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CLOUD WORKFLOW SCHEDULING WITH DEADLINE AND TIME SLOT ALGORITHM

CLOUD WORKFLOW SCHEDULING WITH DEADLINE AND TIME SLOT ALGORITHM

Abstract
Allocating service capacities in cloud computing is based on the assumption that they are unlimited and can be used at any time. However, available service capacities change with workload and cannot satisfy users’ requests at any time from the cloud
provider’s perspective because cloud services can be shared by multiple tasks. Cloud service providers provide available time slots for new user’s requests based on available capacities. In this paper, we consider workflow scheduling with deadline and time slot availability in cloud computing. An iterated heuristic framework is presented for the problem under study which mainly consists of initial solution construction, improvement, and perturbation. Three initial solution construction strategies, two greedy- and fair-based improvement strategies and a perturbation strategy are proposed. Different strategies in the three phases result in several heuristics.
Experimental results show that different initial solution and improvement strategies have different effects on solution qualities.
Module Description:
User:
1.     User Registration:
A registered user is a user of a website, program, or other system who has previously registered. Registered users normally provide some sort of credentials (such as a username or e-mail address, and a password) to the system in order to prove their identity: this is known as logging in
2.     Send Request
User can send the request for work schedule to the cloud service provider.
3.     Download Work schedule
Cloud service providers send the request to the User for downloading the work schedule.
Cloud Service Provider:
1.     Workload
Cloud service provider can load the amount of work.
2.     Work schedule
Work is to be assigned for the user.
3.     Authentication
User can authenticate for the available request.
4.     Send work
After authenticated the user, CSP can send the work to the User.

System analysis
Existing System:
An entire application as a service, which can be directly used with no change. (ii) Basic services are combined to build complex applications, e.g., Xignite and StrikeIron offer Web services hosted on a cloud on a pay-per-use basis [1]. Among a large number of services in cloud computing, there are many services which have same functions and supplied by different cloud service providers (CSPs). However, these services have
Different non-functional properties. Basic services are rented by users for their complex applications with various resource requirements which are usually modeled as workflows. Better services imply higher costs. Services are consumed based on Service-Level Agreements, which define parameters of Quality of Service in terms of the pay-per-use policy. Though there are many parameters or constraints involved in  practical workflow scheduling settings, deadline and time slot are two crucial ones in cloud computing, a new market oriented business model, which offers high quality and low cost information services [2]. However, the two constraints have been considered separately in existing researches.
(i)                Deadlines of the workflow applications need to be met.
(ii)           Unreserved time slots are crucial for resource utilization from the perspective of service providers. (iii) Utilization of time slots in reserved intervals should be improved to avoid renting new resources (saving money). In this paper, we consider the workflow scheduling problem with deadlines and time slot availability (WSDT for short) in cloud computing.


Proposed System:
1.     Service capacities are usually regarded to be unlimited in cloud computing, which can be used at any time. However, from the CSP’s perspective, service capacities are not unlimited. Available service capacities change with workloads, i.e., they cannot satisfy user’s requests at any time when a cloud service is shared by multiple tasks.
2.     Only some available time slots are provided for new coming users by CSPs in terms of their remaining capacities. For example, each activity in Figure1 has different candidate services with various execution times, costs and available time slots. For activity 4, there are two candidate services with different workloads.

3.    Though there are many available time slots, not all of the meet requirements of activities of workflow instances.



Conclusion:
We have considered workflow scheduling with deadline and time slots constraints in cloud computing to minimize total costs.
In this paper, we consider workflow scheduling with deadline and time slot
Availability in cloud computing. An iterated heuristic framework is presented for the problem under study which mainly consists of initial solution construction, improvement, and perturbation. Three initial solution construction strategies, two greedy- and fair-based improvement strategies and a perturbation strategy are proposed


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