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Hamid Saadatfar, Hossein Deldari: A job submission manager for large-scale distributed systems based on job futurity predictor. IJGUC 5(1): 50-59 (2014)

Nowadays by improving the richness of prediction methods and accessing to the more information about systems behavior, the role of proactive strategies in developing more reliable and efficient systems becomes more crucial. However, the goals of prediction and the way that the results can be employed to upgrade the system are still topics which draw recent researchers' attention. In this work, we attempt to decrease Jobs wait time and failure rate by using the results of a job futurity predictor. For achieving this goal, a system component called JSM is proposed. JSM consults the predictor and employs a game theory based model in order to probably rejecting the jobs which are likely to fail. Furthermore, for avoiding from rejecting safety jobs mistakenly, JSM intelligently adopts its decisions with the systems situations. Experimental results state a significant reduction in jobs wait time and failure rate in comparison with other related work.

Abdorreza Savadi, Hossein Deldari: Measurement of the latency parameters of the Multi-BSP model: a multicore benchmarking approach. The Journal of Supercomputing 67(2): 565-584 (2014)

Computer benchmarking is a common method for measuring the parameters of a computational model. It helps to measure the parameters of any computer. With the emergence of multicore computers, the evaluation of computers was brought under consideration. Since these types of computers can be viewed and considered as parallel computers, the evaluation methods for parallel computers may be appropriate for multicore computers. However, because multicore architectures seriously focus on cache hierarchy, there is a need for new and different benchmarks to evaluate them correctly.
To this end, this paper presents a method for measuring the parameters of one of the most famous multicore computational models, namely Multi-Bulk Synchronous Parallel (Multi-BSP). This method measures the hardware latency parameters of multicore computers, namely communication latency (gi ) and synchronization latency (Li ) for all levels of the cache memory hierarchy in a bottom-up manner. By determining the parameters, the performance of algorithms on multicore architectures can be evaluated as a sequence.

Toktam Ghafarian-M., Hossein Deldari, Bahman Javadi, Mohammad H. Yaghmaee, Rajkumar Buyya: CycloidGrid: A proximity-aware P2P-based resource discovery architecture in volunteer computing systems. Future Generation Comp. Syst. 29(6): 1583-1595 (2013)

Volunteer computing which benefits from idle cycles of volunteer resources over the Internet can integrate the power of hundreds to thousands of resources to achieve high computing power. In such an environment the resources are heterogeneous in terms of CPU speed, RAM, disk capacity, and network bandwidth. So finding a suitable resource to run a particular job becomes difficult. Resource discovery architecture is a key factor for overall performance of peer-to-peer based volunteer computing systems. The main contribution of this paper is to develop a proximity-aware resource discovery architecture for peer-to-peer based volunteer computing systems. The proposed resource discovery algorithm consists of two stages. In the first stage, it selects resources based on the requested quality of service and current load of peers. In the second stage, a resource with higher priority to communication delay is selected among the discovered resources. Communication delay between two peers is computed by a network model based on queuing theory, taking into account the background traffic of the Internet. Simulation results show that the proposed resource discovery algorithm improves the response time of user's requests by a factor of 4.04 under a moderate load.

Hamid Saadatfar, Hossein Deldari: A study on combinational effects of job and resource characteristics on energy consumption. Multiagent and Grid Systems 9(4): 301-314 (2013)

By becoming more popular and complex, HPC systems like computational grids, clusters, clouds and the supporting data centers are now changed to remarkable energy consumers. A wide variety of researches, ranging from power-aware hardware design to developing optimized programs and to power-aware job scheduling, have been done hitherto in order to reduce their energy consumption. However, the success of these approaches highly depends to having a precise knowledge about power consumption behavior of the target system. In this paper, some neglected facts are shown about combinational effects of jobs' and resources' characteristics on energy consumption rate and define corresponding parameters which make these facts practically utilizable by formulating them as functions of job-machine characteristics. These facts are supported by the experimental analyses on real machines and analytical studies. The outcome of this paper can be exploited to have more energy efficient task mapping process in large-scale heterogeneous computational systems.

