research article modeling and simulation of a novel relay...

Research ArticleModeling and Simulation of a Novel RelayNode Based Secure Routing Protocol Using MultipleMobile Sink for Wireless Sensor Networks

Madhumathy Perumal1 and Sivakumar Dhandapani2

1Anna University Chennai 600025 India2ECE Department Easwari Engineering College Chennai 600089 India

Correspondence should be addressed to Madhumathy Perumal sakthi999gmailcom

Received 14 June 2015 Accepted 16 August 2015

Academic Editor Gnana Sheela

Copyright copy 2015 M Perumal and S Dhandapani This is an open access article distributed under the Creative CommonsAttribution License which permits unrestricted use distribution and reproduction in any medium provided the original work isproperly cited

Data gathering and optimal path selection for wireless sensor networks (WSN) using existing protocols result in collision Increasein collision further increases the possibility of packet drop Thus there is a necessity to eliminate collision during data aggregationIncreasing the efficiency is the need of the hour with maximum security This paper is an effort to come up with a reliable andenergy efficientWSN routing and secure protocol withminimum delayThis technique is named as relay node based secure routingprotocol for multiple mobile sink (RSRPMS) This protocol finds the rendezvous point for optimal transmission of data using aldquosplitting treerdquo technique in tree-shaped network topology and then to determine all the subsequent positions of a sink the ldquoBiasedRandomWalkrdquo model is used In case of an event the sink gathers the data from all sources when they are in the sensing range ofrendezvous pointOtherwise relay node is selected from its neighbor to transfer packets from rendezvous point to sink A symmetrickey cryptography is used for secure transmission The proposed relay node based secure routing protocol for multiple mobile sink(RSRPMS) is experimented and simulation results are compared with Intelligent Agent-Based Routing (IAR) protocol to prove thatthere is increase in the network lifetime compared with other routing protocols

1 Introduction

Wireless sensor network is self-organized scattered sensingand data propagation network Nodes are resource con-strained tiny autonomous devices They are used to sense theenvironmental conditions in their immediate surroundingsand transmit the data to the sink [1] WSN can be used tomonitor environment and collect data from massive fieldsat a very low cost and with less manpower Mobile devicesare attached to the sensors with robotic elements and thedata is exchanged between sensors nodes to drive applicationslike traffic monitoring environmental monitoring habitatmonitoring and climate study [2 3]

Data Gathering Using Mobile Sink Data gathering usingmobile sink minimizes the precious sensor node energy Theeffectiveness of it can be determined by the total sensorenergy saved and the time saved in gathering the sensory data

from its field or from the trajectory length of themobile sinks[4] Mobile sink in WSN optimizes the energy consumptionand reduces the delay observed during data gathering [5 6]

Routing and Issues on Mobile Sink Data Gathering The sinkpossesses significant replenishable energy resource it shouldmove closer to the subset of sensor devices to collect all therecorded data The energy consumption during this processis very minimalThe sink should be within a sensor range forsingle hop communication and remainwithin the transmitterrange for successful communication This problem becomesseverewhen the number of sensors is increased in a particulararea This results in inadequacy in network communicationtime to upload the data the node has to wait till the sinkreturns back As a result high delivery delay occurs [7]Mobile sink is a new challenge for densely deployed nodesand large WSN [8]

Hindawi Publishing Corporatione Scientific World JournalVolume 2015 Article ID 495945 9 pageshttpdxdoiorg1011552015495945

2 The Scientific World Journal

Protocol for Secure Communication in Mobile Sinks Secur-ing wireless sensor networks [WSN] is the primary and adaunting task because of its characteristics such as unreliablewireless communication constraints with respect to theresources unknown topology and unprotected environmentThe primary security goals here would be to maintain dataconfidentiality by not leaking data to neighboring node toprovide data freshness and to provide high availability andauthenticity by verifying that the data is always sent by anauthentic source

2 Related Literature

Kim et al [9] proposed Intelligent Agent-Based Routing(IAR) protocol for providing data delivery efficiently to themobile sink The IAR protocol is evaluated using mathe-matical analysis Results proved that the protocol supportsmobility of sink with less overhead and an improvement overthe triangular routing problem

