Circuits and Systems, 2013, 4, 401-406 Published Online September 2013 (
Cluster Based Hierarchical Routing Algorithm
for Network on Chip
U. Saravanakumar1, R. Rangarajan2, R. Haripriya2, R. Nithya2, K. Rajasekar1
1Department of Electronics and Communication Engineering, PSG College of Technology, Coimbatore, India
2Department of Electronics and Communication Engineering, Indus College of Engineering, Coimbatore, India
Received July 12, 2013; revised August 12, 2013; accepted August 19, 2013
Copyright © 2013 U. Saravanakumar et al. This is an open access article distributed under the Creative Commons Attribution Li-
cense, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
This paper presents a new logical mechanism called as Cluster Based Hierarchical Routing (CBHR) to improve the ef-
ficiency of NoC. This algorithm comprises the following steps: 1) the network is segmented logically into clusters with
same size or different sizes; 2) algorithms are assigned for internal and global routing; 3) routers working functions are
modified logically to support local and global communication. The experiments have conducted for CBHR algorithm
for two dimensional mesh and torus architectures. The performance of this mechanism is analyzed and compared with
other deterministic and adaptive routing algorithms in terms of energy, throughput with different packet injection ratios.
Keywords: System on Chip; Network on Chip; Deterministic and Adaptive Routing Algorithms; Mesh ; Torus
1. Introduction
A number of processors in bus based System on Chip
(SoC) are increased continuously and they face design
challenges in different aspects [1]. This bus architecture
has faced bottleneck problem when more processors in-
tegrated into single chip. To avoid bottleneck, bus archi-
tecture is replaced with network architecture which is
similar to the data networks. This new technology is
known as Network on Chip (NoC) and it is widely ac-
cepted as a solution for communication issues in SoC.
Data communication between the processors is pack-
etized and transmitted throughout the entire network [2,
3]. The basic components of NoC are processors, memo-
ries, routers and physical links. All the processors, mem-
ory blocks and other cores are connected to routers using
physical links. The routers are interconnected to each
other directly or through other intermediate routers. The
role of router is to make decision where the data is to be
transmitted based on destin ation address in the head er flit
of message packet [4-6]. A routing algorithm plays a ma-
jor role in NoC that helps to communicate one processor
to other processors or memory. This paper presents dif-
ferent routing algorithms such as XY—routing algo-
rithm, OE—turn routing algorithm, and Pseudo adaptive
routing algorithm. Additionally new algorithm has also
proposed in this paper to achieve better performance for
different NoC architectures. These routing algorithms
have implemented on different NoC architectures such as
two Dimensional Mesh and Torus.
The rest of this paper is organized as follows: In Sec-
tion 2, NoC architectures are described; the determinis-
tic and adaptive routing algorithms and proposed CBHR
algorithms are explained in Sections 3 and 4 respectively;
Sections 5 deals with experimental results and discus-
sions of the algorithms.
2. NoC Architectures
The different network topologies like mesh, ring, star,
and torus are used in MPSoCs to overcome the commu-
nication issues. Additionally, some hybrid topologies have
also proposed by VLSI designers especially for multi-
processor SoCs. This section deals with popular network
A mesh-shaped network consists of m columns and n
rows. The 2D mesh architecture is shown in Figure 1(a)
which consists of 16 Processing Elements arranged in 4 ×
4 matrix structure. The routers are situated in the in-
tersections of two wires and the computational resources
are near routers. Addresses of routers and resources can
be easily defined as (x, y) coordinates in mesh. Regular
mesh network is also called as Manhattan Street network.
A Torus network is an improvement of basic mesh
network. A simple torus network is a mesh in which the
heads of the columns are connected to the tails of the
opyright © 2013 SciRes. CS
columns and the left sides of the rows are connected to
the right sides of the rows [7].
Torus network has better path diversity than mesh
network, and it has more minimal routes. Torus archi-
tecture is shown in Figure 1(b). Torus is same as regular
mesh except additional links in every row and column
(red colour links in Figure 1(b)). In mesh, edge switches
are connected only to two neighboring switches, the torus
architecture uses wrap-around channels in order to con-
nect the switches at the edges to the switches at the op-
posite edge. The number of switches is equal to the num-
ber of IP blocks and every switch has five ports. Due to
the long wrap-around channels the packet transmission
delay may become significantly long and require usage
of repeaters. Folding is done by shifting all nodes in even
rows to the right and all nodes in even positions of each
row down, next connecting all the neighbouring nodes in
newly gained rows and columns then pair-wise connect-
ing edge nodes in rows and columns. The wraparound
links are significan tly shor ter an d link p ropag atio n de lays
fit within a single clock cycle [8].
