In Grid Computing:
Grid computing starts new era of modern computing. Grid computing is a version of parallel computing. Grid can works both in LAN and WAN.
Under the title “Grid Computing: Implementation and Performance Evaluation” I designed two algorithm for the scheduling of the “Grid-Bus Broker” (Data Grid service broker for scheduling distributed data host oriented applications across Windows and Unix-variant Grid resources) and developed “file based grid thread implementation: a file-based approach towards improving fault tolerance in the Gridbus Broker” which gives better performance than the current implementation. I also proposed technique to integrate and develop a new Grid Toolkit for Apple and MAC computers and an efficient way of checking Quality of Service (QoS).
An Extended Algorithm to Enhance the Performance of the Gridbus Broker with Data Restoring Technique
Abstract: There are various types of Grids have been developed to support different types of Applications. The Gridbus broker that mainly focused on Data Grid mediates access to distributed resources by discovering suitable data and computational resources, job monitoring, accessing local or remote data sources during job execution, collecting and presenting results. In this paper, we present an enhanced version of Grid Service Broker scheduling on Global Data Grids with job restoration point. In the present version of scheduling algorithm, if any job associated with an application becomes failed during its runtime then the scheduling algorithm just marked the job as failed and reset. But it does not keep any track of the percentage of the work has already been done by the job. In Contrast, our proposed enhanced algorithm utilizes a restore point to store the proportion of task completed by an executor. In case of failure, it starts the job from that restored point rather than its initial point. From the experimental result, we have found that our proposed algorithm increases the performance of the present scheduling algorithm
File Based GRID Thread Implementation in the .NET-based Alchemi Framework
Now a days, Grid computing is considered as one of the emerging technology in which jobs are distributed across the network or Internet. Among the several software toolkits those help us to implement a Grid environment, Alchemi is widely used and open source toolkit that runs on the Windows operating system in the .NET Framework. The node which requests an application to be performed is called Owner. The node that receives the requested application and sends result back to the owner is called Manager. An application is divided into many threads and theses threads are then submitted to other nodes called Executor. The executors execute the thread(s) which is assigned to them and return the result to the Manager after successful completion of execution. During the execution, if any thread fails to complete, then the task is rescheduled to other executor from its initial state. But if we can save the last execution point as well as the results and transfer that information to the manager, we can complete the same job in less time. Based on this principle, in this paper, we have proposed file based GRID thread implementation technique that stores the results of a thread during its execution. In case of any failure, the thread restarts from its last saved value rather than starting from its initial point.
Runtime Thread Rescheduling: An Extended Scheduling Algorithm to Enhance the Performance of the Gridbus Broker
Grid computing is rapidly becoming a requirement for the modern days computing where needs large amount of data to be processed. The Gridbus broker focuses on the Data Grid and schedules jobs depending on data and compute resources. In the current scheduling process, a job is assigned to an executor depending on the compute resource and data resource available at the time of deployment. One major problem is, if there is an idle higher grade compute resource available after the scheduling, it doesn’t take the advantage of that though there are unfinished job. As previous job completion history get privilege at the scheduling time so there is a high possibility for the slower one getting the more number of threads. Also if the last thread is assigned to the slower executor, both these cases create a bottle-neck for the faster job completion. In many cases, the faster one remains idle for a long time after completing its last job. In this paper, we have proposed a technique to reassign a thread to higher grade executor by preempting the thread in lower grade executor. Here we used the data restoration technique which track the information of the thread so far ran on a lower rate compute resource. If there is an idle computer with higher resource after the scheduling, we assigned the thread on computer from the saved point of the job that has already done in the lower power compute resource. By this approach we have improved the performance as well as the reliability of the Grid in a considerable extent.
EFFECT OF HOMOGENEOUS AND HETEROGENEOUS NETWORK STRUCTURE ON ALCHEMI BASED GRID COMPUTING PLATFORM
Modern world is evolving to an era of collaborative computing from personal computing. By the latest few years Grid computing has been established as a means of collaboration for human civilization in many fields. This paper concerned on Alchemi which is a .net based Desktop Grid Computing Framework. Alchemi uses the unutilized processing power, resources and by combining a number of PCs it creates a virtual super computer. Depending on the hosts’ configuration we can define the network of PCs as Homogeneous Network or Heterogeneous Network that eventually serve as a grid platform. Heterogeneous network can be defined as a LAN working together with different hardware and/or software configuration and protocol. In the same way we can define Homogeneous Network as a Network of PCs with same processing power and same protocol. This paper inspects the effect of Heterogeneous and Homogeneous Network on a grid computing platform. Thus we created a test bed where the Homogeneous and Heterogeneous Network have total same processing power. We executed a simple computational application and recorded the result for different number of threads and different size of that application. Processing the data shows us for smaller number of tasks both Networks works almost similar but for bigger tasks Homogeneous networks work better by a considerable amount as the task size increases. So, depending on this result we suggest to have grid platform as more likely to be Homogeneous Network.
In Mobile Communication:
Intelligent Network Based Mobility Control at CDMA
The main idea behind Intelligent Network is the separation of service control from service switching by means of standardized structure. This enables the rapid introduction of new services, features. Increase the ability to achieve integrated service packages by reducing the latency of new services throughout a network. CDMA (code division multiple access) is the most outstanding mobile digital radio technology where channels are defined with codes and use spread spectrum signaling .This paper presents architecture to control CDMA mobility with IN networks. The approach is to move mobility portion and management functions within a CDMA network to an IN platform, so providing mobility as an IN service.