Ahmad Sharieh

BPAOntoSOA: A generic framework to derive software service oriented models from business process architectures

Service Oriented Architecture (SOA) is becoming the architectural style of choice in many enterprises that adopt the notion of business process architecture. This suggests the need for a systematic and unified approach to generate a service model from a given organizational business process architecture. This paper presents a generic framework called BPAOntoSOA which addresses this requirement. BPAOntoSOA is ontology driven and guided starting from the business process architecture and using the quality of service QoSOnto ontology to ensure the proper alignment of the resultant services with the associated non-functional requirements. It is enriched by an associated domain specific ontology, for example, the healthcare sector. Also, this framework embodies a service identification process that implements an adapted affinity based clustering algorithm to enhance the correctness of mapping business functions to services in the resulting service oriented model.

Solving traveling salesman problem using parallel repetitive nearest neighbor algorithm on OTIS-Hypercube and OTIS-Mesh optoelectronic architectures

Over the past years, researchers drew their attention to propose optoelectronic architectures, including optical transpose interconnection system (OTIS) networks. On the other hand, there are limited attempts devoted to design parallel algorithms for applications that could be mapped on such optoelectronic architectures. Thus, exploiting the attractive features of OTIS networks and investigating their performance in solving combinatorial optimization problems become a great necessity. In this paper, a parallel repetitive nearest neighbor algorithm for solving the symmetric traveling salesman problem on OTIS-Hypercube and OTIS-Mesh optoelectronic architectures is presented. This algorithm has been evaluated analytically and by simulation on both optoelectronic architectures in terms of number of communication steps, parallel run time, speedup, efficiency, cost and communication cost. The simulation results attained almost near-linear speedup and high efficiency among the two selected optoelectronic architectures, where OTIS-Hypercube gained better results in comparison with OTIS-Mesh.

Resource Utilization in Cloud Computing as an Optimization Problem

In this paper, an algorithm for resource utilization problem in cloud computing based on greedy method is presented. A privately-owned cloud that provides services to a huge number of users is assumed. For a given resource, hundreds or thousands of requests accumulate over time to use that resource by different users worldwide via the Internet. A prior knowledge of the requests to use that resource is also assumed. The main concern is to find the best utilization schedule for a given resource in terms of profit obtained by utilizing that resource, and the number of time slices during which the resource will be utilized. The problem is proved to be an NP-Complete problem. A greedy algorithm is proposed and analyzed in terms of its runtime complexity. The proposed solution is based on a combination of the 0/1 Knapsack problem and the activity-selection problem. The algorithm is implemented using Java. Results show good performance with a runtime complexity O((F-S)nLogn)

Translating RAD business process models into BPMN

Modelling business processes using BPMN has been emerging as the preferred choice for organisations seeking to enact their business processes in service-oriented environments. However, a number of organisations have their business processes modelled using Role Activity Diagramming, RAD. In this research, we introduce a new approach to translating RAD business process models to their respective BPMN ones carried out in two stages starting from identifying the corresponding BPMN notation to RAD modelling constructs, and then introducing a new algorithm to translate a given RAD business process model to its suggested corresponding BPMN model demonstrated by an example from the healthcare domain. This translation revealed that all RAD process elements can be mapped to BMPN. However, there still remains space for the business process modeller to enhance the newly generated BPMN model with the extra rich features of BPMN. Finally, this work makes a further contribution to the emerging trend of bridging the gap between business process models and systems in addition to paving the way for the migration of legacy RAD models to BPMN for their enactment in SOA environments.

NMVSA Greedy Solution for Vertex Cover Problem

Minimum vertex cover (MVC) is a well-known NP-Complete optimization problem. The importance of MVC in theory and practical comes from the wide range of its applications. This paper describes a polynomial time greedy algorithm to find near optimal solutions for MVC. The new algorithm NMVAS is a modification of already existed algorithm called MVAS which uses the same principle of selecting candidate from the neighborhood of the vertex with a modification in the selection procedure. A comparative study is conducted between the NMVAS and MVAS which shows that the proposed algorithm NMVSA provides better or equal results in the most cases of the underlying data sets which leads to a better average approximation ratio of NMVAS. NMVAS inherits the simplicity of the original algorithm.

