Query processing optimization in broadcasting XML data in mobile communications

Todays, XML as a de facto standard is used to broadcast data over mobile wireless networks. In these networks, mobile clients send their XML queries over a wireless broadcast channel and recieve their desired XML data from the channel. However, downloading the whole XML data by a mobile device is a challenge since the mobile devices used by clients are small battery powered devices with limited resources. To meet this challenge, the XML data should be indexed in such a way that the desired XML data can be found easily and only such data can be downloaded instead of the whole XML data by the mobile clients. Several indexing methods are proposed to selectively access the XML data over an XML stream. However, the existing indexing methods cause an increase in the size of XML stream by including some extra information over the XML stream. In this paper, a new XML stream structure is proposed to disseminate the XML data over a broadcast channel by grouping and summarizing the structural information of XML nodes. By summarizing such information, the size of XML stream can be reduced and therefore, the latency of retrieving the desired XML data over a wirless broadcast channel can be reduced. The proposed XML stream structure also contains indexes in order to skip from the irrelevant parts over the XML stream. It therefore can reduce the energy consumption of mobile devices in downloading the results of XML queries. In addition, our proposed XML stream structure can process different types of XML queries and experimental results showed that it improves the performace of XML query processing over the XML data stream compared to the existing research works in terms of access and tuning times.

     

An encoding scheme based on fractional number for querying and updating XML data

In order to facilitate the XML query processing, several labeling schemes have been proposed to directly determine the structural relationships between two arbitrary XML nodes without accessing the original XML documents. However, the existing XML labeling schemes have to re-label the pre-existing nodes or re-calculate the label values when a new node is inserted into the XML document during an update process. In this paper, we devise a novel encoding scheme based on the fractional number to encode the labels of the XML nodes. Moreover, we propose a mapping method to convert our proposed fractional number based encoding scheme to bit string based encoding scheme with the intention to minimize the label size and save the storage space. By applying our proposed bit string encoding scheme to the range-based labeling scheme and the prefix labeling scheme, the process of re-labeling the pre-existing nodes can be avoided when nodes are inserted as leaf nodes and sibling nodes without affecting the order of XML nodes. In addition, we propose an algorithm to control the increment of label size when new nodes are inserted frequently at a fix place of an XML tree. Experimental results show that our proposed bit string encoding scheme provides efficient support to the process of XML updating without sacrificing the query performance when it is applied to the range-based labeling schemes.     

A hybrid electromagnetism algorithm for multi-depot periodic vehicle routing problem

Electromagnetism algorithm is a meta-heuristic proposed to derive approximate solutions for computationally hard problems. In the literature, several successful applications have been reported for graph-based optimization problems, such as scheduling problems. This paper presents a novel hybrid electromagnetism algorithm called SA_EM to solve the multi-depot periodic vehicle routing problem (MDPVRP). The main feature of the hybrid algorithm is to hybridize the solution construction mechanism of the electromagnetism (EM) with simulated annealing (SA). Moreover, during implementing the hybrid algorithm, cyclic transfers, an effective class of neighborhood search is applied. The objective consists of two terms as follows: total traveled distance at each depot and total waiting time of all customers to take service. Distances are assumed Euclidean or straight line. These conditions are exactly consistent with the real-world situation and have little attention in the literature. Finally, the experimental results have shown that the proposed hybrid method is competitive to solve the vehicle routing problem compared with the best existing methods in terms of solution quality.     

An efficient stream structure for broadcasting the encrypted XML data in mobile wireless broadcast channels

In mobile wireless broadcast networks, XML data is encrypted before it is sent over the broadcast channel in order to ensure the confidentiality of XML data. In these networks, mobile clients must not have access to all the XML data; rather they should have access to some parts of the XML data that are relevant to them and to which they are authorized to have access. In this paper, a new encrypted XML data stream structure is proposed which supports the confidentiality of XML data over the broadcast channel. In our proposed stream structure, the size of encrypted XML data stream is reduced by grouping the paths, XML nodes, texts, and attributes together. The proposed structure includes several indexes to skip from irrelevant data over the broadcast channel. The experimental results demonstrate that the use of our proposed stream structure efficiently disseminates XML data in mobile wireless broadcast networks in a secure manner and the indexes in our proposed stream structure improve the performance of XML query processing over the encrypted XML data stream.

     

Controller placement in software defined networks using multi-objective antlion algorithm

Software defined network (SDN) is a new modern network technology which decouples control plane and data plane to simplify network management. The separation of control plane from data plane arises the control placement problem (CPP) in these networks. The main questions in the CPP are (1) how many controllers are required to be used in such networks and (2) where these controllers should be placed. To achieve an efficient solution for such problem in SDN, we define the CPP as a multi-objective combinational optimization problem in this paper and solve the CPP by applying the antlion optimization algorithm on it. We consider three metrics for the CPP: (a) Inter-controllers latency, (b) switch to controller latency, and (c) multiple disjoint connectivity paths between switches and controllers. We evaluate our proposed solution by performing several experiments using different real network topologies. Experimental results show that our proposed solution provides better performance compared to the existing solutions.

