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Mr. Ravinder Kumar , Dr. P. S. Mundra / International Journal of Engineering Research and
                     Applications (IJERA) ISSN: 2248-9622 www.ijera.com
                            Vol. 2, Issue 4, July-August 2012, pp.588-592
   Advanced Data Routing Protocol With Improved Hopping in Chiron
                             Mr. Ravinder Kumar* , Dr. P. S. Mundra**
            *
              (Department of Electronics and Communication Engineering, Punjab Technical University, India
                          M.Tech (ECE) Scholar, Chandigarh College of Engineering, Landran)
           **
              (Department of Electronics and Communication Engineering, Punjab Technical University, India
                        Professor in Chandigarh College of Engineering. Landran, Punjab, India)



ABSTRACT
         Wireless sensor network [1] generally consists      have been proposed to address this topic [2] Chain-based
of large number of sensor nodes. The wireless sensor         routing is one of most significant routing mechanisms. In
network can be defined as large number of small              such routing scheme, sensor nodes are linked into a single
sensing self powered nodes which gather the                  or multiple chains in advance. In data dissemination
information from the geographical area and                   phase, each node communicates only with its closest
communicate in wireless fashion with the goal of             neighbors, and takes turns to be the chain leader for
handing their processed data to the base station. Due        transmitting the aggregated data to the BS. Even the chain
to the power restriction of sensor nodes, efficient          based routing protocols can effectively balance the node’s
routing in wireless sensor networks is a critical            energy dissipation, and thus significantly extend the
approach to saving node’s energy and thus prolonging         network life time they would be easy to cause serious
the network lifetime. In this paper, we propose              transmission delays and redundant paths, particularly for
advanced data routing protocol with improved                 large sensing areas. In order to improve the deficiencies as
Hopping in Chiron. As in Chiron chain leader                 aforementioned we propose advanced data routing
belonging to the certain covering angle transmits the        protocol with improved Hopping in Chiron. In CHIRON
gathered data to the chain leader of the different           the technique of Beam Star [9] is first used to divide the
covering angle this creates the increase in distance,        sensing area into several fan-shaped groups. The sensor
and delay. So the main goal of our research is to            nodes within each group are then self organized into a
improve the overall lifetime of network, time required       chain for data dissemination. Unlike traditional
to transfer the packets and improvement in number of         approaches, instead of taking turns, we consider the node
survival sensor. Simulation results show that the            with a maximum residual energy as chain leader
proposed protocol is superior to Chiron. Comparing           candidate. In addition, for avoiding a longer transmission
to the Chiron the proposed protocol scheme achieves          would be incurred among chain leaders, the nearest
improvement about 8% to 12%, 9% to 13.5% , 5%                downstream chain leader will be elected for relaying the
to 11% in overall lifetime of the network, number of         aggregated sensing information. With these strategies, our
survival node and time taken for packets transmission        proposed protocol has the following merits. 1) Each node
respectively under various small and large simulation        can get its location information passively from the BS
areas respectively.                                          with a minimum control overhead. 2) The collected
                                                             sensing data can be reported to the BS, in a short-haul and
Key Words-- Wireless Sensor Network, Routing                 multi-hop transmission manner. 3) It can effectively
protocol, Chiron, lifetime                                   reduce the chain length and redundant transmission path,
                                                             so thus significantly improve the delay time and save
INTRODUCTION                                                 network energy as compared to other counterparts.
          Wireless Sensor Networks (WSNs) have gained
a great deal of attentions in recent years [3]. A WSN
generally consists of a large number of battery-powered,
resource constraints wireless sensor nodes, which might
be randomly deployed in an unattended and unreachable
terrain, for sensing and collecting the wanted data from
the surroundings, and thus reporting the fused information
to a remote Base Station (BS). WSNs have been widely
employed in several applications such as habitat
monitoring, disaster supervising, and bioinformatics [1]
[10]. Due to the characteristics of random deployment and
low cost with sensor nodes, it is expected to be difficult   The sensor nodes are usually scattered in a sensor field as
and unnecessary for recharging them once their energies      shown in Figure1.Each of these scattered sensor nodes has
are exhausted. As a consequence, how to conserve node’s      the capabilities to collect data and route data back to the
power and thus prolong the network lifetime is a critical    sink. Data are routed back to the sink by a multi-hop
issue in WSNs. Several power-efficient routing protocols     infrastructure less architecture through the sink as shown


