In this paper we probe the routing algorithm that maximizes the quality of the network. In this regard, we present various scenarios for comparisons among different routing algorithms in a wireless sensor network. Using simulations conducted in NS-2, we compare the performance of genetic algorithm (GA) to the Dijkstra algorithm, Ad hoc On-Demand Distance Vector (AODV), GA-based AODV Routing (GA-AODV), grade diffusion (GD) algorithm, directed diffusion algorithm and GA combined with the GD algorithm. We assume the presence of faulty nodes and work on finding out the performance that enhances the lifespan of the sensor network. In this regard, we have simulated routing algorithms while considering faulty nodes up to 50% of the functioning nodes. Nodes are considered to be dynamic and we assumed different mobility speeds of the nodes. Our results demonstrate that GA can be used in different network configurations as it shows a better performance in the wireless sensor network.
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The proposed work is based on the path optimization approach for wireless sensor network (WSN). Path optimization is achieved by using the NSG 2.1 Tool, TCL Script file and NS2 simulator to improve the quality of service (QoS). Path optimization approach finds best suitable path between sensor nodes of WSN. The routing approach is not only the solution to improve the quality but also improves the WSN performance. The node cardinally is taken under consideration using the ad-hoc on demand distance vector routing protocol mechanism. Ad hoc approach emphasize on sensor nodes coverage area performance along with simulation time. NSG 2.1 Tool calculates the sensor node packet data delivery speed which can facilitate inter-node communication successfully. An experimental result verified that the proposed design is the best possible method which can escape from slow network response while covering maximum sensor nodes. It achieves coverage support in sensor node deployment. The result outcomes show best path for transferring packet from one sensor node to another node. The coverage area of sensor node gives the percentage of average coverage ratio of each node with respect to the simulation time.
相似文献In underwater communication, establishing a communication link between the sensor in the sea bed and the surface sinks is a daunting task. Further, the data has to be transmitted with minimum delay and maximum reliability. Therefore, the present study proposes a biobjective routing protocol for underwater wireless sensor networks. The existing protocols are reviewed and it is found that the traditional depth based and vector-based routing protocols are not able to tackle these conflicting objectives and hence suffer transmission failures with high delay. A biobjective optimization of delay and reliability of routes is proposed to obtain pareto-optimal routes employing uninformed search technique and a modified greedy best first search heuristic. Through simulation experiments, it is found that the biobjective protocol performs better than depth based, delay based and reliability-based routing protocols. However, since the biobjective routing problem in underwater wireless sensor networks is known to be NP-hard and dynamic in nature, the computational effort of uninformed search in yielding the exact solutions increases as the network size increases. The modified greedy best first search heuristic is employed to yield sub-optimal routes with less computational effort without compromising on the quality of the solutions and hence suitable for larger networks.
相似文献Many application domains require that sensor node to be deployed in harsh or hostile environments, such as active volcano area tracking endangered species, etc. making these nodes more prone to failures. The most challenging problem is monitoring the illegal movement within the sensor networks. Attacker prefers mobile malicious node because by making the diversity of path intruder maximize his impact. The emerging technology of sensor network expected Intrusion detection technique for a dynamic environment. In this paper, a defective mechanism based on three-step negotiation is performed for identifying the mobile malicious node using the mobile agent. In many approaches, the multi-mobile agents are used to collect the data from all the sensor nodes after verification. But it is inefficient to verify all the sensor nodes (SNs) in the network, because of mobility, energy consumption, and high delay. In the proposed system this can be solved by grouping sensor nodes into clusters and a single mobile agent performs verification only with all the cluster heads instead of verifying all the SNs. The simulation result shows the proposed system shows a better result than the existing system.
相似文献In recent years, cloud computing provides a spectacular platform for numerous users with persistent and alternative varying requirements. In the cloud environment, security and service availability are the two most significant factors during the data encryption process. For providing optimal service availability, it is necessary to establish a load balancing technique that is capable of balancing the request from diverse nodes present in the cloud. This paper aims in establishing a dynamic load balancing technique using the APMG approach. Here in this paper, we integrated adaptive neuro-fuzzy interference system-polynomial neural network as well as memory-based grey wolf optimization algorithm for optimal load balancing. The memory-based grey wolf optimization algorithm is employed to enhance the precision of ANFIS-PNN and to maximize the locations of the membership functions respectively. Also, two significant factors namely the turnaround time and CPU utilization involved in optimal load balancing scheme are evaluated. Finally, the performance evaluation of the proposed MG-ANFIS based dynamic load balancing approach is compared with various other load balancing approaches to determine the system performances.
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