Toktam Ghafarian-M., Hossein Deldari, Bahman Javadi, Rajkumar Buyya: A proximity-aware load balancing in peer-to-peer-based volunteer computing systems. The Journal of Supercomputing 65(2): 797-822 (2013)

One of the main challenges in peer-to-peer-based volunteer computing systems is an efficient resource discovery algorithm. Load balancing is a part of resource discovery algorithm and aims to minimize the overall response time of the system. This paper introduces an analytical model based on distributed parallel queues to optimize the average response time of the system in a distributed manner. The proposed resource discovery algorithm consists of two phases. In the first phase, it selects peers in a load-balanced manner based on QoS constraints of request. In the second phase, a proximity-aware feature is applied to select the peer with minimum communication overhead among selected peers in the first phase. Two dispatching strategies are proposed for the load balancing based on stochastic analysis of routing in the distributed parallel queues. These policies adopt probabilistic and deterministic sequences to redirect requests to the capable peers in the system. Simulation results show that the proposed resource discovery algorithm improves the response time of user's requests by a factor of 1.8 under a moderate load.

Hamid Saadatfar, Hamid Fadishei, Hossein Deldari: Predicting Job Failures in AuverGrid Based on Workload Log Analysis. New Generation Comput. 30(1): 73-94 (2012)

Grid systems are popular today due to their ability to solve large problems in business and science. Job failures which are inherent in any computational environment are more common in grids due to their dynamic and complex nature. Furthermore, traditional methods for job failure recovery have proven costly and thus a need to shift toward proactive and predictive management strategies is necessary in such systems. In this paper, an innovative effort has been made to predict the futurity of jobs in a production grid environment. First of all, we investigated the relationship between workload characteristics and job failures by analyzing workload traces of AuverGrid which is a part of EGEE (Enabling Grids for E-science) project. After the recognition of failure patterns, the success or failure status of jobs during 6 months of AuverGrid activity was predicted with approximately 96% accuracy. The quality of services on the grid can be improved by integrating the result of this work into management services like scheduling and monitoring.

Abdorreza Savadi, Morteza Moradi, Hossein Deldari: Multi-DaC programming model: a variant of multi-BSP model for divide-and-conquer algorithms. DAMP 2012: 41-46

Nowadays, the evolution of multi-core architectures goes towards increasing the number of cores and levels of cache. Meanwhile, current typical parallel programming models are unable to exploit the potential of these processors efficiently. In order to achieve desired performance on these hardwares we need to understand architectural parameters appropriately and also apply them in algorithm design. Computational models such as Multi-BSP, illustrate these parameters and explain adequate methods for designing algorithms on multi-cores. One of the most applicable categories of problems is Divide-and-Conquer (DaC) that needs to be adapted by such model for implementing on these systems.
In this paper, we have attempted to make a mapping between DaC tree and the Memory Hierarchy (MH) of multi-core processor. Multi-BSP model inspired us to introduce Multi-DaC programming model. Analogous to Multi-BSP analysis, lower bounds for communication and synchronization costs have been presented in the paper respecting DaC algorithms. This work is a step towards making multi-core programming easy and tries to obtain correct analysis of DaC algorithm behavior on multi-core architectures.

Toktam Ghafarian-M., Hossein Deldari, H. Mohhamad, Mohhamad-H. Yaghmaee-M.: Proximity-Aware Resource Discovery Architecture in Peer-to-Peer Based Volunteer Computing System. CIT 2011: 83-90

Volunteer computing which benefit from idle cycles of desktop PCs over the Internet can integrate power of hundreds to thousands desktop systems to achieve high computing power. Centralized volunteer computing system has dedicated servers to maintain information about the resources. However, in the decentralized system resource information is distributed in the system. Resource discovery architecture is a key factor for peer-to-peer based volunteer computing system. Usually, there is a complex relationship between the distribution of resource information and performance of a system. The main contribution of this paper is to develop a proximity-aware resource discovery architecture for peer-to-peer based volunteer computing system. This architecture has simplicity of a centralized system and can achieve close performance compared to this system, and it is scalable. Furthermore, proposed architecture distributes jobs among the resources fairly. Two resource discovery algorithm with and without proximity-aware feature are compared. The proximity-aware resource discovery algorithm can gain a better result.