                                                                                                           588 | P a g e
Mr. Ravinder Kumar , Dr. P. S. Mundra / International Journal of Engineering Research and
                      Applications (IJERA) ISSN: 2248-9622 www.ijera.com
                             Vol. 2, Issue 4, July-August 2012, pp.588-592
in Figure 1. The sink may communicate with the task             then take turns to act as the chain leader. In data
manager node via Internet or satellite.                         dissemination phase, every node receives the sensing
                                                                information from its closest upstream neighbour, and then
The remainder of this paper is organized as follows. In         passes its aggregated data toward the designated leader,
Section 2, routing technique used in WSN is discussed. In       via its downstream neighbour, and finally the base station.
section 3 some previous related works which motivate our        Although the PEGASIS constructs a chain connecting all
research are briefly reviewed and discussed. The design         nodes to balance network energy dissipation, there are
philosophy and implementation of our proposed protocol          still some flaws with this scheme. 1) For a large sensing
are detailed in Section 4. Section 5 discusses the improved     field and real-time applications, the single long chain may
scheme. Section 6 manifests our simulation environments,        introduce an unacceptable data delay time. 2) Since the
parameters, and results. The conclusion follows in Section      chain leader is elected by taking turns, for some cases,
7.                                                              several sensor nodes might reversely transmit their
                                                                aggregated data to the designated leader, which is far
2. ROUTING TECHNIQUES IN WSN                                    away from the BS than itself. This will result in redundant
          Wireless sensor networks (WSN) consist of             transmission paths, and therefore seriously waste network
small nodes with sensing, computation, and wireless             energy. 3) The single chain leader may become a
communications capabilities. Many routing, power                bottleneck.
management, and data dissemination protocols have been
specifically designed for WSNs where energy awareness           B. Enhanced PEGASIS
is an essential design issue. Routing protocols in WSNs                   In 2007, Jung et al. proposed a variation of
might differ depending on the application and network           PEGASIS routing scheme, termed as Enhanced PEGASIS
architecture. Overall, the routing techniques [2] are           [7]. In their method, the sensing area, centred at the BS, is
classified into three categories based on the underlying        circularized into several concentric cluster levels. For
network structure: flat, hierarchical, and location-based       each cluster level, based on the greedy algorithm of
routing. Figure 2 shows routing protocols in WSNs.              PEGASIS, a node chain is constructed. In data
                                                                transmission, the common nodes also conduct a similar
                                                                way as the PEGASIS to transfer their sensing data to its
                                                                chain leader. After that, from the highest (farthest) cluster
                                                                level to the lowest (near to the BS), a multi-hop and
                                                                leader-by-leader data propagation task will be followed.
                                                                The EPEGASIS although has considered the location of
                                                                the BS to slightly improve the redundant transmission
                                                                path and the network lifetime, there are still some
                                                                problems with that scheme. 1) For large sensing areas, the
                                                                node chain in each concentric cluster would still become
                                                                lengthy, and thus result in a longer transmission delay. 2)
                                                                Since the leader node election strategy is same as that in
                                                                PEGASIS (by taking turns), it did not consider the node’s
                                                                residual energy. 3) While the distribution of sensor nodes
          Figure 2: Routing Protocols in WSNs                   is not even, the transmission distance between two chain-
                                                                leaders in different cluster levels might be lengthy, this
In flat networks all nodes play the same role, while            would consume more energy.
hierarchical protocols aim to cluster the nodes so that
cluster heads can do some aggregation and reduction of          4. PROPOSED PROTOCOL
data in order to save energy. Location-based protocols                   For improving the deficiencies with the
utilize position information to relay the data to the desired   aforementioned schemes, in this section, we thus propose
regions rather than the whole network.                          an energy efficient [4] hierarchical chain-based routing
                                                                protocol. The design philosophy is described as follows.
3. RELATED WORK
         In general, three strategies are considered for the    A. Network model and assumptions
design of data aggregation techniques in WSNs. They are              Without loss of generality, in our research, we also
cluster based, tree-based [6], and chain-based. In this         consider a WSN of n energy-constrained sensor nodes,
section, we only review chain-based routing protocols,          which are randomly deployed over a sensing field. The
PEGASIS and Enhanced [5], and point out their pros and          BS is located at a corner of the sensing area, and equipped
cons that motivate our research.                                with a directional antenna and unlimited power. As a
                                                                result, the BS can adaptively adjust its transmission power
A. PEGASIS                                                      level and antenna direction to send control packets to all
         PEGASIS is a basic chain-based routing                 nodes in the WSN. Besides, for easy discussion, we define
protocol. In which, all nodes in the sensing area are first     some notations as follows:
organized into a chain by using a greedy algorithm, and

