1. ENERGY EFFICIENT ROUTING
PROTOCOL IN WSN
*Neelam Chauhan * Pearmjeet Singh
*M Tech (Final Year CSE) at BRCM, Behal, Bhiwani * M Tech (Microelectronics & VLSI Design)
*er.neelam.choudhary@gmail.com Lecturer, ECE Department, Govt Polytechnic,Loharu,
Bhiwani,Haryana, India
*chauhan.paramjeet@gmail.com
Abstract: In Nowadays the popularity of Wireless wireless channels to form intelligent distributed sensor
Sensor Networks have increased tremendously, due to the system.
vast potential of the sensor networks to connect the
physical world with the virtual world. Since these devices A wireless sensor node has very limited energy supply that
rely on battery power and may be placed in hostile is usually supplied with battery, and it is almost infeasible
environments replacing them becomes a tedious task. Thus, for a sensor terminal to recharge or replace the battery
improving the energy of these networks becomes power after deployment in distant or urgent issue hazardous
important. environments. Therefore, in order to prolong the whole
The paper provides an energy efficient protocol for sensor network lifetime, energy efficiency, especially power
data management. The protocol employs replicated data saving on each sensor node, becomes an in WSN
sinks to achieve
(1) Resiliency to data sinks failure. 11 Background Knowledge
(2) Efficiency in storing and retrieving sensor data.
A simple address assignment scheme is introduced that 2.1 Energy Efficient Communication Protocol
partitions the sensor field into cells, where each cell
contains one data sink and all sensors that are closest to this An Energy Efficient Protocol for storing and retrieving
data sink. It is shown that this scheme is scalable and sensor data. With some new features this protocol also
resilient against data sink and sensor node failures. provides fault tolerance in the presence of data sink and
Furthermore, the scheme has a reasonably low message sensor failures. As a result, this protocol can maximize the
complexity and high energy efficiency. overall life of the sensor network.
Now what is the role of sensor node in wireless sensor
Keywords: WSN Routing ,WSN Protocol , De Bruijn
network?
Digraphs ,Energy Efficient Communication Protocol, Sensors are usually very simple units that are equipped
FLOC. with a sensing functionality. One can expect that wireless
sensors become smaller, cheaper, and more powerful.
1 Introduction Sensors can even carry out simple computations and
communicate with each other. However, a wireless sensor
As a revolution of information sensing and collecting, node has limited resources since it typically runs on battery
wireless sensor network is an emerging distributed sensing power and usually has a very small memory space. Thus,
technology that has a wide range of applications such as sensing devices must operate under severe resource
remote environment monitoring, military sensing, and constraints and one of the foremost goals is to minimize the
intelligence information gathering and so on.. energy consumption. Therefore, there is a need for an
energy-efficient communication scheme to store and
retrieve a vast amount of sensor data. But in many
applications, the sensing devices are placed outdoors,
resulting in a vulnerability to various noises and errors.
.
2.2 Problem Definition
1) What kind of data storage and retrieval structure in a
wireless sensor network is energy-efficient?
2) How can we make the wireless sensing system fault
Figure.1: Framework of a Wireless Sensor Network tolerant, when sensor nodes and data sinks may fail?
3) How can we achieve scalability in wireless sensor data
management so that the sensor system can be easily
The wireless sensor networks are composed of a large expanded by deploying new sensors and even adding new
number of inexpensive and small sensor nodes (called as data sink?
collectors) as well as an information collection center
(called as base station, sink), which are connected via

2. As an effort to answer these questions, a protocol based on . . . ,sn}. The data sinks are sensor-oblivious, which means
ideas inspired by de Bruijn digraphs and Voronoi diagrams. that a sensor can store and retrieve data to and from any
De Bruijn Digraphs:-The basics of de Bruijn digraphs [2] data sink. It is assume that the t data sinks are reasonably
let h and k is integer’s ≥ 2. The de Bruijn digraph B(h, k) regularly deployed over the sensor field.
has vertex set V = {0, 1, . . . , h − 1}k, and there is an edge
from vertex a = (a1, . . . , ak) to vertex b = (b1, . . . , bk) if The following assumptions about the cost for an interaction
and only if ai = bi+1 for all i in the range 1 ≤ i ≤ k − 1.. between a data sink and a sensor.
Thus every vertex has an out-degree of h, and the diameter The cost (energy consumption) of storing and retrieving
of B (h, k) is equal to k. data is the same at every data sink.