Similarly [10] have highlighted the difference between amobile relay and the mobile sink Amobile relay collects datawhenever it is closer to sensor nodes Mechanical movementis employed to transport the data to the sink As it doesnot use the wireless links for transmission to the sink thelatency in delivering data is significant In contrast mobilesink performs various operations like distributing the loadamong the sensor nodes collecting data continuously fromthe nodes and moving slowly and discontinuously in datagathering process

In one attempt the mobile sink is a moving strategybased on remaining energy of the sensor nodes whichbalance the network workload and increase the network lifetime [11] Consequently [12] proposed a query-based datacollection scheme in which mobile sink issues queries in thesensing field and the response is received through multihopcommunicationTheproblemwith such query-based systemsis that the sink mobility causes the query and responsepackets to take different routes Query-based data collectionscheme (QBDCS) consumes lesser energy and deliveredpacket with minimum latency Moreover QBDCS selects theoptimal time for sending its query packet and tailored therouting process for sensor nodes for forwarding packets Theperformance of theQBDCSwas evaluated by comparingwitha ldquoNaiverdquo scheme using the OMNeT++ simulation tool

Reference [13] proposes RECPE a collection protocolwhich is reliable in a significant high scale WSN for aggre-gating packets from the source to sinkThis protocol has suc-cessfully covered all the routes in the network by employingexpected transmission count for forward links (ETF)methodfor constructing a collection tree thereby reducing the con-sequence of the asymmetric link in the entire networkMore-over the proposed protocol also utilized Trickle algorithmand pipeline mechanismThis mechanismminimizes controlinformation and increases the effectiveness of data deliveryReference [14] proposed a Mobile Sink Based Reliable andEnergy Efficient Data Gathering (MSREEDG) technique forgathering data in tree-shaped network topology in WSN andcompared with constant pause time method

Reference [15] uses an agent-based architecture that savesthe bandwidth and segregates SAPID (self-organized agent-based architecture for power-aware intrusion detection)in two phases This agent architecture principally uses aKohonen Self-Organizing Map to recognize the patterns andidentify anomalies appropriately for unauthorized users Ref-erence [16] tackles the hotspot problem and presents amobilesink based Routing Protocol (MSRP) for extending networklifetime for cluster based architecture in WSN MSRP movesto gather the data which in turn reduces the hotspot problemSimilarly various protocols are discussed in [17ndash19]

An alternative protocol to minimize the energy con-sumption and overhead during the data retrieval process isproposed in [20] Adaptive mobile strategy is implementedfor hierarchical networks in a large scale that are presentedin [21] The trajectory of mobile sink is planned in such away that no multihop relays are required for transmissionof data to the sink Reference [22] presents using multihopforwarding forming a cluster around the expected position ofa mobile sink guaranteeing minimum energy consumptionwith packet delay is discussed in [23]

A new data gathering scheme named as MaximumAmount Shortest Path to increase the network throughputand to save energy by efficiently assigning the sensor nodesis discussed in [24] A weighted rendezvous planning (WRP)heuristic is presented in [25] in this each sensor node isassigned with a weight appropriate to its hop distance and thenumber of data packets it forwards In another attempt [26]mobility patterns for data collection of the sink are presentedFrequent location updates from mobile sinks increase theenergy consumption in wireless transmissions [27]

In [28] a model for investigating the joint sink mobilityis presented and routing problem is constrained by thesink with a predefined number of locations The routingprotocol between multiple source and sink is proposed in[29] Reference [30] proposed secure energy efficient datacollection for mobile sink using a session based symmetrickey cryptography method to increase the life time of thenetwork Among all other security goals only authenticationof the node and data fairness is considered in this paperseveral internal attacks are out of the scope of this paper

Based on the literature review of the mobile sinks thispaper proposes a protocol called relay node based securerouting protocol for multiple mobile sink which is usedfor data gathering and the simulation results are comparedwith IAR protocol The results are demonstrated in such away that the proposed protocol performs better in terms ofperformance metrics like delivery ratio and energy efficiencyand reduces the delay and overhead in the WSN