                                                                                                              589 | P a g e
Mr. Ravinder Kumar , Dr. P. S. Mundra / International Journal of Engineering Research and
                        Applications (IJERA) ISSN: 2248-9622 www.ijera.com
                               Vol. 2, Issue 4, July-August 2012, pp.588-592
         R: the transmission range of the BS. For
          simplicity, we use distinct integers (1 … n) to
          represent various ranges.
         θ: the beam width (covering angle) of the
          directional antenna. Also, similar to the
          definition of R, different integers (1 … n) are
          used to indicate distinct angles.
         G θ, R: the group id. Theoretically, by changing
          different values of θ and R, the sensing area can
          be divided into n * n groups. Those are G1,1 G1,2
          …, G1,n, …, Gn,1, …, G n ,n
         Ni: the node i; the node set N= {n1, n2, n3… n
          i}, where 1≤i≤|N|.                                    Figure (3): Grouping example with R=1…3 and θ=1...2
         C x, y: the id of a chain which was formed in
          group G x, y. the chain set C= {c1,1 c1,2 ….}.        2. Chain Formation Phase
         L x, y: the leader node id of chain C x, y. The                In this phase, the nodes within each group Gx,y
          leader set L= {l1,1, l1,2…}.                         will be linked together to form a chain Cx,y respectively.
         Neighbour (ni): the neighbouring nodes of ni.        The chain formation process is same as that in PEGASIS
          The neighbouring nodes mean the nodes which          scheme. For each group G x,y, the node ni with the
          are locating in the transmission range of a          maximum value of dis (ni, BS) (that is farthest away from
          specific node.                                       the BS) is initiated to create the group chain. By using a
         Res (ni): the residual energy of node ni.            [6] algorithm, the nearest node (to ni) of neighbour (ni)
         Dis(x, y): the distance between nodes x and y.       will be chosen to link the node ni, and become as the
          The BS can be deemed as a special sensor node.       newly initiate node in next linking step. The process is
                                                               repeated until all nodes are put together, and thus finally a
B. OPERATION OF PROPOSED PROTOCOL                              group chain Cx,y is formed.
        The operation of proposed protocol consists of
four phases: 1) Group Construction Phase. 2) Chain             3. Leader Node Election Phase
Formation Phase. 3) Leader Node Election Phase and 4)                   For data transmission, a leader node in each
Data Collection and Transmission Phase.                        group chain must be selected for collecting and
                                                               forwarding the aggregated data to the BS. Unlike the
                                                               PEGASIS and EPEGASIS schemes, in which the leader
1. Group Construction Phase                                    in each chain is elected in a round-robin manner, proposed
          The main purpose of this phase is ready to divide    protocol chooses the chain leader (lx,y) based on the
the sensing field into a number of smaller areas so that it    maximum value Res(ni) of group nodes. Initially, in each
can create multiple shorter chains to reduce the data          group, the node farthest away from the BS is assigned to
propagation delay and redundant transmission path in           be the group chain leader. After that, for each data
later phases. Instead of using concentric clusters as          transmission round, the node with the maximum residual
EPEGASIS scheme does, the proposed protocol adopts             energy will be elected. The residual power information of
the technique of Beam Star to organize its groups. After       each node ni can be forwarded with the fused data to the
the sensor nodes are scattered, the BS gradually sweeps        chain leader lx,y along the chain cx,y, so that the chain
the whole sensing area, by successively changing different     leader can determine which node will be the new leader
transmission power levels and antenna directions, to send      for                    next                   transmission
control information (including the values of R and θ) to all
nodes. After all nodes receiving such control packets, they
can easily determine which group they are respectively
belonging to. In addition, by the received signal strength
indication (RSSI), every node can also figure out the
value of dis(ni, BS). A grouping example with R=1...3 and
θ=1...2 is shown in Figure 3.




                                                                Figure (4): The group chains constructed from Figure 3



                                                                                                             590 | P a g e
Mr. Ravinder Kumar , Dr. P. S. Mundra / International Journal of Engineering Research and
                      Applications (IJERA) ISSN: 2248-9622 www.ijera.com
                             Vol. 2, Issue 4, July-August 2012, pp.588-592
4. Data Collection and Transmission Phase
          After completed the previous three phases, the          B. Simulation results
data collection and transmission phase begins. The data           Figure 6 shows the simulation results of improved number
transmission procedure in proposed protocol is similar to         of survival sensor nodes versus number of iterations. In
that in PEGASIS scheme. Firstly, the normal nodes in              CHIRON routing is done on the basis of changing of
each group Gx,y transmit their collected data along the           covering angles. But in proposed algorithm there is no
cx,y, by passing through their nearest nodes, to the chain        change in the covering angle occurs to transmit the data.
leader lx,y. And then, starting from the farthest groups, the     Figure 6(a) shows that the numbers of survival rate of
chain leaders collaboratively relay their aggregated              nodes are increased; Figure 6(b) shows that the overall
sensing information to the BS, in a multi-hop, leader-by-         lifetime of the network is increased. Figure 6(c) shows the
leader transmission manner. In order to avoid a longer            improvement in the time taken to transferring the packets.
transmission distance incurred between two chain leaders.




