Routing Techniques for Reliable Wireless Sensor Network

8/6/2019 Routing Techniques for Reliable Wireless Sensor Network

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Abstract Wireless Sensor Network (WSN) is a collection ofthousands of tiny sensor nodes having capability of wirelesscommunication, limited computation and sensing. It is now usedin many application including military, environmental,healthcare application, home automation and traffic control. In

this paper we will compare Data centric routing protocols forwireless sensor network. It also discusses about simulation basedstudy of routing protocols such as Flooding and DirectedDiffusion.

KeywordsRouting Protocols, Wireless Sensor Network, Data-

centric, Flooding, Directed Diffusion

I. INTRODUCTIONA sensor network is composed of a large number of tinyautonomous devices, called sensor nodes [1] [2]. Sensors are

small nodes which are capable of data processing andcommunication. The sensor node measures ambient conditionsfrom environment, transform it into electrical signals and

sends via radio transceiver to a sink and then this aggregated

information is sent back to a base station through a gateway

[1]. Sensor networks are distributed sensors to monitor

conditions like temperature, sound, vibration, pressure and

pollutants etc. WSN links physical world and digital datanetwork and provide a distributed network having the

constraint of scalability, lifetime and energy efficiency.

Routing in sensor networks is very challenging due to several

characteristics that distinguish them from contemporary

communication and wireless ad-hoc networks. First of all, it isnot possible to build a global addressing scheme for the

deployment of sheer number of sensor nodes. Therefore,

classical IP-based protocols cannot be applied to sensor

networks. Second, in contrary to typical communication

networks almost all applications of sensor networks requirethe flow of sensed data from multiple regions (sources) to a

particular sink. Third, generated data traffic has significant

redundancy in it since multiple sensors may generate samedata within the vicinity of a phenomenon. Such redundancy

needs to be exploited by the routing protocols to improve

energy and bandwidth utilization. Fourth, sensor nodes aretightly constrained in terms of transmission power, on-board

energy, processing capacity and storage and thus require

careful resource management. The main contribution of this

paper is that we have carried out a simulation based study of

routing protocols such as Flooding and Directed Diffusion to

understand their behavior when used in a sensor network

environment. We also provide the study of previous research

work of routing protocol which comes under data-centric

category. Our aim is to help better understanding of thecurrent data-centric routing protocols for wireless sensor

networks.

II.DESCRIPTIONOFROUTINGPROTOCOLRouting is a process of determining a path between source and

destination upon request of data transmission. In WSNs, the

layer that is mainly used to implement the routing of theincoming data is called as network layer. When the sink is far

away from the source or not in the range of source node,

multi-hop technique is followed. So, intermediate sensor

nodes have to relay their packets. In many applications of

sensor networks, it is not feasible to assign global identifiers to

each node due to the sheer number of nodes deployed. Such

lack of global identification along with random deployment of

sensor nodes makes it hard to select a specific set of sensor

nodes to be queried.

Protocols, which name the data and query the nodes based on

some attributes of the data are categorized as data-centric.In

data-centric routing, the sink sends queries to certain regions

and waits for data from the sensors located in the selected

regions. In this category, protocols mainly apply flood based

data transferring .Since data is being requested through

queries, attribute based naming is necessary to specify the

properties of data.Some of the Data centric Routing Protocols

are: Flooding, Sensor Protocols for Information via

Negotiation (SPIN), Directed Diffusion, Improved Directed

Diffusion,and Rumor Routing.

In this section, we will describe these protocols in details and

highlight the key ideas.

A. FloodingIn flooding [5] [6], the source node floods all events to every

node in the network. Whenever a sensor receives a datamessage, it keeps a copy of the message and forwards the

message to every one of its neighboring sensors and the cycle

repeats until the packet arrives at the destination or themaximum number of hops for the packet is reached as shown

in Figure 2.1.

