Wireless Sensor Networks need primal information like location of the Nodes to start working and sending environment data. One method for setting a Sensor network in a battlefield is to drop them from helicopter or to fire from artillery. It will cost a lot to Equip all network Nodes with GPS. So to reduce these costs, only a few of Nodes called anchor Nodes are equipped with gps. Location of Nodes are estimated by using belief propagation algorithm with measuring distance between Nodes (with use of recieved signal strength) and location information of anchor Nodes. Since the cost of anchor Nodes is reletively high, their number is important. also position of anchor Nodes affects algorithms error. In this paper, by using multi-objective algorithms with two objectives of error reduction and anchor Nodes number reduction, position and number of anchor Nodes are determined. results show that by using this methond, a few solutions are provided which are better than similar algorithms in terms of error reduction and energy consumption.

The majority of wireless Sensor network (WSN) security protocols state that a direct connection from an attacker can give them total control of a Sensor node. A high level of security is necessary for the acceptance and adoption of Sensor networks in a variety of applications. In order to clarify this issue, the current study focuses on identifying abnormalities in Nodes and cluster heads as well as developing a method to identify new cluster heads and find anomalies in cluster heads and Nodes. We simulated our suggested method using MATLAB tools and the Database of the Intel Research Laboratory. The purpose of the performed simulation is to identify the faulty Sensor. Using the IBRL database, Sensors that fail over time and their failure model is the form that shows the beats in the form of pulses, we find out that the Sensor is broken and is of no value. Of course, this does not mean that the Sensor is invasive or intrusive. We have tried by clustering through Euclidean distance that identify disturbing Sensors. But in this part of the simulation, we didn't have any data that shows disturbing Sensors, it only shows broken Sensors. We have placed the Sensors randomly in a 50 x 50 space and we want to identify the abnormal node.

Security is the major area of concern in communication channel. Security is very crucial in wireless Sensor networks which are deployed in remote environments. Adversary can disrupt the communication within multi hop Sensor networks by launching the attack. The common attacks which disrupt the communication of Nodes are packet dropping, packet modification, packet fake routing, badmouthing attack and Sybil attack. In this paper we considered these attacks and presented a solution to identify the attacks. Many approaches have been proposed to diminish these attacks, but very few methods can detect these attacks effectively. In this simple scheme, every node selects a parent node to forward the packet towards base station or sink. Each node append its unique identity and trust to the parent as a path marker. It encrypts the bytes using a secret key generated and shared among the sink. The encrypted packet is then forwarded to the parent node. Base station can identify the malicious Nodes by using these unique identity and trust value.

The Delay Tolerant Mobile Sensor Networks (DTMSNs) distinguish themselves from conventional Sensor networks by means of several features such as node mobility, loose connectivity, and delay tolerability. In comparison with conventional networks, prominent feature of these networks is that there is not end-to-end path between source and destination. Due to energy limitation, one of the crucial issues in large-scale networks is energy storage that can be overcome this problem by distribution of multi-sink in a network at the same time. In this paper, in order to covering large area, we determine a new radio range to sink Nodes that prevents the presence of Nodes in the radio range of multiple sinks and sending data to a large number of sinks. Then, we represent Replica Adaptive Data Gathering Protocol. Simulation results indicate that the proposed protocol significantly improves message delivery rate with lower transmission overhead and also lower delay in data delivery than the other existing DTMSNs routing protocols.

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.

In order to solve some security issues in Wireless Sensor Networks (WSNs), node to node authentication method based on digital watermarking technique for verification of relative Nodes is proposed. In the proposed method, some algorithms with low computational for generation, embedding and detection of security ID are designed. The collected data packets by the Nodes are marked using security ID. In the proposed method, header is used to mark the packets. Since the nature of the Sensor networks is cooperative, using the head of the packets is proposed for authentication. Also using the marked head can prevent from sending and receiving fake data in the other Nodes. Simulations have been performed in environments with imposing unrealistic data and having a probability from 1% to 10%. Comparing the proposed method with other methods shows that the proposed method in term of security, reducing traffic and increasing network lifetime is more effective.

wireless Sensor networks (WSNs) are one of the most important distributed computing systems and environmental conditions have a great impact on their functionality. Some Sensor Nodes in WSNs have a battery as the power source and use renewable energy such as solar energy to charge it. If the batteries are not charged by harvesting energy from the environment, the tasks of the Sensor Nodes will fail. To prevent it, the Sensor Nodes can also decide to migrate tasks to neighbor Nodes based on their battery status. On the other, the arrival rate of tasks at day hours is more than the arrival rate of tasks at night hours, but the charging rate of batteries is higher during the day than at night. Therefore, decisions of WSNs should be based on information from environmental conditions. The different arrival rates of tasks and charge rates of the batteries at day and night hours as the main environmental conditions have been ignored in the modeling of WSNs. In this paper, we model a WSN node using Stochastic Reward Nets (SRN) and then compute the steady-state probabilities of processing, failure, and migration of tasks and evaluate the impact of different environmental conditions on them in the WSNs. The results prove that changing the charge rate has a greater impact on the WSN functionality than changing the arrival rate.