                     Cluster Head                                            Figure6 (a): Number of survival nodes
                Dots are Sensor Nodes
    Arrows shows the data transmission from Cluster
         Figure 5: The data transmission flows
     Head to Cluster Head in same covering angle

           Figure 5: The data transmission flows

5. IMPROVED SCHEME
           In Chiron the sensor field is used to split the area
into the number of smaller area so that it can create
multiple shorter chains to transmit the information. But
due to change in covering angle occur at regular intervals
so it increase the total distance and time to reach the
information at the base station hence the lifetime of the
network is affected. So to improve these parameter we
change the scheme of data transmission flow. In proposed
scheme the data is transmitted from cluster head to cluster
in same covering angle. Hence data has no need to change
its path from one covering angle to other. So the distance               Figure6 (b): Overall lifetime of the network
and time is decreased to transmit the information to the
base station also the overall life and number of survival
nodes are improved.

6. SIMULATION AND RESULTS
         For evaluation the performance of our proposed
protocol, in this section, we use a simulation tool
MATLAB [8] to conduct several experiments.

A. Simulation environment and parameters
          In our simulations, we consider three different
sizes of sensing area: 100*100 m2, 200*200 m2 each is
with 100 randomly deployed sensor nodes and 1000
iterations. The BS is located on the corner of sensing
field. For each simulation scenario, the results are drawn
by the average value of 10 runs.

                                                                                                               591 | P a g e
Mr. Ravinder Kumar , Dr. P. S. Mundra / International Journal of Engineering Research and
                        Applications (IJERA) ISSN: 2248-9622 www.ijera.com
                               Vol. 2, Issue 4, July-August 2012, pp.588-592

                                                                [5]   Liu Yueyang, Ji Hong, Yue Guangxin, “An
                                                                      energy-efficient   PEGASIS-based       enhanced
                                                                      algorithm in WSN”, China communications,
                                                                      Beijing, China, August 2006, pp.91-97.

                                                                [6]   S. Hussain, and O. Islam, “An Energy Efficient
                                                                      Spanning Tree Based Networks,” Proceedings
                                                                      of Wireless Communications and Networking
                                                                      Conference, pp. 4383-4388, 2007.

                                                                [7]   S. M. Jung, Y. J. Han, and T. M. Chung, “The
                                                                      Concentric Clustering Scheme for Efficient
                                                                      Energy Consumption in the PEGASIS,”
                                                                      Proceedings of the 9th International Conference
                                                                      on Advanced Communication Technology, Vol.
   Figure6 (c): time taken for packet transferring in ms              1, pp. 260-265, 2007.

                                                                [8]   Technical Computer: The MatWorks MATLAB
7. CONCLUSION
                                                                      and Simulink for http://www.mathworks.com/
          In this paper, we propose an Advanced data
routing protocol with improved hopping in Chiron which
                                                                [9]   S. Mao, and Y. T. Hou, “BeamStar: An Edge-
is suitable for large sensor networks with power and time
                                                                      Based        Approach to Routing in Wireless
constraints. As in case of chiron there are more hopping
                                                                      Sensor Networks,” IEEE Transactions on
to transmits the data to the base station but in our case the
                                                                      Mobile Computing, Vol. 6, Issue 11, pp. 1284-
data is transmitted through cluster head to cluster in same
                                                                      1296, 2007.
covering angle hence it reduces the extra distance covered
in Chiron also the time taken to tranfering the packet to
the base station thus it shows significantly improvement
in the survival of overall sensors and lifetime of the
network. Simulation results shows that the proposed
protocol is superior to Chiron. Comparing to the Chiron
the proposed protocol scheme achieves improvement
about 8% to 12%, 9% to 13.5% , 5% to 11% in overall
lifetime of the network, number of survival node and
time taken for packets transmisson respectively.

