Computation offloading is one of the means to reduce delay and save energy in Mobile Edge Computing (MEC). Through reasonable offloading decisions, industrial costs can be greatly reduced. Aiming at the problems of long delay and high energy consumption after the deployment of MEC servers in the industrial production line, a computation offloading strategy based on Particle Swarm Optimization (PSO) was proposed, namely PSAO. First, the actual problem was modeled to a delay model and an energy consumption model. Since it was targeted at delay-sensitive applications, the model was transformed into a delay minimization problem under the constraints of energy consumption, and a penalty function was used to balance delay and energy consumption. Second, according to the PSO, the computation offloading decision vector was obtained, and each computation task was reasonably allocated to the corresponding MEC server through the centralized control method. Finally, through simulation experiments, the delay data of local offloading strategy, MEC baseline offloading strategy, Artificial Fish Swarm Algorithm (AFSA) based offloading strategy and PSAO were compared and analyzed. The average total delay of PSAO was much lower than those of the other three offloading strategies, and PSAO reduces the total cost of the original system by 20%. Experimental results show that the proposed strategy can effectively reduce the delay in MEC and balance the loads of MEC servers.

To solve the problems of insufficient search power and low convergence accuracy in the optimization process of Biogeography-Based Optimization (BBO) algorithm, an Improved Migration Operator BBO (IMO-BBO) algorithm was proposed. On the basis of BBO algorithm and combining with the evolution thinking of “survival of the fittest”, the migration operator was improved by taking migration distance into consideration, and the differential strategy was used to replace individuals unsuitable to migration, so as to increase the local exploration ability of the algorithm. At the same time, the concept of multi-population was introduced to enrich the species diversity. IMO-BBO algorithm was tested on 13 benchmark functions. The results show that compared with the Covariance Matrix based Migration BBO hybrid with Differential Evolution (CMM-DE/BBO) algorithm and the original BBO algorithm, the improved algorithm enhances the search ability for global optimal solutions and simultaneously improves the convergence speed and the accuracy significantly. IMO-BBO was applied to PID parameter tuning, the results show that the controller optimized by this algorithm has faster response speed and more stabile accuracy.

In Video-On-Demand (VOD) applications, it is desired that the encrypted multimedia data are still partially perceptible after encryption in order to stimulate the purchase of the high-quality versions of the multimedia products. This perceptual encryption requires specific algorithms for encrypting the video data. Duo to lack of H.264 video perceptual encryption algorithms for mobile communication application, a video encryption algorithm based on ZU Chongzhi's (ZUC) algorithm and Compressive Sensing (CS) was proposed. First of all, ZUC algorithm was utilized to construct a random measurement matrix. Then the quantified Discrete Cosine Transformation (DCT) coefficients were measured by measurement matrix, and the measured values were regarded as new quantified DCT coefficients to encode, which realized the encryption by using the difference between original and new coefficients. Finally, the characteristics of a good perception encryption algorithm were defined. The experimental results show that the proposed algorithm has little effect on video compression bit rate with low time complexity, and it is also sensitive to key change with good perceptual security.

Handover procedure of modern cellular wireless networks depends on IP-based technology. IETF Proxy Mobile IPv6 (PMIPv6) protocol guarantees the Quality of Service (Qos) in fast handover moving while it does not support realtime communications between two mobile nodes. Therefore Cluster Mobile Node (CMN) algorithm was proposed to reduce handover delay in the system by applied Media Independent Handover (MIH) Technology. Also, the algorithm extended PMIPv6 protocol with an Aggregated Proxy Binding Update (A-PBU) scheme in the paper. Finally, the network model and mobile model were simulated and the effectiveness of handover delay was analyzed. Quantitative results show a significant reduction in handover delay compared with the original handover algorithm.

To remove the noise of optical images while preserving its fine details, the extant object scale was upgraded to the decimal object scale for reflecting the size of local object structure more accurately, and a hybrid image filter which contains two parts was proposed. The first part was an adaptive Gaussian filter based on decimal object scale, the scale of the Gaussian kernel and the mask size of filtering were controlled adaptively by the decimal object scale. The second part was an adaptive median filter based on decimal object scale, and the impulse noise points which were selected adaptively by the decimal object scale were filtered. The weakness of the first part in suppressing the impulse noise was remedied by the second part. Both theory analysis and simulation results show that the presented method can suppress various point-like noise and it is superior to several traditional methods in preserving the fine details and signal to noise ratio.

OLAP is one of important techniques in DSS.The computation of CUBE is the basis of ad hoc query in OLAP.In order to advance the corresponding to querying,we must pre aggregate data in tables or multidimensional databases.Typically,the computation of CUBE consists of materializing strategy,the choice of materialized paths and its optimization and CUBE algorithms.Based on them,this paper analyzes and expatiates concepts,strategies,steps,methods and performances about the computation of CUBE in details.