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With the use of computers in every field, the usage intensity of processors is increasing day by day. In order to cope with this intensity, processors need to be constantly updated and improved. Various scheduling algorithms are being developed every day in order to continuously improve and accelerate the processors and to cope with the processing intensity. The main purpose of the scheduling algorithms is to increase the efficiency of the processor. For this, the processor needs to make a planning between the pending processes. Planning can be done by giving different priorities or using different methods. In order to increase the efficiency of the processor, in this paper, existing algorithms were examined. Round Robin Algorithm was improved using Genetic Algorithm. It is aimed to find the optimum values by selecting the quantum value according to the pending processes and their parameters. When the developed new method compared with the existing standard algorithms, it is observed that the waiting time and the turnaround time were shorter than the other algorithms. [ABSTRACT FROM AUTHOR]

Wireless Personal Area Networks (WPANs) are computer networks used for data transmission among devices such as computers, telephones and industrial devices. These networks are operated in short ranges using low data rates and low-power radio signals. IEEE 802.15.4 protocol is a common standard used in these networks. Each packet is spitted into symbols including four data bits, and each of these symbols translated to thirty two bits Pseudo Noise(PN) chip sequences in physical layer of IEEE 802.15.4 protocol. In this paper, it is aimed to find the best data chip sequences to obtain maximum data transfer in a time unit for different wireless channel types for IEEE 802.15.4 protocol. To accomplish this, an adaptive data sequence generator mechanism is proposed. Performance analyses of IEEE 802.15.4 protocol with traditional and proposed PN sequences are made. The proposed method increased the packet transmission success by adjusting the length of chip sequences. These sequences considerably increase data throughput compared to standard IEEE 802.15.4 sequences. The success of the proposal is illustrated in tables and graphs showing comparative performance results. [ABSTRACT FROM AUTHOR]

Differential Evolution (DE) algorithm is a new heuristic approach mainly having three advantages; finding the true global minimum regardless of the initial parameter values, fast convergence, and using few control parameters. DE algorithm is a population based algorithm like genetic algorithms using similar operators; crossover, mutation and selection. In this work, we have compared the performance of DE algorithm to that of some other well known versions of genetic algorithms: PGA, Grefensstette, Eshelman. In simulation studies, De Jong's test functions have been used. From the simulation results, it was observed that the convergence speed of DE is significantly better than genetic algorithms. Therefore, DE algorithm seems to be a promising approach for engineering optimization problems. [ABSTRACT FROM AUTHOR]