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Advances in Natural and Applied Sciences, 9(7) June 2015, Pages: 100-108
AENSI Journals
Advances in Natural and Applied Sciences
ISSN:1995-0772 EISSN: 1998-1090
Journal home page: www.aensiweb.com/ANAS
An Efficient and Novel Buffer Clustering Technique For Minimal Data Loss, Load
Balancing and Effective Queue Management in Multi Core Processors
1
Anusha, V., 2V. Parthasarathy, 3Bellamkonda Prithvi, 4Aarthi Priya Bellamkonda
1
M.E Student, vel tech multi tech Dr. Rangarajan Dr. Sakunthala Engineering College, Avadi, Tamilnadu, India.
Professor, vel tech multi tech Dr. Rangarajan Dr. Sakunthala Engineering College, Avadi, Tamilnadu, India.
B.E. Student, vel tech multi tech Dr. Rangarajan Dr. Sakunthala Engineering College, Avadi, Tamilnadu, India.
4
B.Tech Student, Holy Mary Institute of Technology, Bogaram, Hyderabad.
2
3
ARTICLE INFO
Article history:
Received 6 March 2015
Accepted 25 April 2015
Published 29 May 2015
Keywords:
Network On-Chip (Noc), System OnChip (Soc), Buffer Management, Multi
core Processors, Buffer Clustering,
and RED Algorithm.
ABSTRACT
Since buffer utilization plays a vital role in multicore processors, recent research works
have suggested various techniques to optimize the buffer utilization. As the most
recently used shared queue technique results in high throughput and power
consumption, this paper proposes a novel technique to make the buffer utilization more
efficient. The proposed work uses a clustering methodology to partition the buffers into
clusters, where each buffer holds a threshold value, based on which the data packets
will be either transmitted or discarded. Further, this paper attempts to avoid collisions
during data transmission through the implementation of RED algorithm. This work
improves the buffer utilization along with optimal power consumption and effective
throughput achievement.
© 2015 AENSI Publisher All rights reserved.
To Cite This Article: Anusha, V., V. Parthasarathy, Bellamkonda Prithvi, Aarthi Priya Bellamkonda., An Efficient and Novel Buffer
Clustering Technique For Minimal Data Loss, Load Balancing and Effective Queue Management in Multi Core Processors. Adv. in Nat.
Appl. Sci., 9(7): 100-108, 2015
INTRODUCTION
Network On-Chip (NoC) is the connection of
many cores that are integrated into a single System
On-Chip (SoC). A NoC contains routers, links, and
network interfaces. In which the routers are used to
direct the data over the links, and topology is used to
describe the logical layout. The basic process of the
network interface is to disconnect the computation
from a network. NoC contains four important aspects
they are computation, memory, communication, and
I/O (Anna Adamaszek, 2011). NOC can improve
design productivity by supporting modularity and
reuse of complex cores.
Two basic types of routing are Static Routing
and Dynamic Routing. In dynamic routing there are
three kinds of routing 1. Distance vector routing 2.
Link state routing 3.Hybrid routing. Also the routing
process can be classified into several of two types
they are 1. Unicast Routing 2.Multicast Routing. In
unicast routing, the packets have a single destination,
while in the case of multicast routing, the packets
have multiple destinations. Between unicast and
multicast routing the unicast routing is more suitable
for on-chip communication, because the unicast is
practical approach, since it’s having end-to-end
communication links between the components of the
on-chip network. Based on the routing decision,
unicast routing can be further classified into four
classes: centralized routing, source routing,
distributed routing and multiphase routing (Ankur
Agarwal, 2009).
Various routing algorithms have been proposed
for the Network On-Chip. Most researchers
suggested that the static routing algorithms are
performed well in network on-chip, and the
performance is based on the static behaviour of the
NOC process. Most NOC implementations used
either XY routing or street sign routing algorithms
(Ankur Agarwal, 2009).
Buffer management is a concept and it plays an
important role in routing process in order to achieve
efficiency. And it contains the two important
mechanisms they are buffer manager and buffer
cache. The buffer manager provides the authority to
access the database and it also updates the database.
And the role of buffer cache is to reducing the I/O
files. Buffer management is used to enhance
performance of network.
RED algorithm plays a vital role in buffer
management. RED stands by Random Early
Detection (or) Random Early Drop (or) Random
Corresponding Author: Anusha, V., M.E Student, vel tech multi tech Dr. Rangarajan Dr. Sakunthala Engineering College,
Avadi, Tamilnadu, India.