REFERENCES
  [1]     I. F. Akyildiz, W. Su, Y. Sankarasubramaniam,
          and E. Cayirci, “A Survey on Sensor Networks,”
          IEEE Commun. Mag. Vol. 38, pp. 102-114,
          2002.

   [2]    J. N. Al-Karaki and A. E. Kamal, “Routing
          Techniques       in Wireless Sensor Networks:
          A Survey,” Proceedings of the IEEE Wireless
          Communications, Vol. 11, pp. 6-28, 2004.

  [3]     C. Y. Chong and S. P. Kumar, “Sensor
          Networks: Evolution, Opportunities, and
          Challenges,” Proceedings of the IEEE, Vol. 91,
          pp. 1247-1256, 2003.

   [4]    Yongchang Yu and Yichang Song, “An Energy-
          Efficient Chain-Based Routing Protocol in
          Wireless Sensor Network”, 2010 International
          Conference on Computer Application and
          System Modeling (ICCASM 2010), Taiyuan,
          978-1-4244-7237-6/ 2010, IEEE, pp. V11-486 -
          V11-489.


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ADVANCED DATA ROUTING FOR WIRELESS SENSOR NETWORKS

  • 1. Mr. Ravinder Kumar , Dr. P. S. Mundra / International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 www.ijera.com Vol. 2, Issue 4, July-August 2012, pp.588-592 Advanced Data Routing Protocol With Improved Hopping in Chiron Mr. Ravinder Kumar* , Dr. P. S. Mundra** * (Department of Electronics and Communication Engineering, Punjab Technical University, India M.Tech (ECE) Scholar, Chandigarh College of Engineering, Landran) ** (Department of Electronics and Communication Engineering, Punjab Technical University, India Professor in Chandigarh College of Engineering. Landran, Punjab, India) ABSTRACT Wireless sensor network [1] generally consists have been proposed to address this topic [2] Chain-based of large number of sensor nodes. The wireless sensor routing is one of most significant routing mechanisms. In network can be defined as large number of small such routing scheme, sensor nodes are linked into a single sensing self powered nodes which gather the or multiple chains in advance. In data dissemination information from the geographical area and phase, each node communicates only with its closest communicate in wireless fashion with the goal of neighbors, and takes turns to be the chain leader for handing their processed data to the base station. Due transmitting the aggregated data to the BS. Even the chain to the power restriction of sensor nodes, efficient based routing protocols can effectively balance the node’s routing in wireless sensor networks is a critical energy dissipation, and thus significantly extend the approach to saving node’s energy and thus prolonging network life time they would be easy to cause serious the network lifetime. In this paper, we propose transmission delays and redundant paths, particularly for advanced data routing protocol with improved large sensing areas. In order to improve the deficiencies as Hopping in Chiron. As in Chiron chain leader aforementioned we propose advanced data routing belonging to the certain covering angle transmits the protocol with improved Hopping in Chiron. In CHIRON gathered data to the chain leader of the different the technique of Beam Star [9] is first used to divide the covering angle this creates the increase in distance, sensing area into several fan-shaped groups. The sensor and delay. So the main goal of our research is to nodes within each group are then self organized into a improve the overall lifetime of network, time required chain for data dissemination. Unlike traditional to transfer the packets and improvement in number of approaches, instead of taking turns, we consider the node survival sensor. Simulation results show that the with a maximum residual energy as chain leader proposed protocol is superior to Chiron. Comparing candidate. In addition, for avoiding a longer transmission to the Chiron the proposed protocol scheme achieves would be incurred among chain leaders, the nearest improvement about 8% to 12%, 9% to 13.5% , 5% downstream chain leader will be elected for relaying the to 11% in overall lifetime of the network, number of aggregated sensing information. With these strategies, our survival node and time taken for packets transmission proposed protocol has the following merits. 1) Each node respectively under various small and large simulation can get its location information passively from the BS areas respectively. with a minimum control overhead. 2) The collected sensing data can be reported to the BS, in a short-haul and Key Words-- Wireless Sensor Network, Routing multi-hop transmission manner. 