Khondker Hasan

Permanent URI for this collectionhttps://hdl.handle.net/10657.1/2319

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Dr. Khondker Hasan is an Assistant Professor of Computer Science at University of Houston-Clear Lake. He has extensive hands-on experience in the following areas:

  • Distributed Network Systems and Big Data.
  • Enterprise Java Programming (J2EE) and Testing Environment.
  • Dot Net Development (C#), MSTest, TFS Build definitions, and other TFS services.
  • Parallel algorithms and programming for GPGPU using CUDA.
  • Distributed algorithms and programming in Linux environment with C/C++.
  • Advanced Relational & Object-Oriented Databases and performance optimization (LINQ).
  • Mathematical knowledge with experience developing comprehensive algorithms.

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Recent Submissions

Now showing 1 - 10 of 10
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    Cost Effective GPS-GPRS Based Object Tracking System
    (International MultiConference of Engineers and Computer Scientists, 2009-03-18) Hasan, Khondker
    This paper proposes and implements a low cost object tracking system using GPS and GPRS. The system allows a user to view the present and the past positions recorded of a target object on Google Map through the internet. The system reads the current position of the object using GPS, the data is sent via GPRS service from the GSM network towards a web server using the POST method of the HTTP protocol. The object's position data is then stored in the database for live and past tracking. A web application is developed using PHP, JavaScript, Ajax and MySQL with the Google Map embedded. The existing live tracking systems that are available now a days use SMS for the communication to the server which turned out to be expensive. (SMS are used for communication to device). We have used the GPRS service which made our system a low cost tracking solution for localizing an object position and status. This system is very useful for car theft situations (alarm alert, engine starting, localizing), for adolescent drivers being watched and monitored by parents (speed limit exceeding, leaving a specific area), as well as for human and pet tracking.
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    A Model for Least Distance Protocol in MANET Using Artificial Intelligence Search Techniques
    (International Journal of Electrical & Computer Sciences, 2011-04) Hasan, Khondker
    As mobile adhoc networks operate with nodes carrying small amount of energy, reducing energy consumption is a major issue in adhoc networks. The paper discusses a protocol along with its implementation which incorporates Artificial intelligence search techniques, namely A* search and Dijkstra's algorithm to reduce the distance traversed by both the data and the control information. The transmission path is determined by the means of A* search, which gives the shortest path possible. This greatly reduces the distance traversed. This paper also focuses on the performance of this protocol compared with swarm intelligence which is another artificial intelligence protocol implemented by MANET (mobile adhoc network). A collection of proposed transmission protocols' characteristics has been presented in this paper. An extensive empirical study has been carried out to validate the protocol's performance.
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    Bio-Medical Data Integration Based on MetaQuerier Architecture
    (The 2011 International Conference on Bioinformatics and Computational Biology, 2011-07-18) Hasan, Khondker
    The emergence of a large number of bio medical data sets on the Internet has resulted in the need for flexible and efficient approaches to integrate information from multiple bio medical data sources and services. Thus data are scattered in different web sites and web databases. User struggling hard and for them it is extremely difficult for them to find accurate data from the web efficiently. In this paper, we tried to present our approach to establish an architecture which will automatically generate web data integration, optimize the composition, and execute the required output efficiently. While data integration techniques have been applied to the bio medical data domain, the focus has been on answering specific user queries. Thus we have found the indication towards large scale data integration. So the issue arises for which data integration architecture can be used. There are so many proposed large scale data integration architecture are available. Among all of them we designed our paper based on the MetaQuerier architecture. It’s large scale integration over web databases. MetaQuerier architecture has five basic processes which will be clarified in this paper briefly. We used this architecture to implement our bio medical data integration and try to generate a well structured output. Here our first task is to explore the MetaQuerier architecture and secondly we will explore the design in terms of bio medical data.
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    Predicting CPU Availability of a Multi-core Processor Executing Concurrent Java Threads
    (World Academy of Science and Computer Science Research, Education, and Applications, 2011-07) Hasan, Khondker
    Techniques for predicting the availability of CPU resources associated with the execution of multiple concurrent Java threads on a multi-core architecture are introduced. Prediction of CPU availability is important in the context of making thread assignment and scheduling decisions. Theoretically derived upper and lower bound formulas for estimating CPU availability are introduced. Input parameters to the formulas include: number of cores; number of threads; and the unloaded CPU usage factor for each thread. Extensive experimental studies and statistical analysis are performed to validate the theoretical bounds and provide a basis for an empirical model for predicting CPU availability. To facilitate scientific and controlled empirical evaluation, synthetically generated threads are employed that are parameterized by their unloaded CPU usage factor, defined as the fraction of time a thread spends utilizing CPU resources on an unloaded system.
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    Composite Prediction Model and Task Distribution on a Cluster of Multi-core Processors
    (IEEE Computer Society, 2013-12) Hasan, Khondker