The cost of sending and receiving data to and from a data
sink can be computed by the hop count in the routing path
to the data sink times a fixed cost per hop.
Each sensor tries to minimize the cost of storing and
retrieving data by communicating with the nearest data
sink, where the distance from a sensor to a data sink is
measured in terms of hop counts. It follows that the sensor
network is partitioned into cells such that the sensors in the
same cell communicate with the same data sink.
Figure 2 : Illustrate the digraph B (2, 2). The nodes on the border of two or more cells “border
nodes”. It assumes that unique identifiers (ID) are given to
data sinks. It also assumes that every sensor node has a
Thus every vertex has an out-degree of h, and the diameter unique identifier, such as a MAC address . There is no
of B (h, k) is equal to k. One possible routing scheme in a functional difference among data sinks, that is, they all act
de Bruijn digraph works as follows. Suppose that the as final data storage and gateway to the outside networks.
destination address is b = (b1. . . bk) and the source address Data can be sent to any of the data sinks as long as the data
is a = (a1, . . . , aℓ, b1, . . . , bk−ℓ), where (b1, . . . , bk−ℓ) is sink is alive.
the longest prefix of b at the tail of a. Then the routing can
be done by left-shifting the source address ℓ times,
inserting one digit of the destination address in each step, It also assume that the wireless sensor nodes as well as the
starting from digit bk−ℓ+1. data sinks are stationary, i.e. not mobile. It also assume that
the data sink servers know the total number n of sensor
It is noted that it is not possible to use de Bruijn routing in a nodes, and that only a subset of the sensors are within one-
sensor network, since the de Bruijn digraph cannot, in hop range from the data sinks (if all the sensors are within a
general, be embedded into the available communication radio range from the data sinks, then there is no need for
topology of the sensor network. However, we can retain routing). The wireless signal (message) that a sensor node
much of the routing principle for the communication of sends is broadcast within the radio range, that is, every
sensor nodes to data sinks. node within the radio range of a sensor node ith will hear
It is well-known that de Bruijn networks can provide the messages broadcast by ith. Delivering a message
efficient routing among large number of nodes. In this requires more processing power than receiving a message.
routing scheme imitates certain aspects de Bruijn routing, Therefore, in the design of the energy efficient protocol, it
but is simpler, more flexible, and dynamically tries to minimize the redundant delivery of messages
reconfigurable. In this scheme, the address of a sensor node without compromising the fault-tolerance in data
already indicates the length of the path to the closest data transmission.
sink.
111 WSN Protocol
2.3 System Model and Assumption 3.1 The Protocol
The communication architecture uses a hybrid model that In this section, the description of protocol for energy-
effectively utilizes a variation of the peer-to-peer efficient, fault-tolerant data storage and retrieval, without
communication paradigm among the sensors, and a relying on any geographic or physical location information
variation of the client server paradigm between the sensors of the sensors as well as the servers. The new protocol uses
and the data sinks. The wireless sensors act as clients in the the five types of messages:
networked sensor system and the data sinks act as servers. 1) The initialization message (init) is used in the
The data sinks process the return feedback control data to initialization step to assign hop-count based addresses.
the sensor nodes. 2) The toSink message is used to send a message from a
sensor node to the data sink to perform a data storage
Let W (t, n) denote a wireless sensor network with t operation.
replicated data sinks D = {d1. . . dt}, and n sensors S = {s1,

3. 3) The fromSink message is used to broadcast a message
from the data sink server to every sensor node. This
message carries the ID of the sending data sink. This type
of message is used when the server proactively retrieves
data from the sensors or when it needs to broadcast control
messages to the sensors.
4) The peer message is used to communicate among the
peer sensors.
5) The node Fail message is used to inform nodes about a
failed node. This type of message is used by successors of a
failed node to negotiate new routing paths. Figure 1 : Sensor Network with three Data Sinks
First, the description about how the initial setup is
performed, where one or more de Bruijn-style addresses are Figure 1 shows a sensor network with three data sinks (that
assigned to each sensor node. Then I illustrate how are depicted by black circles) and several sensor nodes (that
message routing is performed. Finally, The explanation are depicted by white circles). If two nodes are within
about how resilience against node failures is achieved radio-range of each other, then there is an edge between
these nodes.