The reminder of the paper is prepared in such a way thatSection 3 discusses the problem formulation architecturedata gathering routing protocol relay node selection algo-rithm and security protocol in detail Section 4 discusses theexperimentation and simulation results in detail using theproposedmethod and also gives a detailed comparison of theresults to show the superiority of the proposed methodThenthe paper discusses the results and finally concludes

The Scientific World Journal 3

Sensor node Sink

Figure 1 Proposed architecture of multiple mobile sink

3 The Proposed Solution

31 Problem Formulation Reference [14] proposedMSREEDG protocol for gathering data The sinkrsquos nextmoving position is determined by using a Biased RandomWalk model The optimal path for data transmission isestimated by rendezvous point selection method andsplitting tree process When the sensor senses the data andwhen it is ready for transmission the data are encoded andtransmitted to the sink and then it decodes the data and theresulting message is stored in local buffer After decoding allthe blocks the original data bundle is reconstructed by themobile sink The increase in the packet loss is prevented bymaximizing the sink pause time In this process only singlesink is used and when sink is out of its range the source hasto wait for the sink till it comes back to its region

This process can be enhanced for multiple numbers ofsinks and designing an efficient routing protocol for datagathering Here a relay node based secure routing protocolusing multiple mobile sink for data gathering for WSN isproposed

32 Proposed Architecture The source and sink know theirlocation It is also assumed that multiple sinks move in thenetwork The proposed architecture is shown in Figure 1

33 Data Gathering Routing Protocol

Let 119878 be the source nodeLet119863 be the sink nodeLet QP be query packetLet RePmr be rendezvous pointLet RN

119894be the relay node

Let RP119899be the new relay path

Let RP119900be the old relay path

Let RP seq be the sequence number of relay pathLet RP mes and R CLR be the relay path setup andclear message with RP seq

(1) If event occurs initially a rendezvous point (RePmr)is selected

(2) Then sink has to transmit QP to RePmr once the eventoccursThe fields in the QP are represented as the following

Sink IDHop countTransmitter distance

(3) RePmr broadcasts the QP with hop count countervalue as zero

(4) When the neighboring nodes receive the QP theyrebroadcast the packet by incrementing hop countcounter by 1Thus as this query propagated new hopnode towards RePmr is estimated that is in one hopcommunication distance

(5) If next new hop node gt 1

ThenTwo nodes compare the packets arrivaltime (Tpa)The new next hop node with earlier Tpa ischosen

End ifSource transmits the path request message(P REQ) to all its neighbors and the neigh-bor node that sends the (P REP) is chosenas next new hop nodeIf119863move in its radio range of RePmr

Then119863 receives the collected data from theRePmrElse119863 chooses RN

119894from its neighbor nodes

to transmit the data from RePmr to sink(Relay node selection)

End ifHere the node which is nearest to119863 is selectedas RN

(6) If an event occurs Ni enclosing it collectively pro-cesses the signal One among the nodes becomes 119878 togenerate the data reports

(7) When 119878 matches the data sent by QP the data isforwarded to one hop distance node

(8) If the next new hop node is failed or its battery isexhausted

Then

119878P REQ997888997888997888997888997888rarr Neigh

119894

Neigh119894

P REP997888997888997888997888rarr 119878

(1)

119878 chooses the respective Neigh119894as next new hop

nodeEnd if


34 RelayNode Selection When data packets are not receivedby 119863 for predefined time interval 119879 it suspects that theyare out of the coverage radio range In order to prevent thisaction the following steps are executed

(i) RePmr transmits at least one packet at interval of119879119899 period (119899 is integer)

(ii) If RePmr does not have data to send in 119879119899duration it transmits NULL packetThus when119878 does not receive the data packet for 119879 itperforms the following actions to select the relaynode

(1) Relay node request message (R REQ) is sent to itsNeigh

119894

119863R REQ997888997888997888997888997888rarr Neigh

119894 (2)

(2) Neigh119894node will reply to the sink

Neigh119894

R REP997888997888997888997888997888rarr 119863 (3)

(3) Sink chooses the node which is nearer to it asimmediate relay node

(4) The relay path message is sent through IRN

119863RP mes997888997888997888997888997888rarr IRN

119894

RP mes997888997888997888997888997888rarr RePmr (4)

