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Routing protocols in wireless sensor networks (WSN) are a crucial challenge for which the goal is maximizing the system lifetime. Since the sensor nodes are with limited capabilities, these routing protocols should be simple, scalable, energy‐efficient, and robust to deal with a very large number of nodes, and also self‐configurable to node failures and changes of the network topology dynamically. The purpose of this paper is to present a new algorithm for cluster forming in WSN based on the node energy required to transmit to the base station.

Rotation selection of cluster‐head considering the remoteness of the nodes to the sink, and the network node residual energy.

The simulation results show that this algorithm allows network stability extension compared to the most known clustering algorithm.

Giving a probability to become cluster‐head based on the remoteness of the node to the sink.

With the increasing acclaim of Wireless Sensor Networks and its diverse applications, research has been directed into optimising and prolonging the network lifetime. Energy efficiency has been a critical factor due to the energy resource impediment of batteries in sensor nodes. The proposed routing algorithm therefore aims at extending lifetime of sensors by enhancing load distribution in the network. The scheme is based on the chain-based routing technique of the PEGASIS (Power Energy GAthering in Sensor Information Systems) protocol and uses Ant Colony Optimisation to obtain the optimal chain. The contribution of the proposed work is the integration of the clustering method to PEGASIS with Ant Colony Optimisation to reduce redundancy of data, neighbour nodes distance and transmission delay associated with long links, and the employment an appropriate cluster head selection method. Simulation results indicates proposed method’s superiority in terms of residual energy along with considerable improvement regarding network lifetime, and significant reduction in delay when compared with existing PEGASIS protocol and optimised PEG-ACO chain respectively.

Scalability is a fundamental problem in mobile ad hoc networks (MANETs), where network topology includes large number of nodes and demands a large number of packets in network that characterized by dynamic topologies, existence of bandwidth constrained, variable capacity links, energy constraint and nodes are highly prone to security threats. The key purpose of this paper is to overview the efficiency of the proposed clustering scheme for large-scale MANETs and its performance evaluation and especially in the case of a large number of nodes in the network.

Designing clustering schemes for MANETs, which are efficient and scalable in the case of large number of mobile nodes, has received a great attention in the last few years. It is widely used to improve resources management, hierarchical routing protocol design, quality of service, network performance parameters such as routing delay, bandwidth consumption, throughput and security. MANETs are characterized by limited wireless bandwidth, nodes mobility that results in a high frequency of failure regarding wireless links, energy constraint and nodes are highly prone to security threats. Due to all these features, the design of a scalable and efficient clustering scheme is quite complex. Many clustering schemes have been proposed to divide nodes into clusters, focusing on different metrics and purposes.

To the best of the author's knowledge, the different proposed clustering schemes are not scalable when the network size increases to a very large number. The paper presents the clustering scheme in detail and its performance evaluation by simulating MANETs composed of a large number of mobile nodes. The authors compare the performance of the scheme with a number of existing clustering schemes such as lowest-ID, highest degree, and weighted clustering algorithm, based on a number of performance metrics. Simulation results show that the scheme performs better than other clustering schemes, based on the performance metrics considered, for large-scale MANETs.

This paper addresses the problem of scalability in MANETs when there are high numbers of node in the network. The paper analyses the performance of the proposed clustering scheme for large-scale MANETs. The obtained results show that the different proposed clustering schemes do not allow the scalability when the network size is very large. The scheme supports scalability efficiently when the number of nodes increases in the network (more than 2,000 nodes).

This paper aims to provide prolonging network lifetime and optimizing energy consumption in mobile wireless sensor networks (MWSNs). Forming clusters of mobile nodes is a great task owing to their dynamic nature. Such clustering has to be performed with a higher consumption of energy. Perhaps sensor nodes might be supplied with batteries that cannot be recharged or replaced while in the field of operation. One optimistic approach to handle the issue of energy consumption is an efficient way of cluster organization using the particle swarm optimization (PSO) technique.

In this paper two improved versions of centralized PSO, namely, unequal clustering PSO (UC-PSO) and hybrid K-means clustering PSO (KC-PSO), are proposed, with a focus of achieving various aspects of clustering parameters such as energy consumption, network lifetime and packet delivery ratio to achieve energy-efficient and reliable communication in MWSNs.

Theoretical analysis and simulation results show that improved PSO algorithms provide a balanced energy consumption among the cluster heads and increase the network lifetime effectively.

In this work, each sensor node transmits and receives packets at same energy level only. In this work, focus was on centralized clustering only.

To validate the proposed swarm optimization algorithm, a simulation-based performance analysis has been carried out using NS-2. In each scenario, a given number of sensors are randomly deployed and performed in a monitored area. In this work, simulations were carried out in a 100 × 100 m² network consisting 200 nodes by using a network simulator under various parameters. The coordinate of base station is assumed to be 50 × 175. The energy consumption due to communication is calculated using the first-order radio model. It is considered that all nodes have batteries with initial energy of 2 J, and the sensing range is fixed at 20 m. The transmission range of each node is up to 25 m and node mobility is set to 10 m/s.