Mahboobeh Houshmand, Elaheh Soleymanpour, Hossein Salami, Mahya Amerian, Hossein Deldari: Efficient Scheduling of Task Graphs to Multiprocessors Using a Combination of Modified Simulated Annealing and List Based Scheduling. IITSI 2010: 350-354

Multiprocessor task scheduling is a well known NP-hard problem and numerous methods have been proposed to optimally solve it. The objective is makespan minimization, i.e. we want the last task to complete as early as possible. Simulated Annealing (SA) has been considered a very good tool for complex nonlinear optimization problem, such as multiprocessor task scheduling. However, a major disadvantage of the technique is that it is extremely slow. List-based scheduling algorithms are regarded as having acceptable results. In this paper we use a list scheduling based algorithm to find an initial solution and in the neighborhood generation phase of simulated annealing. We also parameterize SA and use a modified version of it. Simulation results show that our approach significantly improves the initial solution in considerably low time for different number of tasks; i.e. it efficiently outperforms the used list based scheduling approach.

Golnar Gharooni-fard, Fahime Moein-darbari, Hossein Deldari, Anahita Morvaridi: Scheduling of scientific workflows using a chaos-genetic algorithm. ICCS 2010: 1445-1454

The main idea of developing Grid is to make effective use of the computation power distributed all over the world. Economical issues are the most vital motivations of resource owners to share their services. This means that users are required to pay for access to services based on their usage and level of QoS they need. Therefore total cost of executing an application is becoming one of the most important parameters in evaluating QoS, which users tend to decrease.
Since, many applications are described in the form of dependent tasks, scheduling of these workflows has become a major challenge in grid environment. In this paper, a novel genetic algorithm called chaos-genetic algorithm is used to solve the scheduling problem considering both user's budget and deadline. Due to the nature of chaotic variables such as pseudo-randomness, ergodicity and irregularity, the evolutional process of chaos-genetic algorithm makes individuals of subgenerations distribute ergodically in the defined space and circumvents the premature of the individuals of traditional genetic algorithms (TGA). The results of applying chaos-genetic scheduling algorithm (CGS) showed greater performances of CGS compared to traditional genetic algorithm (TGS) on both balanced and unbalanced workflows.

Mohsen Amini Salehi, Hossein Deldari, Bahare Mokarram Dorri: Balancing Load in a Computational Grid Applying Adaptive, Intelligent Colonies of Ants. Informatica (Slovenia) 33(2): 151-159 (2009)

Load balancing is substantial when developing parallel and distributed computing applications. The emergence of computational grids extends the necessity of this problem. Ant colony is a meta-heuristic method that can be instrumental for grid load balancing. This paper presents an echo system of adaptive fuzzy ants. The ants in this environment can create new ones and may also commit suicide depending on existing conditions. A new concept called Ant level load balancing is presented here for improving the performance of the mechanism. A performance evaluation model is also derived. Then theoretical analyses, which are supported with experiment results, prove that this new mechanism surpasses its predecessor.

Leila Khatibzadeh, Hossein Deldari: An Agent-based Service Discovery Algorithm Using Agent Directors for Grid Computing. GCA 2008: 68-73

Jalal A. Nasiri, M. Amir Moulavi, Sepideh Nazemi Gelyan, Hossein Deldari, Hadi Sadoghi Yazdi, A. Eshghi Shargh: An Efficient Parallel Eye Detection Algorithm on Facial Color Images. SNPD 2008: 706-711