3. Deterministic and Adaptive Routing
3.1. Deterministic Algorithm
The traditional XY routing algorithm for multi-compu-
ters is first proposed by Intel Corporation and adap ted for
NoC by Wang Zhang et al. The working func tion of XY
and YX routing algorithm is described in Figure 2. In
XY algorithm is performed the routing function by in-
creasing the x coordinate value of routers in the network
from source until reaching the column of destination
router and then start to increase the value of y coordinate
until reaching destination router. After reaching the des-
tination router, the message forwards to corresponding
processor. In case of YX routing algorithm, the packet is
routed by increasing y coordinate value first and increas-
ing x coordinate value next. The XY/YX algorithm is
simple to implement in any kind of network those are
having mesh structure [9-11].
(a) (b)
Figure 1. NoC Architectures: (a) 2D Mesh; (b) Torus.
3.2. Adaptive Routing Algorithm
The Odd-Even turn algorithm is proposed by Chiu for
two dimensional mesh networks with no virtual channels.
Figure 3 shows the possible routing path based on adap-
tive algorithm. It is a kind of distributed adap tive routing
algorithm and the main advantage of this algorithm is
deadlock free by restricting some of the turns. This algo-
rithm is also suitable for torus network. In a two-dimen-
sion mesh with dimensions n x m each node is identified
by its coordinate (x, y). A column is called even if its x
dimension element is even numerical column and odd if
its x dimension element is an odd number. A turn is a
90-degree turn in the following description. There are
eight types of tu rns, according to th e travelling direction s
of the associated I/O ports. A turn is called an ES turn if
it involves a change of direction from East port to South
port. Similarly, other seven types of turns are defined as,
EN, WS, WN, SE, SW, NE, and NW turns, where E, W,
S, and N indicate East, West, South, and North, respec-
tively [12,13].
The OE turn algorithm performs the routing function
based on two conditions and they are described in the
Figure 4.
Condition 1: Any packet is not allowed to take a turn
from East to North at any routers located in an even
column, and it is not allowed to take a turn from North to
West at any nodes located in an odd column
Condition 2: Any packet is not allowed to take a turn
from East to South at any routers located in an even
column, and it is not allowed to take a turn from South to
West at any nodes located in an odd column
The adaptive odd—even turn routing algorithm is
more complex than classic XY routing algorithm but it
provides deadlock free condition.
Figure 2. Deterministic algorithms for mesh NoC.
Copyright © 2013 SciRes. CS
3.3. Pseudo Adaptive Routing Algorithm
The pseudo adaptive routing algorithm is proposed by
Dehyadgari et al. This algorithm is developed based on
both deterministic and adaptive approach with respect to
the network load. If the network load is low, th e packet is
routed using classic XY routing algorithm (deterministic)
else the packet is routed using adaptive mode. The con
gestion in the routing p ath can be iden tified by setting the
Figure 3. Adaptive routing algorithm for mesh NoC.
Figure 4. Conditions to perform adaptive algorithm.
threshold level for input buffer in the router. The thresh-
old value is fixed as 100% free (ready to receive a data),
75% free (assume buffer is loading with data), 50% free
(assume buffer is full) and 100% busy (can’t ready to
receive a data). Based on the threshold value, the router
decides the port where the data to be routed. This algo-
rithm offers possible paths from source to destination
with low traffic load before receiving the status of heavy
traffic [9].
4. CBHR Algorithm
The deadlock free is the main concept in any network
and different routing algorithms have proposed to achieve
the same. One of the method is, hierarchical routing
scheme proposed by Holsmark et al. In their work, each
subnet works perform the routing function using internal
routing algorithm and each subnets are interconnected
with global routing algorithm. In this chapter, a cluster
based hierarchical routing logic is introduced. The entire
network is divided into several clusters logically and its
size can be varied depends on network size as shown in
Figure 5. The clusters in the network are standalone net-
work and the routers do not bother about other clusters
In this work, the two different network sizes 4 × 4 and
8 × 8 are considered. For 4 × 4 network architecture, it is
divided into four clusters and each having four routers.
For 8 × 8 network architecture, it is divided into four
cluster wi th 16 routers or 16 clusters wit h 4 routers.
4.1. CBHR Protocol
The packets are routed to the destination in the same
cluster or other clusters in the network using internal
Figure 5. CBHR concept in NoC architectures.
