Int. Journal of Electrical & Electronics Engg.
Vol. 2, Spl. Issue 1 (2015)
e-ISSN: 1694-2310 | p-ISSN: 1694-2426
A Survey on Routing Protocols in Wireless Sensor Network Using Mobile Sink 1
Deepak Kumar, 2Deepali
1,2
CS Department, Guru Nanak College, Budhlada, India
Abstract— Wireless sensor network (WSN) is collection of large number of sensor nodes which senses the physical conditions of environment and send the data to sink. WSN can be classified as static and mobile WSN. In static routing protocol, energy consumption is not uniformly distributed. To avoid this problem, wireless sensor network with mobile sink can be used, where mobile sink gathers data from other nodes using 1-hop communication. In this paper, we presented the various types of WSN. At last, we compared the various routing protocol of WSN with mobile sink based on parameter no. of sinks, mobility of CH and mobility pattern. Keywords—Static WSN. Mobile WSN, Sink node,Cluster head
I. INTRODUCTION WSN is collection of large number of sensor nodes which senses the physical conditions of environment and send the data to sink. The various application of WSN is in military area, environment area, health, home and other commercial areas [1]. A sensor network design is influenced by many factors like fault tolerance, scalability, production costs, operating environment, transmission media and power consumption. WSN is divided into categories based on type of communication: Single-hop and Multi-hop. In Single-hop communication, CH directly sends their aggregate data to sink. In Multi-hop, CH may send their aggregate to other CH that is nearer to CH rather than sink directly. CH uses one or more CH to send its data to sink. Fig 1.1 shows the categorization of WSN. WSN can be classified as static and mobile WSN. In static WSN, energy efficient routing algorithm can be categorized as follows: data centric routing algorithm, location based routing algorithm and hierarchical routing algorithm. Data centric routing algorithm finds route from multiple sources to single destination by using metadata [2]. Location based routing algorithm requires actual location information for every sensor node. Hierarchical routing algorithm divides the network into clusters [3]. Cluster head (CH) is elected in each cluster. CH collects data from its members, aggregates the data and sends to sink. This approach is energy efficient but relatively complex than other approaches. Wireless Network
Sensor
Static WSN
Location Based
Node Mobility
Sink Mobility
Hierarchi cal Weak Mobility
Fig 1 Categorization of WSN
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An outline of this paper is as follows. Section II presents the Low Energy Adaptive Cluster Hierarchy (LEACH) protocol. Section III presents the related work. Section IV presents comparison of routing protocols based on mobile sink WSN and section V describes the conclusion of the paper. II. LEACH Protocol LEACH [5] is a cluster based approach in which both sensor nodes and sink are stationary. LEACH works in rounds. Each round begins with set up phase followed by steady phase. In set up phase, CH is elected. Each node generates random number between 0 and 1. This number is compared with threshold value T(n) which is calculated by using Eq. (1).
∗(
)
T(n) = if n ∈ G
0, Otherwise
(1)
Where P is percentage of CHs, r is number of rounds and G is set of nodes that have not been CHs in the last 1/P rounds. If the random value is less than T (n), the node becomes CH for current round. In steady phase, all NonCH nodes send data to CH and then CH aggregate all data and send it to the sink.
Mobile WSN
Relay agent Mobility Data centric
In WSN, mobility can be divided into three classes: sink mobility, node mobility, relay agent mobility[4]. In sink mobility, sink node’s position is not static throughout the lifetime of network. With sink mobility, we can achieve load balancing and longer network lifetime. In node mobility, sensor nodes are mobile. It is further categorized into two classes: Weak mobility, Strong mobility. In weak mobility, mobility takes place due to death of some network nodes. In strong mobility, mobility takes place due to external factors. In relay agent mobility, the end system is mobile. Sink mobility can be classified according to movement as: random mobility, predictable mobility and controlled mobility. In random mobility, nodes move randomly in network. In predictable mobility, nodes move along a trajectory with given speed. In controlled mobility, external entity controls the node movement.