This proposed work utilizes the swarm behaviors and targets the improvement of mobile nodes’ lifetime and energy consumption.

PSO algorithms have been implemented for dynamic sensor nodes, which optimize the clustering and CH selection in MWSNs. A new fitness function is evaluated to improve the network lifetime, energy consumption, cluster formation, packet transmissions and cluster head selection.

This paper is a review of a number routing protocols in the internet of vehicles (IoV). IoV emphasizes information interaction among humans, vehicles and a roadside unit (RSU), within which routing is one of the most important steps in IoV network.

In this paper, the authors have summarized different research data on routing protocols in the IoV. Several routing protocols for IoV have been proposed in the literature. Their classification is made according to some criteria such as topology-based, position-based, transmission strategy and network structure. This paper focuses on the transmission strategy criteria. There exist three types of protocols that are based on this strategy: unicast protocol, broadcast protocols and multicast protocols. This later type is classified into two subclasses: geocast and cluster-based protocols. The taxonomy of the transmission strategy is presented in this study. We discuss the advantages and disadvantages of each type with a general comparison between the five types.

The authors can deduce that many challenges are encountered when designing routing protocols for IoV.

A simple and well-explained presentation of the functioning of the IoV is provided with a comparison among each categories of protocols is well presented along with the advantages and disadvantages of each type. The authors examined the main problems encountered during the design of IoV routing protocol, such as the quick change of topology, the frequent disconnection, the big volume of data to be processed and stored in the IoV, and the problem of network fragmentation. This work explores, compares existing routing protocols in IoV and provides a critical analysis. For that, the authors extract the challenges and propose future perspectives for each categories of protocols.

In a wireless sensor network (WSN), the sensor nodes are distributed in the network, and in general, they are linked through wireless intermediate to assemble physical data. The nodes drop their energy after a specific duration because they are battery-powered, which also reduces network lifetime. In addition, the routing process and cluster head (CH) selection process is the most significant one in WSN. Enhancing network lifetime through balancing path reliability is more challenging in WSN. This paper aims to devise a multihop routing technique with developed IIWEHO technique.

In this method, WSN nodes are simulated originally, and it is fed to the clustering process. Meanwhile, the CH is selected with low energy-based adaptive clustering model with hierarchy (LEACH) model. After CH selection, multipath routing is performed by developed improved invasive weed-based elephant herd optimization (IIWEHO) algorithm. In addition, the multipath routing is selected based on certain fitness functions like delay, energy, link quality and distance. However, the developed IIWEHO technique is the combination of IIWO method and EHO algorithm.

The performance of developed optimization method is estimated with different metrics, like distance, energy, delay and throughput and achieved improved performance for the proposed method.

This paper presents an effectual multihop routing method, named IIWEHO technique in WSN. The developed IIWEHO algorithm is newly devised by incorporating EHO and IIWO approaches. The fitness measures, which include intra- and inter-distance, delay, link quality, delay and consumption of energy, are considered in this model. The proposed model simulates the WSN nodes, and CH selection is done by the LEACH protocol. The suitable CH is chosen for transmitting data through base station from the source to destination. Here, the routing system is devised by a developed optimization technique. The selection of multipath routing is carried out using the developed IIWEHO technique. The developed optimization approach selects the multipath depending on various multi-objective functions.

Internet of Things (IoT) is an up-and-coming conception that intends to link multiple devices with each other. The aim of this study is to provide a significant analysis of Green IoT. The IoT devices sense, gather and send out significant data from their ambiance. This exchange of huge data among billions of devices demands enormous energy. Green IoT visualizes the concept of minimizing the energy consumption of IoT devices and keeping the environment safe.

This paper attempts to analyze diverse techniques associated with energy-efficient protocols in green IoT pertaining to machine-to-machine (M2M) communication. Here, it reviews 73 research papers and states a significant analysis. Initially, the analysis focuses on different contributions related to green energy constraints, especially energy efficiency, and different hierarchical routing protocols. Moreover, the contributions of different optimization algorithms in different state-of-the-art works are also observed and reviewed. Later the performance measures computed in entire contributions along with the energy constraints are also checked to validate the effectiveness of entire contributions. As the number of contributions to energy-efficient protocols in IoT is low, the research gap will focus on the development of intelligent energy-efficient protocols to build up green IoT.

The analysis was mainly focused on the green energy constraints and the different robust protocols and also gives information on a few powerful optimization algorithms. The parameters considered by the previous research works for improving the performance were also analyzed in this paper to get an idea for future works. Finally, the paper gives some brief description of the research gaps and challenges for future consideration that helps during the development of an energy-efficient green IoT pertaining to M2M communication.

