In this paper, we develop a trust based security protocol based on a cross-layer approach which attains confidentiality and authentication of packets in both routing and link layers of MANETs. In the first phase of the protocol, we design a trust based packet forwarding scheme for detecting and isolating the malicious nodes using the routing layer information. It uses trust values to favor packet forwarding by maintaining a trust counter for each node. A node is punished or rewarded by decreasing or increasing the trust counter. If the trust counter value falls below a trust threshold, the corresponding intermediate node is marked as malicious. In the next phase of the protocol, we provide link-layer security using the CBC-X mode of authentication and encryption. By simulation results, we show that the proposed cross-layer security protocol achieves high packet delivery ratio while attaining low delay and overhead. B. Neighbor attackThe neighbor attack and the black hole attack prevent the data from being delivered to the destination. But the neighbor attacker does not catch and capture the data packets from the source node. It leaves the settings as soon as sending the false messages. C. Wormhole attackTwo malicious nodes share a private communication link between them. One node captures the traffic information of the network and sends them directly to other node. Warm hole can eavesdrop the traffic, maliciously drop the packets, and perform man-in-the-middle attacks against the network protocols.[6]. D. DoS (Denial of Service) attackWhen the network bandwidth is hacked by a malicious node [5], then it results to the DoS attack. In order to utilize precious network resources like bandwidth, or to utilize node resources like memory or computation power, the attacker inserts packets into the network. The specific instances of the DoS attack are the routing table overflow attack and energy consumption attack. E. Information Disclosure attackThe information disclosure attack aims at the privacy requirements of network. The confidential information's like A. Rajaram received the B.E. degree in electronics and communication engineering from the Govt., college of Technology, Coimbatore, Anna University, Chennai, India, in 2006, the M.E. degree in electronics and communication engineering (Applied Electronics) from the Govt., college of Technology, Anna University, Chennai, India, in 2008 and he is currently pursuing the full time Ph.D. degree in electronics and communication engineering from the Anna University Coimbatore, Coimbatore, India. His research interests include communication and networks mobile adhoc networks, wireless communication networks (WiFi, WiMax HighSlot GSM), novel VLSI NOC Design approaches to address issues such as low-power, cross-talk, hardware acceleration, Design issues includes OFDM MIMO and noise Suppression in MAI Systems, ASIC design, Control systems, Fuzzy logic and Networks, AI, Sensor Networks.

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This paper presents a new approach that minimizes copper & iron losses and optimizes the efficiency of a variable speed Induction motor drive. This method is based on a simple induction motor field oriented control model includes iron losses uses only conventional IM parameters. In literature, Fuzzy logic and Genetic Algorithms have been used for efficiency optimization of induction motor drives. This paper proposes integration of Fuzzy model identification and PSO algorithm for loss minimization. An improvement of efficiency is obtained by adjusting the magnetizing current component with respect to the torque current component to give the minimum total copper and iron losses. The whole circuit is simulated using MATLAB 7.6. The proposed method is compared with other soft computing techniques. The results obtained by Fuzzy PSO shows better results compared with other approaches.

Multi-objective optimisation is a proven well known parameter tuning technique in complex power system problems. It is especially suited to solve complex transmission network expansion planning. This paper proposes a practical method for transmission network expansion planning by bacterial foraging technique. The electricity industry has always been interested in expanding investment in the transmission sector of the industry. As load demand increases and generation expands to meet the need, transmission expansion becomes important in order to increase social welfare by reducing total system operating cost, and to make the system more reliable. In this context, two objectives: investment cost and network adequacy restrictions are considered to overcome the drawbacks of conventional mathematical optimization method in arriving at local optimum and dimension disasters, we introduced the bacterial foraging technique into transmission network optimal planning for the first time, from which the optimal scheme is generated. The bacterial foraging is used as the optimization tool to obtain the Pareto approximation set solutions. The proposed algorithm is implemented on typical IEEE 6 bus systems and performance is assessed by statistical test.

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