(5) When RePmr receives the RP mes data packets aretransmitted in the path traversed by RP mes Thisrelay path is flagged with RP seqThe following is noted When 119863 moves away fromradio range or after completing its relay path setupthere may be possibility of packet drop This isprevented by RePmr by caching the overhead packetswhich are transmitted to 119863 The cached packets arerouted to119863 when RePmr receives RP mes

(6) If119863 is again away from its transmission range of IRN119894

then it selects new IRN119894(as per step (3))

(7) 119863 then transmits RP mes to RePmr through the newlyselected IRN

119894in separate relay path RP

119899which is

flagged with RP119899SEQ

(a) When RePmr receives relay path setup messageIf RP119900exists for the same sink

Then

RePmrR CLR997888997888997888997888997888rarr RP

119900 (5)

End ifWhen old relay path exists then RePmr sendR CLRmessage along RP

119900which is flagged with

RP119900SEQ

(b) When the relay path gets a new RP mes thenit does not remove the RP

119900state RP

119900state

is maintained until the path receives R CLRfor RP

119900 Figure 2 shows the flow chart of the

proposed protocol

35 Security Protocol for Data Gathering Security protocolsecurely gathers the sensed data and transmits it to the sinkIn this proposed model reactive type of data collection isused This protocol provides high degree of security withminimum overhead Symmetric key is used in WSN becauseof less computation as it uses same keys for encryption anddecryption The source and sink communication is showedin Figure 3

Secret key of the sensor node is 119878119894

Secret key of the sink node is 119878119904

Shared key is 119878shPrime number is119873

119894

Code for sink authentication is CSACode for node authentication is CNACode for message authentication is CMACipher text data is CT

119889

Hash function is119867()

351 The Process at the Sink Node Consider the followingequations

CSA =119867(119864(119873119894 119878119904))

Data = CT119889oplus CSA oplus 119878

119894= CT119889oplus CNA

At the sink node the cipher text is decrypted to get theoriginal message

(1) When the sink comes into a range of rendezvous pointit generates a large prime number

(2) Sink calculates CSA (CSA =119867(119864(119873119894 119878119904)))

(3) CSA is broadcasted among the neighbor nodes(4) 119861msg is broadcasted to all the nodes (119861msg = 119878sh oplus 119878119904 oplus

CSA)(5) Cipher message is received and decrypted with its

secret key (Data = CT119889oplus CSA oplus 119878

119894= CT119889oplus CNA)

(6) Compare the decrypted data with CMA if data issame accept it else reject the data

(7) If the data is rejected NAC is sent to the respectivenode

(8) The process is repeated till all the data is transmittedwithin its time slot

352 The Process at Source Node Consider the followingequations

CNA = CSA oplus119878119894

CT119889= Data oplus CNA

At the source node the plain text is encrypted with thesecret key

(1) Sensor node calculates its secret key when CSA isreceived (CNA = CSA oplus 119878

119894)


Start

Find the rendezvous point

Calculate distance to mobile sinks

Node i intransmission range

Announce neighbor node statusf = 1

Wait for neighbor sensor nodesannouncements f = 1

Wait for join requests

End of joinrequest

Yes No

No

No

In the transmissionrange of relay

node

Wait for neighbor sensor nodesannouncements f = f + 1

Send join request to relay nodesCreate TDMA schedule

Communicate with mobile sinksWait for schedule from relay

nodes

Communicate with relay node

Stop

YesYes

Figure 2 Flowchart of the proposed routing protocol

Source Sink

CSA = H(E(Ni Ss))

Bmsg = Ss oplus Ssh oplus CSA

CTd = data oplus CNA

Figure 3 Source and sink communication

(2) Sensor receives the 119861msg and calculates119861msg oplus CSA oplus 119878sh

(3) The corresponding result is compared with the sinksecret key if it is same accept the message else rejectthe message

(4) Sensor encrypts its data with secret key and generatesits cipher text CT

119889= Data oplus CNA

(5) CMA is added at the end of the packet for verification

(6) The process is done till the end of the data packets

4 Experimentation and Simulation

NS2 simulation is employed to evaluate relay node basedsecure routing protocol for multiple mobile sink (RSRPMS)In this case randomly deployed sensor nodes covering thearea of 600 times 600m are varied from 50 100 150 and 200 to250 kbps data rate and nodes are varied from 20 to 100 nodesThe time taken for simulation is 50 sec