Routing Techniques for Reliable Wireless Sensor Networks

Samir Agarwal Susant K. Satpathy Lokesh K Sharma Department of CSE Department of CSE Department of IT

RCET, RCET, Bhilai, (C.G.), India Bhilai, (C.G.), India Bhilai, (C.G.), India

[email protected] [email protected] [email protected]
mailto:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]


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Figure 2.1 The Flooding Protocol

It is suitable for various network types, node distributions and

environments. The main advantage of flooding is the increased

reliability provided by this routing method. Since the message

will be sent to at least once to every host it is almost

guaranteed to reach its destination. But the unlimited

broadcasting the packets in the flooding scheme will cause the

broadcast storm. The flooding routing protocol has three

deficiencies as:

Implosion: Because the nodes in the flooding schemedeliver the packets by broadcasting, the same packet

may achieve the same node via different routes.

When a sensor node receives a packet, it will not

check the packet if it has received the packet before.

This character makes the duplicated packets sent to

the same place.

Overlap: When these two sensors detect same event,they may both send a data of this event to the sink.

This may cause that the duplicated information of an

event is sent to the sink.

Resource blindness: When a sensor node is nottransmitting packets in flooding, it doesnt change

their actives, even if the sensor nodes dont have

much power to operation.

B. Directed DiffusionDirect Diffusion [4][5][6] is the data centric protocol.

It consists of several elements: interests, data

messages, gradients, and reinforcements. First, sink

node requests data by sending interests. An interest

message is a query or an interrogation, which

specifies what a user wants to its neighbors for

named data. The data is named using attribute-value

pairs and it is the collected or processed information

of a phenomenon thatmatches an interest of a user.The interests are flooded over the whole network by

the sink. Such data can be an event, which is a shortdescription of the sensed phenomenon. Whenever a

node receives an interest, it will check whether the

interest exists or new one. If it is a new interest, the

sensor node will set up a gradient toward the senderto draw down data that matches the interest. Eachpair of neighboring nodes will establish a gradient to

each other. After the gradient establishment stage, the

source node begins to send the related data that

matches the interest to the sink. The data are

generally broadcasted to all its gradient neighbors.

Events are propagated toward the interest originators

along multiple gradient paths. The sensor network

reinforces one or a small number of these paths. The

reinforcement scheme in directed diffusion is

generally designed for minimum delay or maximum

number of packets received during a certain period oftime as shown in Figure 2.2

Figure 2.2 Directed Diffusion,(a) Interest Propagation, (b) Intial

Gradient Setup, (c) Data Delivery

Simulation of flooding and Directed Diffusion protocol is

performed on same topology having 20 nodes with energy 6

joules. Nodes in the network are in random position. The

difference between the simulation of flooding and directed

diffusion is that in directed diffusion the communication starts

from sink itself the sink sends the interest about what it needs,source node sends a gradient in reply and then data is being

delivered to the sink. In this simulation scenario in flooding

the lifetime of the network with energy 6 joule is almost 75seconds and in directed diffusion is 87 sec. After this

simulation time the network reaches to the crashing stage and

communication between the nodes vanish completely. If

energy of the network is increased, it will work for more

simulation time. Figure 2.3 showing Number of sent packets is

increasing more in directed diffusion with simulation time and

also showing number of dropped packets is less as compare to

flooding with simulation time.

Figure 2.3 Comparison in flooding and Directed Diffusion


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C. Energy-aware routingShah et al. [3][8] proposed to use a set of sub-optimal pathsoccasionally to increase the lifetime of the network. These

paths are chosen by means of a probability function, which

depends on the energy consumption of each path. Network

survivability is the main metric that the approach is concerned

with. The approach argues that using the minimum energy

path all the time will deplete the energy of nodes on that path.

Instead, one of the multiple paths is used with a certainprobability so that the whole network lifetime increases. The

protocol assumes that each node is addressable through a

class-based addressing which includes the location and typesof the nodes.

The described approach is similar to Directed Diffusion in the

way potential paths from data sources to the sink are

discovered. In Directed Diffusion, data is sent throughmultiple paths, one of them being reinforced to send at higher

rates. On the other hand, Shah et al. select a single path

randomly from the multiple alternatives in order to save

energy. Therefore, when compared to Directed Diffusion, it

provides an overall improvement of 21.5% energy saving anda 44% increase in network lifetime. However, such single pathusage hinders the ability of recovering from a node or path

failure as opposed to Directed Diffusion. In addition, the

approach requires gathering the location information and

setting up the addressing mechanism for the nodes, which

complicate route setup compared to the Directed Diffusion.