E-mail: [email protected]
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Advances in Natural and Applied Sciences, 9(7) June 2015, Pages: 100-108
Early Delay. The main objective of the algorithm is
to reduce the congestion within a network. It will
drops the packets probabilistic based on average
number of packets in the buffer, and it will use the
same probabilistic for all the flows (Sonia Jain and
EytanModiano).
Reordering Buffer Management: This problem
can occur when the number of data arrives into a
processing station and the data has to be processed.
In this case the cost of processing the data is fully
depending on the order of the processing
(Bjerregaard, T. and S. Mahadevan, 2006).
Decision Problem: This problem can occur at the
network when many packets arrive and overload
occurs (Prashant Krishna, 2013).
In proposed system the Network On-chip is
divided into local clusters by using partition
clustering algorithm, and then threshold value can be
set at each and every buffer in the cluster. If the
capacity of the buffer is ten then the threshold value
is set as eight in order to avoid bottleneck. The
incoming packet first checks the threshold value in
order to inject the packet into buffers. If the threshold
value is less than the default value then the data will
be transferred into the buffer, otherwise the data will
get discarded. This process can be done by using
RED algorithm. Within a cluster itself it will find out
the alternate buffer to inject the packets so that this
work will reduce the latency when compared to
existing work.
The remaining part of the paper discusses on the
following information: section 2 reports the literature
work done relevant to buffer utilization on network
on-chip, the simulation work of the proposed system
is presented in section 3, section 4 is recorded with
discussion on the results obtained and finally section
5 concludes the proposed work with the direction for
future enhancement.
1.
Literature Review:
Salem and NASRI (2011) reported on QoS
metric modeling using the network on-chip (NoC)
modeling in order to establish QoS metric and they
focused on the network delay bound and packet
losses. Their work is fully based on network calculus
theory which is a mathematical model used to
determine the dataflow between IP’s interconnected
over NoC. They have proposed QoS metric based on
QoS parameter. It serves for multi-application
services using calculus model.
Songpo Zhang et al (2011) described and
derivate RED algorithm in order to create the new
algorithm. They have mentioned a problem that
when the packet arrives at the gateway its having the
improper queue length of packet-marking
probability. To resolve this problem they presented a
new algorithm called SW-RED, it will dynamically
adjust the weight and offers efficient packet-marking.
Andrea Francini (2011) mentioned twofold. In
first one she mentioned due to the manner of the
RED algorithm it maps the buffer occupancy levels
onto packet drop probabilities and it will naturally
flawed. In second one she introduced Periodic Early
Detection (PED), she determined that the buffer
management system with touch less arrangement
survive 100% link utilization. For this purpose the
PED rule requires only 2.5% memory.
Wei Shi et al (2011) reported on Hierarchical
Bit-line Buffer (HiBB) for shared buffer in network
on-chip in that they mentioned corresponding to
traffics the HiBB can be configured. They have
proposed two methods to improve the router. As well
light-loaded directions and traffic situation of the
total network will be determined by using
congestion-aware output-port allocation system.
Their second proposal is to configure the shared
buffer with the help of an efficient run-time Virtual
Channel (VC) regulation scheme. By which the VC’s
are allocated with respect to loads of network.
Finally they mentioned their proposed work saves
about 6.9% area and reduces 70% power
consumption.
S.Umamaheswari et al (2012) reported on
dynamic buffer management, the main intension of
their work is to create heterogeneous router. Under
various communication requirements in fault-tolerant
adaptive NoC applications the buffer slots of the
heterogeneous router dynamically specified in order
to improve the performance. In their proposed work
in order to improve the performance the buffer slots
of the heterogeneous router dynamically re-allocated
for different applications. The number of hotspots
using EBLA (Extended Buffer Loan Algorithm)
supports the process of reallocation. The oversized
IP’s (Internet Protocols) destroyed the regular meshbased NoC architecture. The result of this process is
mesh-based NoC with irregular manner and it wants
a novel routing algorithm in case if there is any
faulty links.
