Optimization of data allocation in hierarchical memory for blocked shortest paths algorithms

This paper is devoted to the reduction of data transfer between the main memory and direct mapped cache for blocked shortest paths algorithms (BSPA), which represent data by a D[M×M] matrix of blocks. For large graphs, the cache size S = δ×M2, δ < 1 is smaller than the matrix size. The cache assigns a group of main memory blocks to a single cache block. BSPA performs multiple recalculations of a block over one or two other blocks and may access up to three blocks simultaneously. If the blocks are assigned to the same cache block, conflicts occur among the blocks, which imply active transfer of data between memory levels. The distribution of blocks on groups and the block conflict count strongly depends on the allocation and ordering of the matrix blocks in main memory. To solve the problem of optimal block allocation, the paper introduces a block conflict weighted graph and recognizes two cases of block mapping: non-conflict and minimum-conflict. In first case, it formulates an equitable color-class-size constrained coloring problem on the conflict graph and solves it by developing deterministic and random algorithms. In second case, the paper formulates a problem of weighted defective color-count constrained coloring of the conflict graph and solves it by developing a random algorithm. Experimental results show that the equitable random algorithm provides an upper bound of the cache size that is very close to the lower bound estimated over the size of a complete subgraph, and show that a non-conflict matrix allocation is possible at δ = 0.5 for M = 4 and at δ = 0.1 for M = 20. For a low cache size, the weighted defective algorithm gives the number of remaining conflicts that is up to 8.8 times less than the original BSPA gives. The proposed model and algorithms are applicable to set-associative cache as well.

Game Development of “Prokes” to Socialize the Prevention of Covid-19

The level of awareness of the Indonesian people to orderly and comply with the implementation of health protocols is still very low. Special touch to young people is needed in socializing health protocols and new normal life. Game of “Prokes” is expected as a means for socialization of covid-19 prevention. The proposed method is agile method that is combined using shuffle random algorithm to randomize question in quiz of this game. The blackbox result was 100% functionality of the game has run well. There was a significant difference between user knowledge before and after playing the game of “Prokes” as indicated by t value of 2.297, t table value of 2.004, and the critical value of ? = 0.05. The proposed method had an GEQ result of 3.04. Therefore, the game feasible as a means of socialization in prevention covid-19 using health protocols and new normal for the young generations.

AMatrix factorization technique using parameter tuning of singular value decomposition for Recommender Systems

In this article we explained the concepts of SVD and algorithm evolution. MF technique and the working of it with computational formulas. PCA withstep-by-step approach with example and A novel approach of Hyper SVD and How to fine tune it and pseudocode of the Hyper SVD with the Experimental setup using SurpriseLib and computing RMSE and MSE for the accuracy purpose and solving with the real time example which solves the cold start hassle also together and it can be seen that comparison of SVD and Hyper SVD and Random algorithm is done and types of Movies they recommended. There is far more difference between the results of the both algorithms and movie recommendations as per the results Hyper SVD is flexible and efficient and superior compared to other algorithms.

Scientific workflow scheduling based on data transformation graph for remote sensing application

&lt;p&gt;&lt;strong&gt;Abstract: &lt;/strong&gt;As the amount of data and computation of scientific workflow applications continue to grow, distributed and heterogeneous computing infrastructures such as inter-cloud environments provide this type of application with a great number of computing resources to meet corresponding needs. In the inter-cloud environment, how to effectively map tasks to cloud service providers to meet QoS(quality of service) constraints based on user requirements has become an important research direction. Remote sensing applications need to process terabytes of data each time, however frequent and huge data transmission across the cloud will bring huge performance bottlenecks for execution, and seriously affect the result of QoS constraints such as makespan and cost. Using a data transformation graph(DTG) to study the data transfer process of global drought detection application, the specific optimization strategy is obtained based on the characteristics of application and environment, and according to this, one inter-cloud workflow scheduling method based on genetic algorithm is proposed, under the condition of satisfying the user&amp;#8217;s QoS constraints, the makespan the cost can be minimized. The experimental results show that compared with the standard genetic algorithm, random algorithm, random algorithm, and round-robin algorithm, the optimized genetic algorithm can greatly improve the scheduling performance of data computation-intensive scientific workflows such as remote sensing applications and reduce the impact of performance bottlenecks.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Keywords: &lt;/strong&gt;scientific workflow scheduling; inter-cloud environment; remote sensing application; data transformation graph;&lt;/p&gt;