Strong Mobility
III. RELATED WORK In [6] author proposed a protocol in which sink mobility is considered for removing the problem of energy depletion of nodes that are nearer to sink. In this, sink changes its position when the energy of nearby nodes becomes low. Sink moves to that zone which has maximum residual energy. Simulation result shows that proposed protocol NITTTR, Chandigarh
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Int. Journal of Electrical & Electronics Engg.
Vol. 2, Spl. Issue 1 (2015)
increase the network lifetime than the protocol that having static nodes. In [7] author proposed a protocol that using mobile sink. In this protocol, when each round begins, clustering is performed and CH get selected as in LEACH. All CHs send a status packet across the network which gives the information of maximum distance from sink supported by CH for performing the data communication. Node’s remaining energy and lifetime is tracked down for calculation of this distance. The optimal point for sink is a new location where data communication with all the CHs can take place in minimum cost of energy. Simulation result shows that proposed protocol increases network lifetime. In [8] author proposed a protocol that having both node and sink mobility. In proposed protocol, after deployment of sensor nodes, network is divided into clusters and each cluster contains sensor node with different roles such that gateway node, CH node and ordinary sensor node. Sink selects a gateway node in each cluster which has highest remaining energy and lowest mobility level. Sink selects two CH in each cluster such that two nodes jointly can cover the entire cluster. Ordinary nodes send their data to CH. CH aggregates the data and send to gateway node. Gateway node collects data from both CH and send to sink. This hierarchical protocol reduces energy consumption and increases network lifetime. Simulation results show that the proposed protocol is better than CBR-Mobile in terms of throughput, average energy consumption and network lifetime. In [9] author proposed a scheme based upon controlled mobility of sink. In this protocol, mathematical model Mixed Integer Linear Programming (MILP) is used for finding the path of sink such that it will consume less energy and increase network lifetime. Simulation result shows that the proposed scheme increases network lifetime. In [10] author proposed Mobile-Sink based Energy efficient Clustering Algorithm (MECA).In this algorithm, initially mobile sink is deployed at the edge of the sensing field that moves along a fixed track and is predictable. Sink only needs to broadcast its current location at the beginning and that too just for once. After that, sensor nodes keep record of initial position of sink and reduce angle by:∗∆ = (2) Where is velocity, R is radius of transmission range and ∆ is time interval. In this, sensing field is divided into equal sectors. In each sector, a node is selected as CH based on residual energy. In setup phase, non-CHs send their data to CH. After collecting data, CH aggregates that data and sends it to the sink. MECA uses multi-hop transmission for intra cluster routing for saving energy. Simulation results show that MECA is better than LEACH in terms of energy consumption. In [11] author proposed Energy Efficient Competitive protocol [20]. In this protocol, candidate CH is selected based on probability. Each candidate CH computes competition range as:-residual energy and node id. Competition range is calculated as: NITTTR, Chandigarh
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e-ISSN: 1694-2310 | p-ISSN: 1694-2426
=
×
( ,
)
+
(3)
Where is maximum distance, is minimum distance, ( , ) is distance between node and sink. Candidate CHs that are in competition range will compete for final CH based on residual energy. If two candidate CHs have same residual energy and are in competition range, then candidate CH having low node id will be selected as CH. In setup phase, multi-hop communication is take place. If the distance between CH and sink is less than threshold value, then CH sends aggregate data directly to sink. Else, CH send data to relay node. Each CH select relay node as minimum cost node as:()= ( )
( )
∗
( )
,
( , (
[0,1]
)
,
( ,
( ,
)
) )
+ (1 − ) ∗ (4)
Where ( , ) is distance between node and node , SN is sink and ( ) is energy of node j. Sink is mobile with certain speed and with predefined path. Sink has scheduled park position. Each CH finds optimal park position for sending their data to sink. Simulations results show that mobile sink prolong network lifetime and improve energy efficiency. In [12] author proposed a protocol that having multiple mobile sink. In this protocol, sensor nodes are deployed randomly in the network. One sink node has fixed position which controlled the other mobile sink nodes. Mobile sink nodes collect the data from CHs which reduce communication cost of CHs and increase the network lifetime. Then mobile sink nodes send the aggregated data to static sink. Simulation results show that proposed algorithm is better than shortest hop path algorithm in terms of network lifetime and packet delivery ratio. IV.PROTOCOL COMPARISON The papers surveyed have common objective which is to uniformly distribute energy consumption by all sensor nodes using mobile sink. This improves the overall lifetime of the network. Protocols discussed in section III are compared and presented in Table 1. COMPARISON OF ROUTING PROTOCOLS IN MOBILE
Protoc ol
WSN
Characteristics No. of sinks
Mobility is provided to CH Sink
[6]
Multiple
Mobile
Static
[7] [8]
Single Single
Static Mobile
[9]
Single
Mobile Mobile Mobile
[10]
Multiple
[11]
Single
[12]
Multiple
[13]
Multiple
Mobile Mobile
Static Static Static
Mobile
Static
Mobile
Static
Mobility pattern Random and Predefined Controlled Random Controlled Predefined Predefined and Controlled Random and predefined Random and predefined
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Int. Journal of Electrical & Electronics Engg.
