Despite the many applications of wireless sensor networks, due to limited resources such as energy and memory in the sensor, this type of network against malicious attacks are very weak and vulnerable.Therefore, as an effective complement to traditional security methods, management, ensuring a key role in the discovery of suspicious behavior in wireless sensor networks.The main issue is how we can recognize the ideal of nodes in this environment of complex shapes to achieve?In this paper, Markov chain model to calculate the amount of short-term confidence of nodes used and a management system to ensure the reduction of environmental impacts of complex motives have been proposed to compute node status.There's also a new computing model with factors for calculating the long-term reliability suggested that the impact of environmental change in the calculation parameters dropped.Simulation results show that the proposed algorithm can effectively suspicious behavior of wireless sensor network nodes to discover.Can be meaningfully compared to those of packet delivery to provide a more appropriate rate.Finally, better security in wireless sensor networks provide.For TEST!!

Wireless Sensor Networks are considered to be among the most rapidly evolving technological domains thanks to the numerous benefits that their usage provides. As a result, from their first appearance until the present day, Wireless Sensor Networks have had a continuously growing range of applications. The purpose of this article is to provide an up-to-date presentation of both traditional and most recent applications of Wireless Sensor Networks and hopefully not only enable the comprehension of this scientific area but also facilitate the perception of novel applications. In order to achieve this goal, the main categories of applications of Wireless Sensor Networks are identified, and characteristic examples of them are studied. Their particular characteristics are explained, while their pros and cons are denoted. Next, a discussion on certain considerations that are related with each one of these specific categories takes place. Finally, concluding remarks are drawn.

One of the most important applications of wireless sensor networks was to estimate the unknown phenomenon. The cooperative activities of wireless sensors and scattered information of sensor nodes over network are used to decentralized estimation. Precoder design done on the sensor nodes in order to provide an optimal estimate of the actual amount. Precoder design is an optimization problem. Since the channel is wireless link on the wireless sensor networks. Therefore, assuming the access of full channel state information isnt correct in this network. Since the perfect channel state information is required in the precoder design process, so the effects of the channel estimation investigated on precoder design process. On the issue of channel estimation, channel estimated by using of the known training sequence method with LS and MMSE criteria. Since power restriction is the key subject in the wireless sensor networks, therefore in this study power restriction considered in the channel estimation and precoder design problem.

Wireless sensor networks are one of the most important tools for information acquisition and environment identification in many application areas. Recent advances in the field of electronics and wireless telecommunications have led to the design and manufacture of sensors with low power consumption, small size, reasonable price and various applications. Most research in the area of wireless sensor networks has focused on two dimensional sensor networks while in the real world, most of the applications are three dimensional. Some research in this area has focused on underwater, space, forestry, and environment applications. The main objective of the current research is increasing network lifetime by defining new parameters and embedding them in the fuzzy clustering or fuzzy C-means algorithm that has been adapted for three dimensional wireless sensor networks. One of the parameters that has been used in this research is limited movement of sensors. By adding this ability to the network, there is an expectation of improvement in network performance. The results of the experiments indicate the positive effect of this ability on network performance and lifetime.

This paper is a survey of an effective routing enhancement for sensor nodes in WSNs. The adoption of WSNs has risen as a result of recent developments in wireless technology (WSNs). Because of its promising properties, such as low cost, low power, simple implementation, and ease of maintenance, a Wireless sensor network has become widely employed for monitoring and controlling applications in our daily lives. In general, scalable and dependable WSN models with shorter latency times, precise data transfer between nodes, low energy consumption, and longer life are required. The performance of a wireless sensor network greatly relies on the routing approach used, so that communications between multiple wireless sensor nodes are managed by routing protocols. To enhance routing in WSNs the following parameters should be considered: Shortest path, energy consumption, network lifetime, mean delay, Mean jitter, Packet delivery ratio, lost packets, throughput and the energy consumption of the entire WSN. The most important constraints of wireless sensor networks are energy consumption and network lifetime. We will use a capsule network to make the enhancement routing in WSNs by enhancing and optimizing routing protocols for WSNs.

