A Gossip Protocol for
Dynamic Resource Management in Large Cloud Environments
ABSTRACT:
We address the
problem of dynamic resource management for a large-scale cloud environment. Our
contribution includes outlining a distributed middleware architecture and
presenting one of its key elements: a gossip protocol that (1) ensures fair
resource allocation among sites/applications, (2) dynamically adapts the
allocation to load changes and (3) scales both in the number of physical machines
and sites/applications. We formalize the resource allocation problem as that of
dynamically maximizing the cloud utility under CPU and memory constraints. We
first present a protocol that computes an optimal solution without considering
memory constraints and prove correctness and convergence properties. Then, we
extend that protocol to provide an efficient heuristic solution for the
complete problem, which includes minimizing the cost for adapting an
allocation. The protocol continuously executes on dynamic, local input and does
not require global synchronization, as other proposed gossip protocols do. We
evaluate the heuristic protocol through simulation and find its performance to
be well-aligned with our design goals.
EXISTING SYSTEM:
} Gossip
protocols are used in an existing system for resource allocation in cloud
environment.
} Gossip
protocols used in an existing system assume static input and produce a single
output value.
} Whenever
the input changes, they are restarted and produce a new output value.
} The
above process requires global synchronization.
DISADVANTAGES OF
EXISTING SYSTEM:
} Drawbacks
of the existing system :
} Gossip
protocol in the existing system assumes static input and produces a single
output value.
} Whenever
the input changes, they restarted and produce a new output value which leads to
time consumption and requires global synchronization.
} It’s
hard to adapt to changes as the input is static.
PROPOSED SYSTEM:
} Gossip
protocol used in the proposed system executes in a middleware platform.
} The
protocol ensures three design goals namely fairness, adaptability and
scalability.
} The
protocol continuously executes while its input and consequently its output
dynamically changes.
} We
evaluate the heuristic protocol through simulation and find its performance to
be well-aligned with our design goals.
} We
treat all machines as equivalent in the sense they do not belong to specific
racks or clusters.
ADVANTAGES OF PROPOSED
SYSTEM:
} Advantages
of the proposed system are as follows:
} Global
synchronization can be avoided, as there is a single continuous execution
instead of a sequence of executions with restarts.
} The
system can continuously adapt to changes in local input.
} The
gossip protocol continuously executes and dynamically solves the problem of
optimally placing applications in a cloud, achieving fair resource allocation.
DATA
FLOW DIAGRAM:
MODULES:
} VM
Evaluation
} Resource
Allocation
} Adaptation
} Demand
Sharing
} Evaluation
MODULES DESCRIPTION
VM Evaluation
} VM
Evaluation is the evaluation of virtual machines in the cloud.
} The
evaluation is based on the physical memory usage of the virtual machines in the
cloud.
} Load
of each virtual machine in the cloud is computed and sent to the client for
further process.
} The
virtual machine which has most free memory will be ready to receive and process
the module/process selected by the client.
} The
evaluation has made for the maximum utility of all virtual machines in the
cloud.
Resource Allocation
} Resource
allocation refers to the allocation of cloud resources to the process sent by
the client.
} The
most free memory virtual machine in the cloud will receive the process.
} The
resource of the virtual machine is allocated to the process.
} The
resources are allocated without memory constraints.
Adaptation
} Adaptation
is the process of resource allocation for modified process.
} The
client appending something to the process which is already allocated in the
cloud for reallocation.
} The
resource is allocated with memory constraints using heuristic algorithm.
} The
memory load of the virtual machines in the cloud is computed and also the
memory demand of the modified process is computed.
} Depend
upon the memory usage of VM and demand of process, the resources are allocated
to the process.
Demand Sharing
} Demand
Sharing is based on heuristic algorithm and it refers to sharing of memory
demand of the process while demand exceeds the capacity of virtual machine.
} The
virtual machines in the cloud are evaluated and memory demand of the process is
calculated. If the demand exceeds the capacity of VM, the process is split
(divided).
} Memory
demand is computed for the split process.
} The
process of high memory demand is allocated in high free memory VM and other
process is allocated in another VM.
Evaluation
} The
overall dynamic resource allocation in large cloud environment is evaluated and
displayed as pie graph.
} The
graph shows the overall usage of the virtual machines in the cloud.
} The
graph shows the maximum utility of the Virtual machine under memory
constraints.
} Equal
usage of all virtual machines in the cloud is shown in the graph.
HARDWARE REQUIREMENTS:
} System : Pentium IV 2.4 GHZ
} Hard
Disk : 160 GB
} Monitor : 15 VGA color
} Mouse : Logitech
} RAM : 2 GB
SOFTWARE REQUIREMENTS:
} Operating
System : Windows XP
} Language : Java
} IDE : Net beans
} Tool : VM ware Workstation 2.1
REFERENCE:
Fetahi Wuhib, Rolf Stadler, and Mike
Spreitzer, “A Gossip Protocol for Dynamic Resource Management in Large Cloud
Environments”, IEEE TRANSACTIONS ON
NETWORK AND SERVICE MANAGEMENT, VOL. 9, NO. 2, JUNE 2012.
**********************************
A Gossip Protocol for Dynamic Resource Management in Large Cloud Environments, A Gossip Protocol for Dynamic Resource Management in Large Cloud Environments 2012 ieee, A Gossip Protocol for Dynamic Resource Management in Large Cloud Environments abstract, A Gossip Protocol for Dynamic Resource Management in Large Cloud Environments base paper, A Gossip Protocol for Dynamic Resource Management in Large Cloud Environments ppt, A Gossip Protocol for Dynamic Resource Management in Large Cloud Environments review documents, A Gossip Protocol for Dynamic Resource Management in Large Cloud Environments document, A Gossip Protocol for Dynamic Resource Management in Large Cloud Environments details, A Gossip Protocol for Dynamic Resource Management in Large Cloud Environments source code,A Gossip Protocol for Dynamic Resource Management in Large Cloud Environments video file, A Gossip Protocol for Dynamic Resource Management in Large Cloud Environments project, A Gossip Protocol for Dynamic Resource Management in Large Cloud Environments in java