    An approach to efficiently schedule heterogeneous tasks in a distributed environment is presented. Given a set of tasks each with varied CPU and main memory requirements, and a cluster of compute nodes (which are significantly less than the number of tasks), our goal is to find an assignment of tasks to compute nodes such that the total time taken to execute all the tasks is minimized. The task assignment problem in general is NP-Hard and it is further complicated by the changing dynamics (changes to CPU and main memory availability) of the compute nodes. Our solution methodology involves the following: a) develop an analytical model that will determine the upper and lower bounds on the efficiency of a compute node, given the number of processor cores in each compute node, the number of threads in execution, aggregate CPU load, and main memory and CPU availability and b) using these bounds and some properties of the tasks (CPU and main memory utilization values) two tasks assignment models are proposed and extensively evaluated empirically. The key challenge is to determine the CPU availability for a new task. We have proposed a new model (composite) to derive these bounds and experiments have shown that our derived bounds are consistently tight. For all our empirical evaluations on UNIX systems, we have used tasks that are both synthetic (allowing us to control the CPU and memory requirements) for validating composite model and real-world tasks such as prime number generator, merge sort, image rendering, and others for validating task assignment models.
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    A New Composite CPU/Memory Model for Predicting Efficiency of Multi-core Processing
    (IEEE Computer Society, 2014-02) Hasan, Khondker
    Techniques for predicting the efficiency of multi-core processing associated with a set of tasks with varied CPU and main memory requirements are introduced. Given a set of tasks each with different CPU and main memory requirements, and a multi-core system (which generally has fewer cores than the number of tasks), our goal is to derive equations for upper-and lower-bounds to estimate the efficiency with which the tasks are executed. Prediction of execution efficiency of processes due to CPU and required memory availability is important in the context of making process assignment, load balancing, and scheduling decisions in distributed systems. Input parameters to models include: number of cores, number of threads, CPU usage factor of threads, available memory frames, required amount of memory for each thread, and others. Additionally, a CPU availability average prediction model is introduced from the empirical study for the set of applications that require a single predicted value instead of bounds. Extensive experimental studies and statistical analysis are performed and observed that the proposed efficiency bounds are consistently tight. The model provides a basis of an empirical model for predicting execution efficiency of threads while CPU and memory resources are uncertain. To facilitate scientific and controlled empirical evaluation, real-world benchmark programs with dynamic behavior are employed on UNIX systems that are parameterized by their CPU usage factor and memory requirement.
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    Performance Prediction and Analysis of Compute-intensive Tasks on GPUs
    (The 11th IFIP International Conference on Network and Parallel Computing, 2014) Hasan, Khondker
    Using Graphics Processing Units (GPUs) to solve general purpose problems has received significant attention both in academia and industry. Harnessing the power of these devices however requires knowledge of the underlying architecture and the programming model. In this paper, we develop analytical models to predict the performance of GPUs for computationally intensive tasks. Our models are based on varying the relevant parameters - including total number of threads, number of blocks, and number of streaming multi-processors - and predicting the performance of a program for a specified instance of these parameters. The approach can be used in the context of heterogeneous environments where distinct types of GPU devices with different hardware configurations are employed.
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    A New Multi-core CPU Resource Availability Prediction Model for Concurrent Processes
    (The 2017 IAENG International Conference on Computer Science, 2017-03) Hasan, Khondker
    The efficiency of a multi-core architecture is directly related to the mechanisms that map the threads (processes in execution) to the cores. Determining the CPU resource availability of a multi-core architecture based on the characteristics of the threads that are in execution is the art of system performance prediction. Prediction of CPU resource availability is important in the context of making process assignment, load balancing, and scheduling decisions. In distributed infrastructure, CPU resources are allocated on demand for a chosen set of compute nodes. In this paper, a prediction model is derived for multi-core architectures and empirical evaluations are performed with real-world benchmark programs in a heterogeneous environment to demonstrate the accuracy of the proposed model. This model can be utilized in various time-sensitive applications like resource allocation in a cloud environment, task distribution (determining the order for faster processing time) in distributed systems, and others.
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    A model-driven approach for predicting and analysing the execution efficiency of multi-core processing
    (International Journal of Computational Science and Engineering, 2017-03) Hasan, Khondker
    Techniques for predicting the efficiency of multi-core processing associated with a set of tasks with varied CPU and main memory requirements are introduced. Prediction of CPU and memory availability is important in the context of making process assignment, load balancing, and scheduling decisions in distributed systems. Given a set of tasks each with varied CPU and main memory requirements, and a multi-core system (which generally has fewer cores than the number of tasks), we provide upper- and lower-bound models (formulas) for the efficiency with which the tasks are executed. In addition, a model for average CPU availability is introduced from the empirical study for applications that require a single predicted value instead of bounds. To facilitate scientific and controlled empirical evaluation, real-world benchmark programs with dynamic behaviour (CPU and memory requirements change in a short interval of time) are employed on UNIX systems that are parameterised by their CPU usage factor and memory requirement.
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    Performance Enhancement and Prediction Model of Concurrent Thread Execution in JVM
    (14th Int'l Conference on Modeling, Simulation and Visualization Methods, 2017-07) Hasan, Khondker
    Performance of a Java Virtual Machine (JVM) is quantified in terms of the JVM’s relative CPU availability at executing concurrent Java threads. The total CPU loading of a JVM is defined by the sum of the CPU utilization factors of all threads executing on the JVM. Sharp performance degradation has been observed while JVM executes concurrent threads with exactly same CPU load. An analytical model has been proposed and implemented to improve the scenario. Extensive experimental studies and statistical analysis are performed to validate the performance enhancement of concurrent thread execution and provide a basis for an empirical model for improving CPU performance. To facilitate scientific and controlled empirical evaluation, synthetically generated threads are employed that are parameterized by their CPU utilization factor, which is defined as the fraction of time a thread spends utilizing CPU resources.