Networking data analytics is increasingly used for enhanced network visibility and controllability. We draw the similarities between the Software Defined Networking (SDN) architecture and the MapReduce programming model. Inspired by the similarity, we suggest the necessary data plane innovations to make network data plane devices function as distributed mappers and optionally, reducers. A strea...

This paper describes how to convert a machine learning problem into a series of map-reduce tasks. We study logistic regression algorithm. In logistic regression algorithm, it is assumed that samples are independent and each sample is assigned a probability. Parameters are obtained by maxmizing the product of all sample probabilities. Rapid expansion of training samples brings challenges to mach...

While several approaches have been developed to enhance the efficiency of hierarchical Artificial Intelligence planning (AI-planning), complex problems in AI-planning are challenging overcome. To find a solution plan, planner produces huge search space that may be infinite. A whose small is likely more efficient than large space. In this paper, we will present new approach integrating with map-...

Due to the recent overwhelming growth rate of large-scale data, the development of faster processing algorithms with optimal performance has become a dire need of the time. In this paper, we propose two novel algorithms, ADABOOST.PL (Parallel ADABOOST) and LOGITBOOST.PL (Parallel LOGITBOOST), that facilitate simultaneous participation of multiple computing nodes to construct a boosted classifie...

We’ll start out with a very simple learning algorithm: multinomial Naive Bayes. Our implementation is in Table 1. Each training example is a labeled document d = (i, y, (w1, . . . , wni)) with an identifier i, a label y from a small set Y = {y1, . . . , yK}, and a “bag of words”. The bag of words are wj’s, encoded here as a list of strings, so that wj is the word/token at position j of document...

Map Reduce is used to handle and support massive data sets .rabidly increasing in data size, and big data are imperative today to make an analysis of this data. Map-Reduce gets more helpful information by using two simple functions map and reduce with load balancing, fault tolerance, and high scalability .the most important operation in the analysis process is join. This paper explains new two-...

Volker Weispfenning and his group in Passau have had a long interest in computer algebra. In this talk, REDUCE, one of the algebra programs they use, will be discussed. The development of this program began over forty years ago. We shall discuss the design decisions that have influenced its long-term survival, and the way in which the program has evolved with time.

Codon Optimization helps increasing immuno-stimulatory nucleotide motifs or decreasing immunesuppresive motifs in DNA expression vectors. This enhances the efficiency of DNA vaccinations. In this paper, we investigate the existing Pattern Matching algorithm for Codon Optimization and try to rewrite the algorithm in MapReduce programming model for execution speed-up and faster computation. Keywo...