As processing power becomes cheaper and more available by using cluster of computers, the need for parallel algorithms which can harness this computing potentials is increasing. Eye detection is an application of parallel algorithms. Detecting eyes in images plays an important role in many applications such as face detection/recognition. In addition, its widespread usage as a part of series applications made it a nontrivial task which should be worked on. Moreover, existing algorithms are usually much time-consuming. In this paper we have proposed a parallel algorithm in EREW PRAM model for eye detection in colorimages. Using color characteristics is a useful way to detect eyes. We use special color space, YCbCr which itscomponents give us worthwhile information about eyes. Wemake two maps in parallel according to their componentsand merge them to obtain a final map. The proposed algorithmhas been examined with MPI and its implementation results on CVL and Iranian databases showed that parallel approach reduces the time of detection efficiently. Exploiting p processors has reduced the time of detection to (n/p)+c which c is the communication overhead between the processors and n is the number of pixels of a particular image.

Moein Shakeri, Hossein Deldari, Homa Foroughi, Fuzzy Traffic Light Control Using Cellular Automata , Ubiquitous Computing And Communication Journal, Volume 3. No. 3, ISSN 1994-4608, 2008.

Moein Shakeri, Arash Deldari, Hossein Deldari, Ghamarnaz Tadayon, Three Leveled Fuzzy System for Traffic Light and Urban Traffic Control Based on Cellular Automata , IEEE International Joint Conferences on Computer, Information, and Systems Sciences, and Engineering,University of Bridgeport, USA, 5-13 Dec, 2008.

Moein Shakeri, Hossein Deldari, A Novel Fuzzy Method to Traffic Light Control Based on Unidirectional Selective Cellular Automata for Urban Traffic , 11th IEEE International Conference on Computer and Information Technology (ICCIT2008), Faculty of Electrical & Electronic Engineering, Khulna University of Engineering & Technology (KUET), Khulna - 9203, Bangladesh,25-27 Dec. 2008.

Moein Shakeri, Hossein Deldari, Homa Foroughi, A Novel Fuzzy Background Subtraction Method Based on Cellular Automata for Urban Traffic Applications , 9th IEEE International Conference on Signal Processing (ICSP'08),Beijing Jiaotong University (Northern Jiaotong University),Beijing, China,Oct.26-29, 2008.

Computational structure of cellular automata has attracted researchers and vastly been used in various fields of science. They are especially suitable for modeling natural systems that can be described as massive collections of simple objects interacting locally with each other, such as motion detection in image processing. On the other hand, extraction of moving objects from an image sequence is a fundamental problem in dynamic image analysis Nowadays background modeling and subtraction algorithms are commonly used in real-time urban traffic applications for detecting and tracking vehicles and monitoring streets. In this paper by the use of cellular automata, a novel fuzzy approach for background subtraction with a particular interest to the problem of vehicle detection is presented. Our experimental results demonstrate that fuzzy-cellular system is much more efficient, robust and accurate than classical approaches.

Moein Shakeri, Hossein Deldari, Homa Foroughi, Alireza Rezvanian, Parallel Sorting On Linear Cellular Automata, Proceedings of the International Conference on Parallel and Distributed Processing Techniques and Applications, PDPTA 2008, Las Vegas, Nevada, USA, July 14-17, 2008, CSREA Press 2008.

Sorting is one of the fundamental problems in computer science and being used vastly in various domains. So different serial and parallel approaches have been proposed. One of the parallel sorting methods are algorithms that are based on computational model of cellular automata. A cellular automata machine is a structure of interconnected elementary automata evolving in a parallel and synchronous way .The most famous sorting algorithm for one dimensional cellular automata machine is Gordillo and Luna’s. This algorithm sorts n numbers in 2n-3 steps. In this paper three new sorting algorithms are proposed. In the two first proposed algorithms, despite using smaller neighborhood radius, sorting steps have not been changed and in the third algorithm sorting steps are reduced by regarding same neighborhood radius as Gordillo- Luna’s second algorithms.

Hossein Deldari, Mojtaba Sabeghi, Roohollah Mafi, An Agent-based Approach to Grid Programming, Kuwait Journal of Science and Engineering, Vol. 34 No.2, December 2007, ISSN 1024-8684.