Copyright © 2013 SciRes. CS
cluster or other clusters in the network using internal
routing or external routing algorithm. If the destination
address is in the same cluster, internal routing can be
done by tagging the additional information of cluster id
and destination router id. If the destination address is in
the different cluster, the routing can be done through
boundary nodes and some additional information of
cluster id, boundary router id and destination router
address. Figure 6 shows the dedicated packet format for
CBHR based NoC.
4.2. Routing Function
In the CBHR, the routing function first takes the details
of header flit in the pack et which contains th e destination
router address and cluster id if the destination in the same
data header
cluster id destinati on id
data header
cluster id destinati on id
boundary router id
Figure 6. Packet format if (a) destination in same cluster (b)
destination address in different c l uste r.
Figure 7. CBHR for mesh NoC.
cluster or cluster id, boundary router id and destination
router id if the destination router in the different netwo rk.
Consider the case 1: from the header flit information, if
both the cluster id and router address are equal then the
corresponding port is set to the local PE. Otherwise, in-
ternal routing function (in this case XY for domain 1
which consist of clusters 1 and 3 or OE for domain 2
which consist of clusters 2 and 4) is called with destina-
tion router address. Consider the case 2: if the cluster ids
are different, the external routing function (in this case
pseudo adaptive is selected in order to identify the net-
work load and avoid congestion) is invoked with cluster
id and boundary router id. Th e working functio ns of two
cases are clearly described in Figure 7. The boundary
routers are designed using logical concept to adopt both
internal and external routing algorithms.
The router to support CBHR is designed with two ad-
ditional concepts, one is comparator to compare the des-
tination address and current address with cluster ids and
another one is multiplexer to select routing func tion to be
done whether it is internal or global. The routers in the
boundary regions are designed with threshold value as
discussed earlier to identify the congestion in the net-
work. As like in mesh NoC, the CBHR algorithm is ap-
plied on torus NoC but the cluster size has varied. In
Figure 8, the brown colour routers are identified as
boundary routers, that are support both deterministic and
adaptive algorithm. Here also, the classic XY algorithm
and OE algorithm are used for local routing in cluster 1
and 2 respectively. The pseudo adaptive algorithm is
Figure 8. CBHR for torus NoC.
Copyright © 2013 SciRes. CS
used as a global routing mechanism for data transmission
from one cluster to another cluster.
5. Simulation Results and Discussions
The two dimensional mesh and torus architectures with
16 and 64 PEs are considered for the evaluation of
XY/YX, OE and CBHR algorithms. These algorithms are
simulated in Network Simulator under Linux environ-
ment. To understand the effective of routing algorithms
on NoCs, throughput and energy are assumed as evalua-
tion metrics. The experiments are conducted for routing
algorithms with two different packet sizes 210 and 512 in
60 seconds’ simulation time. For simulation purpose, the
distance between source router and destination routers
are considered in three categories named as minimum
(Number of links in 16 PEs: 1 and 64 PEs: 1), moderate
(Number of links in 16 PEs: 4 and 64 PEs: 7) and maxi-
mum (Number of links in 16 PEs: 6 and 64 PEs: 14).
Finally the performances of these three algorithms are
compared for mesh and torus NoC architectures with
different packet sizes. The energy consumption for data
transmission from source to destination using XY, OE
and CBHR algorithms are described in Figure 9 and the
values are listed in Table 1 under packet size of 210 and
512. For both mesh and torus NoC architectures, the
CBHR algorithm works very well. The CBHR algorithm
consumes the energy of 36.345 J and 28.881 J to transmit
Energy in J
Mesh (PS=210) Mesh(PS=512)Torus(PS=210) Torus(P S=512)
Energy Consumption
Figure 9. Energy comparison of routing algorithms with
210 and 512 packet sizes.
Table 1. Energy consumption of routing algorithms.
Energy Consumption (J)
8 × 8 Mesh 8 × 8 Torus
210 46.9 48.2 44.23 29.3 33.5 30.9
512 40.5 42.4 36.3 33.5 35.4 28.9
za packet size of 512 for maximum distance range in
mesh NoC and torus NoC respectively. Therefore, the
CBHR algorithm consumes 16.8% less energy than OE
algorithm and 11.1% less than classic XY routing algo-
rithm for mesh NoCs. For torus NoC, the CBHR algo-
rithm consumes less energy 22.7% than OE and 15.9%
than classic XY routing algorithm. The throughput of
algorithms for 8 × 8 mesh and torus NoCs with 210 and
512 packet sizes are described in Table 2. From the Ta-
ble 2, the throughput of the CBHR algorithm on torus
NoC is higher than other algorithms on different NoC ar-
The throughput of routing algorithms for NoC in terms
of Kbps is compared in Figure 10 with 512 as a packet
size. As a result, the new logic CBHR on torus NoC is
more efficient than XY and OE algorithms on mesh and
torus NoC architectures. But this new algorithm performs
very well in NoC with more number of processors than
NoC with less count of processors.
