Comparison Analysis Of PSO And SMO

Geographic Adaptive Fidelity (GAF): Geographic Adaptive Fidelity is an energy-aware location based routing algorithm planned for mobile ad-hoc networks but has been used to WSNs. Geographic Adaptive Fidelity conserving energy by switching off redundant sensors nodes. In this routing protocol, the entire network is classified into number of static zones and a virtual grid is made for the covered region. Every node utilizes its GPS-indicated location to link itself with a point in the virtual grid. Nodes linked to the same point on the grid are assumed equivalent with respect to packet routing costs. Nodes within a zone cooperate by choosing one node to show the zone for a period of time whereas the rest of the nodes sleep. A sample situation is considered from

The Hierarchical Power Aware Routing (HPAR) is a power aware routing protocol that divides the network into a group of sensors called zones [12]. In this, the cluster zones are formatted, then the decision is made that how message is routed so the battery life can be maximized. This protocol provides an approximation algorithm called max-min ZPmin algorithm. In this algorithm by applying Dijkshtra algorithm the path who consumes less power is found. Then the second path is found that maximizes the minimal residual power. The advantage is that it provides both transmission power and maximizes battery

In this section, we present the details of proposed protocol. Our protocol implements the idea of probabilities for cluster heads selection based on initial energy and residual energy of sensor nodes as well as the average energy of the sensor network.

In order to test the effectiveness of IGA and GA when solving the timetabling problem, a comparison with the PSO algorithm was performed to investigate trends of performance. All coding was written in MATLAB code and the test case focused on the three above algorithms. All tests were executed on a 3.30 Ghz Intel core i5 processor with 16 GB of ram. The convergence graphs for IGA, GA, and PSO below shows progress until a valid solution for each of the algorithms were discovered. Each of the algorithms simulated 1,000 generations. The graph in Figure 10 - 14 provides a comparison of the proposed algorithm with the conventional population operator based algorithm.

A group of wireless sensor nodes (devices) dynamically constructs a temporary network without the exercise of any pre-existing network infrastructure or centralized administration. The main goal of ad-hoc networking is multihop broadcasting in which packets are transferred from source node to destination node through the intermediate nodes (hops). The main function of multi hop WSN is to enable communication between two terminal devices through a bit of middle nodes, which are transferring information from one level to another level. On the foundation of network connectivity, it dynamically gets to determine that which nodes should get included in routing, each node involved in routing transmit the data to further

A WSN is a type of wireless networks that consists of collection sensor nodes which are tiny devices. Each sensor node of the network has different processing capability. It may contain multiple types of memory (program, data and flash memories), have a RF transceiver, have a power source (e.g., batteries and solar cells), and accommodate various sensors and actuators. The nodes communicate wirelessly and often self-organize after being deployed in an ad hoc fashion [13, 14]. Optimum need of each sensor node is to maximize its own utility function. Also the whole network requires resource assignments balance to perform in a useful and efficient way. This chapter presents a brief survey on WSNs showing its types, characterizing features, protocols and applications.

Roshan Singh Sachan et al (2012), “Misdirection Attack in WSN: Topological Analysis and an Algorithm for Delay and Throughput Prediction”, 2012 There are various types of attack that the wireless sensor network faces. There are a lot of instances that have been occurring in which the detection of the attack of DoS and misdirection attacks has not been possible. The node in misled in such a way that the node reaches to any other node except for the destination node. The degradation of performance occurs due to such cases. Here in the article such an attack has been proposed on the topological analysis of the wireless network. An algorithm is proposed which will provide a help for the assistance in throughput and delaying of the packets. Better performance is observed in the tree network topology than in the mesh topology network [7].

Thanks for offering your support or guidance for us. In our unit there are many CO’s have a potential and experience with them and they would like to apply for the SCO. However, some of them are hesitant to take this opportunity because they have not given opportunity for acting up as ASCO.

World Wide Web). The nodes can be static or dynamic [24]. Wireless Sensor Networks (WSN) will continue to play a very important role in our day to day lives. A WSN contains of sensor nodes that are powered by little unique batteries. These sensor nodes are densely arranged in the area to be monitored to sense and transmit information towards the base station. WSN can simplify structure design and operation, as the environment being monitored does not need the communication or energy infrastructure connected with wired networks [25].

4 different thresholding algorithms are calculated and the one which covers results of other selected thresholds is applied on the optimal single-channel image

T.F.Chen [9] segmentation is the process of portioning the images, where we need to find the particular portion, there are several methods segmentation such as active contour, etc. segmentation can be done both manually and automatically. Here the new technique of segmentation known as level sets segmentation are described, the level set segmentation reduces the problems of finding the curves which is enclose with respect to the region of interest. The implementation of this involves the normal speed and vector field, entropy condition etc. The implementation results produced was two different curves, which can be splitted.

Image Segmentation is concerned about segmenting the image into various segments using various techniques. In early days a semi-automatic approach was being used to detect the exact boundaries of the brain tumor. However the semiautomatic methods were not very successful as they had human induced errors and were time consuming. A better application of tumor detection was made by introducing fully automated tumor detection systems. Various methods have been proposed like Markov random fields method, Fuzzy c-means (FCM) clustering, Otsu’s thresholding, K-Mean’s, neural network. In this project, four different algorithms namely Otsu’s method, Thresholding, K-means method and Fuzzy c-means and PSO have been used for designing the brain tumor extraction system. Various segmentation techniques which will be used in this project to segregate the different regions on the basis of interest are described as follows:

An accurate cost function for the transmission system is formulated where both fixed and variable costs for all planned facilities are includes, in addition to the cost energy losses. The cost function is then minimized, using (BBO) algorithms. We can be used to derive algorithms for optimization. We apply the BBO on the model of IEEE of 6-bus test system.

3.2.18 MST-PSO: Minimum Spanning Tree-PSO Authors proposed a base spreading over tree-PSO based clustering algorithm of the weighted chart of the WSNs. The optimized route between the nodes and its cluster heads is looked from the whole ideal tree on the premise of energy

Software designs and programming approaches for the middleware design should facilitate the balance between communication and computing. Energy awareness, routing, efficient resource utilization and data delivery have always been the key parameters for an efficient programming model for WSN.