Tuesday, 15 March 2016
Tuesday, 17 November 2015
IEEE projects 2015 @ Rs.2500 only - 1 crore projects
1Croreprojects provides career oriented and real time projects for Final year students in B.E/B.Tech/MCA/MSC/M.E/M.Tech.
The Team of experts from the IT industry forms the core development team at 1Croreprojects. 1Croreprojectsteam has rich experience in Planning, developing & deploying Live projects in the industry. Backed by such rich experience, TTA guides the students for their Final year projects.
We provide projects in the following domains,
DOMAINS
JAVA
J2EE
.NET
VLSI
MAT LAB
NS2
Embedded
Robotics
Automation
GSM
GPRS
ORACLE/SQL
IEEE Project Areas
IEEE Transactions on Knowledge and Data Engineering (Data mining)
IEEE Transactions on Image Processing
IEEE Transactions on Mobile Computing
IEEE Transactions on Cloud Computing
IEEE Transactions on Software Engineering
IEEE Transactions on Networking
IEEE Transactions on Communications
IEEE Transactions on Wireless Communications
IEEE Transactions on Dependable and Secure Computing (Network Security)
HIGHLIGHTS
Government certification for your project
100% Placement oriented training
Projects based on SDLC model
Projects guided by 15 years experienced IT professionals
Live Video for project execution
Voice recorded base paper explanation
Free Software's & Installation support for Laptop's & Desktops
Free placement booklet
Free Technology (JAVA/.NET/PHP&MYSQL) training
End to End support for Projects
Seminar from the experts
Free Soft skills training
Free Aptitude training
Project Support
Abstract, Diagrams, Review Details, Relevant Materials, Presentation
Supporting Documents, Software E-Books
Software Development Standards & Procedure
E-Book, Theory Classes, Lab Working Programs, Project Design & Implementation
1 CRORE PROJECTS
Door No: 214/215,2nd Floor,
No. 172, Raahat Plaza, (Shopping Mall) ,Arcot Road, Vadapalani, Chennai,
Tamin Nadu, INDIA - 600 026
Email id: 1croreprojects@gmail.com
website:1croreprojects.com
Phone : +91 97518 00789 / +91 72999 51536
Mca final year projects @ Rs.3500 only - 1 crore projects
Mca final year projects
1Croreprojects provides career oriented and real time projects for Final year students in B.E/B.Tech/MCA/MSC/M.E/M.Tech.
The Team of experts from the IT industry forms the core development team at 1Croreprojects. 1Croreprojectsteam has rich experience in Planning, developing & deploying Live projects in the industry. Backed by such rich experience, TTA guides the students for their Final year projects.
We provide projects in the following domains,
DOMAINS
JAVA
J2EE
.NET
VLSI
MAT LAB
NS2
Embedded
Robotics
Automation
GSM
GPRS
ORACLE/SQL
IEEE Project Areas
IEEE Transactions on Knowledge and Data Engineering (Data mining)
IEEE Transactions on Image Processing
IEEE Transactions on Mobile Computing
IEEE Transactions on Cloud Computing
IEEE Transactions on Software Engineering
IEEE Transactions on Networking
IEEE Transactions on Communications
IEEE Transactions on Wireless Communications
IEEE Transactions on Dependable and Secure Computing (Network Security)
HIGHLIGHTS
Government certification for your project
100% Placement oriented training
Projects based on SDLC model
Projects guided by 15 years experienced IT professionals
Live Video for project execution
Voice recorded base paper explanation
Free Software's & Installation support for Laptop's & Desktops
Free placement booklet
Free Technology (JAVA/.NET/PHP&MYSQL) training
End to End support for Projects
Seminar from the experts
Free Soft skills training
Free Aptitude training
Project Support
Abstract, Diagrams, Review Details, Relevant Materials, Presentation
Supporting Documents, Software E-Books
Software Development Standards & Procedure
E-Book, Theory Classes, Lab Working Programs, Project Design & Implementation
1 CRORE PROJECTS
Door No: 214/215,2nd Floor,
No. 172, Raahat Plaza, (Shopping Mall) ,Arcot Road, Vadapalani, Chennai,
Tamin Nadu, INDIA - 600 026
Email id: 1croreprojects@gmail.com
website:1croreprojects.com
Phone : +91 97518 00789 / +91 72999 51536
dotnet ieee projects @ Rs.2500 only - 1 crore projects
Dotnet ieee projects
1CROREPROJECTS the leading Training & Development company in Chennai provides best in class career oriented & real time Final year projects in Chennai for students pursuing B.E, B.Tech,M.E, M.tech, MCA, Bsc & Msc.