3.2 Initialization of WSN
The data sink servers start the initialization step by a
dynamic address assignment procedure. The t data sink
servers have addresses 1. . . t. Suppose that the data sink
server i has h sensors within its one-hop radio range. The
data sink server i assigns the h sensor nodes the addresses
(i, 0), (i, 1). . . (i, h − 1). When a sensor node s with h′ one-
hop neighbors receives an address a = (a1, a2. . . aℓ) from
an one-hop neighbor j, then it takes one of the following
actions:
If s does not have a valid address, then s takes a as its
address. And it assigns each one-hop neighbor, except j, an
address in the range of (a1, a2, . . . , aℓ, 0), . . . , (a1, a2, . . .
, aℓ, h′ − 2). • If s already has a valid address of length ℓ, Figure 2 : Result after Address Assignment
then it keeps a as an alias address. Notice that all aliases of
a sensor node have the same length.
Sensor network after address assignment. Some nodes have
If s has a valid address of length ℓ′ > ℓ, then it deletes all its
several address aliases that lead to different routes in to
address aliases and keeps a as a new address. And it once
Sink messages
again assigns each one-hop neighbor, except j, an address
in the range of (a1, a2. . . aℓ, 0), . . . , (a1, a2, . . . , aℓ, h′
−2).
In this way, every sensor node that is reachable from a data
sink will receive at least one address. The number of
address aliases of a sensor node does not exceed the
number of its one hop neighbors. A sensor node informs its
one-hop neighbors about its address aliases.
This simple address assignment scheme has some
remarkable properties:
If a sensor node has an address alias (a1, a2. . . aℓ), then
there is a path of ℓ−1 hops to the data Sink a1, and there is
no shorter path to a1. This assignment scheme realizes the Figure 3 : illustrates the subdivision into different cells.
partitioning into cells. If a node has only address aliases
that start with a1, then it is within the cell of a1. Induced partition of the network. All nodes that have an
address alias beginning with the same digit belong to the
The border nodes are characterized by the fact that they same cell. Border nodes belonging to two different cells are
have address aliases that start with different digits. The shaded grey.
main features of the address assignment.
Each cell contains a data sink and all sensor nodes that are
closer to this data sink than to any other in terms of hop-
count. If a sensor node has the same distance from more
than one data sink, then it belongs to the cell of each of
those data sinks; such nodes are called border nodes.

4. The nodes 120, 230, 310 are examples of such border Example 3: Suppose that node 130 wants to send a peer
nodes. If a sensor node s has address (a1, a2, . . . , aℓ−1, message to node 210 in the sensor network given in Figure
aℓ), then there exists a node p with address (a1, a2, . . . , 3.6(c). Then the message is routed through 130 → 13 → 1,
aℓ−1).p a predecessor of s, and s a successor of p. The and then forwarded to data sink 2, and the final hops are 2
associates of s are all one-hop neighbors of s that are → 21 → 210.
neither predecessor nor successors.
A straightforward routing rule for peer messages could use
3.3 Routing a sequence of predecessors until the node with the longest
common prefix of a and b is reached, from which b can be
After the addresses have been assigned to the nodes,
reached through successors. Our peer message routing rule
routing is performed. The most common type of message is
improves upon this rule by taking shortcuts whenever
a to Sink message from a sensor node to a data sink, which
Information about one-hop neighbors reveals such a
is typically routed through predecessors. Occasionally, a
possibility, as was shown in Example 1. Unlike to Sink
data sink may send from Sink messages to the sensor
routing, it should be noted that peer routing is not
nodes, which are forwarded through successors. A peer
necessarily optimal; this is the price one has to pay for the
message is routed through any combination of
very limited memory usage. In view of the fact that peer
predecessors, associates, and successors.
messages are rare and typically local, this does not appear
to be a significant disadvantage.
A to Sink message is routed by randomly selecting one
predecessor; this is done by right-shifting one randomly
The energy efficient protocol makes typically multiple
selected address alias. Then the same process is repeated
paths available while routing from sensor node to a data
until the data sink is reached. For instance, one possible
sink; unlike many other routing protocols for sensor
path from the address (a1, . . . , aℓ) is through the
networks, such as directed diffusion, ours will always
predecessors (a1, . . . , aℓ−1), (a1, . . . , aℓ−2), . . . , (a1, a2)
ensure that the selected route is optimal, so that load
to the data sink a1.
balancing does not come at the cost of energy efficient.
A from Sink message is broadcast by sending the message
from the data sink to its successors, and each sensor node
receiving such a message forwards it to all its successors.