Multi-task offloading scheme for UAV-enabled fog computing networks

In unmanned aerial vehicle (UAV)-enabled fog computing networks, how to efficiently offload multiple tasks to the computing nodes is a challenging combinatorial optimization problem. In this paper, in order to optimize the total delay for the UAV-enabled fog computing networks, a simple scheduling algorithm and a multi-task offloading scheme based on fireworks algorithm (FWA) are proposed. First, the system model of multiple tasks offloading in UAV-enabled fog computing networks is described in detail. Then, a simple scheduling algorithm is proposed to optimize the delay of the tasks allocated to a single node. Based on the scheduling algorithm, a multi-task offloading scheme for all tasks and all computing nodes is presented. Finally, simulation results show that the performance of a proposed scheduling algorithm and offloading strategy outperforms than that of a genetic algorithm and a random algorithm. This result can provide an effective optimization for multi-task offloading in UAV-enabled fog computing networks.

Game Development of “Kwace Adat Bali” for The Socialization of Balinese Traditional Dress-Up Ethics

Many young people have begun to violate the ethics of Balinese traditional dress up by using strict lacy blouse (kebaya), high split sarong (kamen), men sarong (kamen) that not taper on the tip and excessive accessories. Game of “Kwace Adat Bali” is expected as a means of socialization in Balinese traditional dress-up ethics appropriately. In this game, the Balinese traditional dress-up style is classified into three types, namely light traditional clothing (payas alit), middle traditional clothing (payas madya), and great traditional clothing (payas agung). The proposed method is Design Game Based-Learning Instructional Design (DGBL-ID) which is combined with a shuffle random algorithm to shuffle game items. The Game of “Kwace Adat Bali” has tested using alpha testing, beta testing, t-test, and game engagement questionnaire (GEQ). The alpha testing result was 100% game functionality has run suitable for the design. Beta testing shows that overall this game got a value of 77% from 65 respondents. There was a significant difference between user knowledge before and after playing the game of “Kwace Adat Bali” as indicated by t table value of 1.997, t value of 6.5, and the critical value of α = 0.05. The proposed method had an engagement rate of 8.7% higher than just using the DGBL-ID method in developing the game. Therefore, it can be concluded that the game feasible is considered as a new means of socialization in Balinese traditional dress up ethics for the younger generation.

A Parallel Mix Self-Adaptive Genetic Algorithm for Solving the Dynamic Economic Dispatch Problem

The purpose of this paper is to propose a parallel genetic algorithm that has adaptive and self-adaptive characteristics at the same time for solving the Dynamic Economic Dispatch (DED) problem that is a challenging problem to solve. The algorithm selects the proper operators (using adaptive features) and probabilities (using the self-adaptive code) that produce the most fittable individuals. Regarding operations, the choice is made between four different types of crossover: simple, arithmetical, non-uniform arithmetical, and linear. Concerning mutation, we used four types of mutations (uniform, non-uniform, creep, and enhanced apso). The choice is made scholastically, which is uniform at the beginning of the algorithm, being adapted as the AG executes. The crossover and mutation probabilities are coded into the genes, transforming this part of the algorithm into self-adaptive. The multicore version was coded using OpenMP. An ANOVA test, along with a Tukey test, proved that the mixed self-adaptive algorithm works better than both: a random algorithm, which chooses operators randomly, and a combination of operators set previously in the DED optimization. Regarding the performance of the parallel approach, results have shown that a speedup of up to 3.19 can be reached with no loss in the quality of solutions.

Visualization of the Chaos Game for non-hyperbolic iterated function system

The chaos game is a random algorithm generally applied to contracting (hyperbolic) iterated function system (IFS) which makes it possible to obtain the unique attractor of the dynamic system. However, when applied to non-contractive IFS extremely interesting results can be obtained that are not only important from a theoretical and application point of view, but can also be part of a mathematical didactics that seeks to modernize teaching. In this sense, this research present some results related to the application of the chaos game to non-contracting IFS are presented.