Computational Grids have provided the usage of computational distributed resources for computation-intensive applications. The developement of programs, the brain, that use these capbilities, the brwan, is one of the challenging issues for grid computing. In this paper, an effort has been made in order to tackle tis problem by applying a mobile agent-based programiing model on the grid. This model called Alchemi+ has been materialized by extending Alchemi TM grid infrastructure and adding agent properties and navigational commands. Alchemi+ will let the user develop his parallel progrm using agents' mobility and communication between them. In order to evaluate the system, a matrix multiplication algorithm as well as an algorithm for finding convex hull of a series of points have been implemented in the mentioned system.

Saeed Abrishami, Hossein Deldari, HPF-G: A High-Level Programming Environment in Grid, 3rd Conference on Information and Knowledge Technology (IKT'07), Ferdowsi University of Mashhad, Iran, November 2007.

Hossein Deldari, Rasoul Taghipour, An Optimal Leader Selection Algorithm for Trust Management in Grid Computing Environment, 3rd Conference on Information and Knowledge Technology (IKT'07), Ferdowsi University of Mashhad, Iran, November 2007.

Hamed Vadat-Nejad, Reza Monsefi, Hossein Deldari, Distributed Resource Scheduling in Grid Computing using Fuzzy Approach, 3rd Conference on Information and Knowledge Technology (IKT'07), Ferdowsi University of Mashhad, Iran, November 2007.

Alireza Salehan, Hossein Deldari, An Optimal Location Transparency Model in Distributed Systems, 10th Iranian Student Conference on Electrical Engineering (ISCEE), Isfahan University of TEchnology, Iran, September 4-6, 2007.

Amin Milani Fard, Arash Deldari, Hossein Deldari, Quick Grammar Type Recognition: Concepts and Techniques, International conference on Compilers, Related Technologies and Applications (CoRTA'2007), The University of Beira Interior Publication, pp. 51-61, July 6th, 2007, Covilha, Portugal.

This paper intends to give an overview to grammar classification in terms of language specification and parsing methods; an important and always fashionable topic in computer science, compilers and language processing area. It is known that when a conflict happens in constructing the parsing table, the grammar is not acceptable by that parsing method, however we are interested in quick ways to determine a given grammar type. Although so many papers and books have been published containing useful information about this matter, none of them covers all the recognition aspects of grammars especially quick methods. We finalized the work with our quick grammar recognizer algorithm to detect grammar type.

Mohsen Amini Salehi, Hossain Deldari, Bahare Mokarram Dorri, MLBLM: A Multi-level Load Balancing Mechanism in Agent-based Grid, 8th International Conference on Distributed Computing and Networking, (ICDCN 2006), the Indian Institute of Technology Guwahati, India, December 27-30, 2006, also published in LNCS 4308, pp. 157 – 162, 2006.

A computational grid is a widespread computing environment that provides huge computational power for large-scale distributed applications. Load balancing, has a considerable effect on the grid middleware performance. Current load balancing methods cannot satisfy all necessities for the grid. In this paper, a Multi-level Load Balancing Method (MLBM) is proposed. Cooperation among different levels in this method, removes disadvantages of each level, while satisfy most of load balancing requirements needed. Simulation results indicate that this new mechanism surpasses its predecessors in increasing efficiency and decreasing communication overhead.

Vahid Salmani, Mahmoud Naghibzadeh, Amirali Habibi, Hossein Deldari, Quantitative Comparison of Job-level Dynamic Scheduling Policies in Parallel Real-time Systems, In Proceedings of IEEE TENCON 2006, Hong Kong, November 2006.

Scheduling algorithms play an important role in design of real-time systems. Due to high processing power and low price of multiprocessors, real-time scheduling in such systems is more interesting; however, more complicated. Earliest Deadline First (EDF) and Least Laxity First (LLF) are two well-known and extensively applied dynamic scheduling algorithms on which many researches have already been done. However, to the best of our knowledge, the efficiency of aforementioned algorithms has not been compared under similar conditions. Perhaps the main reason is that LLF algorithm is fully dynamic and impractical to implement. In this research, we have used a job-level dynamic and practical version of LLF which is called Modified Least Laxity First (MLLF) algorithm instead of the traditional LLF and have compared its performance with EDF algorithm from many different aspects. The success ratio has been chosen as the key factor for evaluation of the algorithms.