IV Related Work and Comparison
Suppose that a peer message is sent from a node with
address a = (a1. . . aℓ) to a node with address b = (b1, . . . ,
bk). The node a or any node receiving the message
forwards it to the one-hop neighbor that has an address The work is related to two intertwined themes in wireless
alias with the longest common prefix with b; if several one- sensor networks: routing and data aggregation. Numerous
hop neighbors qualify, then the one with the shortest architectures and protocols have been proposed to solve
address alias is chosen. If a data sink 6= b1 receives such a both problems at the same time.
message, then it will forward it to the data sink b1. Initial Flooding of Message:-An initial flooding of
messages in the sensor field to establish the routing paths.
The design of the protocol ensures that the routing of the to This step is somewhat similar to directed diffusion ,a
Sink messages is optimal; in a typical sensor network mechanism that uses limited flooding of queries towards
application the to Sink messages are by far the most events and sets up reverse gradients for the best path. One
frequent ones, since they are used to communicate the fundamental difference is that directed diffusion is
sensor data. designed for the single data sink scenario, whereas the
energy efficient routing protocol can serve multiple data
Example 1: Suppose that the node 131=310 in the sensor sinks.
network given in Figure 3 wants to send a to Sink message GPSR: is an efficient routing scheme that relies on the
to a data sink. If it chooses its alias 131, then the resulting localized nodes and restricts flooding to a geographical
route will be 131 → 13 → 1. If it chooses its address alias region . One drawback of this approach, however, is its
310, then the resulting route will be 310 → 31 → 3. Peer assumption that the locations of the sensor nodes are
messages can be used, for example, by a sensor to check known to all nodes in the network. Where new change in
whether its sensor readings are reasonable. Although such the protocol such that knowledge of locations is not
messages are rare or not used at all in typical sensor required.
network applications, we remark that routing between any SHORT: is a self-healing, path- and energy-aware routing
two nodes is possible. An example shows the above framework shows a good performance with the reduced
routing rule. energy costs .In a path-aware scheme, shorter paths are
found by connecting non-adjacent nodes on a path that are
Example 2: Consider the sensor network given in Figure 3 within communication range of each other. In an energy-
Suppose that node 110 wants to send peer message to node aware scheme, a routing path is switched when the energy
210. Since both neighbors of 110 have an empty common of the nodes on the path is running low. By letting the
prefix with 210, the message is forwarded to 11, the shorter neighboring nodes of a route, together with the on-route
address alias. Among the neighbors of 11, the node nodes, monitor the route, up-to-date information of local
200 have the longest common prefix with 210, so it is topology and link quality can be exploited. The work
routed there, and node 200 routes the message to 210. resembles their approach regarding self-healing and
energy-efficiency. In new case, the routing of messages to a

5. data sink is optimal, and the advantage of shortcuts in peer the introduction of alternate paths with neighbor node
message routing, though without introducing much (sensor node, data sink) according to the location also.
overhead. The most common application in sensor networks is the
FLOC: (Clustering service) called FLOC, which can delivery of sensor data. The protocol ensures that such
achieve efficient and scalable control in large-scale ad hoc messages from the sensor nodes are always routed in an
wireless sensor networks. To achieve high energy optimal way to the closest data sink using the least possible
efficiency and resiliency, role-based hierarchical self- number of hops.
organized networks are explored in Depending on their The overhead of keeping routing tables to accommodate the
connectivity and sensing capability, sensor nodes are memory constraints of sensor nodes is totally avoided. A
assigned the role of data collection and data dissemination. node simply needs to keep the address aliases of itself and
Based on certain metrics, the network is partitioned into of its one-hop neighbors. Furthermore, this protocol does
sensing zones, in which the sensor nodes collaborate to not require any location information. The reasonably low
achieve a sensing objective. message complexity of our scheme can extend the battery
In the energy efficient protocol, this approach relies only on life of each node, maximizing the overall life of the sensor
local information. However, as a hierarchy-based network.
architecture, this approach is vulnerable to failures,
especially when particular roles are prone to become points
of failure. The systematic rotation of roles among the nodes
can resolve this problem. A periodically repeated role
assignment scheme is proposed in for Bluetooth-based VI References
sensor networks.
