Energy based encryption and keying with collision avoidance in wireless sensor networks
Designing cost-efficient, secure network protocols for Wireless Sensor Networks (WSNs) is a challenging problem because sensors are resource-limited wireless devices. Resource limited in the sense limited energy level, memory and computational capacity. Since the communication cost is the most dominant factor in a sensor’s energy consumption. We introduce an Energy-Efficient Energy Based Encryption and Keying with Collision Avoidance scheme for WSNs that significantly reduces the number of transmissions needed for rekeying. This is done to avoid stale keys. Energy based encryption is a secure communication framework where sensed data is encoded using a scheme based on a permutation code generated by using the RC4 encryption mechanism. Dynamic keys are used for the packets in the stream. The intermediate nodes in the path verify the authenticity and integrity of the incoming packets. The key generated by the sender’s virtual energy, this avoids the rekeying. Energy based encryption efficiently transfers data between the nodes that are added in the watched list. Energy based encryption reduces transmission overhead. Transmission overhead increases if the packet size and also while transferring control messages for rekeying. During data transmission, if more than one node transmits data to same destination at same time the data gets collided at the receiving side. Retransmission reduces the energy level of the sensor node. While data is transmitted by first node and the next node must wait in queue until the first node completes its transmission. This mechanism avoids data collision in the destination and also it results in energy savings of a node because there is no need to transfer the same data again and again to the same destination if data collision occurs during transmission.
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Enforcing socially selfish awareness routing among users
In the real world, most people are socially selfish; i.e., they are willing to forward packets with whom they have social ties but not to others, which varies with the strength of the social tie. A Social Selfishness Aware Routing (SSAR) algorithm to allow user selfishness and for having better routing performance in an efficient way is proposed. To select a forwarding node, SSAR considers both users’ willingness to forward and their contact based approaches, which results in a better forwarding method than purely contact-opportunities. SSAR also formulates the packet forwarding process as a Multiple Knapsack Problem with Assignment Restrictions (MKPAR) to satisfy user demands for selfishness and performance. Trace-based simulations show that SSAR allows users to maintain selfishness and it achieves better routing performance with low transmission cost.
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Learning-based compiler level optimization of branching statement layout using execution patterns and dynamic code reordering
Code layout is an important factor that determines the performance of any application. For branching intensive loops where decisions have to be made among several branching paths (as in real time systems), an optimized layout of the conditional statements can increase the performance largely. Current methods can predict branches dynamically using speculative execution which can be resource intensive. Static branch prediction techniques are not as accurate. In this work a compiler based optimization for branching instructions by code reordering has been proposed. The proposed design consists of a code reordering component that along with the compiler can dynamically generate layout-optimized code, by reordering the conditions in the source program. The reordering is done base on dynamic run-time execution patterns. Based on the current execution pattern and the history, the most optimal program can be run, minimizing evaluation of conditions.
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Differential evolutionary algorithm for optimization of pid controller parameters applied to electromagnetic levitation system
Differential Evolutionary Algorithm is a simple but powerful computing tool for real parameter optimization. This article describes the application of this technique for designing a PID controller for Electromagnetic levitation system (EMLS).EMLS is inherently unstable and strongly non-linear in nature. Classical controllers designed for this system give no satisfactory performance. Little change in the operating air gap position deteriorates the controller performance making the system unstable. Therefore a need arises to make one controller such that it will give the optimum performance in the sense of changing gap positions .To that end Differential Evolutionary Algorithm (DEA) is used to fulfil this goal. The analysis is performed within the mathematical programming environment of MATLAB using both DEA and Conventional Genetic Algorithm (CGA) and a detailed comparative study is presented.
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Improved swarm intelligence for solving symmetric travelling salesman problems having premature convergence
Ant colony optimization is unique convergence of Swarm Intelligence and Bio-Inspired Artificial Intelligence. Ants are social insects with limited skills that live in colonies able to solve complex problems. The intelligence of the global society arises from self organization mechanisms, based on the indirect communication between individuals through pheromones. The Symmetric Travelling Salesman Problem here presented is a typical case that requires a self organization type of algorithm, in order to cope with the problem dynamics. The simulation results show how the ant colony optimization is able to solve the different possible routing cases. The innovation in this entire proposal (paper) is that an attempt has been made to improve the existing ant colony algorithm and then apply to the problem set. Ant colony optimization (ACO) has been successfully applied to solve combinatorial optimization problems, but it still has some drawbacks such as stagnation behavior, long computational time, and premature convergence. These drawbacks are more evident when the problem size increases. In this paper, I have reported the analysis of using a reduced/lower pheromone trail bound and a dynamic updating rule for the heuristic parameters based on entropy to improve the efficiency of ACO in solving Traveling Salesman Problems (TSPs). TSPs are NP-hard problem. Even though the problem itself is simple, when the number of city is large, the search space will become extremely large and it becomes very difficult to find the optimal solution in a short time. From my simulations, it can be found that the proposed algorithm indeed has superior search performance over traditional ACO algorithms do.