Hamed Vahdat Nejad, and Hossein Deldari, A Parallel Quadtree Approach for Image Compression using Wavelets, Enformatika Transactions on Engineering, Computing and Technology, Vol. 14, August 2006, ISSN 1305-5313, Pages 396-399.

Wavelet transforms are multiresolution decompositions that can be used to analyze signals and images. Image compression is one of major applications of wavelet transforms in image processing. It is considered as one of the most powerful methods that provides a high compression ratio. However, its implementation is very time-consuming. At the other hand, parallel computing technologies are an efficient method for image compression using wavelets. In this paper, we propose a parallel wavelet compression algorithm based on quadtrees. We implement the algorithm using MatlabMPI (a parallel, message passing version of Matlab), and compute its isoefficiency function, and show that it is scalable. Our experimental results confirm the efficiency of the algorithm also.

Ebrahim Bagheri, Hossein Deldari, Dejong Function Optimization by Means of a Parallel Approach to Fuzzified Genetic Algorithm, IEEE Symposium on Computers and Communications (ISCC'06), June 26-29, Pula-Cagliari, Sardinia, Italy, Pages 675-680.

Genetic Algorithms are very powerful search methods that are used in different optimization problems. Parallel versions of genetic algorithms are easily implemented and usually increase algorithm performance. Fuzzy control as another optimization solution along with genetic algorithms can significantly increase algorithm performance. Two variations for genetic algorithm and fuzzy system composition exist. In the first approach Genetic algorithms are used to optimize and model the structure of fuzzy systems through knowledge base or membership function design while the second approach exploits fuzzy to dynamically supervise genetic algorithm performance by speedily reaching an optimal solution. In this paper we propose a new method for fuzzy parallel genetic algorithms, in which a parallel client-server single population fuzzy genetic algorithm is configured to optimize the performance of the first three Dejong functions in order to reach a global solution in the least possible iterations. Simulations show much improvement in genetic algorithm performance evaluation.

Mohsen Amini Salehi, Hossain Deldari, A Novel Load Balancing Method in an Agent-based Grid, IEEE International Conference on Computing and Informatics (ICOCI 2006), June 6-8, 2006, Kuala Lumpur, Malaysia.

A computational grid is a widespread computing environment which provides huge computational power for large-scale distributed applications. One of the most important issues in such an environment is resource management. Load balancing which is a part of resource manager, has a considerable effect on resources’ performance. There are several factors which affect the stability of the load balancing in the grid. Among these factors, accurate criterion for estimating the workload, considering the workload transmission cost, validity of the information about other nodes and the overhead imposed by the method are more effective. In this paper we propose a novel method for load balancing which tries to satisfy these factors. The proposed method is implemented on an agent-based resource management system, called ARMS. There are several simulations which indicate that the proposed method outperforms than similar methods.

Mohsen Amini Salehi, Hossain Deldari, Grid Load Balancing using an Echo System of Intelligent Ants, In Proceedings of the IASTED International Conference on Parallel and distributed Computing and Networks, Pages 47-52, Feruary 2006, Innsbruck, Austria.

A computational grid is a widespread computing environment that provides huge computational power for large-scale distributed applications. One of the most important issues in such an environment is resource management for which agent-based approaches are appropriate. Load balancing as a part of resource management, has a considerable effect on performance. Ant colony is a metaheuristic that can be instrumental for grid load balancing. This paper presents an echo system of intelligent, autonomous and cooperative ants. The ants in this environment can procreate and also may commit suicide depending on existing conditions. A new concept called Ant level load balancing is presented for improving the performance of the mechanism. A performance evaluation model is derived. Theoretical analyses and simulation results indicate that this new mechanism surpasses its predecessor.