3) It can effectively protocol, Chiron, lifetime reduce the chain length and redundant transmission path, so thus significantly improve the delay time and save INTRODUCTION network energy as compared to other counterparts. Wireless Sensor Networks (WSNs) have gained a great deal of attentions in recent years [3]. A WSN generally consists of a large number of battery-powered, resource constraints wireless sensor nodes, which might be randomly deployed in an unattended and unreachable terrain, for sensing and collecting the wanted data from the surroundings, and thus reporting the fused information to a remote Base Station (BS). WSNs have been widely employed in several applications such as habitat monitoring, disaster supervising, and bioinformatics [1] [10]. Due to the characteristics of random deployment and low cost with sensor nodes, it is expected to be difficult The sensor nodes are usually scattered in a sensor field as and unnecessary for recharging them once their energies shown in Figure1.Each of these scattered sensor nodes has are exhausted. As a consequence, how to conserve node’s the capabilities to collect data and route data back to the power and thus prolong the network lifetime is a critical sink. Data are routed back to the sink by a multi-hop issue in WSNs. Several power-efficient routing protocols infrastructure less architecture through the sink as shown 588 | P a g e
  • 2. Mr. Ravinder Kumar , Dr. P. S. Mundra / International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 www.ijera.com Vol. 2, Issue 4, July-August 2012, pp.588-592 in Figure 1. The sink may communicate with the task then take turns to act as the chain leader. In data manager node via Internet or satellite. dissemination phase, every node receives the sensing information from its closest upstream neighbour, and then The remainder of this paper is organized as follows. In passes its aggregated data toward the designated leader, Section 2, routing technique used in WSN is discussed. In via its downstream neighbour, and finally the base station. section 3 some previous related works which motivate our Although the PEGASIS constructs a chain connecting all research are briefly reviewed and discussed. The design nodes to balance network energy dissipation, there are philosophy and implementation of our proposed protocol still some flaws with this scheme. 1) For a large sensing are detailed in Section 4. Section 5 discusses the improved field and real-time applications, the single long chain may scheme. Section 6 manifests our simulation environments, introduce an unacceptable data delay time. 2) Since the parameters, and results. The conclusion follows in Section chain leader is elected by taking turns, for some cases, 7. several sensor nodes might reversely transmit their aggregated data to the designated leader, which is far 2. ROUTING TECHNIQUES IN WSN away from the BS than itself. This will result in redundant Wireless sensor networks (WSN) consist of transmission paths, and therefore seriously waste network small nodes with sensing, computation, and wireless energy. 3) The single chain leader may become a communications capabilities. Many routing, power bottleneck. management, and data dissemination protocols have been specifically designed for WSNs where energy awareness B. Enhanced PEGASIS is an essential design issue. Routing protocols in WSNs In 2007, Jung et al. proposed a variation of might differ depending on the application and network PEGASIS routing scheme, termed as Enhanced PEGASIS architecture. Overall, the routing techniques [2] are [7]. In their method, the sensing area, centred at the BS, is classified into three categories based on the underlying circularized into several concentric cluster levels. For network structure: flat, hierarchical, and location-based each cluster level, based on the greedy algorithm of routing. Figure 2 shows routing protocols in WSNs. PEGASIS, a node chain is constructed. In data transmission, the common nodes also conduct a similar way as the PEGASIS to transfer their sensing data to its chain leader. After that, from the highest (farthest) cluster level to the lowest (near to the BS), a multi-hop and leader-by-leader data propagation task will be followed. The EPEGASIS although has considered the location of the BS to slightly improve the redundant transmission path and the network lifetime, there are still some problems with that scheme. 1) For large sensing areas, the node chain in each concentric cluster would still become lengthy, and thus result in a longer transmission delay. 2) Since the leader node election strategy is same as that in PEGASIS (by taking turns), it did not consider the node’s residual energy. 3) While the distribution of sensor nodes Figure 2: Routing Protocols in WSNs is not even, the transmission distance between two chain- leaders in different cluster levels might be lengthy, this In flat networks all nodes play the same role, while would consume more energy. hierarchical protocols aim to cluster the nodes so that cluster heads can do some aggregation and reduction of 4. PROPOSED PROTOCOL data in order to save energy. Location-based protocols For improving the deficiencies with the utilize position information to relay the data to the desired aforementioned schemes, in this section, we thus propose regions rather than the whole network. an energy efficient [4] hierarchical chain-based routing protocol. The design philosophy is described as follows. 