In clustering algorithms for wireless sensor networks, cluster heads close to the sink node usually encounter much more relay traffic and therefore lose energy rapidly. To address this problem in wireless sensor networks, distance-aware clustering approaches such as EEUC that adjust the cluster size according to the distance between the sink node and each cluster head have been proposed. However, the network lifetime of such approaches is highly dependent on the distribution of the sensor nodes because in randomly distributed sensor networks the approaches do not guarantee that the cluster energy consumption is commensurate with the cluster size. It might be necessary, for example, for sensors to be randomly distributed over the surveillance region (e.g., via aircraft). To solve this problem in wireless sensor networks, a new method called distribution based clustering algorithm (DBCA) was proposed in the present research which is not only aware of the distance but also the density of the sensor nodes. In DBCA, clusters have limited sensor nodes that are determined by the distance between the sink node and the cluster head. The simulation results show that DBCA is 25% to 45% more efficient than previous algorithms in terms of power consumption under different operating conditions.

In this survey, the main and dominant point of pursuit is reviewing some aspects and approaches of networks security that are more appropriate for wireless sensors, by applying effective changes to some details and divisions, and it has been attempted to make them exclusive for the certain wireless sensors network that can be utilized in any particular or crucial industrial fields, like oil and gas pipeline and medical devices for monitoring the patient. Security network algorithms and processing trends are usually accessible and ready to use for everyone, however, it also increases the potential risk and concern of attack for industries that use wireless sensor networks. In this study, basic data has been altered and actually disintegrated before securing; additionally, common algorithms have been employed in order to reduce the risk involved with using wireless sensor networks for maintaining and protecting basic and major industries, and in particular for monitoring pipelines.

The wireless sensor network is a wireless network of self-organized sensors that are distributed at intervals. These sensors are used to group measurements of specific physical quantities or environmental conditions such as temperature, sound, vibration, pressure, motion, or pollutants at various locations. Energy efficiency to extend a wireless sensor network's lifetime should be considered in all network design areas, including hardware and software. Wireless sensor networks may be used in critical applications and transmit sensitive data, so they need methods to secure the data. Secure routing in wireless sensor networks is vital due to the need for data confidentiality, integrity, energy efficiency, authentication, and resilience against attacks. It ensures sensitive data remains private, prevents tampering, optimizes energy usage, verifies node authenticity, and defends against attacks. This paper presents a secure routing method in wireless sensor networks. In the proposed method, due to the nodes' processing limitations and to ensure the security of the exchanged messages, the lightweight columnar transposition cipher method is used. The routing process is done hop by hop, and the next hop is selected based on the parameters of remaining energy, distance to the base station, and node traffic. The proposed routing method is implemented by MATLAB and compared with SMEER and KID-SASR methods. The simulation results show a reduction of end-to-end delay of 50% and 38%, reduction of energy consumption of 39% and 20%, reduction of packet loss rate, and increased number of live nodes by 66% and 59% compared to SMEER and KID-SASR.

Wireless sensor networks (WSNs) are made up of thousands of small sensor nodes that are capable of detecting, calculating, and transferring data via networks. Although there are certain resource limits, wireless transmission is still an effective way to transport information. The secure transfer of data is critical in a WSN. Key management techniques have been established for the purposes of security. Key pre-distribution is one of the key management methods used to assign keys to the devices before deploying them in the wireless sensor networks. The challenges of these schemes include memory consumption due to limited device resources, scalability, connectivity, and resilience against node capture attacks. Combinatorial designs with neutrality characteristics, which are based on mathematical structure and impose low computational overhead and communication overhead, are used in key pre-distribution and information security of wireless sensor networks. In this paper, some key pre-distribution methods based on the combinatorial designs are reviewed. Finally, the comparison of performance parameters is illustrated in tables. Suggestions to improve future research are considered as well.

Wireless Sensor Networks (WSNs) are a special class of wireless ad-hoc networks where their performance is affected by different factors.Congestion is of paramount importance in WSNs. It badly affects channel quality, loss rate, link utilization, throughput, network life time, traffic flow, the number of retransmissions, energy, and delay. In this paper, congestion control schemes are classified as classic or softcomputing-based schemes. The soft computing-based congestion control schemes are classified as fuzzy logic-based, game theory-based, swarm intelligence-based, learning automata-based, and neural network-based congestion control schemes. Thereafter, a comprehensive review of different soft computing-based congestion control schemes in wireless sensor networks is presented. Furthermore, these schemes are compared using different performance metrics. Finally, specific directives are used to design and develop novel soft computing-based congestion control schemes in wireless sensor networks