EasiTPQ：QoS Based Topology Control in Wireless Sensor Network
LIU Wei
CUI Li
Institute of Computing
Technology, Chinese Academy of
Sciences, Beijing 100080
Institute of Computing
Technology, Chinese Academy of
Sciences, Beijing 100080
1
LI Tian Pu
2
Graduate University of Chinese
Academy of Sciences, Beijing
100049
Abstract
With the rapid development of wireless sensor network,
I
1nstitute of Computing
TechnolIogy, Chinese Academy
of Sciences, Beijing 100080
2
Graduate University of Chinese
Academy of Sciences, Beijing
100049
consumption is an important design criterion for sensor
networks, since it is directly related to the network
the requirements for quality of service are growing,
lifetime. Topology control and management is an
particularly in applications where real time imaging,
effective way to control the power level of the network.
video or audio communications are involved. The system
Here how sensor nodes cooperate with each other to
needs to meet optimized energy consumption design
create an efficient and connected network to upper layer
criterion and to satisfy certain QoS requirements at the
is the major problem in topology control process.
same time from long view.
Most of the existing works
Although most of the applications are dealing with
deal with resource allocation (e.g., scheduling or
small data flow obeying the principle of best effort, the
buffering) or routing strategy to achieve QoS. In this
high-speed data flow, however, have to be sustained
paper, we propose to extend QoS support to the topology
from long view. This trend looks more apparent with the
control layer by introducing a number of active nodes
introduction of hybrid sensor networks [2]. In this work,
distributed in a gradient fashion based on their logical
research was focused on a QoS-based topology control
distances to the sink node. Present a novel topology
algorithm which can reduce packet loss rate and latency
control algorithm, namely EasiTPQ (Easy QoS based
in networks where some sensor nodes generate
topology control) for QoS improvement in wireless
high-speed data to sink simultaneously. Energy saving
sensor networks. Simulation results show that data loss
scheme was also designed. Nodes which have little
rate and latency are averagely improved by 60% and
contribution to QoS guarantee were scheduled to sleep to
55%, respectively.
prolong the life time of the network.
The rest of this paper is organized as follows: Section
Key words: gradient change density; QoS; state transmission
II summarizes the related works. Section III describes
our QoS-based topology control algorithm and analyzes
1. Introduction
some crucial parameter selections from simulation.
Finally, Section IV concludes the paper.
A wireless sensor network is composed of a large
number of tiny and inexpensive sensor nodes which can
2. Related Works
compute and communicate by wireless [1]. Sensor nodes
can be deployed densely on a large scale and are hard to
be re-collected and recharged. Thus the level of energy
In topology control, both powering off redundant
nodes and lowering radio power while keeping the
This research was supported by NSFC key project under Grant No. 60533110;
NSFC general project under Grant No. 60572060; CAS “Project of 100 Talents”.
network connected can contribute to power-saving.
transmitting data. The data transmission mode is usually
However, powering off unnecessary nodes can achieve
in a multi-to-one fashion where more relay data flows
better results [3-5].
are transmitted by nodes closer to the sink. Hence for
Since sensor nodes have limited capability of
those interior nodes, the tasks of transmitting data may
computing and limited memory space to storage data, the
be quite heavy with more relay data than local generated
QoS solution for sensor networks can not simply follow
data. Meanwhile the exterior nodes transmit local
those for broad-band networks. Moreover, sensor
collected data mostly. The most exterior nodes have only
network is highly oriented to applications, so that a
got local collected data to transmit.
“fits-all” QoS solution is unlikely existing.
Sequential Assignment Routing (SAR) [6] is the first
3.2. Gradient Topology Structure
protocol for sensor networks that includes a notion of
QoS. Assuming multiple paths to the sink node, each
3.2.1 EasiTPQ Design
sensor uses a SAR algorithm for path selection. It takes
into account the energy and QoS factors on each path.
SPEED [7] is similar to SAR. The protocol requires
Based on the above analysis, the proposed QoS-based
topology control
algorithm,
namely
EasiTPQ,
is
each node to maintain its neighbor’s information. In
designed by reducing exterior redundant nodes and
addition, SPEED strives to ensure a certain speed for
increasing interior active nodes simultaneously to create
each packet delivery so that each application can
a gradient topology structure aiming to meet QoS
estimate the end-to-end delay for the packets by
requirements, e.g. the data loss rate and latency. Fig.1
considering the distance to the sink and the speed of the
illustrates the nodes category created by our EasiTPQ
packet delivery before making the admission decision.
algorithm.
For real-time traffic generated by imaging or video
sensors, the protocol presented in [8] finds a least cost
and energy efficient path that meets certain end-to-end
delay requirement.
