No abstract

In this paper, we seek to address the data gathering in the continually growing Wireless Sensor Networks (WSNs) with the intention to save the nodes' energy. In order to address usual WSN problems, such as data losses, collisions and re-transmissions, a twofold data compression pattern is proposed. We consider that a restricted number of sensor nodes are selected to be active and represent the whole network, while the rest of nodes remain idle and do not participate at all in the data sensing and transmission. Furthermore, the set of active nodes' readings is efficiently reduced, in each time slot, according to the cluster scheduling. Relying on the existing Matrix Completion (MC) techniques, the sink node is unable to recover the entire data matrix due to the existence of completely empty rows that correspond to the inactive nodes, which can be considered as absent nodes for a very long period, or nodes that do not exist at all. Thereby, we propose a complementary interpolation technique, based on a minimization problem that benefits from sensor nodes inter-correlation, to guarantee the reconstruction of all the empty rows, despite their large number. The simulations confirm the efficiency of the proposed approach and show that it outperforms the existing one by up to 70.101% of Normalized Mean Absolute Error on all missed elements, when the number of active nodes is of about 10% of the total number of sensor nodes.

In order to reach higher coding efficiency compared to its predecessor, a state-of-the-art video compression standard, the High Efficiency Video Coding (HEVC), has been designed to rely on many improved coding tools and sophisticated techniques. The new features are achieving significant coding efficiency but at the cost of huge implementation complexity. This complexity has increased the HEVC encoders' need for fast algorithms and hardware friendly implementations. In fact, encoders have to perform the different encoding decisions, overcoming the real-time encoding constraint while taking care of coding efficiency. In this sense, in order to reduce the encoding complexity, HEVC encoders rely on look-ahead mechanisms and pre-processing solutions. In this context, we propose a gradient-based pre-processing stage. We investigate particularly the Prewitt operator used to generate the gradient and we propose necessary approaches that enhance the gradient performance of detecting the HEVC intra modes. We also set different probability scenarios, based on the gradient information, in order to speed up the mode search process. Moreover, we propose a gradient-based estimation of the texture complexity that we use for coding unit decision. Results show that the proposed algorithm achieves a reduction of 42.8% in encoding time with an increase in BD rate of only 1.1%.