We help students in completing the project with detailed explanation on Project development. Training will be provided on each and every module by our skilled trainers and project development team. The trainers are with more than 10 years of experience in IT industry & project development.1CRORE project development team will help you with designing, developing and deploying/executing your projects.
Supported Technologies:
Dot Net
JAVA
PHP/MySQL
Cloud Computing
Android
Supported Domains:
Cloud computing
Networking
Mobile Computing
Secure Computing
Data Mining
Image processing
Parallel & Distributed Systems
Benefits of doing Final Year Project in Chennai at 1CROREPROJECTS :
Project Certification recognized by the industry
INTERNATIONAL ACCREDITATION CERTIFICATION
IEEE 2014 Paper based projects
Projects handled by IT Experts with more than decades of experience
Complete training on JAVA, Dot Net, PHP, Android,.
Free placement Support
Free Software Installations
Continuous support until Project Completion
1 CRORE PROJECTS
Door No: 214/215,2nd Floor,
No. 172, Raahat Plaza, (Shopping Mall) ,Arcot Road, Vadapalani, Chennai,
Tamin Nadu, INDIA - 600 026
Email id: 1croreprojects@gmail.com
website:1croreprojects.com
Phone : +91 97518 00789 / +91 72999 51536
Wednesday, 11 November 2015
Tuesday, 18 August 2015
1CP_RT_J034 Load balancing model for Cloud Data Center
ABSTRACT:
Cloud data center management is a key
problem due to the numerous and heterogeneous strategies that can be applied,
ranging from the VM placement to the federation with other clouds. Performance
evaluation of Cloud Computing infrastructures is required to predict and
quantify the cost-benefit of a strategy portfolio and the corresponding Quality
of Service (QoS) experienced by users. Such analyses are not feasible by
simulation or on-the-field experimentation, due to the great number of
parameters that have to be investigated. In this paper, we present an
analytical model, based on Stochastic Reward Nets (SRNs), that is both scalable
to model systems composed of thousands of resources and flexible to represent
different policies and cloud-specific strategies. Several performance metrics
are defined and evaluated to analyze the behavior of a Cloud data center:
utilization, availability, waiting time, and responsiveness. A resiliency
analysis is also provided to take into account load bursts. Finally, a general
approach is presented that, starting from the concept of system capacity, can
help system managers to opportunely set the data center parameters under
different working conditions.
EXISTING
SYSTEM:
In order to integrate business
requirements and application level needs, in terms of Quality of Service (QoS),
cloud service provisioning is regulated by Service Level Agreements (SLAs):
contracts between clients and providers that express the price for a service,
the QoS levels required during the service provisioning, and the penalties
associated with the SLA violations. In such a context, performance evaluation
plays a key role allowing system managers to evaluate the effects of different
resource management strategies on the data center functioning and to predict
the corresponding costs/benefits.
Cloud systems differ from traditional
distributed systems. First of all, they are characterized by a very large
number of resources that can span different administrative domains. Moreover,
the high level of resource abstraction allows to implement particular resource
management techniques such as VM multiplexing or VM live migration that, even
if transparent to final users, have to be considered in the design of
performance models in order to accurately understand the system behavior.
Finally, different clouds, belonging to the same or to different organizations,
can dynamically join each other to achieve a common goal, usually represented
by the optimization of resources utilization. This mechanism, referred to as cloud
federation, allows to provide and release resources on demand thus
providing elastic capabilities to the whole infrastructure.
DISADVANTAGES
OF EXISTING SYSTEM:
·
On-the-field experiments are mainly
focused on the offered QoS, they are based on a black box approach that makes
difficult to correlate obtained data to the internal resource management
strategies implemented by the system provider.
·
Simulation does not allow to conduct
comprehensive analyses of the system performance due to the great number of
parameters that have to be investigated.
PROPOSED
SYSTEM:
In this paper, we present a stochastic
model, based on Stochastic Reward Nets (SRNs), that exhibits the above
mentioned features allowing to capture the key concepts of an IaaS cloud
system. The proposed model is scalable enough to represent systems composed of
thousands of resources and it makes possible to represent both physical and
virtual resources exploiting cloud specific concepts such as the infrastructure
elasticity. With respect to the existing literature, the innovative aspect of
the present work is that a generic and comprehensive view of a cloud system is
presented. Low level details, such as VM multiplexing, are easily integrated
with cloud based actions such as federation, allowing to investigate different
mixed strategies. An exhaustive set of performance metrics are defined
regarding both the system provider (e.g., utilization) and the final users
(e.g., responsiveness).