Heying Zhang et al (2012) reported on multi-VC
dynamic shared buffers, they have proposed a novel
multi-VC dynamic shared buffer called DAMQ-PF
(Dynamically Allocated Multi-queue-Prefetch). This
is used to minimize the area and memory
requirement of shared buffer among multiple virtual
channels (VC). Without delay they implemented
continuous and concurrent reading and writing of the
shared buffer. Finally they mentioned that the
DAMQ-PF attains high buffer utilization, low write
and read delay and higher throughput. On NoC based
flit switch it satisfies the performance requirements
in good manner.
Daniel U. Becker et al (2012) introduced an
adaptive backpressure which is used to improve the
usage of input buffers of the router which is
dynamically managed. This is done by keep on
changing the stiffness of the flow control feedback
loop with respect to obtained traffic criteria. Based
on the measured downstream congestion the
proposed work heuristically restricts the number of
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credits available in each and every channel. The main
objective of their work is to reduce the area of the
buffer which occupied unproductively. They
mentioned that the adaptive backpressure increases
the network stability and also it reduces latency
about 31%. And also it avoids the performance
degradation.
ZHAO Jian-peng et al (2012) reported on a
congestion control scheme based on improved RED
(Random Early Detection) algorithm, in this they
have introduced an improved RED algorithm called
DFCC (Delay Feedback Congestion Control) which
is based on congestion control scheme. When traffic
occurs it will automatically adjust the link delay in
order reduce the packet loss. And their experimental
result shows that the number of packets increasing
then the packet loss of DFCC system is
comparatively lesser than RED algorithm.
Wen-Fong Wang and Yi-JhouShen (2012)
introduced a Network On-Chip concept. The
performance of the NoC increased by using
congestion management method. For a particular
message the congestion can be checked. In order to
increase the network performance and reduce the
network complexity they have proposed an idea
called (ARC) Automatic Ramp Control. Finally they
mentioned that their congestion control method is
very effective.
Maulik K. Dadhania and K. Vinay Kumar
(2012) reported on modified RED algorithm, in this
paper they mentioned when overcrowd takes place at
the router, web traffic and ECN (Explicit Congestion
mechanism) marked packets are dropped. They
proposed a solution in order to increase the response
time and the number of packets it is transmitted by
web traffic and it will not affect the throughput of the
bottleneck links. They have also tried this solution
with RED algorithm and done a test on some factors
of modified RED algorithm such as performance and
efficiency.
Neila MOUSSA and Rached TOURKI (2013)
reported on performance analysis of network onchip, in this paper they presented the analytical
model of the on chip switch architecture. It is used to
specify the physical and logical property in order to
obtain the improved performance of the on chip
switch architecture.
Chandni M Patel (2013) reported on URED
(Upper Threshold RED). The core part of this paper
is to get over from the disadvantages of the RED
algorithm. So that he introduced a new algorithm
named URED. By made some changes in the existing
algorithm he created a new algorithm. The new
technique is efficient than the previous algorithm and
also it works opposite to DDoS (Distributed Denial
of Service) attack. He has done a simulation in NS2.35 simulator environment. And his simulation
results showed that the URED algorithm provide
better performance than RED and also adaptive
RED, as well he done a comparison between these
two algorithms. The comparison metrics are total
average throughput, total packet drops and average
packet drops.
Salem and Nasri (2011) presented a new NoC
QoS metrics modeling which is based on QoS
parameters. In the NoC nodes he quantifies the buffer
requirements and packet switching technique by
done analysis on End-to-End delays and packet loss.
Their work is fully focused on flit losses which is
occur because of buffer congestion for a network
loading. By which they determine the optimal buffer
size for switch design, this based on the wormhole
routing method.
FaridDaneshgar and MajidTaghipoor (2014)
reported that they proposed a novel algorithm named
DAMQSV and DAMQS. These mechanisms are
used in system on-chip applications and it requires an
interconnection network. These algorithms are used
to optimize the buffer management in an effective
manner with good performance when there is larger
network load and it occupies only lesser amount of
buffer space. They have done simulation on
Modalism environment to test the performance of
these algorithms. During the simulation process they
considered many factors such as different traffic
mode, network size, virtual channel number, buffer
size per virtual/physical channel and routing
protocols. They concluded that these algorithms are
efficient especially DAMQSV is more efficient.
K.Malathi and S.VivekPandian (2014) reported
that they mentioned the solution to overcome the
design complexity in network. They introduced a
buffer less router in order to avoid the design
complexity. And also they discussed the impact of
power reduction.