3. RELATED WORK In general, three strategies are considered for the A. Network model and assumptions design of data aggregation techniques in WSNs. They are Without loss of generality, in our research, we also cluster based, tree-based [6], and chain-based. In this consider a WSN of n energy-constrained sensor nodes, section, we only review chain-based routing protocols, which are randomly deployed over a sensing field. The PEGASIS and Enhanced [5], and point out their pros and BS is located at a corner of the sensing area, and equipped cons that motivate our research. with a directional antenna and unlimited power. As a result, the BS can adaptively adjust its transmission power A. PEGASIS level and antenna direction to send control packets to all PEGASIS is a basic chain-based routing nodes in the WSN. Besides, for easy discussion, we define protocol. In which, all nodes in the sensing area are first some notations as follows: organized into a chain by using a greedy algorithm, and 589 | P a g e
  • 3. Mr. Ravinder Kumar , Dr. P. S. Mundra / International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 www.ijera.com Vol. 2, Issue 4, July-August 2012, pp.588-592  R: the transmission range of the BS. For simplicity, we use distinct integers (1 … n) to represent various ranges.  θ: the beam width (covering angle) of the directional antenna. Also, similar to the definition of R, different integers (1 … n) are used to indicate distinct angles.  G θ, R: the group id. Theoretically, by changing different values of θ and R, the sensing area can be divided into n * n groups. Those are G1,1 G1,2 …, G1,n, …, Gn,1, …, G n ,n  Ni: the node i; the node set N= {n1, n2, n3… n i}, where 1≤i≤|N|. Figure (3): Grouping example with R=1…3 and θ=1...2  C x, y: the id of a chain which was formed in group G x, y. the chain set C= {c1,1 c1,2 ….}. 2. Chain Formation Phase  L x, y: the leader node id of chain C x, y. The In this phase, the nodes within each group Gx,y leader set L= {l1,1, l1,2…}. will be linked together to form a chain Cx,y respectively.  Neighbour (ni): the neighbouring nodes of ni. The chain formation process is same as that in PEGASIS The neighbouring nodes mean the nodes which scheme. For each group G x,y, the node ni with the are locating in the transmission range of a maximum value of dis (ni, BS) (that is farthest away from specific node. the BS) is initiated to create the group chain. By using a  Res (ni): the residual energy of node ni. [6] algorithm, the nearest node (to ni) of neighbour (ni)  Dis(x, y): the distance between nodes x and y. will be chosen to link the node ni, and become as the The BS can be deemed as a special sensor node. newly initiate node in next linking step. The process is repeated until all nodes are put together, and thus finally a B. OPERATION OF PROPOSED PROTOCOL group chain Cx,y is formed. The operation of proposed protocol consists of four phases: 1) Group Construction Phase. 2) Chain 3. Leader Node Election Phase Formation Phase. 3) Leader Node Election Phase and 4) For data transmission, a leader node in each Data Collection and Transmission Phase. group chain must be selected for collecting and forwarding the aggregated data to the BS. Unlike the PEGASIS and EPEGASIS schemes, in which the leader 1. Group Construction Phase in each chain is elected in a round-robin manner, proposed The main purpose of this phase is ready to divide protocol chooses the chain leader (lx,y) based on the the sensing field into a number of smaller areas so that it maximum value Res(ni) of group nodes. Initially, in each can create multiple shorter chains to reduce the data group, the node farthest away from the BS is assigned to propagation delay and redundant transmission path in be the group chain leader. After that, for each data later phases. Instead of using concentric clusters as transmission round, the node with the maximum residual EPEGASIS scheme does, the proposed protocol adopts energy will be elected. The residual power information of the technique of Beam Star to organize its groups. After each node ni can be forwarded with the fused data to the the sensor nodes are scattered, the BS gradually sweeps chain leader lx,y along the chain cx,y, so that the chain the whole sensing area, by successively changing different leader can determine which node will be the new leader transmission power levels and antenna directions, to send for next transmission control information (including the values of R and θ) to all nodes. After all nodes receiving such control packets, they can easily determine which group they are respectively belonging to. In addition, by the received signal strength indication (RSSI), every node can also figure out the value of dis(ni, BS). A grouping example with R=1...3 and θ=1...2 is shown in Figure 3. Figure (4): The group chains constructed from Figure 3 590 | P a g e
