Congestion Control for Wireless Sensor Networks (Dhawan):

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A
BSTRACTS OF THE
REU

S
UMMER
2010

PROGRAM


Congestion Control for Wireless Sensor Networks

(Dhawan):

Congestion control is defined as the proble
m of controlling traffic entry into a data network. The
objective behind doing this is to avoid an
overloading

or
oversubscription
of the links in a
network which can lead to data packets being delayed or even lost. With the increased use of
wireless netwo
rking technologies, packets are often lost due to noise over the air. Hence, the
assumption of a packet being lost as implying congestion does not hold any more. This can lead
to a severe drop in performance in wireless networks especially in more emergent

wireless areas
like ad
-
hoc and sensor networks.

We focus our attention on congestion control in Wireless Sensor Networks (WSNs)

[D1,
D7
]
.
Wireless Sensor Networks (WSNs) consist of a number of low cost sensors that are equipped
with a radio interface. The
se devices are deployed in large numbers over an area of interest and
they monitor the targets in this region and send information to a base station or a gateway node.
A major constraint of these networks is limited battery life [D2
-
D6].
We will consider t
he
problem of congestion in event driven sensor networks

with specific goals of designing energy
efficient algorithms
.

B
IBLIOGRAPHY

[D1] Chee
-
Yee Chong and Kumar, S.P, Sensor ne
tworks: evolution, opportunities, and challenges,
Proceedings of the IEEE, 91(8):1247
-
1256, 2003.

[D2]

Sushil K. Prasad and Akshaye Dhawan, "Distributed Algorithms for lifetime of Wireless Sensor
Networks", In HiPC'07: Proceedings of the 14th Internatio
nal Conference on High Performance
Computing, Springer, 2007.

[D3]

Akshaye Dhawan and Sushil K. Prasad, "A Distributed Algorithmic Framework for Coverage
Problems in Wireless Sensor Networks", APDCM, In Proceedings of the 22nd IEEE Parallel and
Distrib
uted Processing Symposium, 2008 (IPDPS'08)

[D4]

Akshaye Dhawan and Sushil K. Prasad, " Energy Efficient Distributed Algorithms for Sensor
Target Coverage based on Properties of an Optimal Schedule", In HiPC'08: Proceedings of the
15th International Conf
erence on High Performance Computing, Springer, 2008.

[D5]

Akshaye Dhawan and Sushil K. Prasad, " A Distributed Algorithmic Framework for Coverage
Problems in Wireless Sensor Networks ", In International Journal of Parallel, Emergent and
Distributed Sys
tems(IJPEDS), Volume 24, Issue 4, 331, 2009.

[D6]

Akshaye Dhawan and Sushil K. Prasad, "Taming the Exponential State Space of the Maximum
Lifetime Sensor Cover problem", To appear in HiPC'09 Proceedings of the 16th International
Conference on High Perf
ormance Computing, 2009.

[D7] I. Akyildiz and W. Su and Y. Sankarasubramaniam and E. Cayirci, A survey on sensor networks,
IEEE Communication Magazine, 102
-
114, 2002.

[D8]
Dah
-
Ming Chiu, Raj Jain, Analysis of the increase and decrease algorithms for
congestion
avoidance in computer networks, Computer Networks and ISDN Systems, Volume 17, Issue 1,
10 June 1989.

[D9] G. Antoniou, F. Van Harmlen, A semantic web primer, MIT Press, 2004.

[D10]

Robert J. Calin
-
Jageman
,
Akshaye Dhawan
,
Hong Yang
,
Hsiu
-
Ch
ung Wang
,
Hao Tian
,
Piyaphol
Phoungphol
,
Chad Frederick
,
Janaka Balasooriya
,
Yan Chen
,
Sushil K. Prasad
,
Rajshekhar
Sunderraman
,
Ying Zhu
,
Paul S. Katz
: Development of NeuronBank: A Federation of
Customizable Knowledge Bases of Neuronal Circuitry.
IEEE SCW

2007
: 114
-
121