ACQUIRE : is an active query forwarding mechanism in 1 Andrea Kulakov, Georgi Stojanov and Danco
a sensor network. A query packet is forwarded through the Davcev,”Sound and video processing in wireless sensor
network that follows a random or guided path. At each step, networks” Faculty of Electrical Engineering University
a node, upon receiving a query, performs an update to “Sts Cyril and Methodius”,IEEE, April 2006.
gather data from all of its neighbors within a look-ahead of 2 Anwitaman Datta, Sarunas Girdzijauskas, Karl Aberer,”
d steps. As this query progresses through the network, it is On de Bruijn routing in distributed hash tables: There and
gradually resolved into smaller components until it is back again,” IEEE, EPFL 2003.
completely solved and is returned back to the querying 3 Brad Krap, H.T.Kung, “GPSR: Greedy Perimeter
node. This approach works at its best for one-shot, non- Stateless Routing for Wireless Networks”, Proc, of the 6th
aggregate, complex queries for replicated data. Annual Int.Conf.on Mobile Mobile Computing and
TAG: is a high-level abstraction of a declarative interface Networking (MobiCom), pp.243-245, August 2000.
for data collection and aggregation in wireless sensor 4 Chao Gui and Prasant Mohapatra, “A Self –Healing and
networks of TinyOS motes .It realizes a distributed query Optimizing Routing Techniques for Ad-Hoc
aggregation scheme that is sensitive to resource constraints Networks”Proc of the 4th ACM Int.Symp on Mobile Ad
and can cope with lossy communication of wireless sensor Hoc Networking and Computing (MobiHoc), IEEE,
networks. pp.279-290, June2003.
5 C.Intanagonwiwat, R.Govindan and D.Estrin “Directed
So, finally it is noticed that a mobile agent based systems, Diffusion: A Scalable and Robust Communication
where agents exchange data with nearby sensors or access Paradigm for Sensor Networks”, Proc. of the 6th Annual
points that they encounter as they pass by. The advantage Int.Conf.on Mobile Computing and Networking
of such an approach is that fewer infrastructures are (MobiCom), pp56-67, of IEEE, August2000.
required and on the other methods there is no overhead 6 DaiZhi-feng, li-Yuan-Xiang, He-gnoliang, Jong Ya-la,
caused by packet routing. When the density of mobile Shen Xian-Jun, “Uncertain Data Management for Wireless
agents is sufficiently high, the system is more robust than a Sensor Network Using Rough Set Theory” of IEEE June
fixed network. The primary drawback of such a system is 2006.
that the latency is high, so it is not suitable for all 7 Danco Davcev, Andrea Kulakov, and Stojanco
applications. Unexpected failures such as loss of mobile Gancev,”Experiments in Data Management for Wireless
agents or limitations on mobility can compromise the fault- sensor Network” of IEEE, September 2008.
tolerance of such a system. 8 F.L.Lewis “Wireless Sensor Network” Associated
director for Research Head, Advance Controls, sensors &
V Conclusion MEMS Group of Automation & Robotics Research
Institution the University of Texas,http://arri.uta.edu/acs,
During the conduct of study done as a part of paper, on Feb 2004.
energy efficient communication protocol for data storage 9 Haiying Shen, Ting Li “Data Management of Wireless
and retrieval in a wireless sensor network is vulnerable. Sensor Network” of IEEE, May 2009.
10 Hyunyonng Lee, Andreas Klappenecker and
Energy Efficient protocol employs replicated data sinks to Kyoungsook Lee, LAN Lin,”Energy Efficient Data
improve fault tolerance in the face of data sink failures. The Management for Wireless Sensor Network with Data Sink
achievement of resiliency against sensor node and data sink Failure” of IEEE, June 2005.
failures through a dynamic Re-assignment of addresses and 11 Li Qun Zhuang, Jing Bing Zhang, Dan Hong Zhang and
Yi Zhi Zhao,” Data Management for Wireless Sensor

6. Networks: Research Issues and Challenges of IEEE June
2005.
12 Mudasser Iqbal, Hock Beng Lim, Wenqiang Wang,
Yuxia Yao “A Service-Oriented Model for Semantics-
based Data Management in Wireless Sensor Networks” of
IEEE Intelligent Systems center,Nanyang Technological
University,Singapore, Feb 2009.
13 Qian Wang, Kui Ren, and Cong Wang and Wenjing
Lou,” Efficient Fine-grained Data Access Control in
Wireless Sensor Networks”, of IEEE,PID:901523.pdf Feb
2009.
14 Qian Wang, Kui Ren ,Yanchao Zhang and Wenjing
Lou,” Dependable and Secure Sensor Data Storage with
Dynamic Integrity Assurance” of IEEE May 2009.
15 M.Handy,J.Blumenthal and D.Timmermann,”Energy-
Efficient Data Collection for Bluetooth-Based Sensor
Networks”EUROMICRO Symposium on Digital System
Design,pp.566-573,2004.