41 The Performance Evaluation in Terms of Number of SinksThis section describes the simulation results when sinks areincreased as 1 2 and 5 All the performance parameters wereevaluated for node as well as rate From the simulation resultthe proposed protocol proves that it can work better when


0

2

4

6

8

10

12

14

16

21 41 61 81 101

Del

ay (m

s)

Nodes

Nodes versus delay

Sink 1

Sink 2

Sink 5

Figure 4 Nodes versus delay in terms of sink

21 41 61 81 101

Nodes

Nodes versus drop

0

100

200

300

400

500

600

700

800

900

Dro

p (p

kts)

Sink 1

Sink 2

Sink 5

Figure 5 Nodes versus drop in terms of sink

the number of sinks increases This increases the availabilityof the network

42 Simulation Results for Varying Nodes

421 Nodes versus Delay From Figure 4 the delay keepsreducing when the number of sinks increases The operationwith 5 sinks provides better performance than with lessernumber of sinks

422 Nodes versus Drop Figure 5 presents the packet dropfor various node scenarios when the number of sinks is variedas 1 2 and 5 It can be seen that when number of nodes isincreased the drop decreases drastically for 5-sink scenariocompared lesser number of sinks

423 Nodes versus the Energy Figure 6 presents the energyconsumed by various nodes when the sink number is variedas 1 2 and 5 It can be observed that when node number isincreased energy consumption for sink 5 is higher than 1 or2 sinks

424 Nodes versus Overhead Figure 7 presents the overheadfor various node scenarios when sinks are varied from 1 2and 5 However the overhead is very low for 1-sink operationcompared with 2- or 5-sink operations

21 41 61 81 101

Nodes

Nodes versus energy consumption

0

2

4

6

8

10

12

14

16

Ener

gy (J

)

Sink 1

Sink 2

Sink 5

Figure 6 Nodes versus energy in terms of sink

21 41 61 81 101

Nodes

Sink 1

Sink 2

Sink 5

0

5000

10000

15000

20000

25000

Ove

rhea

d

Nodes versus overhead

Figure 7 Nodes versus overhead in terms of sink

43 Simulation Results for Varying Data Rate

431 Rate versus Delay Figure 8 presents the delay versusrate for various rate scenarios when the number of sinks isvaried as 1 2 and 5 It is very clear the delay is minimumfor the 5-sink operation and maximum for a single sinkoperation

432 Rate versus Drop Figure 9 presents the packet drop forvarious rate scenarios when sink is varied as 1 2 and 5Whendata rate is increased the drop increases drastically for 1-sinkscenario compared to 2 or more number of sinks

433 Rate versus Energy Figure 10 presents the packetenergy for various rate scenarios when the sink is variedas 1 2 and 5 as the rate is increased energy consumptionincreases The residual energy of sink 5 is lesser than sink 1and sink 2

434 Rate versus Overhead Figure 11 presents the overheadin terms of data rate for various numbers of sinks It isobserved that overhead ismaximum for 5-sink scenariowhencompared to other sink scenarios

Table 1 presents the comparison between the RSRPMSand IAR techniques In terms of delivery ratio under different


50 100 150 250200

Del

ay (s

)

Rate (kb)

Rate versus delay

0

05

1

15

2

25

3

35

4

45

Sink 1

Sink 2

Sink 5

Figure 8 Rate versus delay in terms of sink

50 100 150 200 250

Rate (kb)

Rate versus drop

0

50

100

150

200

250

300

350

400

450

Dro

p (p

kts)

Sink 1

Sink 2

Sink 5

Figure 9 Data rate versus drop in terms of sink

Table 1 Delivery ratio of the data gathering schemes

Data gathering schemesDelivery ratio ()

Node RateNodes 80 Rate 200 kbps

BSMASD 037426 013937MSREEDG 060471 031161IAR 055215 091863RSRPMS 078017 099556

number of nodes operation RSRPMS shows better perfor-mance than IAR approach by 27 The packet delivery ratioof RSRPMS is 98 higher than IAR approach under differentnumber of rate operations

