Balancing the
Trade-Offs between Query Delay and Data Availability in MANETs
ABSTRACT:
In mobile ad hoc networks (MANETs),
nodes move freely and link/node failures are common, which leads to frequent network
partitions. When a network partition occurs, mobile nodes in one partition are
not able to access data hosted by nodes in other partitions, and hence
significantly degrade the performance of data access. To deal with this
problem, we apply data replication techniques. Existing data replication solutions
in both wired or wireless networks aim at either reducing the query delay or
improving the data availability, but not both. As both metrics are important
for mobile nodes, we propose schemes to balance the trade-offs between data
availability and query delay under different system settings and requirements.
Extensive simulation results show that the proposed schemes can achieve a
balance between these two metrics and provide satisfying system performance.
ARCHITECTURE:
ALGORITHM:
Super-optimal algorithm A super optimal solution for 𝑁𝑖
would
be allocating 𝐶
most
frequently access data items in 𝑁𝑖,
but allocating the other data items in a way that they are all accessible from 𝑁𝑖’s
neighbors (this may not be possible in practice). Its data availability,
denoted as 𝐴𝑠𝑢𝑝𝑒𝑟.
The solution given by the super-optimal algorithm is not a tight upper bound.
It may be better than optimal and it may not be feasible. However, it is too difficult
to find the tight upper bound and this super-optimal algorithm can be used for
performance comparison
EXISTING
SYSTEM:
Existing data replication solutions in either wired
or wireless networks aim at either reducing the query delay or improving the
data availability, but not both. However, most mobile nodes only have limited
storage space, bandwidth and power, and hence it is impossible for one node to
collect and hold all the data considering these constraints.
DISADVANTAGES
OF EXISTING SYSTEM:
v The
drawback of the greedy scheme is that it does not consider the cooperation
between the neighboring nodes and hence its performance may be limited.
v Existing
data replication solutions in both wired and wireless networks aim at either
reducing the query delay or improving the data availability, but not both.
PROPOSED
SYSTEM:
In this paper, we propose new data
replication techniques to address query delay and data availability issues. As
both metrics are important for mobile nodes, we propose techniques to balance
the tradeoffs between data availability and query delay under different system
settings and requirements. Simulation results show that the proposed schemes
can achieve a balance between these two metrics and provide satisfying system
performance.
ADVANTAGES
OF PROPOSED SYSTEM:
ü Low
query delay.
ü
Data
Availability is high.
ü As
both metrics are important for mobile nodes, we propose schemes to balance the
trade-offs between data availability and query delay under different system
settings and requirements
MODULES:
1. Data
Replication
2. The
One-To-One Optimization (OTOO) Scheme
3. The Reliable Neighbor (RN) Scheme
4. Reliable Grouping (RG)
Scheme
MODULE
DESCRIPTION:
1.
Data Replication:
Data replication has been extensively
studied in the Web environment and distributed database systems. However, most
of them either do not consider the storage constraint or ignore the link
failure issue. Before addressing these issues by proposing new data replication
schemes, we first introduce our system model. In a MANET, mobile nodes
collaboratively share data. Multiple nodes exist in the network and they send
query requests to other nodes for some specified data items. Each node creates
replicas of the data items and maintains the replicas in its memory (or disk)
space. During data replication, there is no central server that determines the
allocation of replicas, and mobile nodes determine the data allocation in a
distributed manner.
2. The One-To-One Optimization (OTOO)
Scheme:
1) It considers the access frequency
from a neighboring node to improve data availability.
2) It considers the data size. If other
criteria are the same, the data item with smaller size is given higher
priority for replicating because this can improve the performance while
reducing memory space.
3) It gives high priority to local data
access, and hence the interested data should be replicated locally to improve
data availability and reduce query delay.
4) It considers the impact of data
availability from the neighboring node and link quality. Thus, if the links
between two neighboring nodes are stable, they can have more cooperation’s in
data replication.
3.
The Reliable Neighbor (RN) Scheme:
OTOO considers neighboring nodes
when making data replication choices. However, it still considers its own
access frequency as the most important factor because the access frequency from
a neighboring node is reduced by a factor of the link failure probability. To
further increase the degree of cooperation, we propose the Reliable Neighbor
(RN) scheme which contributes more memory to replicate data for neighboring
nodes. In this scheme, part of the node’s memory is used to hold data for its Reliable
Neighbors. If links are not stable, data on neighboring nodes have low
availability and may incur high query delay. Thus, cooperation in this case
cannot improve data availability and nodes should be more “selfish” in order to
achieve better performance.
4. Reliable Grouping (RG) Scheme:
OTOO only considers one neighboring node
when making data replication decisions. RN further considers all one-hop
neighbors. However, the cooperation’s in both OTOO and RN are not fully
exploited. To further increase the degree of cooperation, we propose the
reliable grouping (RG) scheme which shares Replicas in large and reliable
groups of nodes, whereas OTOO and RN only share replicas among neighboring
nodes. The basic idea of the RG scheme is that it always picks the most suitable
data items to replicate on the most suitable nodes in the group to maximize the
data availability and minimize the data access delay within the group. The RG
scheme can reduce the number of hops that the data need to be transferred to
serve the query.
HARDWARE & SOFTWARE REQUIREMENTS:
HARDWARE REQUIREMENTS:
·
System : Pentium IV 2.4 GHz.
·
Hard Disk : 40 GB.
·
Floppy Drive : 1.44 Mb.
·
Monitor : 15 VGA Color.
·
Mouse : Logitech.
·
Ram : 512 MB.
SOFTWARE
REQUIREMENTS:
·
Operating system :
Windows XP Professional.
·
Coding Language : C#.NET
REFERENCE:
Yang Zhang, Student Member, IEEE,
Liangzhong Yin, Jing Zhao, and Guohong Cao, Fellow, IEEE, “Balancing the
Trade-Offs between Query Delay and Data Availability in MANETs”, IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED
SYSTEMS, VOL. 23, NO. 4, APRIL 2012