More recently, hybrid sensor network attracts more
attention. A three-tired architecture presented in [2] are
composed of normal data collection nodes, data relay
nodes and data relay gateway. A path composed of high
capacity and little latency nodes can be selected
Fig.1 Architecture of EasiTPQ
There are three types of nodes in EasiTPQ: (a) NA
3. QoS-Based Topology Control (EasiTPQ)
(Not Active) nodes which are nodes in sleep mode, (b)
CA (Connectivity Active) nodes which are scheduled to
3.1. The Feasibility and necessity of EasiTPQ
work for network connection and (c) QA (QoS Active)
nodes which are scheduled to work for extra sustain to
Existing research on QoS problem in wireless sensor
meet for QoS requirements. The main design criterion of
network is focused on how to find a proper data path in
EasiTPQ is to add QA nodes as few as possible to satisfy
pre-existing network topology on the hypothesis that this
certain QoS requirements.
path exists. Actually path satisfying all the QoS
Three definitions are introduced as below:
requirements does not always exist， especially topology
Definition 1: Node’s active power value AP:
control scheme is adopted.
AP denotes the value or capacity to become an
By analyzing the architecture of WSN, we conclude
that each node in network has different functionalities in
active node.
AP   
e
   NT
E
（1）
Thus
hi (n ) represents the active neighbor number of
Where e is node’s remaining power, and E is node’s
initial power. N T （Neighbor Total） is the number of
local node which have a hop count i to sink node.
node’s neighbor it can communicate whiles in non-sleep
3.2.2 EasiTPQ implementation
state. N T reflects the importance of node in the
network and can be used to differentiate crucial nodes
from other normal ones.  and  are the weight
In EasiTPQ, nodes are in one of the four states: R_Test,
R_Passive, R_Active and R_Sleep. Fig.2 shows a state
transition diagram.
value between this two parameters, and can be flexibly
configured according specific application.
Definition 2: The sorting function Ap
The function  (N ) is the value order of local node’s
Ap among all Ap values it can hear.
 ( N )  {N : Ap _ local  Ap (i ), 1  i  N }
A p _ local is the
(1) Initially, only sink node is in the active state and
Ap value of local node, and
Ap (i ) is other node’s Ap value this local node can
hear at its R_Test stage. So definition 2 reflects a
Ap sorting relation between local nodes and its
neighbors.
Definition 3: Gradient descending function (M )
(M )
is the relation between node’s active
neighbor number and its hop count to sink.
( M )1  hi (n)  M  (i  1)
( M ) 2  hi (n)  M  i  1
Fig.2 Diagram of EasiTPQ state transitions
(2)
（3-1）
（3-2）
In this paper, we focus our attention mainly on two
types of function, including a liner descending function
and a square root descending function described in
other nodes are in R_Passive state with their radio on to
overhear all packets transmitted by their active neighbors.
No data packets are forwarded in this state since this is a
listen-only state.
(2)
Sink node
sends Topo_Initial command
by
broadcasting which informs nodes in network to enter
the process of EasiTPQ algorithm.
(3) Nodes received Topo_Initial command enters R_Test
state from R_Passive state, and start to exchange data
and routing control messages.
(4) Nodes in R_Test state start to broadcast message
including AP value and, at the same time, to set up a
timer Tt. When Tt expires, the node enters the R_Active
state. Before Tt expires, if the node finds that the average
data loss rate
PL is higher than the average loss before
formula (3-1) and (3-2) respectively. The reason of
entering in the R_Test state, then the node moves into the
R_Passive state. N 0 is the active neighbor count need
selecting these two types of function is that these two
to be decided with a minimal value of N min . N min is
simple functions can be used as examples to evaluate the
effect of node’s gradient distribution schemes to the
set in view of the basic network connectivity target [9].
From above information we know that N 0 is a crucial
overall QoS performance of the network. M is the initial
parameter in EasiTPQ and this value has a gradient
number of neighbors and is often set by the value of the
diameter of network. i is the hop count between each
property which changes according to hop count from this
node to the sink. P0 is the average data loss before
node to the sink node and the initial value is set to 1.
entering in R_Test state, which is the influence of data
loss rate when this node enter the data transmission
root descending scheme).
process.
1200
(5) Nodes in R_Passive state set up a timer Tp. When Tp
the data loss rate PL higher than PT , the node makes a
transition to the R_Test state to transmit data. PT denotes
the minimal data loss rate application required, which is
1000
Latency(ms)
expires, the node enters the R_Sleep state. Before Tp
expires, if the number of neighbors is below N min or
LA1
LA2
LA3
a parameter related to the QoS property.
800
600
400
200
(6) Nodes in R_Active state transfer to R_Test state after
0
a period of time Ta to detect whether it should become an
4
8
12
16
20
24
data rate(kbps)
inactive node. This detection process may balance the
power consumption among nodes, and may avoid the
crucial nodes consume all its power to make other nodes
30
Packet loss rate(%)
logically broken down (e.g. could not transmit data
continually). A node which enters the R_Sleep state turns
the radio off, sets a timer Ts, and goes to sleep. When Ts
expires, the node moves into R_Passive state.
