Cloud computing is a highly popular computing paradigm providing on-demand resources with high reliability and availability. The user requests are fulfilled by providing a virtual machine with the requested configuration. However, with the ever-increasing load on the cloud resources, the need for optimal resource utilization of the cloud resources has become the need of the hour. Load balancing has been identified as one of the possible ways to improve resource utilization in the cloud and the current state-of-the-art algorithms indicate the numerous attempts made to find the approximate solution for this NP-hard problem. In this work, we have focused on evaluating the efficiency of the Hungarian algorithm for load distribution in the cloud and compared its performance with First-come-first-serve (FCFS). The simulations were carried out in CloudSim and show remarkable improvement in various performance parameters. Finish time of a given task schedule was reduced by 41% and average execution time was reduced by 13% in the Hungarian algorithm when compared with FCFS.  The simulations were carried out under different workload conditions to validate our results.

QCA is the trending technologies for designing less hardware and low power consumed circuits measured in Nano-scale. These QCA cells are accustomed to construct combinational and sequential circuits. In this paper we presented a design for developing a basic arithmetic unit called full adder using Quantum cellular automata. The new submitted FA consists fewer amounts of quantum cells and delay also minimizes, when compared with the existing architecture.

In this paper, the bit error rate (BER) performance of SFBC-OFDM systems for frequency selective fading channels is observed for various antenna orientations and modulation schemes. The objective is to find out a suitable configuration with minimum number of receiving antenna that requires minimum signal power level at the receiver to provide reliable voice and video communication. We have considered both M-ary phase shift keying (MPSK) and M-ary quadrature amplitude modulation (MQAM) in the performance analysis considering both perfect and imperfect channel state information (CSI). The authors have expressed the BER under imperfect channel estimation condition as a function of BER under perfect channel condition in this paper. The finding shows, for a BTS with 4 transmitting antenna and MS with 2 receiving antenna BPSK performs better for both perfect and imperfect CSI. Maximum permissible channel estimation error increases with the usage of more receiving antenna at the expense of increased cost.

A compact ultra-wideband bandpass filter having highly selectivity and wide bandwidth simultaneously is proposed, which adopts a modified multiple-mode resonator (MMR) and annular structures. The modified MMR is constructed by multiple uniform-impedance stubs and a dumbbell-based stepped-impedance stub. Two transmission zeros are created by the dumbbell-based stepped-impedance stub at the lower and upper cutoff frequencies to improve the selectivity. Additionally, two annular defected ground structures in the aperture ground are adopted to enhance the coupling factor and reduce the etching size. This bandpass filter has a fractional bandwidth of 127% with selectivity of up to 0.939. The measured results are in good agreement with the simulation results.

The prediction of wireless communication signals is of paramount importance for proper network planning. The existing prediction models such as Okumura-Hata, Co-operative for Scientific and Technical Research (COST-231) and free space are less accurate for predicting path-loss values of wireless signals due to differences in propagation environments. Hence, this paper develops a path-loss model using Adaptive Neuro-Fuzzy Inference System (ANFIS) for accurate prediction of wireless High Speed Packet Access (HSPA) network signal in Ibadan, Nigeria. This is achieved by measuring the Received Signal Strength (RSS) from three Base Transmitting Stations (BTS) operating at 2100 MHz frequency in Ojo (longitude E 3’ 53.1060’, latitude N 7’27.2558’), Dugbe (longitude E 3’50.4361’, latitude N 7’ 23.0678’) and Challenge (longitude E 3’ 53.1060’, latitude N 7’ 21.258’) areas of Ibadan using the Drive Test. Ericson Test Equipment for Mobile System (TEMS) phone, Global Positioning System (GPS) and Computer System are used to obtain RSS data at different distances. Base station parameters such as the transmitting antenna height, receiving antenna height, carrier frequency and distance are used as input variables to train ANFIS to develop a model. These base station parameters are also used to investigate the suitability of Okumura-Hata, COST-231 and free space model. A five layer ANFIS structure is developed and trained using Least Square Error (LSE) and Gradient Descent (GD) method to adjust the consequent and premise parameters. The performance of the developed ANFIS model is evaluated using Mean Square Error (MSE) and Root Mean Square Error (RMSE) and compared with Okumura-Hata, COST 231 and free space. The results obtained for ANFIS give lower RMSE and MSE indicating the suitability of ANFIS model for path-loss prediction. The developed ANFIS model can be used for network planning and budgeting in these environments.