CLOUD Computing Projects

CLOUD Computing Projects defined as category of computing which relies on sharing computing resources rather than local server or personal device to handle applications. We develop cloud report thesis for PhD students which describes a new supplement, consumption and delivery model for IT services based on internet. We provide cloud report academic thesis as application scalability with dynamic scalable and virtualized resource as service over internet. We implement cloud report thesis for research scholars to share the resources on different nodes with various application. We schedule task by user requirements scheduling strategy is the key technology in cloud computing.

CLOUD COMPUTING PROJECTS

CLOUD Computing Projects Scheduling:

  We implement following scheduling methods in cloud computing from Elsevier papers are.

Real time scheduling:

  Our main objective of this scheduling to enhance throughput & minimize average response time instead of deadlines we implement time utility function (TUF) a profit TUF & penalty TUF associated with each task at same time.

Cloud service scheduling:

   We categorize cloud service scheduling as:

User level scheduling:

Deal with problem raised by service provision among provider and customer.

System level scheduling:

Handle resource management within data center.

Workflow scheduling:

We enable application structure in directed acyclic graph form. We represent each node with constituent task & every edge represent inter task dependency of application.

Heuristic scheduling:

We resolve class NP hard problem by enumeration method, approximation/heuristic method. We define heuristic as suboptimal algorithm to find reasonable good solutions. Approximation algorithms are used to find approximate solution to optimized solution.

CLOUD COMPUTING PROJECTS FOR CSE STUDENTS

Static & dynamic scheduling:

Static scheduling:

It allows prefetching required data and pipelining various stages of task execution. It imposes less runtime overhead.

Dynamic scheduling:

The execution time of task may not be known and task allocation is done on fly as application executes.

RAS in cloud computing:

We developed more than 75+projects in cloud computing and their significance given as:

Resource scarcity:

It occurs when there is a limited resource.

Under provision:

It arises when applications is assigned with few number of resources than demand.

Resource contention:

It arises when two application try to access same resources at same time.

Resource fragmentation:

It arises when resource are isolated.

Over provision:

It arises when application get surplus resources than demanded one.

RAS parameter:

We provide following parameters are:

• Gossip.
• SLA.
• Execution time.
• Hardware resource dependency.
• Utility function.
• Auction.
• Policy.
• Virtual machine.

CLOUD Computing Projects Advantages:

• It does not need to end on hardware & software system.
• Cloud provides share resource over internet during resource scarcity.