The Fuzzy Scheduling Algorithm for the Parallel Key Searching Problem on Cloud Environment

Author(s):  
Pimsiri Tubthong ◽  
Vasin Suttichaya
Author(s):  
Shailendra Raghuvanshi ◽  
Priyanka Dubey

Load balancing of non-preemptive independent tasks on virtual machines (VMs) is an important aspect of task scheduling in clouds. Whenever certain VMs are overloaded and remaining VMs are under loaded with tasks for processing, the load has to be balanced to achieve optimal machine utilization. In this paper, we propose an algorithm named honey bee behavior inspired load balancing, which aims to achieve well balanced load across virtual machines for maximizing the throughput. The proposed algorithm also balances the priorities of tasks on the machines in such a way that the amount of waiting time of the tasks in the queue is minimal. We have compared the proposed algorithm with existing load balancing and scheduling algorithms. The experimental results show that the algorithm is effective when compared with existing algorithms. Our approach illustrates that there is a significant improvement in average execution time and reduction in waiting time of tasks on queue using workflowsim simulator in JAVA.


Author(s):  
Ravi Mahadevan ◽  
Neelamegam Anbazhagan

<span>Online Nowadays, the enterprises &amp; individuals are contributing their workloads on cloud service providers which are going to increase on daily basis. There are   large amount CSP are available to offer virtualized and dynamic resource on pay and use basis. However, there are almost CSP failed to maintain quality of service (QOS) and minimal resource optimization. Some of the existing approaches are highly dedicated on scheduling policy but, it does not considered reliable services with optimized QOS. To offer best solution of above problem, the framework proposes Enhanced Minimal Resource Optimization based Scheduling Algorithm to minimize the resources and maintain the QOS.  The method avoids delay in Request-Response model in cloud environment. To avoid overload for resource allocation, the proposed design utilized optimized scheduling policy.  Proposed mechanisms utilized optimized service brokering policy to reduce the delay response in cloud environment. The framework also help cloud user to prefer best CSP according to their prior services. The method offers rising trend of resource based structure to reduce the placement churn extensively. Proposed system utilized efficient scheduling policy to transmit data request to CSP with minimal data processing time. The entire utilization is to improve the QOS of cloud service provider in the features of multi-dimensional resource. Based on experimental evaluations, proposed technique improves the CPT (Computation Processing Time) 301.72 milliseconds, BU (Bandwidth Utilization) 20 Mbps, CPUU (CPU Utilization) 5% &amp; MRU (Memory Resource Utilization) 3% on given input parameters compare than existing methodology.</span>


Author(s):  
Muhammad Aliyu ◽  
Murali M. ◽  
Abdulsalam Y. Gital ◽  
Souley Boukari ◽  
Rumana Kabir ◽  
...  

As cloud resource demand grows, supply chain management (SCM), which is the core function of cloud computing, faces serious challenges. Quite a number of techniques have been proposed by many researchers for such a challenge. As such, numerous proposed strategies are still under reckoning and modification so as to enhance its potential. An optimized dynamic scheme that combined several algorithms' characteristics was proposed to map out such a challenge. The hybridized proposed scheme involved the meta-heuristic swarm mechanism of ant colony optimization (ACO) and deterministic spanning tree (SPT) algorithm as it obtained faster convergence chain, ensured resource utilization in least time and cost. Extensive experiments conducted in cloudsim simulator provided an efficient result in terms of minimized makespan time and throughput as compared to SPT, round robin (RR), and pre-emptive fair scheduling algorithm (PFSA) as it significantly improves performance.


Author(s):  
Lavanya S. ◽  
Susila N. ◽  
Venkatachalam K.

In recent times, the cloud has become a leading technology demanding its functionality in every business. According to research firm IDC and Gartner study, nearly one-third of the worldwide enterprise application market will be SaaS-based by 2018, driving annual SaaS revenue to $50.8 billion, from $22.6 billion in 2013. Downtime is treated as the primary drawback which may affect great deals in businesses. The service unavailability leads to a major disruption affecting the business environment. Hence, utmost care should be taken to scale the availability of services. As cloud computing has plenty of uncertainty with respect to network bandwidth and resources accessibility, delegating the computing resources as services should be scheduled accordingly. This chapter proposes a study on cloud of clouds and its impact on a business enterprise. It is also decided to propose a suitable scheduling algorithm to the cloud of cloud environment so as to trim the downtime problem faced by the cloud computing environment.


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