Mojtaba Sabeghi, Hossein Deldari, Vahid Salmani, Malihe Bahekmat, Toktam Taghavi, A Fuzzy Algorithm for Real-Time Scheduling of Soft Periodic Tasks on Multiprocessor Systems, In Proceedings of IADIS International Conference on Applied Computing, February 25-28, 2006, San Sebastian, Spain, Pages 467-471.

Many scheduling algorithms have been studied to guarantee the time constraints of real-time processes. Scheduling decision of these algorithms is usually based on parameters which are assumed to be crisp. However, in many circumstances the values of these parameters are vague. The vagueness of parameters suggests that we make use of fuzzy logic to decide in what order the requests should be executed to better utilize the system and as a result reduce the chance of a request being missed. Our main contribution is proposing a fuzzy approach to multiprocessor real-time scheduling in which the scheduling parameters are treated as fuzzy variables. A simulation is also performed and the results are judged against each other. It is concluded that the proposed fuzzy approach is very promising and it has the potential to be considered for future research.

M. Sabeghi, H. Deldari, and S. Khajouei, A Fuzzy Algorithm for Scheduling Periodic Tasks on Multiprocessor Soft Real-Time Systems, International Journal of Computer Science and Network Security, Pages 88-97, March 30, 2006. Also appeared in the Proceedings of the 17th IASTED International Conference Modeling And Simulation Pages 436-442, May 2006 , Montreal, QC. Canada.

In this paper we consider the use of fuzzy logic in the scheduling of periodic tasks in soft real-time multiprocessor systems. Most researches concerning real-time system scheduling assumes scheduling constraint to be precise. However, in many circumstances the values of these parameters are vague. The vagueness of parameters suggests that we make use of fuzzy logic to decide in what order the requests should be executed to better utilize the system and as a result reduce the chance of a request being missed. Our main contribution is proposing a fuzzy approach to multiprocessor real-time scheduling in which the scheduling parameters are treated as fuzzy variables. A simulation is also performed and the results are judged against each other. It is concluded that the proposed fuzzy approach is very promising and it has the potential to be considered for future research.

Ebrahim Bagheri, Hossein Deldari, Fuzzy Genetic Algorithm Parallelization for Dejong Function Optimization, International Journal of Pure and Applied Mathematics, 2006, vol.26 no. 3, Pages 321-334.

Genetic Algorithms are very powerful search methods that are used in different optimization problems. Parallel versions of genetic algorithms are easily implemented and usually increase algorithm performance. Fuzzy control as another optimization solution along with genetic algorithms can significantly increase algorithm performance. Two variations for genetic algorithm and fuzzy system composition exist. In the first approach Genetic algorithms are used to optimize and model the structure of fuzzy systems through knowledge base or membership function design while the second approach exploits fuzzy to dynamically supervise genetic algorithm performance by speedily reaching an optimal solution. In this paper we propose a new method for fuzzy parallel genetic algorithms, in which a parallel client-server single population fuzzy genetic algorithm is configured to optimize the performance of the first three Dejong functions in order to reach a global solution in the least possible iterations. Simulations show much improvement in genetic algorithm performance evaluation.

Ebrahim Bagheri, Hossein Deldari, Designing a Fuzzy Parallel Genetic Algorithm, 10th International Annual Computer Conference of Iran Computer Society (CSICC’05), 2005, Tehran, Iran.

Roohollah Mafi, Hossein Deldari, Mojtaba Mazoochi, Alchemi+: An Agent-Based Approach to Grid Programming, Parallel Processing and Applied Mathematics, 6th International Conference, (PPAM 2005), Poznan, Poland, September 11-14, 2005, Pages 188-195.

Computational grids have provided the usage of computational distributed resources for computation intensive applications. The development of programs that use these capabilities is one of the challenging issues for grid computing. In this article, an effort has been made to solve this problem by presenting mobile-agent-based parallel programming on the grid. The presentation of this model which has been realized by extending Alchemi^TM grid system with adding agent properties and navigational commands that let user to develop his program by using mobile agents. To evaluate the system, algorithms of matrix multiplication and convex hull have been implemented in the mentioned system.