  • 4. Mr. Ravinder Kumar , Dr. P. S. Mundra / International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 www.ijera.com Vol. 2, Issue 4, July-August 2012, pp.588-592 4. Data Collection and Transmission Phase After completed the previous three phases, the B. Simulation results data collection and transmission phase begins. The data Figure 6 shows the simulation results of improved number transmission procedure in proposed protocol is similar to of survival sensor nodes versus number of iterations. In that in PEGASIS scheme. Firstly, the normal nodes in CHIRON routing is done on the basis of changing of each group Gx,y transmit their collected data along the covering angles. But in proposed algorithm there is no cx,y, by passing through their nearest nodes, to the chain change in the covering angle occurs to transmit the data. leader lx,y. And then, starting from the farthest groups, the Figure 6(a) shows that the numbers of survival rate of chain leaders collaboratively relay their aggregated nodes are increased; Figure 6(b) shows that the overall sensing information to the BS, in a multi-hop, leader-by- lifetime of the network is increased. Figure 6(c) shows the leader transmission manner. In order to avoid a longer improvement in the time taken to transferring the packets. transmission distance incurred between two chain leaders. Cluster Head Figure6 (a): Number of survival nodes Dots are Sensor Nodes Arrows shows the data transmission from Cluster Figure 5: The data transmission flows Head to Cluster Head in same covering angle Figure 5: The data transmission flows 5. IMPROVED SCHEME In Chiron the sensor field is used to split the area into the number of smaller area so that it can create multiple shorter chains to transmit the information. But due to change in covering angle occur at regular intervals so it increase the total distance and time to reach the information at the base station hence the lifetime of the network is affected. So to improve these parameter we change the scheme of data transmission flow. In proposed scheme the data is transmitted from cluster head to cluster in same covering angle. Hence data has no need to change its path from one covering angle to other. So the distance Figure6 (b): Overall lifetime of the network and time is decreased to transmit the information to the base station also the overall life and number of survival nodes are improved. 6. SIMULATION AND RESULTS For evaluation the performance of our proposed protocol, in this section, we use a simulation tool MATLAB [8] to conduct several experiments. A. Simulation environment and parameters In our simulations, we consider three different sizes of sensing area: 100*100 m2, 200*200 m2 each is with 100 randomly deployed sensor nodes and 1000 iterations. The BS is located on the corner of sensing field. For each simulation scenario, the results are drawn by the average value of 10 runs. 591 | P a g e
  • 5. Mr. Ravinder Kumar , Dr. P. S. Mundra / International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 www.ijera.com Vol. 2, Issue 4, July-August 2012, pp.588-592 [5] Liu Yueyang, Ji Hong, Yue Guangxin, “An energy-efficient PEGASIS-based enhanced algorithm in WSN”, China communications, Beijing, China, August 2006, pp.91-97. [6] S. Hussain, and O. Islam, “An Energy Efficient Spanning Tree Based Networks,” Proceedings of Wireless Communications and Networking Conference, pp. 4383-4388, 2007. [7] S. M. Jung, Y. J. Han, and T. M. Chung, “The Concentric Clustering Scheme for Efficient Energy Consumption in the PEGASIS,” Proceedings of the 9th International Conference on Advanced Communication Technology, Vol. Figure6 (c): time taken for packet transferring in ms 1, pp. 260-265, 2007. [8] Technical Computer: The MatWorks MATLAB 7. CONCLUSION and Simulink for http://www.mathworks.com/ In this paper, we propose an Advanced data routing protocol with improved hopping in Chiron which [9] S. Mao, and Y. T. Hou, “BeamStar: An Edge- is suitable for large sensor networks with power and time Based Approach to Routing in Wireless constraints. As in case of chiron there are more hopping Sensor Networks,” IEEE Transactions on to transmits the data to the base station but in our case the Mobile Computing, Vol. 6, Issue 11, pp. 1284- data is transmitted through cluster head to cluster in same 1296, 2007. covering angle hence it reduces the extra distance covered in Chiron also the time taken to tranfering the packet to the base station thus it shows significantly improvement in the survival of overall sensors and lifetime of the network. Simulation results shows that the proposed protocol is superior to Chiron. Comparing to the Chiron the proposed protocol scheme achieves improvement about 8% to 12%, 9% to 13.5% , 5% to 11% in overall lifetime of the network, number of survival node and time taken for packets transmisson respectively. REFERENCES [1] I. F. Akyildiz, W. Su, Y. Sankarasubramaniam, and E. Cayirci, “A Survey on Sensor Networks,” IEEE Commun. Mag. Vol. 38, pp. 102-114, 2002. [2] J. N. Al-Karaki and A. E. Kamal, “Routing Techniques in Wireless Sensor Networks: A Survey,” Proceedings of the IEEE Wireless Communications, Vol. 11, pp. 6-28, 2004. [3] C. Y. Chong and S. P. Kumar, “Sensor Networks: Evolution, Opportunities, and Challenges,” Proceedings of the IEEE, Vol. 91, pp. 1247-1256, 2003. [4] Yongchang Yu and Yichang Song, “An Energy- Efficient Chain-Based Routing Protocol in Wireless Sensor Network”, 2010 International Conference on Computer Application and System Modeling (ICCASM 2010), Taiyuan, 978-1-4244-7237-6/ 2010, IEEE, pp. V11-486 - V11-489. 592 | P a g e