Vol. 2, Spl. Issue 1 (2015)
V. CONCLUSION In static WSN energy consumption is not uniformly distributed between all sensor nodes of the network. This causes a limited network lifetime. To avoid this problem, wireless sensor network with mobile sink can be used. In this paper, we presented the various types of WSN. At last, we compared the various routing protocol of WSN with mobile sink based on parameter.
REFERENCES .F.Akyildiz,W. Su, Y. Sankarassubramaniam, E.Cayirci, “Wireless Sensor Networks: a survey,” Computer Networks(Elsevier), vol. 38, pp. 393422, 2002. B.Krishnamachari, D.Estrin, S.Wicker, “Modelling Data-centric routing in Wireless sensor network,” IEEE Infocom, pp. 1-11, 2002. Prabagarane, C. A.Navin, Partibane, Nagarajan, V. Krishnakiran, “Hierarchictal routing algorithm for cluster based multi hop Mobile Adhoc network,” IEEE Communication Society, pp. 1116-1120, 2004. A.Raja, X. Su, “Mobility handling in mac for wireless ad hoc networks,” Wirel. Commun. Mob. Comput. ,Vol. 9, pp. 303-311, 2009.
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e-ISSN: 1694-2310 | p-ISSN: 1694-2426
W.R.Heinzelman, “Energy-Efficient Communication Protocol for Wireless Microsensor Networks,” Proc. of the 33rd Hawaii International Conference on System Sciences, pp. 1-10, 2000. M.Marta, M.Cardei, “Using Sink Mobility to increase Wireless sensor Network lifetime,” IEEE 2008. M.H.Khodashahi, F.Tashtarian, M.H.Y. Moghaddam, M.T.Honary, “Optimal Location of Mobile sink in Wireless Sensoe,” IEEE Communication Society, 2010. H.K.D. Sarma, A.Kar, R.Mall, “Energy Efficient Routing protocol Wireless sensor networks with node and sink Mobility,” IEEE, 2011. F.Tashtarian, M.H.Y. Moghaddam, S.Effati, “Energy Efficient Data Gathering Algorithm in Hierarchical Wireless sensor network with Mobile Sink,” Proc. of 2nd International Conference on Computer and Knowledge Engineering, pp. 232-237, 2012. J.Wang, Y.Yin, J.U.Kim, S.Lee, C.F,Lai, “An Mobile-sonk Based Energy Efficient Clustering Algorithm for Wireless sensor networks,” Proc. of 12th International Conference on Computer and Information Technology, pp. 678-683, 2012. J.Wang, X.Yang, Tinghuai, M.Wuz, J.Kim, “An Energy-efficient Competitive Clustering algorithm for Wireless sensor networks using Mobile Sink,” International Journal of Grid and Distributed Computing, vol. 5, pp. 79-92, 2012. V.Jose, G.Sadashivappa, “A Novel Energy efficient Routing algorithm for wireless sensor network using Sink Mobility,” International Journal of Wireless & Mobile Networks, vol. 6, pp. 15-25, 2014.
NITTTR, Chandigarh
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