After all above procedures, the active nodes form a
network architecture consisting of three types of nodes.
The neighbor number N min ensures the basic network
20
15
10
5
0
connectivity [9], while other active nodes or QA nodes
4
ensure some QoS performance in network.
8
12
16
20
24
data rate(kbps)
3.3. Performance evaluation and parameter
analysis
PL1
PL2
PL3
25
Fig.3 Packet loss rate and Latency
From Fig.3, we can see that
(a) The performance in PL2 is improved by 50%
In the simulation part, we use NS2 simulation tools
Averagely than that of PL1, which can verify the
and choose parameters as below:   0.6 ，
  0.4 , PT  15 % ，Tp=2min，Ts=2min，Tt=4min，
efficiency of adding QA nodes?
Ta=4min， N min =2, and node number is 120. Network
exceed certain value. This may because those more extra
performances were examined according to different
 (N ) schemes as shown in (3-1) and (3-2),
active QA nodes in exterior circle may cause more
respectively.
threshold, the negative effect of channel competition will
The simulation results of data loss rate and data
(b) The performance of PL3 decrease fast when data rate
channel competition. When data rate exceeds some
suppress the QoS contribution by these extra active QA
latency are shown in Fig.3. PL1 and LA1 is the initial
nodes.
network data loss rate and data latency whose topology
(c) PL3 has an improvement by 70% in the data rate
is obtained by ASCENT [9]. PL2 and LA2 is the network
range of 0-20Kbps.Many real time imaging and audio
data loss rate and data latency whose topology is
communications are in this range. Other applications
obtained by EasiTPQ using formula (3-1) (in a liner
with higher data rate than the threshold may choose PL2
descending scheme). And PL3 and LA3 is the network
scheme for better QoS performance.
data loss rate and data latency whose topology is
(d) The latency from node to sink of LA3 is always less
obtained by EasiTPQ using formula (3-2) (in a square
than that of LA1 with an improvement by 40% in
average. This may because those packages successfully
adjustment,” in Proc. IEEE INFOCOM, 2000, pp. 404–413.
transmitted have more easy access to MAC channel, so
[Online]. Available: citeseer. nj.nec.com
less channel access latency can be acquired.
/ramanathan00topology.html
(e) LA2 has a very good latency performance. The
[4] G.C˘alinescu, I.M˘andoiu, and A.Zelikovsky, “Symmetric
latency of LA2 is less than that of LA1 with an
connectivity with minimum power consumption in radio
improvement by averagely 70% in the data rate range of
networks,” in 2nd IFIP International Conference on Theoretical
0-20Kbps. This may because that LA2 scheme both have
Computer Science (TCS 2002). Kluwer Academic Publishers,
a less channel access latency and have less extra hop
2002, pp. 119–130.
latency compare to LA3 scheme in that data rate range.
[5] M.Stemm and R.H.Katz. Measuring and reducing energy
But when the data rate exceeds some threshold the MAC
consumption of network interfaces in hand-held devices. IEICE
latency might be apparent compared to other factors
Transactions on Communications, E80-B(8):1125–1131, Aug.
which are the same as LA1, if considering the extra hop
1997.
latency the larger latency may occur.
[6] B.Chen, K.Jamieson, H.Balakrishnan, and R.Morris. Span:
An energy-efficient coordination algorithm for topology
4. Conclusions
maintenance in ad hoc wireless networks. ACM Wireless
Networks, 8(5), September 2002.
The EasiTPQ algorithm proposed in this paper is a
[7] C. Schurgers, V. Tsiatsis, and M. Srivastava. STEM:
QoS based topology control algorithm. EasiTPQ makes
Topology management for energy efficientsensor networks. In
use of the fact that each node in network has different
IEEE Aerospace Conference,pages 78–89, March, 2002.
functionalities in data transmission, e.g., some nodes
[8] K. Sohrabi, J. Gao, V. Ailawadhi and G. Pottie, “Protocols
bear more data relay tasks whilst some other nodes only
for Self-Organization of a Wireless Sensor Network, ” IEEE
transmits data generated by itself. EasiTPQ schedule
Personal Communications, pp. 16-27, October 2000.
more nodes active if these nodes are responsible more
[9]
to “relay” data tasks. Simulation results show that
selfconfiguring sensor network topologies. In Twenty
EasiTPQ enables improved data loss rate and delay
First International Annual Joint Conference of the IEEE
performance by 60% and 55% respectively compared with
Computer and Communications Societies (INFOCOM),
another existing topology control algorithm such as
June 2002
ASCENT. EasiTPQ is more useful if the data rate range
is within a certain range. The QoS problem is highly
oriented to application in wireless sensor network.
Further experimental or simulation works need to be
carried out to study the concrete parameter settings for
particular applications.
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