To the best of the authors’ knowledge, this is the first work that reviews 65 research papers and states the significant analysis of green IoT.

This paper aims to present a comprehensive review in major research areas of unmanned air vehicles (UAVs) navigation, i.e. three degree-of-freedom (3D) path planning, routing algorithm and routing protocols. The paper is further aimed to provide a meaningful comparison among these algorithms and methods and also intend to find the best ones for a particular application.

The major UAV navigation research areas are further classified into different categories based on methods and models. Each category is discussed in detail with updated research work done in that very domain. Performance evaluation criteria are defined separately for each category. Based on these criteria and research challenges, research questions are also proposed in this work and answered in discussion according to the presented literature review.

The research has found that conventional and node-based algorithms are a popular choice for path planning. Similarly, the graph-based methods are preferred for route planning and hybrid routing protocols are proved better in providing performance. The research has also found promising areas for future research directions, i.e. critical link method for UAV path planning and queuing theory as a routing algorithm for large UAV networks.

The proposed work is a first attempt to provide a comprehensive study on all research aspects of UAV navigation. In addition, a comparison of these methods, algorithms and techniques based on standard performance criteria is also presented the very first time.

Cross-layer approach in media access control (MAC) layer will address interference and jamming problems. Hybrid distributed MAC can be used for simultaneous voice, data transmissions in wireless sensor network (WSN) and Internet of Things (IoT) applications. Choosing the correct objective function in Nash equilibrium for game theory will address fairness index and resource allocation to the nodes. Game theory optimization for distributed may increase the network performance. The purpose of this study is to survey the various operations that can be carried out using distributive and adaptive MAC protocol. Hill climbing distributed MAC does not need a central coordination system and location-based transmission with neighbor awareness reduces transmission power.

Distributed MAC in wireless networks is used to address the challenges like network lifetime, reduced energy consumption and for improving delay performance. In this paper, a survey is made on various cooperative communications in MAC protocols, optimization techniques used to improve MAC performance in various applications and mathematical approaches involved in game theory optimization for MAC protocol.

Spatial reuse of channel improved by 3%–29%, and multichannel improves throughput by 8% using distributed MAC protocol. Nash equilibrium is found to perform well, which focuses on energy utility in the network by individual players. Fuzzy logic improves channel selection by 17% and secondary users’ involvement by 8%. Cross-layer approach in MAC layer will address interference and jamming problems. Hybrid distributed MAC can be used for simultaneous voice, data transmissions in WSN and IoT applications. Cross-layer and cooperative communication give energy savings of 27% and reduces hop distance by 4.7%. Choosing the correct objective function in Nash equilibrium for game theory will address fairness index and resource allocation to the nodes.

Other optimization techniques can be applied for WSN to analyze the performance.

Game theory optimization for distributed may increase the network performance. Optimal cuckoo search improves throughput by 90% and reduces delay by 91%. Stochastic approaches detect 80% attacks even in 90% malicious nodes.

Channel allocations in centralized or static manner must be based on traffic demands whether dynamic traffic or fluctuated traffic. Usage of multimedia devices also increased which in turn increased the demand for high throughput. Cochannel interference keep on changing or mitigations occur which can be handled by proper resource allocations. Network survival is by efficient usage of valid patis in the network by avoiding transmission failures and time slots’ effective usage.

Literature survey is carried out to find the methods which give better performance.

The purpose of this paper is to introduce a new data dissemination model in order to improve the performance of transmission in VANET. It proposes a protocol named Epidemic and Transmission-Segment-based Geographic Routing (ETSGR) and outlining the issues due to high mobility of nodes and uncertain physical topologies in the network. The proposed ETSGR is mainly used to analyze the vehicle state, direction, distance, traffic density and link quality of the network.

This research work based on ETSGR protocol mainly uses epidemic algorithm in order to find the vehicle state based on susceptible, infected and recovered (SIR) model. Furthermore, the vehicle position and finding the head node in the network is utilized using the transmission segment protocol based on geographic routing and analyses each node to form the segments and find the destination to transmit the data in timely manner.

The paper provides the enhancement of the performance based on some metrics such as end-to-end delay that obtained 0.62%, data throughput as 32.3%, packet delivery ratio as 67% and one-hop communication as 13%. The proposed ETSGR protocol analyzes the state of the vehicle correctly and each node segmented to transmit the data with the timely manner and obtaining reliable performance even with high mobility of nodes in the network.

The proposed ETSGR protocol may have some limitation when considering the timing which should improve even in increasing many number of vehicles and different road segments.

This paper includes some suggestions for the practical deployment of the approach in which a real-time traffic analysis can be evaluated for taking prior actions during an emergency situation and proper dissemination of data in timely manner can help utilize the guidance of proper planning of roads.

This research fulfills an enhanced protocol to improve the performance of data dissemination.