BEE COLONIES APPLIED TO MULTIPROCESSOR SCHEDULING

In order to achieve the high performance, we need to have an efficient scheduling of a parallelprogram onto the processors in multiprocessor systems that minimizes the entire executiontime. This problem of multiprocessor scheduling can be stated as finding a schedule for ageneral task graph to be executed on a multiprocessor system so that the schedule length can be minimize [10]. This scheduling problem is known to be NP- Hard.In multi processor task scheduling, we have a number of CPU’s on which a number of tasksare to be scheduled that the program’s execution time is minimized. According to [10], thetasks scheduling problem is a key factor for a parallel multiprocessor system to gain betterperformance. A task can be partitioned into a group of subtasks and represented as a DAG(Directed Acyclic Graph), so the problem can be stated as finding a schedule for a DAG to beexecuted in a parallel multiprocessor system so that the schedule can be minimized. Thishelps to reduce processing time and increase processor utilization. The aim of this thesis workis to check and compare the results obtained by Bee Colony algorithm with already generatedbest known results in multi processor task scheduling domain.

Separation and Execution of graphical engine on a cross platform IDE to enhance performance

“Biosim” is a simulation software which works to simulate the harvesting system.This system is able to design a model for any logistic problem with the combination of several objects so that the artificial system can show the performance of an individual model. The system will also describe the efficiency, possibility to be chosen for real life application of that particular model. So, when any one wish to setup a logistic model like- harvesting system, in real life he/she may be noticed about the suitable prostitution for his plants and factories as well as he/she may get information about the least number of objects, total time to complete the task, total investment required for his model, total amount of noise produced for his establishment in advance. It will produce an advance over view for his model. But “Biosim” is quite slow .As it is an object based system, it takes long time to make its decision. Here the main task is to modify the system so that it can work faster than the previous. So, the main objective of this thesis is to reduce the load of “Biosim” by making some modification of the original system as well as to increase its efficiency. So that the whole system will be faster than the previous one and performs more efficiently when it will be applied in real life. Theconcept is to separate the execution part of ”Biosim” form its graphical engine and run this separated portion in a third generation language platform. C++ is chosenhere as this external platform. After completing the proposed system, results with different models have been observed. The results show that, for any type of plants of fields, for any number of trucks, the proposed system is faster than the original system. The proposed system takes at least 15% less time “Biosim”. The efficiency increase with the complexity of than the original the model. More complex the model, more efficient the proposed system is than original “Biosim”.Depending on the complexity of a model, the proposed system can be 56.53 % faster than the original “Biosim”.

GENESIS: an efficient, transparent and easy to use cluster operating system

Present operating systems are not built to support parallel computing––they do not provide services to manage parallelism, i.e., to globally manage parallel processes and computational resources. The cluster operating environments that are used to assist the execution of parallel applications do not provide support for both programming paradigms, message passing (MP) or distributed shared memory (DSM)––they are mainly offered as separate components implemented at the user level as library and independent server processes. Due to poor operating systems users must deal with clusters as a set of independent computers rather than to see this cluster as a single powerful computer. A single system image (SSI) of the cluster is not offered to users. There is a need for an operating system for clusters. We claim and demonstrate in this paper that it is possible to develop a cluster operating system that is able to efficiently manage parallelism; use cluster resources efficiently; support MP in the form of standard MP and PVM, and DSM; offer SSI; and make it easy to use. We show that to achieve these aims this operating system should inherit many features of a distributed operating system and provide new services which address the needs of parallel processes, cluster's resources, and application developers. In order to substantiate the claim the first version of a cluster operating system managing parallelism and offering SSI, called GENESIS, has been developed.

The development of an efficient checkpointing facility exploiting operating systems services of the GENESIS cluster operating system

Recent research efforts of parallel processing on non-dedicated clusters have focused on high execution performance, parallelism management, transparent access to resources, and making clusters easy to use. However, as a collection of independent computers used by multiple users, clusters are susceptible to failure. This paper shows the development of a coordinated checkpointing facility for the GENESIS cluster operating system. This facility was developed by exploiting existing operating system services. High performance and low overheads are achieved by allowing the processes of a parallel application to continue executing during the creation of checkpoints, while maintaining low demands on cluster resources by using coordinated checkpointing.

Dynamic parallel job scheduling in multi-cluster computing systems

Job scheduling is a complex problem, yet it is fundamental to sustaining and improving the performance of parallel processing systems. In this paper, we address an on-line parallel job scheduling problem in heterogeneous multi-cluster computing systems. We propose a new space-sharing scheduling policy and show that it performs substantially better than the conventional policies.

Robust parallel job scheduling infrastructure for service-oriented grid computing systems

Recent trends in grid computing development is moving towards a service-oriented architecture. With the momentum gaining for the service-oriented grid computing systems, the issue of deploying support for integrated scheduling and fault-tolerant approaches becomes paramount importance. To this end, we propose a scalable framework that loosely couples the dynamic job scheduling approach with the hybrid replications approach to schedule jobs efficiently while at the same time providing fault-tolerance. The novelty of the proposed framework is that it uses passive replication approach under high system load and active replication approach under low system loads. The switch between these two replication methods is also done dynamically and transparently.

A comparative study at the logical level of centralised and distributed recovery in clusters

Cluster systems are becoming more prevalent in today’s computer society and users are beginning to request that these systems be reliable. Currently, most clusters have been designed to provide high performance at the cost of providing little to no reliability. To combat this, this report looks at how a recovery facility, based on either a centralised or distributed approach could be implemented into a cluster that is supported by a check pointing facility. This recovery facility can then recover failed user processes by using checkpoints of the processes that have been taken during failure free execution.