<span>The area of Mobile Adhoc Network (MANET) has being a demanded topic of research for more than a decade because of its attractive communication features associated with various issues. This paper primarily discusses on the security issues, which has been still unsolved after abundant research work. The paper basically stresses on the potential features of Swarm Intelligence (SI) and its associated techniques to mitigate the security issues. Majority of the previous researches based on SI has used Ant Colony Optimization (ACO) or Particle Swarm Optimization (PSO) extensively. Elaborated discussion on SI with respect to trust management, authentication, and attack models are made with support of some of the recent studies done in same area. The paper finally concludes by discussing the open issues and problem identification of the review.</span>

There is no direct method for design of beams. In general the dimensions of the beam and reinforcement are initially assumed and then the interaction formula is used to verify the suitability of chosen dimensions. This approach necessitates few trials for coming up with an economical and safe design. This paper demonstrates the applicability of Artificial Neural Networks (ANN) and Genetic Algorithms (GA) for the design of beams subjected to moment and shear. A hybrid neural network model which combines the features of feed forward neural networks and genetic algorithms has been developed for the design of beam subjected to moment and shear. The network has been trained with design data obtained from design experts in the field. The hybrid neural network model learned the design of beam in just 1000 training cycles. After successful learning, the model predicted the depth of the beam, area of steel, spacing of stirrups required for new problems with accuracy satisfying all design constraints. The various stages involved in the development of a genetic algorithm based neural network model are addressed at length in this paper.

Wireless sensor-actor networks (WSAN) consist of a vast number of sensors and few actors. Generally, these networks are deployed in an unprotected environment to sense the physical world, and perform reliable actions on it. Hence, these networks are always susceptible to various kinds of passive and active attacks by malicious nodes. The back hole and gray hole attacks are part of active attacks. These attacks degrade the network efficiency and performance. In this paper, an efficient trust based secured coordination mechanism is proposed to counter the black hole and gray hole attacks on the delay and energy efficient routing protocol in sensor-actor networks. In the proposed mechanism, each sensor analyzes the trust level of its 1 − hop sensors based on the experience, recommendation, and knowledge. The analyzed trust value is transferred to the actor. The actor analyzes these values to identify the malicious nodes in its cluster region. The proposed trust based secured coordination mechanism (TBSC) is simulated using NS2. The performance is analyzed with respect to packet delivery ratio, average energy dissipation in the network, and average end-to-end delay. The simulation results reveal that TBSC mechanism performs well for the delay and energy efficient routing protocol compared to the existing security mechanisms.

efficiency is increased. Each cell can hold up-to multiple A framework is designed for an ad hoc network, which is a MANET nodes. For a single iteration, under the new data matrix of cells of equal size and are connected in taurus structure the running time is decreased to a lower value. The structure. Each cell is of equal size and there are 100 of them next major design aspect is that it is assumed the simulation and contains number of nodes. The cells are connected in space as an infinite plane and that a node wanders off edge of taurus to make the simulation space infinite i.e. if the nodes simulation terrain will appear to enter at the opposite edges wanders off the boundary of one side then it appears at the and thus desired number of nodes will participate in the entire opposite side, this guarantee that all the nodes will participate simulation run. For this MPI [5] environment is used to run in the entire simulation. For this a parallel simulator is the program. designed considering routing protocols.The cells of the framework are connected in taurus form i.e.

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