumption.

Mobile Ad hoc Network (MANET) has mobile and battery operated nodes which can provide communication facility to users irrespective of any infrastructure and centralized control. It is a self-deployed and self-operated communication network having typical applications such as disaster relief, information exchange at conference or classroom and battle field communication etc. MANETs have many challenges such as limited battery power, lack of centralized control and security, the need for special routing protocols etc. Due to highly dynamic and dispersed nature of MANETs, routing becomes one of the important concerns in MANET. The network can get partitioned due to mobility and/or exhaustion of the nodes. Therefore, energy efficient routing is of great importance for the MANETs. This paper presents a simulation study of existing MANET routing protocols like AODV, DSR, and DSDV based on various metrics like packet delivery ratio (PDR), energy consumption, throughput, overheads, network lifetime and end to end delay to select a suitable protocol for further modification in order to improve the energy efficiency of the nodes. The simulation results show that the DSR protocol performs better than that of AODV and DSDV. Hence DSR protocol is modified based on an algorithm that considers the nodes' residual energy to extend the network lifetime. Implementation of modified protocol shows 22 % increase in the network lifetime and 13 % reduction in energy consumption.

A mobile ad hoc network, or MANET, is a type of wireless network where information is forwarded from a source node to destination node via a number of intermediary nodes. One of the most important restrictions on a MANET is the possibility of packet collisions, which can negatively impact throughput, routing cost, and end-to-end latency because nodes in the network move randomly at variable velocities. In this manuscript, the energy-efficient, two-stage routing protocol in mobile ad hoc networks technique utilizing the features of the hybrid wolf bird and Portia spider optimization algorithm (HWBPSOA-EETSRP-MANET) is proposed. Nodes are distributed randomly in the MANET environment. Every node has a wireless transceiver equipped in order to communicate. The data transmission procedure is initiated by a source node when it wants to send data to a destination node. Several intermediary nodes are chosen by the source node to transmit the data to a destination node. When several nodes are trying to send data on the same channel at the same time, a packet collision may occur. These packet collisions are detected by utilizing the carrier sense multiple access with collision avoidance (CSMA/CA) mechanism. After that, it maximizes the number of pathways returned by the energy-efficient, two-stage routing protocol (EETSRP) technique. Finally, it calculates the fitness values of the pathways by using hybrid wolf bird and Portia spider optimization algorithm (HWBPSOA) to determine the optimal route for the destination. The route with the highest fitness value is considered to be the most optimum route. The proposed HWBPSOA-EETSRP-MANET method is implemented in MATLAB, and the performance metrics like throughput, packet delivery ratio, and end-to-end delay are evaluated. The performance of the proposed method attains a 21.51%, 52.38%, and 21.51% higher packet delivery ratio, a 28%, 50%, and 21.51% higher throughput, and a 19.43%, 28.57%, and 13.78% lower end-to-end delay. A significant amount of energy consumption attainments are observed when compared with existing method likes adaptive routing protocol in mobile ad hoc networks utilizing genetic algorithm (GOA-ARP-MANET), elephant herding optimization ad hoc on-demand multipath distance vector routing protocol for MANET (EHOA-AOMDV-MANET), and enhanced-ant-AODV for optimal route selection in mobile ad hoc network (EAOA-AODV-MANET), respectively.

The wireless sensor networks (WSNs) with dynamic topology communication among the sensor nodes is vulnerable to numerous attacks. As they have limited power, there arises a conflict between the complex security scheme and the consumption of energy which are inversely proportional to each other. Hence, a trade‐off should be accomplished between the implemented scheme and energy. A novel secure and energy‐aware routing technique quantized indexive energy‐aware clustering‐based combinatorial stochastic sampled bat optimization (QIEAC‐CSSBO) is proposed which consists of clustering, optimal route path identification, and route maintenance. The clustering process and selection of cluster head (CH) with high residual energy is done using the quantized Schutz indexive Linde–Buzo–Gray algorithm (QIEAC). Optimal route identification is done using CSSBO (combinatorial stochastic sampled Prevosti’s bat optimization), and fitness of every bat is measured on combinatorial functions, namely, distance, energy, trust, and link stability among nodes. Stochastic universal sampling selection procedure is applied to select the global best optimal path for secure data transmission. Lastly, route maintenance process is performed to identify alternative route while link failure occurs among nodes. Experimental assessment is performed using various performance metrics, namely, energy consumption, packet delivery ratio, packet drop rate, throughput, and delay. The proposed method QIEAC‐CSSBO enhances the performance of packet delivery ratio by 4%, throughput by 26%, and packet drop rate by 27% and reduces energy consumption by 11%, as well as delay by 16% as compared to existing techniques.

Vehicular Ad Hoc Networks (VANETs), a subclass of Mobile Ad Hoc Networks (MANETs), rely on efficient routing protocols to maintain reliable communication in highly dynamic and decentralized environments. While numerous routing strategies have been proposed, their performance varies significantly with the choice of underlying mobility models that simulate real vehicular movement. This study presents a two-phase evaluation of five widely used routing protocols—Ad hoc On-Demand Distance Vector (AODV), Dynamic Source Routing (DSR), Destination-Sequenced Distance Vector (DSDV), Optimized Link State Routing (OLSR), and Geographic Routing Protocol (GRP)—across fourteen realistic mobility models, including the Intelligent Driver Model (IDM), Car-Following Model (CFM), and Lighthill–Whitham–Richards (LWR) model. Simulations are executed using Simulation of Urban Mobility (SUMO), Network Simulator 3 (NS-3), and the Veins framework. The performance is assessed using eight key metrics: Packet Delivery Ratio (PDR), End-to-End Delay (E2ED), Throughput, Jitter, Energy Consumption, Packet Loss Ratio (PLR), Normalized Routing Load (NRL), and Link Breakage Rate (LBR). Among the evaluated protocol–mobility combinations, AODV paired with the CFM model demonstrated comparatively favorable performance under the considered simulation configuration: 93% PDR, 79.4 ms E2ED, 332 kbps throughput, 3.4 ms jitter, 3.48 J energy consumption, 7% PLR, 0.3 NRL, and 5 link breakages per simulation. This study provides a systematic and unified comparative evaluation of five widely used routing protocols across fourteen simulation-based vehicular mobility models. The findings provide scenario-specific comparative insights for simulation-based VANET performance evaluation and offer practical, simulation-based guidance for selecting suitable protocol–mobility model combinations under the evaluated experimental conditions.