A multipath mechanism for wireless sensors network

This study proposes a technique for multipath data transmission in Wireless Sensor Network (WSN) by proposing a novel optimisation algorithm, named exponential cat swarm optimisation (ECSO), by integrating the exponential weighted moving average and CSO. Initially, the CH is selected by the penguin fuzzy‐based ant colony optimisation (PFuzzyACO) technique, which is the integration of fuzzy, ACO and penguin search optimisation algorithm (PeSOA). After the selection of the optimal CH, the multipath transmission is done by the proposed ECSO algorithm. Here, an optimal path is selected for transmitting the routeing information from source to destination based on various parameters such as trust, energy, distance, delay, traffic density and link lifetime (LLT). Thus, the CHs with maximum trust, energy and LLT, and minimum distance, delay and traffic density are adapted for multipath data transmission using the proposed ECSO algorithm. The proposed ECSO algorithm shows 18.75, 2.99 and 29.87% improvements in terms of number of alive nodes, throughput and network energy, respectively, than the existing PFuzzyACO, which has high performance than the other comparative methods such as artificial bee colony, ACO, fractional artificial bee colony, Low‐Energy Adaptive Clustering Hierarchy (LEACH), FuzzyACO and PeSOA.

BIM2RT: BWAS-immune mechanism based multipath reliable transmission with fault tolerance in wireless sensor networks

How to ensure high quality multi-path transmission is of great importance for wireless sensor network, hence, in this paper, we propose a novel multi-path transmission method based on network coding. Wireless sensor networks are made up of three types nodes, among which the base station records the data of each cluster from the gateways, and the sensor can collect data from external environment. Afterwards, wireless sensors receive information from the gateway, and send it to neighbor nodes. Afterwards, we propose a novel multi-path transmission model for wireless sensor network, which is represented as a directed hypergraph. To solve the issue of packet loss which is obtained by the high bit error rate, the actual number of packets transmitted by the source node is obtained. Then, we calculate the times of network coding, and the group numbers is randomly selected by the source code from the sensing area. Finally, the proposed algorithm can achieve lower transmission cost, energy consumption and time cost than other methods.

FCMPR:A multi-path secure transmission method based on link security assessment and fountain coding

This study investigated programmed control of transmitting video and audio streaming data with P4 switches in software defined networks. When a packet is transmitted to a P4 switch, the switch checks the match actions and invokes a random function to determine which output port the packet should be sent to. Thus, the switches in the network can route the streaming data via different path according to the random function so as to provide multipath transmission. Simulation results showed that the proposed multipath transmission mechanism can improve transmission efficiency, reliability, and network throughput.

Wireless sensor networks (WSNs) have become one of the essential components of the Internet of Things (IoT). In any IoT application, different sensor-based devices gather data from physical objects and transmit the sensed information to the base station (BS). The BS analyzes this information depending on the sensor location. A high-performance intelligent WSNs is essential for any IoT-based application. In this article, high-performance intelligent WSNs are referred to as IoT-enabled WSNs. In IoT-enabled WSNs, fault occurrence probability is much more than traditional networks. Faulty nodes and broken links affect the reliability of the IoT-enabled WSNs. Various fault-tolerance algorithms enhance the network’s reliability using multipath transmission, relay node placement, and backup node selection. However, these algorithms suffer from huge data transmission delays, packet overhead, and less detection accuracy. In this work, a multiobjective-deep reinforcement-learning (DRL)-based algorithm is proposed for fault tolerance in IoT-enabled WSNs. The main objective of this work is to detect the faulty nodes with high accuracy and less overhead. Furthermore, this work focuses on reliable data transmission after fault detection. Finally, a mobile sink (MS) is used for energy-efficient data gathering that significantly improves the network lifetime. Extensive simulations and theoretical analysis prove that the proposed algorithm outperformed as compared to the state-of-the-art algorithms in terms of fault detection accuracy (FDA), false alarm rate (FAR), false-positive rate (FPR), network lifetime, and throughput.

VoIP application.The theoretical analysis evaluated the multipath transmission model and verified that the Latent Handover can efficiently optimize the handover process and enhance transmission efficiency during handover.Extensive simulations under different scenarios verified that the multipath mechanism can effectively enhance VoIP transmission and mobility efficiency.

In wireless sensor networks, the energy consumption of sensors is not uniform over the whole region of deployment. The uneven energy usage occurs because some sensors have to transmit data to farther distances or have to transmit more data packets than others. This leads to a shorter duration of operation because some sensors’ energy will deplete fast creating holes in the network. To alleviate this problem, we proposed an algorithm we named Procrastinated Clustering and Multi-Hop Routing (PCMR). To prolong the operation, it will optimally assign sensors with different precomputed procrastination periods to schedule the clustering and routing processes. In PCMR, sensors’ clustering and routing intervals depend on their locations in the network with respect to the sink. The algorithm could reduce and balance energy consumption for sensors distributed over a wide area. Procrastination periods are precomputed off-line before deployment. Therefore, it is easy to implement and is efficient, even for a large network for which real-time reorganization would involve transmitting a large number of signaling packets. The results from simulations show that the proposed PCMR algorithm could balance energy usage among sensors, and prolong the network lifetime compared to existing works based on techniques such as adjusting cluster size and/or multi-path transmission.