Figure 12 shows energy schemes for 200 kbps data ratewith 100 nodes Residual energy of MSREEDG is higherthan BSMASD but lesser than RSRPM RSRPMS is higherthan Intelligent Agent-Based Routing protocol by 82Thusthe proposed protocol increases the energy efficiency andreliability of the data The overall result proves that theproposed protocol increases the network life time with high

0

5

10

15

20

25

50 100 150 200 250

Ener

gy (J

)

Rate (kb)

Rate versus residual energy

Sink 1

Sink 2

Sink 5

Figure 10 Rate versus energy in terms of sink

50 100 150 200 250

Rate (kb)

Rate versus overhead

0

5000

10000

15000

20000

25000

Ove

rhea

d

Sink 1

Sink 2

Sink 5

Figure 11 Rate versus overhead in terms of sink

BSMASD MSREEDG IAR RSRPMSEnergy efficient schemes

Performance analysis of energy efficientschemes for varying rate

024681012141618

Resid

ual e

nerg

y (J

)

Figure 12 Performance analysis of energy efficient schemes forvarying data rate

reliability integrity availability with minimum delay energydrop and overhead

5 Conclusion

This paper proposes a reliable and energy efficient WSNrouting protocol withminimumdelay called relay node basedsecure routing protocol for multiple mobile sink (RSRPMS)The experimental simulations using the proposed protocol


are carried out rigorously and the results are compared withIntelligent Agent-Based Routing (IAR) protocol to prove thesuperiority in delivery of transmitted data and increase inthe network lifetime compared with other routing protocolsThe proposed routing protocol performance was also addi-tionally compared with traditional schemes like BSMASDand MSREEDG techniques The parameters of comparisonincluded packet drop energy delay and overhead Thesimulations were carried out using NS2 simulator undervarious conditions of operations like varying the nodes anddata rateThe simulation result proves that the proposed relaynode based secure routing protocol used for mobile sinkincreases the delivery ratio and energy efficiency Thus theproposed routing protocol increases the network lifetime

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

References

[1] K Akkaya M Younis and M Bangad ldquoSink repositioning forenhanced performance in wireless sensor networksrdquo ComputerNetworks vol 49 no 4 pp 512ndash534 2005

[2] I F AkyildizW Su Y Sankarasubramaniam and E Cayirci ldquoAsurvey on sensor networksrdquo IEEE Communications Magazinevol 40 no 8 pp 102ndash114 2002

[3] M H Anisi A H Abdullah and S A Razak ldquoEnergy-efficientdata collection in wireless sensor networksrdquo Wireless SensorNetwork vol 3 no 10 pp 329ndash333 2011

[4] K Almirsquoani A Viglas and L Libman ldquoEnergy-efficient datagathering with tour length-constrained mobile elements inwireless sensor networksrdquo in Proceedings of the 35th AnnualIEEE Conference on Local Computer Networks (LCN rsquo10) pp582ndash589 IEEE October 2010

[5] G Anastasi E Borgia M Conti and E Gregori ldquoA hybridadaptive protocol for reliable data delivery in WSNs withmultiple mobile sinksrdquoThe Computer Journal vol 54 no 2 pp213ndash229 2011

[6] V Safdar F Bashir Z Hamid H Afzal and J Y Pyun ldquoA hybridrouting protocol for wireless sensor networks with mobilesinksrdquo in Proceedings of the 7th International Symposium onWireless and Pervasive Computing (ISWPC rsquo12) pp 1ndash5 IEEEDalian China July 2012

[7] H M N D Bandara A P Jayasumana and T H IllangasekareldquoCluster tree based self organization of virtual sensor networksrdquoin Proceedings of the IEEE GLOBECOM Workshops pp 1ndash6IEEE December 2008

[8] Z A Eu H-P Tan and W K G Seah ldquoOpportunisticrouting in wireless sensor networks powered by ambient energyharvestingrdquo Computer Networks vol 54 no 17 pp 2943ndash29662010