ADVANTAGES
OF PROPOSED SYSTEM:
To provide a fair comparison among
different resource management strategies, also taking into account the system
elasticity, a performance evaluation approach is described. Such an approach,
based on the concept of system capacity, presents a holistic view of a cloud
system and it allows system managers to study the better solution with respect
to an established goal and to opportunely set the system parameters.
MODULES:
1.
System Queuing
2.
Scheduling
Module
3.
VM Placement
Module
4.
Federation
Module
5.
Arrival Process
MODULES
DESCRIPTION:
1.
System Queuing:
Job requests (in terms
of VM instantiation requests) are en-queued in the system queue. Such a queue
has a finite size Q, once its limit is reached further requests are rejected.
The system queue is managed according to a FIFO scheduling policy.
2.
Scheduling Module:
When a resource is
available a job is accepted and the corresponding VM is instantiated. We assume
that the instantiation time is negligible and that the service time (i.e., the
time needed to execute a job) is exponentially distributed with mean1/μ.
3.
VM Placement:
According to the VM
multiplexing technique the cloud system can provide a number M of logical
resources greater than N. In this case, multiple VMs can be allocated in the
same physical machine (PM), e.g., a core in a multicore architecture. Multiple
VMs sharing the same PM can incur in a reduction of the performance mainly due
to I/O interference between VMs.
4.
Federation Module:
Cloud federation allows
the system to use, in particular situations, the resources offered by other
public cloud systems through a sharing and paying model. In this way, elastic
capabilities can be exploited in order to respond to particular load
conditions. Job requests can be redirected to other clouds by transferring the
corresponding VM disk images through the network.
5.
Arrival Process:
Finally, we respect to
the arrival process we will investigate three different scenarios. In the first
one (Constant arrival process) we assume the arrival process be a homogeneous
Poisson process with rate λ. However, large scale distributed systems with
thousands of users, such as cloud systems, could exhibit
self-similarity/long-range dependence with respect to the arrival process. The
last scenario (Bursty arrival process) takes into account the presence of a
burst whit fixed and short duration and it will be used in order to investigate
the system resiliency
SYSTEM CONFIGURATION:-
HARDWARE CONFIGURATION:-
ü Processor - Pentium –IV
ü Speed - 1.1
Ghz
ü RAM - 256
MB(min)
ü Hard Disk -
20 GB
ü Key Board -
Standard Windows Keyboard
ü Mouse - Two
or Three Button Mouse
ü Monitor - SVGA
SOFTWARE CONFIGURATION:-
ü Operating System : Windows XP
ü Programming Language :
JAVA/J2EE
ü Java Version :
JDK 1.6 & above.
CONTACT US
1 CRORE PROJECTS
Door No: 214/215,2nd Floor,
No. 172, Raahat Plaza, (Shopping Mall) ,Arcot Road, Vadapalani, Chennai,
Tamin Nadu, INDIA - 600 026
Email id: 1croreprojects@gmail.com
website:1croreprojects.com
Phone : +91 97518 00789 / +91 72999 51536
1CP_RT_J033 IPTV Portal System
ABSTRACT:
Virtualized cloud-based services can take advantage of statistical multiplexing across applications to yield significant cost savings. However, achieving similar savings with real-time services can be a challenge. In this paper, we seek to lower a provider’s costs for real-time IPTV services through a virtualized IPTV architecture and through intelligent time-shifting of selected services. Using Live TV and Video-on-Demand (VoD) as examples, we show that we can take advantage of the different deadlines associated with each service to effectively multiplex these services. We provide a generalized framework for computing the amount of resources needed to support multiple services, without missing the deadline for any service. We construct the problem as an optimization formulation that uses a generic cost function. We consider multiple forms for the cost function (e.g., maximum, convex and concave functions) reflecting the cost of providing the service. The solution to this formulation gives the number of servers needed at different time instants to support these services. We implement a simple mechanism for time-shifting scheduled jobs in a simulator and study the reduction in server load using real traces from an operational IPTV network. Our results show that we are able to reduce the load by (compared to a possible as predicted by the optimization framework).