The simulation results show that, there is no major
improvement in 16 PEs No C but it shows better result in
64 PEs. The estimation from ITRS in 2011, the number
of processors is increased gradually. For those cases, this
type of hybrid routing logics helps to improve the per-
formance of NoC architectures.
6. Conclusion
In this paper, both deterministic and adaptive routing
algorithms have been discussed for NoC architectures. A
new logical approach called Cluster Based Hierarchical
Table 2. Throughput of routing algorithms for mesh and
torus NoC.
Throughput (packets/60 seconds)
8 × 8 Mesh 8 × 8 Torus
2104737.84933.036214.1 4875.4 5239.16712.4
5124199.14649.065673.4 4307.3 4927.25990.2
Throu ghput in
Figure 10. Throughput comparison.
Copyright © 2013 SciRes. CS
Copyright © 2013 SciRes. CS
Routing (CBHR) algorithm for NoC is introduced. To
evaluate the performance of routing algorithms, two dif-
ferent NoC architectures such as two dimensional mesh
and torus are considered with various sizes. This CBHR
helps to reduce the energy consumption considerably in
torus architecture. The simulation results also show that,
throughput is increased for NoC with more processors.
[1] ITRS, International Technology Roadmap for Semicon-
ductors, 2012.
[2] T. N. Theis, “The Future of Interconnection Technology,”
IBM Journal of Research and Development, Vol. 44, No.
3, 2000, pp. 379-390. doi:10.1147/rd.443.0379
[3] W. J. Dally and B. Towles, “Route Packets, Not Wires:
On-Chip Interconnection Networks,” Proceedings of the
38th Design Automation Conference (DAC), Las Vegas,
18-22 June 2001.
[4] T. Bjerregaard and S. Mahadevan, “A Survey of Research
and Practices of Network-on-Chip,” ACM Computing
Surveys, Vol. 38, No. 1, 2006.
[5] L. Benini and G. De Micheli, “Networks on Chips: A Ne w
SoC Paradigm,” Computer, Vol. 35, No. 1, 2002, pp. 70-
78. doi:10.1109/2.976921
[6] J. Nurmi, “Network-on-Chip: A New Paradigm for Sys-
tem-on-Chip Design,” Proceedings of International Sym-
posium on System-on-Chip, Tampere, 17 November 2005,
pp. 2-6.
[7] J. Henkel, W. Wolf and S. T. Chakradhar, “On-Chip Net-
works: A Scalable, Communicationcentric Embedded Sys-
tem Design Paradigm,” Proceedings of 17th International
Conference on VLSI Design, Mumbai, 5-9 January 2004,
p. 845. doi:10.1109/ICVD.2004.1261037
[8] W. J. Dally and C. L. Seitz, “Torus Routing Chip,” Dis-
tributed computing, Vol. 1, No. 4, 1986, pp. 187-196.
[9] M. Dehyadgari, M. Nickray, A. Afzali-kusha and Z. Na-
vabi, “Evaluation of Pseudo Adaptive XY Routing Using
an Object Oriented Model for NOC,” Proceedings of the
17th International Conference on Microelectronics, Is-
lamabad, 13-15 December 2005.
[10] Intel Corporation, “A Touchstone DELTA System De-
scription,” Intel Corporation, Portland, 1991.
[11] S. Lillevik, “The Touchstone 30 Gigaflop DELTA Proto-
type,” Proceedings of 6th Distributed Memory Computing
Conference, Portland, 28 April-1 May 1991.
[12] G.-M. Chiu, “The Odd-Even Turn Model for Adaptive
Routing,” IEEE Transactions on Parallel and Distributed
Systems, Vol. 11, No. 7, 2000, pp. 729-738.
[13] W. Zhang, L. Hou, J. Wang, S. Geng and W. Wu, “Com-
parison Research between XY and Odd-Even Routing
Algorithm of a 2-Dimension 3X3 Mesh Topology Net-
work-on-Chip,” Proceedings of the WRI Global Congress
on Intelligent Systems (GCIS '09),” Washington DC,
19-21 May 2009, pp. 329-333.
[14] R. Holsmark, S. Kumar, M. Palesi and A. Mejia, “HiRA:
A Methodology for Deadlock Free Routing in Hierarchi-
cal Networks on Chip,” Proceedings of 3rd ACM/IEEE
International Symposium on Networks-on-Chip, San Die-
go, 10-13 May 2009, pp. 2-11.