Today main objective of wsn is to minimize the energy dissipation for the whole network. Clustering is one of the most knows methods widely used to face these challenges. Fix Cluster Head Selection (FCHS) routing protocol analyses how the system lifetime is improved by fixing the selection of clusters head. In this paper a cluster based communication protocol with considering the low energy consumption in wireless sensor networks, is introduced which balanced the energy load among the sensor node. Fix Cluster Head Selection (FCHS) analyses the cluster head selection to find the optimal probability of becoming a cluster head. Simulation result of FCHS corresponding to LEACH in mat lab shows that these designs increase the lifetime of the network 105 %. We found that FCHS yield longer stability region for higher values of extra energy brought by more powerful nodes. Finally, LEACH protocol and the improved algorithm simulate in MATLAB, and make Performance analysis and comparison in number of nodes alive, total energy consumption in network and a round of node death distribution. The results show that, FCHS compared with LEACH protocol, the improved algorithm prolongs the network life cycle, raises energy utilization and has good load balance.

Wireless sensor “motes” is small or tiny embedded systems equipped with radios for wireless communication in the networks, which depend on batteries as a power source. The development of Medium Access Control (MAC) protocols which search is for to minimize the energy consumption in the wireless sensor network. Recent contention based MAC protocols reduce energy usage by placing the radio in a low power sleep state when not sending or receiving the message. In this paper the main emphasis is on the analysis of the Contention Based MAC Protocols and energy consumption in the networks. Based on the work done by various researchers conclude that S-MAC is the backbone of all the MAC protocols for wireless sensor networks. Our proposed work investigated the energy usage and compared the performance of IEEE 802.11 MAC protocol with S-MAC protocol on different modes like without periodic sleep and with periodic sleep on different performance metrics like Remaining Energy vs Time, Energy consumption vs global packet id and Average End to End Delay vs Time. The performance of S-MAC protocol improves on the basis of duty-cycle parameter, which determines the length of sleep period in a frame and this parameter is a variable. So changing the duty cycle will change the performance of S-MAC protocol. Finally, we have used the different routing protocol with S-MAC to evaluate the energy consumption. The experimented worked done on Network Simulator Ns2- 2.34.KeywordsMedium Access ProtocolWireless Sensor NetworkIdle listeningSleep StateS-MACEnergy ConsumptionDuty cycle

Data aggregation in wireless sensor networks is widely used to collect data in an energy efficient manner to eliminate redundant data transmission so that prolong the network lifetime. To meet the data aggregation needs in wireless sensor networks, this paper proposes a novel multi-path routing algorithm, called EAD, to process in-network data aggregation. For each sensor on the routing paths, EAD evaluates its neighbors based on the residual energy, deviation angle and distance, and selects the k neighbors with the minimal evaluation costs as its forwarding nodes in order to balance energy consumption of the wireless sensor network on the premise of ensuring the reliability and performance. Simulation results show that EAD can effectively prolong network lifetime, reduce latency and ensure the reliability by adjusting the weight of each influencing factor.

This study examines the directions and mechanisms for improving data reliability in Bigdata and blockchain technologies. Currently, there is a sharp increase in data flow, data processing is performed in computer networks, and an increase in the volume of data also leads to an increase in the problem of data reliability. It is important to identify solutions based on the use of modern technologies to solve these problems. Observations show that data reliability violations are mainly observed in three areas, namely due to artificial and natural redundancy in data transmission, the integrity of interconnected data in data transmission and storage, and errors in large-scale data processing. The features and capabilities of Bigdata class data and blockchain technology to improve data reliability were mentioned. Data from the Bigdata class was analyzed to improve the reliability of data based on blockchain mechanisms.

The wireless power transfer technology in Wireless Sensor Networks (WSNs) lets the sensors replenish their energy through the Mobile Chargers (MCs). The new network is named Wireless Rechargeable Sensor Networks (WRSNs) in the literature. In these networks, the mobile charger scheduling is very important to retrieve the sensors' energy. In some of the proposed approaches, a deterministic and predetermined path is determined for MCs by using the information from the entire network. These approaches are not appropriate for the uncertain real networks in which the network changes over time. For this reason, we propose an online, grid-based and decentralized method. In this method, MCs select some sensors for renewing their energy by considering the status of the grid cells around them. The purpose of our method named Coverage Aware Charging (CAC) is to replenish the power of low-energy sensors as well as keeping a better network coverage. Finally, we evaluate CAC by using comprehensive simulation different situations.

In this article, efficient power saving scheme and corresponding algorithm must be developed and designed in order to provide reasonable energy consumption and to improve the network lifetime for wireless sensor network systems. The clusterbased technique is one of the approaches to reduce energy consumption in wireless sensor networks. In this article, we propose a saving energy clustering algorithm to provide efficient energy consumption in such networks. The main idea of this article is to reduce data transmission distance of sensor nodes in wireless sensor networks by using the uniform cluster concepts. In order to make an ideal distribution for sensor node clusters, we calculate the average distance between the sensor nodes and take into account the residual energy for selecting the appropriate cluster head nodes. The lifetime of wireless sensor networks is extended by using the uniform cluster location and balancing the network loading among the clusters. Simulation results indicate the superior performance of our proposed algorithm to strike the appropriate performance in the energy consumption and network lifetime for the wireless sensor networks.

Fault tolerance and reliable transmission are hot issues in wireless sensor networks. For the problems that the fault of nodes or links will affect the transmission stability and reliability of the network, a gradient based multipath reliable transmission strategy with fault tolerance is presented for wireless sensor networks. Firstly nonuniform clustering topology is established in nonequal clustering probability based on twice K-means algorithm. Then it calculates the comprehensive measurements (CM) of cluster heads by the quality evaluation function and establishes the contour lines. Finally gradient based multiple disjoint transmission paths are established by the mechanisms of load balance and linear erasure coding. It also establishes the transmission mathematical model to analyze the performance of the network. Simulation shows that this strategy has good performance of fault tolerance. It improves the transmission reliability of the network and energy efficiency.