EXISTING SYSTEM:
Servers in the VHO serve VoD using unicast, while
Live TV is typically multicast from servers using IP Multicast. When users
change channels while watching live TV, we need to provide additional
functionality so that the channel change takes effect quickly. For each channel
change, the user has to join the multicast group associated with the channel,
and wait for enough data to be buffered before the video is displayed; this can
take some time. As a result, there have been many attempts to support instant
channel change by mitigating the user perceived channel switching latency
DISADVANTAGES
OF EXISTING SYSTEM:
] More
Waiting Time
] More
Switching latency
] Not
Cost effective
PROPOSED SYSTEM:
We propose a) To use a cloud computing
infrastructure with virtualization to handle the combined workload of multiple
services flexibly and dynamically, b) To either advance or delay one service
when we anticipate a change in the workload of another service, and c) To
provide a general optimization framework for computing the amount of resources
to support multiple services without missing the deadline for any service.
ADVANTAGES
OF PROPOSED SYSTEM:
In this paper, we consider two potential strategies
for serving VoD requests. The first strategy is a postponement based strategy.
In this strategy, we assume that each chunk for VoD has a deadline seconds
after the request for that chunk. This would let the user play the content up
to seconds after the request. The second strategy is an advancement based
strategy. In this strategy, we assume that requests for all chunks in the VoD
content are made when the user requests the content. Since all chunks are
requested at the start, the deadline for each chunk is different with the first
chunk having deadline of zero, the second chunk having deadline of one and so
on. With this request pattern, the server can potentially deliver huge amount
of content for the user in the same time instant violating downlink bandwidth
constraint.
MODULES DESCRIPTION:
Optimization
Framework
An IPTV service
provider is typically involved in delivering multiple real time services, such
as Live TV, VoD and in some cases, a network-based DVR service. Each unit of
data in a service has a deadline for delivery. For instance, each chunk of video
file for VoD need to be serviced by its playback deadline so that the playout
buffer at the client does not under-run. In this section, we analyze the amount
of resources required when multiple real time services with deadlines are
deployed in a cloud infrastructure. There have been multiple efforts in the
past to analytically estimate the resource requirements for serving arriving
requests which have a delay constraint. These have been studied especially in
the context of voice, including delivering VoIP packets, and have generally
assumed the arrival process is Poisson.
Impact of Cost
Functions on Server Requirements
We investigate
linear, convex, and concave functions. With convex functions, the cost
increases slowly initially and subsequently grows faster. For concave
functions, the cost increases quickly initially and then flattens out,
indicating a point of diminishing unit costs (e.g., slab or tiered pricing).
Minimizing a convex cost function results in averaging the number of servers
(i.e., the tendency is to service requests equally throughout their deadlines
so as to smooth out the requirements of the number of servers needed to serve all
the requests). Minimizing a concave cost function results in finding the
extremal points away from the maximum (as shown in the example below) to reduce
cost. This may result in the system holding back the requests until just prior
to their deadline and serving them in a burst, to get the benefit of a lower
unit cost because of the concave cost function (e.g., slab pricing). The
concave optimization problem is thus optimally solved by finding boundary
points in the server-capacity region of the solution space.
Linear Cost Function
The linear cost represents
the total number of servers used. The minimum number of total servers needed is
the total number of incoming requests. The optimal strategy is not unique. Any
strategy that serves all the requests while meeting the deadline and using a
total number of servers equal to the number of service requests is optimal. One
strategy for meeting this cost is to set to serve all requests as they arrive.
The optimal cost associated with this cost function does not depend on the
deadline assigned to each service class.
SYSTEM CONFIGURATION:-
HARDWARE CONFIGURATION:-
Processor - Pentium –IV
Speed - 1.1 Ghz
RAM - 256 MB(min)
Hard Disk - 20 GB
Key Board - Standard Windows Keyboard
Mouse - Two or Three Button Mouse
Monitor - SVGA
SOFTWARE CONFIGURATION:-
Operating System : Windows XP
Programming Language :
JAVA/J2EE.
Java Version :
JDK 1.6 & above.
Database :
MYSQL
CONTACT US
1 CRORE PROJECTS
Door No: 214/215,2nd Floor,
No. 172, Raahat Plaza, (Shopping Mall) ,Arcot Road, Vadapalani, Chennai,
Tamin Nadu, INDIA - 600 026
Email id: 1croreprojects@gmail.com
website:1croreprojects.com
Phone : +91 97518 00789 / +91 72999 51536
CONTACT US
1 CRORE PROJECTS
Door No: 214/215,2nd Floor,
No. 172, Raahat Plaza, (Shopping Mall) ,Arcot Road, Vadapalani, Chennai,
Tamin Nadu, INDIA - 600 026
Email id: 1croreprojects@gmail.com
website:1croreprojects.com
Phone : +91 97518 00789 / +91 72999 51536
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