V.Parthasarathy and V.Rajamani (2008) they
introduced a new techniques called as flow discard
and early flow discard. These techniques are used to
analysis the performance of routing and switching in
optical IP networks. By using these techniques they
achieved the lower loss rate which is about 24.95%
and in optical packet routing which is 71.17%.
V.Parthasarathy et al (2009) presented a new
scheme for contention resolution in bulk flow TCP
routing in optical IP network. Also they had done a
simulation work. They studied about packet loss rate
and flow loss rate for both fixed size and variable
size flows. And they achieved the flow loss rate
about 0.038 for variable size flow and flow loss rate
about 0.043 for fixed size flows intended for 200
packets transmission.
2.
Experiment:
This session includes the experimental part of
above mentioned work.
The above mentioned snap shot indicates the
cluster formation of network on-chip in 16 numbers
of processors with buffers. Each cluster having its
own source to transfer the data into buffers. In that
threshold value can set at each and every buffer in
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the local cluster. Threshold value is 75% of buffer
capacity in order to avoid bottleneck. The connection
between the clusters are virtual not physical, but the
connection within the cluster is physical.
Fig. 1: Cluster Formation of Network On-Chip.
Fig. 2: Packet Transformation in Network On-Chip.
The incoming packet from the source first
checks the threshold value of the corresponding
buffer. If the buffer having the empty space in it the
data will be transmit into the processor of the
corresponding buffer, or else the packet will be
transferred into the buffer of the another processor in
the same cluster itself.
Here the data is enter into buffer, because in this
case the buffer having the empty space in it. After
sometimes it will transmit into the processor for the
particular process. So that here the buffer space is
utilized in higher level and also efficient too. Within
the cluster itself it will find out the buffer space so
that it will take only lesser amount of time.
This snap shot indicates the successful
transformation of packet into the processor. In this
case the data is transferred into the processor.
The above mentioned snap shot indicates the
process which takes place in another cluster in the
network on-chip. In this case the incoming packet
from the source first enter into the buffer, here the
data checks the threshold value of the buffer. Here
the threshold value exceeds its level so that the data
is transferred into another buffer in the same cluster.
Here also the data checks the threshold value of the
buffer.
In this buffer also the threshold value exceeds its
level. Finally the data get dropped due to the
insufficient space in the buffer of the corresponding
processor. But, the packet drop will occur only at
certain cases not frequently. The packet drop will not
affect the performance of the buffer.
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3.
Result and Analysis:
The proposed work will reduce the time taken to
find out the empty space in the buffer as well it will
reduces the network traffic. Data loss also will be
Fig. 3: Checking Threshold Value.
Fig. 4: Successful Transformation of Packet.
Fig. 5: Checking Threshold Value.
low in this proposed work. The following graph will
show the comparison between existing and proposed
system in terms of data loss, buffer utilization,
throughput and latency.
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Fig. 6: Packet Drop.
This graph indicates the data loss between
shared queues and cluster method. When compared
to shared queues that are conventional method data
loss is low in cluster based method. Because in
conventional method the data have to search for the
empty buffer on the whole network. So, it traverse
the long distance on the network during this
travelling it may loss many data compared to cluster
based method.
This graph indicates the buffer utilization
between conventional method and cluster based
method. The cluster based method utilizing the more
buffer space when compared to conventional based
method because in this case it will uses the utmost
buffer space until it attain the threshold value. As
well it’s having one of the added advantages that it
avoids the problem of bottleneck occurrence.
This graph is about throughput between
conventional method and cluster based method.
Throughput is higher in cluster based method
because of the clustering technique. It will find out
the buffer space within the cluster itself so within
short span of time it will find the buffer space as well
it transfers the large amount of data.
This graph is about latency between
conventional method and cluster based method.
Latency is low in cluster based method because
within a local cluster itself it will find out the empty
buffer space so, comparatively latency is low in
cluster based method. In case of conventional
method the data searches for the empty space on the
whole network so it will take large amount of time to
find out the empty buffer space.
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4.
Conclusion:
In order to efficiently utilize the buffer space in
the multicore processor, the proposed work uses the
clustering methodology and partitions the buffers
into clusters. The threshold value assigned to each
buffer in the cluster allows determining the
availability of the buffer for packet transmission. The
RED algorithm implemented in this paper ensures
the avoidance of collision during the data
transmission. Thus, the proposed work optimizes the
buffer utilization and achieves reduced throughput
and power consumption compared to the existing
shared queue technique in the multicore processor.
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