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Chaos image encryption using pixel shuffling with henon map
The advent of wireless communications both inside and outside the home-office environment has led to an increased demand for effective encryption systems. The beauty of encryption technology comes out in more pronounced way when there is no absolute relation between cipher and original data and it is possible to rebuild the original image in much easier way. As chaotic systems are known to be more random and non-predictable, they can be made utilized in achieving the encryption. The transposition technology of encryption systems requires scrambleness behaviour in order to achieve the encryption of the data. This srambleness behaviour can be derived from the randomness property of chaos which can be better utilized in the techniques like transposition system. In wireless communication systems, bandwidth utilization is an important criterion. In order to use encryption system in wireless communication; key space plays an important role for the efficient utilization of the bandwidth. In this paper we present a chaos-based encryption algorithm for images. This algorithm is based on pixel scrambling where inthe randomness of the chaos is made utilized to scramble the position of the data. The position of the data is scrambled in the order of randomness of the elements obtained from the chaotic map and again rearranged back to their original position in decryption process.
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Secure chaotic modulation schemes using henon map
Future communication should operate at higher data rates, be more reliable, and operate in increasingly crowded frequency allocations. New technologies are being tried in this direction and chaotic communication is one among them. Equivalently, chaotic signals decorrelate rapidly with themselves. The autocorrelation function of a chaotic signal has a large peak at zero and decays rapidly. Same random sequence can be obtained provided we know the exact initial condition for the process. The nonlinear, unstable and aperiodic characteristic of chaotic signals has numerous features that make it attractive for communication use. Chaotic communication is rather a new field in communication research. During the past 15 years, there has been a tremendous interest worldwide in possibility of exploiting chaos in wideband communication system. In this direction already 4 generations of chaotic communication is evolved. In this project we have implemented five different types of chaotic modulation. Demodulation is either coherent or non coherent, based on the type of modulation. For coherent demodulation we used correlator receiver and adaptive filter receiver. We have made a comparison among different types of modulation techniques.
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ANN assisted network reconfiguration for enhancement of voltage stability in power networks
Due to economic reasons arising out of deregulation and open market of electricity, modern day power systems are being operated closer to their stability limits. Maintaining voltage stability and specified voltage levels at all nodes in a large & heavily loaded Power network is a critical & challenging task for power engineers. A number of different approaches have been reported in papers for improvement of voltage stability. In this paper a method for improving voltage stability in a power network has been suggested based on Network Reconfiguration approach. Network Reconfiguration is intended to enhance the voltage stability by determination of switching options that maximizes voltage stability for a particular set of loads and is performed by altering the topological structure of the system. In this paper, reconfiguration of a power network is achieved by addition of new power lines to the existing network. The paper reports an application of ANNs in voltage stability enhancement. A generalized ANN model has been proposed for enhancement of voltage stability under varying load conditions. Training data sets for ANN training is generated by varying both real and reactive loads at the buses. An IEEE-14 Bus system considered to demonstrate the performance of the developed ANN model. The proposed ANN model is trained using conjugate Gradient Descent Back-propagation Algorithm and tested by applying arbitrary input data. The test results of the ANN model are found to be closely matching of the results obtained by off-line simulation.
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FPGA implementation of an efficient space vector pulse width modulation algorithm
In this paper a resource efficient SVPWM algorithm having low computational overheads, is proposed. This can be used for Three Phase voltage source inverter to supply variable voltage and variable frequency to three phase ac drives. This technique has the advantages such as lower switching losses, higher output voltage for the same dc bus voltage, and better harmonic performance. Conventional scheme is theoretically simple, the implementation is difficult especially with the advance of switching frequency (low sampling period). The complicated procedures will result in long processing time and extensive computational resources. Using this resource efficient SVPWM algorithm, the conventional SVPWM is decomposed into fast integer operations entirely by using an intermediate vector, which will properly counteract the redundant calculations of the remaining procedures. Since it can be implemented without any multiplier or divider, the fast algorithm is especially suitable for field programmable gate array applications. It ensures lower hardware resource usage, and at the same time, operates faster. Also the Field Programmable Gate Arrays (FPGAs) offer high computational ability and flexibility due to their parallel execution and reconfigurable hardware. Hence the scheme suggests the implementation of a resource efficient algorithm for SVPWM generation using FPGA and obtains higher sampling rates with minimal use of hardware resources Hence a modified SVPWM algorithm is developed by using intermediate vectors and the transformed mathematical equations, from the conventional SVPWM algorithm. This modified algorithm is then implemented using VHDL, downloaded on XILINX Spartan 2E kit XC3S200E and the waveforms were observed on the oscilloscope.
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A survey on topologies of multilevel inverters
Multilevel inverter technology has emerged recently as a very important alternative in the area of high-power system. They give low harmonics, smaller distortion even at low switching frequencies and has low commutation loss but they suffers from complexity problem requiring large number of power devices and complex control algorithm. This paper presents some important topologies like diode-clamped(neutral -point clamped), capacitor-clamped (flying capacitor), and cascaded multicell inverter with separate dc sources and comparison between these topologies is done on the basis of total loss and estimated cost of each topology .Other emerging topology and modulation schemes are also discussed along with their advantages.
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