D. Rumor RoutingRumor routing [7] is another variation of Directed Diffusion

and is mainly intended for contexts in which geographic

routing criteria are not applicable. Generally Directed

Diffusion floods the query to the entire network when there is

no geographic criterion to diffuse tasks. However, in somecases there is only a little amount of data requested from the

nodes and thus the use of flooding is unnecessary. Analternative approach is to flood the events if number of events

is small and number of queries is large. Rumor routing is

between event flooding and query flooding. The idea is to

route the queries to the nodes that have observed a particularevent rather than flooding the entire network to retrieve

information about the occurring events.

In order to flood events through the network, the rumor

routing algorithm employs long lived packets, called agents.

When a node detects an event, it adds such event to its local

table and generates an agent. Agents travel the network inorder to propagate information about local events to distant

nodes. When a node generates a query for an event, the nodes

that know the route, can respond to the query by referring its

event table. Hence, the cost of flooding the whole network isavoided. Rumor routing maintains only one path between

source and destination as opposed to Directed Diffusion where

data can be sent through multiple paths at low rates.

Simulation results have shown that rumor routing achieves

significant energy saving over event flooding and can also

handle nodes failure. However, rumor routing performs well

only when the number of events is small. For large number of

events, the cost of maintaining agents and event-tables in each

node may not be amortized if there is not enough interest on

those events from the sink. Another issue to deal with is

tuning the overhead through adjusting parameters used in the

algorithm such as time-to-live for queries and agents.

E. Gradient-Based RoutingSchurgers et al. [8] have proposed a slightly changed version

of Directed Diffusion, called Gradient-based routing (GBR).

The idea is to keep the number of hops when the interest is

diffused through the network. Hence, each node can discoverthe minimum number of hops to the sink, which is called

height of the node. The difference between a nodes height

and that of its neighbor is considered the gradient on that link.

A packet is forwarded on a link with the largest gradient.

The authors aim at using some auxiliary techniques such as

data aggregation and traffic spreading along with GBR inorder to balance the traffic uniformly over the network. Nodes

acting as a relay for multiple paths can create a data

combining entity in order to aggregate data. On the otherhand, three different data spreading techniques have beenpresented:

Stochastic Scheme: When there are two or more nexthops with the same gradient, the node chooses one of

them at random.

Energy- based scheme: When a nodes energy dropsbelow a certain threshold, it increases its height so

that other sensors are discouraged from sending data

to that node.

Stream-based scheme: The idea is to divert newstreams away from nodes that are currently part ofthe path of other streams.

The data spreading schemes strives to achieve an even

distribution of the traffic throughout the whole network, which

helps in balancing the load on sensor nodes and increases the

network lifetime. The employed techniques for traffic load

balancing and data fusion are also applicable to other routing

protocols for enhanced performance. Through simulation GBR

has been shown to outperform Directed Diffusion in terms of

total communication energy.

F. CADRConstrained anisotropic diffusion routing (CADR) [9] is a

protocol, which strives to be a general form of Directed

Diffusion. Two techniques namely information-driven sensor

querying (IDSQ) and constrained anisotropic diffusion routing(CADR) are proposed. The idea is to query sensors and route

data in a network in order to maximize the information gain,

while minimizing the latency and bandwidth. This is achieved

by activating only the sensors that are close to a particular

event and dynamically adjusting data routes. The major

difference from Directed Diffusion is the consideration of


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information gain in addition to the communication cost. In

CADR, each node evaluates an information/cost objective and

routes data based on the local information/cost gradient and

end-user requirements. The information utility measure is

modeled using standard estimation theory.

Since CADR diffuses queries by using a set of information

criteria to select which sensors to get the data, simulation

results confirmed that it is more energy efficient than DirectedDiffusion where queries are diffused in an isotropic fashion,

reaching nearest neighbors first.