Toward International Multi-sign Languages

An extensive research study was conducted into the trend in educational institutions towards the teaching of sign languages using the Web and the new advances in multimedia computers. A sign language is a visual language and therefore is easier taught by the use of pictures and other multimedia assets. Todays computers allow the average home user to see more than a still picture and a description to explain a word in sign language. Multimedia computers allow the use of audio and video footage to explain the signed word with a spoken as well as written description. The key to expressive and receptive use of sign language and finger spelling is exposure. Sign language classes provide exposure, as do extracurricular activities and required interaction time. Given the time constraints of teaching both a language and interpretation of that language, ways to increase exposure time during the process were looked for. The World Wide Web has become a resource that provides increased exposure to finger spelling and sign language vocabulary. The paper introduces system requirements and design process, as well as a prototypal application for developing an online international multi-sign languages interactive system. The system will provide dictionaries and editors to provide services for multi-international sign languages for objects and their correspondence words and phrases with their finger spelling. This enables several classes of users to use this kind of facility, and enhance the communication abilities between deaf people and those who are not familiar with the sign languages and help them to learn it in a different, interesting way using the computer or the Web.

Parallel heuristic local search algorithm on OTIS hyper hexa-cell and OTIS mesh of trees optoelectronic architectures

Heuristic local search algorithms have achieved good results in tackling combinatorial optimization problems, such as Travelling Salesman Problem (TSP). One of the well-known local search algorithms is the 2-opt algorithm. As a local search algorithm, 2-opt has achieved approximate optimal solutions for TSP within a reasonable time, especially for small data instances. However, solving large data instances of TSP using 2-opt requires extensive computation and considerable CPU time. Therefore, this paper presents a parallel version of the 2-opt algorithm, exploiting the features of Optical Transpose Interconnection System (OTIS) in solving the TSP. In this paper, we present the Parallel Repetitive 2-Opt (PRTO) algorithm for solving symmetric TSP on OTIS Hyper Hexa-Cell (OTIS-HHC) and OTIS Mesh of Trees (OTIS-MOT) optoelectronic architectures. We assess the performance of our algorithm analytically in terms of parallel time complexity, speedup, efficiency, cost, and communication cost on both optoelectronic architectures. Furthermore, a set of simulation experiments is conducted on various instances from the standard TSP library. The simulation results confirm that our algorithm is efficient regarding speedup and efficiency. For instance, the PRTO algorithm achieves a speedup of 32.9 for 6880 cities over OTIS-HHC with 36 processors. Moreover, the superiority of PRTO algorithm is shown through solving the TSP on OTIS-HHC and OTIS-MOT; its performance has been compared with the performance of the Parallel Repetitive Nearest Neighbor (PRNN) algorithm in terms of speedup, efficiency, and solution quality. For example, as a best case, the PRTO algorithm has shown 34 times improved speedup over the PRNN algorithm.

A mathematical model for hybrid-multi-cloud environment

Cloud Computing is a type of internet based service provider, where resources can be shared among users. Transparency is a key issue in CC, where clients are unaware of the source of the service requested. CC services can be in a form of applications, storage, and others. Services provided by different clouds differ in many criteria such as cost and response time. This paper presents a mathematical model for a hybrid-multi-cloud environment, where a set of clouds provide set of services to multiple clients regardless of their platform. The services can be customized and offered to customers according to the predefined criteria and regardless of his/her platform. The model can be used to implement cloud computing environment for better utilization.

A Heuristic Approach for Service Allocation in Cloud Computing

Cloud computing systems are considered complex systems, because of the various classes of services offered for users and the big challenges for providers to meet the increasing demands. Thus, service allocation is a critical issue in cloud computing. Fuzzy modeling is one choice to deal with such complexity. In this paper, the authors introduce a new heuristic service allocation model for cloud computing service allocation. Fuzzy sets are used to determine a candidate cloud for providing a service and crisp sets are used to serve requests from a cloud. Supply and demand are used as the fuzzy input to provide the desired heuristic allocation model for the candidate cloud, and a set of parameters are used to determine a cloud user needs.

A Comparison between Chemical Reaction Optimization and Genetic Algorithms for Max Flow Problem

This paper presents a comparison between the performance of Chemical Reaction Optimization algorithm and Genetic algorithm in solving maximum flow problem with the performance of Ford-Fulkerson algorithm in that. The algorithms have been implemented sequentially using JAVA programming language, and executed to find maximum flow problem using different network size. Ford-Fulkerson algorithm which is based on the idea of finding augmenting path is the most popular algorithm used to find maximum flow value but its time complexity is high. The main aim of this study is to determine which algorithm will give results closer to the Ford-Fulkerson results in less time and with the same degree of accuracy. The results showed that both algorithms can solve Max Flow problem with accuracy results close to Ford Fulkerson results, with a better performance achieved when using the genetic algorithm in term of time and accuracy.