H. Deldari and T. Ghafarian, Parallel Genetic Algorithm Using Algorithmic Skeleton, ESTEGHLAL Journal of Engineering Isfahan University of Technology, Volume 22, No 2, Pages 1-19, March 2004.

H. Deldari, Performance Modeling of Parallel Algorithmic Skeletons, In Proceeding of the third International Annual Computer Conference of the Computer Society of Iran, CSICC'97, Computer Engineering Department , Iran University of Science and technology , Tehran, Iran, December 23-25, 1997, pages 75-85.

Several authors have proposed the use of algorithmic skeletons as a high-level, machine-independent means of developing parallel programs. This paper addresses the question of modeling the performance of such skeletons. This model is a generic higher order complexity function. Instatiation of the skeleton with specific set of functional parameters enables the time complexity of the particular application to be derived. The approach is illustracted by case studies based on application-specifi languages for image processing. The computational model used in this study is BSP. Two different versions of algorithms have been designed and implementd and the performance model for both version have been derived.

H. Deldari, J.R. Davy, P.M. Dew, A Skeleton for Parallel CSG with a Performance Model, Technical report, School of computer studies research report series, University of Leeds, 1997.

We Describe a metholdology for modelling the performance of the parallel algorithmic skeletons and illustrate it using a new skeleton which supports set membership classification problems in Constructive Solid Geometry. These problems are characterised by potentially unbalances tree structures with data-dependent computations at the nodes. The skeleton achieves good parallel efficiency on the class of computations permitted, the methodology accurately predicts the asymptotic performance of specific CSG applications.

H. Deldari, J.R. Davy and P. M. Dew, Parallel CSG, Skeletons and Performance Modeling, In Proceeding of the Second Annual Computer Conference (CSICC 96), pages 115 -122, Amirkabir University of technology, December 1996.

We describe an efficient implementation of a parallel algorithmic skeleton which supports set membership classification problems in constructive Solid Geometry. A performance modeling methodology is developed, which realistically predicts the asymptotic performance of specific CSG applications.

H. Deldari, A Performance Study for Parallel Algorithmic Skeletons, PhD thesis, University of Leeds, Division of Computer Science, 1996.

H. Deldari, John Davy, Peter Dew, The Performance of Parallel Algorithmic Skeletons, In Parallel Programming and Applications edited by Peter Fritzson and Leif Finmo Pages 65-74, IOS Press 1995.

Several authors have proposed the use of algorithmic skeletons as a high-level machine independent means of developing parallel programs. This paper addresses the question of modeling the performance of such skeletons. The execution time for a skeleton is presented as a generic higher order complexity function. Instantiation of the skeleton with a specific set of functional parameters enables the time complexity of the particular application to be derived. The approach is illustrated by examples based on existing special purpose languages for image processing, and is extended to analyse the scalability of skeleton-based applications, using isoefficiency functions.

John Davy, Hossain Deldari, Peter M. Dew, Constructive Solid Geometry Using Algorithmic Skeletons, In Proceeding of the fifth Eurographics workshop on Programming Paradigms in Graphics, held in Maastricht, The Netherlands, September 2-3, 1995.

This paper presents a feasibility study in the use of parallel algorithmic skeletons to program applications of constructive solid geometry(CSG). The potential for such an approach arises from the frequent use of divide-and-conquer (D&C) methods in this domain, which are amenable to highly parallel implementation. A prototype Geometric Evaluation Library (GEL) is described, which captures the structure of these algorithms. GEL includes a small set of polymorphic high-order functions, which capture the fundamental algorithmic structures independently of underlying geometric domain. An efficient parallel implementation of one of these functions shows the potential to develop them as parallel algorithmic skeletons. The paper concludes with a discussion of the potential for further developments of this approach.

J. R. Davy, H. Deldari, and P. M. Dew, Constructive Solid Geometry Using Parallel Algorithmic Skeletons, In Proceedings 5th Eurographics Workshop on Programming Paradigms for Graphics, Springer, 1995.

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