G. COUGARA data-centric protocol that views the network as a huge

distributed database system is proposed in the main idea is to

use declarative queries in order to abstract query processing

from the network layer functions such as selection of relevant

sensors etc. and utilize in-network data aggregation to save

energy. The abstraction is supported through a new querylayer between the network and application layers.

Figure 2.4: Query Plan at leader node: The leader node gets all the reading,

calculates the average and if it is greater than a threshold sends it to the

gateway (sink).

COUGAR proposes architecture for the sensor database

system where sensor nodes select a leader node to performaggregation and transmit the data to the gateway (sink). The

architecture is depicted in Fig. 2.4, which is redrawn from

[24]. The gateway is responsible for generating a query plan,

which specifies the necessary information about the data flow

and in-network computation for the incoming query and send

it to the relevant nodes.. Third, the leader nodes should be

dynamically maintained to prevent them from failure.

III. CONCLUSIONThere are different routing protocols for routing in WSN,

these protocols are application specific and therefore a careful

selection of the underlying routing protocol for WSN is a key

element to measure the performance of a WSN as a whole. In

this paper, we have summarized simulation results of flooding

and Directed Diffusion routing protocols. Directed Diffusion

having more send packets and less Dropped packets compare

to Flooding with increase in simulation time. Thus Directed

Diffusion can perform much better than the Flooding scheme

in similar conditions of networks size and work load. we have

also summarized recent research results on data routing in

sensor networks which comes under data-centric category We

also included in the table whether the protocol is utilizing data

aggregation or not, since it is an important consideration for

routing protocols in terms of energy saving and traffic

optimization.

TABLE I. COMPARISION BETWEEN FLOODING AND DIRECTED

DIFFUSION

Protocol Initial Energy

(joules)

Network Life

Time

Flooding 6 75sec

Directed Diffusion 6 87sec

TABLEII.COMPARISON BETWEEN DATA-CENTRIC AND AGGREGATION

Routing protocol Data centric Data aggregation

SPIN

Directed Diffusion

Rumor Routing

Shah et al.

GBR

CADR

COUGAR

REFERENCES

[1] Chaczko, Z.; Ahmad, F.; Mahadevarr, V "Wireless sensors in networkbased collaborative environments, Information Technology BasedHigher Education and Training, 2005. . 6th International Conference

ITHET 2005. Page(s): F3A/7 - F3A13.2005.[2] R. Min, et al., "An Architecture for a power aware distributed

microsensor node", in the Proceedings of the IEEE Workshop on signal

processing systems (SIPS'00), October 2000.

[3] [2] Yan-Xiao Li; Hao-Shan Shi; Shui-Ping Zhang; "An Efficient EnergyAware MAC Protocol for Wireless Sensor Network , International

Conference ICMULT.2010.

[4] Shousheng Zhao, Fengqi Yu, Baohua Zhao," An Energy EfficientDirected Diffusion Routing Protocol", International Conference on

Computational Intelligence and Security 2007.

[5] Arun Kumar and Ashok Kumar Turuk,"Simulation of Sensor NetworkProtocols and their Comparison", International Conference on Sensors

and Related Networks (SENNET07), VIT University, Vellore, India.Dec. 12-14, 2007. Pp.448-453.

[6] Linliang Zhao, Gaoqiang Liu, Jie Chen, Zhiwei Zhang"Flooding andDirected Diffusion Routing Algorithm in Wireless Sensor

Networks,Ninth International Conference on Hybrid IntelligentSystems,2009.

[7] D. Braginsky and D. Estrin, "Rumor Routing Algorithm for SensorNetworks," in the Proceedings of the First Workshop on Sensor

Networks and Applications (WSNA), Atlanta, GA, October 2002.

[8] C. Schurgers and M.B. Srivastava, Energy efficient routing in wirelesssensor networks, in the MILCOM Proceedings on Communications forNetwork-Centric Operations: Creating the Information Force, McLean,

VA, 2001.

[9] M. Chu, H. Haussecker, and F. Zhao, "Scalable Information-DrivenSensor Querying and Routing for ad hoc Heterogeneous Sensor

Networks," The International Journal of High Performance Computing

Applications, Vol. 16, No. 3, August 2002.

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Routing Techniques for Reliable Wireless Sensor Network