     

A two-stage hybrid flowshop scheduling problem in machine breakdown condition

This paper considers a two-stage hybrid flowshop scheduling problem in machine breakdown condition. By machine breakdown condition we mean that the machine may not always be available during the scheduling period. Machine failure may occur with a known probability after completing a job. Probability of machine failure depends on the previous processed job. The problem to be studied has one machine at the first stage and M parallel identical machines at the second stage. The objective is to find the optimal job combinations and the optimal job schedule such that the makespan is minimized. The proposed problem is compatible with a large scope of real world situations. To solve the problem, first, we introduce one optimal approach for job precedence when there is one machine in both stages and then provide a heuristic algorithm when there are M machines in stage two. To examine the performance of the heuristic, some experiments used are provided as well.     

Functionalization of SBA-15 by dithiooxamide towards removal of Co (II) ions from real samples: Isotherm,thermodynamic and kinetic studies

In this study, mesoporous SBA-15 was functionalized by dithiooxamide ligand through sodium dodecyl sulfate as intermediate. The obtained nanocomposite was considered as a strong adsorbent towards selective removal of the cobalt (II) ions from the industrial wastewater samples. Transmission Electron Microscopy (TEM) analysis, Brunauer-Emmett-Teller (BET) analysis, elemental CHNS (carbon, hydrogen, nitrogen, and sulfur) analysis, and thermo-gravimetric analysis (TGA) were used for characterization, particle size determination, confirming the presence of the used ligand, and measuring the nanocomposite stability, respectively. Effective parameters on the removal of the cobalt (II) ions such as pH, adsorbent dosage, concentration, and contact time have been evaluated. Results showed that the Freundlich isotherm has a bit better correlation coefficient compared to Langmuir isotherm (0.96 versus 0.94, respectively). The maximum amount of Co (II) ions adsorption on 1 g of nanocomposite (q_m) is calculated to be 2500 mg/g that points to the excellent adsorption. Kinetic analyses were conducted using pseudo-first and second-order models and the regression results showed that the pseudo-second-order model is more accurate for the study of the cobalt adsorption due to the higher correlation coefficient (0.99 versus 0.83) compared to the pseudo-first-order model. The result of the present study points that the suggested nanocomposite can be positively used in treating industrial effluents containing cobalt ions.     

Ant colony optimization technique for the sequence-dependent flowshop scheduling problem

In the real world, production scheduling systems, usually optimal job scheduling, requires an explicit consideration of sequence-dependent setup times. One of the most important scheduling criteria in practical systems is makespan. In this paper, the author presents an ant colony optimization (ACO) algorithm for the sequence-dependent permutation flowshop scheduling problem. The proposed ACO algorithm benefits from a new approach for computing the initial pheromone values and a local search. The proposed algorithm is tested on randomly generated problem instances and results indicate that it is very competitive with the existing best metaheuristics.     

A novel hybrid genetic algorithm to solve the sequence-dependent permutation flow-shop scheduling problem

Flow-shop scheduling problem (FSP) deals with the scheduling of a set of jobs that visit a set of machines in the same order. The FSP is NP-hard, which means that there is no efficient algorithm to reach the optimal solution of the problem. To minimize the make-span of large permutation flow-shop scheduling problems in which there are sequence-dependent setup times on each machine, this paper develops one novel hybrid genetic algorithms (HGA). Proposed HGA apply a modified approach to generate the population of initial chromosomes and also use an improved heuristic called the iterated swap procedure to improve them. Also the author uses three genetic operators to make good new offspring. The results are compared to some recently developed heuristics and computational experimental results show that the proposed HGA performs very competitively with respect to accuracy and efficiency of the solutions.     

A hybrid simulated annealing for the single-machine capacitated lot-sizing and scheduling problem with sequence-dependent setup times and costs and dynamic release of jobs

Single-machine capacitated lot-sizing and scheduling problem (SMCLSP) is one of the most famous fields of research in scheduling area. What makes this problem particularly difficult to solve in many real situations is large and sequence-dependent setups and also multiple criterions that must be considered. In this paper, such a problem is formulated and a hybrid simulated annealing for this problem is presented. Also, lower bounds are obtained from solving the problem relaxation, and they are compared with the optimal solutions to estimate the goodness of them. As decision criteria, all of important costs imposed by the solution are considered and also infeasible sequences are mentioned. There is a ceiling value for the manufacturer's cost of each job and according to it, some sequences between jobs are maybe infeasible. It showed the superiority of hybrid simulated annealing (HSA) compared with one of the efficient recent heuristics. The average deviation of the HSA from the corresponding optimal solution for small-size problems ranges from 0% to 10% and from the corresponding lower bound ranges for large-size problems ranges from 11% to 21%. The presented HSA is capable to solve large instances that are mostly compatible with the real-world problems.