[9] J-W Kim J-S In K Hur J-W Kim and D-S Eom ldquoAnintelligent agent-based routing structure for mobile sinks inWSNsrdquo IEEE Transactions on Consumer Electronics vol 56 no4 pp 2310ndash2316 2010

[10] J Luo J Panchard M Piorkowski M Grossglauser and JP Hubaux ldquoMobiRoute routing towards a mobile sink for

improving lifetime in sensor networksrdquo inDistributed Comput-ing in Sensor Systems vol 4026 of Lecture Notes in ComputerScience pp 480ndash497 Springer Berlin Germany 2006

[11] Y Bi L Sun J Ma N Li I A Khan and C Chen ldquoHUMS anautonomousmoving strategy formobile sinks in data-gatheringsensor networksrdquo Eurasip Journal on Wireless Communicationsand Networking vol 2007 Article ID 64574 2007

[12] L Cheng Y Chen C Chen and J Ma ldquoQuery-based datacollection in wireless sensor networks with mobile sinksrdquo inProceedings of the ACM International Wireless Communicationsand Mobile Computing Conference (IWCMC rsquo09) pp 1157ndash1162June 2009

[13] J-J Lei T Park and G-I Kwon ldquoA reliable data collectionprotocol based on erasure-resilient code in asymmetric wirelesssensor networksrdquo International Journal of Distributed SensorNetworks vol 2013 Article ID 730819 8 pages 2013

[14] P Madhumathy and D Sivakumar ldquoMobile sink based reliableand energy efficient data gathering technique forWSNrdquo Journalof Theoretical and Applied Information Technology vol 61 no 1pp 1ndash9 2014

[15] T Srinivasan V Vijaykumar and R Chandrasekar ldquoA self-organized agent-based architecture for power-aware intrusiondetection in wireless ad-hoc networksrdquo in Proceedings of theInternational Conference on Computing amp Informatics (ICOCIrsquo06) pp 1ndash6 IEEE Kuala Lumpur Malaysia June 2006

[16] B Nazir and H Hasbullah ldquoMobile sink based routing protocol(MSRP) for prolonging network lifetime in clustered wirelesssensor networkrdquo in Proceedings of the International Conferenceon Computer Applications and Industrial Electronics (ICCAIErsquo10) pp 624ndash629 December 2010

[17] E Ekici Y Gu andD Bozdag ldquoMobility-based communicationin wireless sensor networksrdquo IEEE Communications Magazinevol 44 no 7 pp 56ndash62 2006

[18] H Karl and A Willig Protocols and Architectures for WirelessSensor Networks John Wiley amp Sons 2007

[19] E B Hamida and G Chelius ldquoStrategies for data disseminationto mobile sinks in wireless sensor networksrdquo IEEE WirelessCommunications vol 15 no 6 pp 31ndash37 2008

[20] C Konstantopoulos G Pantziou D Gavalas A Mpitziopou-los and B Mamalis ldquoA rendezvous-based approach enablingenergy-efficient sensory data collection with mobile SinksrdquoIEEE Transactions on Parallel and Distributed Systems vol 23no 5 pp 809ndash817 2012

[21] E M Saad M H Awadalla and R R Darwish ldquoA datagathering algorithm for a mobile sink in large-scale sensornetworksrdquo in Proceedings of the 4th International Conference onWireless and Mobile Communications (ICWMC rsquo08) pp 207ndash213 August 2008

[22] C Chen J Ma and K Yu ldquoDesigning energy-efficient wirelesssensor networks with mobile sinksrdquo in Proceedings of the4th ACM Conference on Embedded Networked Sensor Systems(SenSys rsquo06) Boulder Colo USA November 2006

[23] A Rasheed and R N Mahapatra ldquoThe three-tier securityscheme in wireless sensor networks with mobile sinksrdquo IEEETransactions on Parallel and Distributed Systems vol 23 no 5pp 958ndash965 2012

[24] S Gao H Zhang and S K Das ldquoEfficient data collection inwireless sensor networks with path-constrained mobile sinksrdquoIEEE Transactions on Mobile Computing vol 10 no 4 pp 592ndash608 2011


[25] H Salarian K-W Chin and F Naghdy ldquoAn energy-efficientmobile-sink path selection strategy for wireless sensor net-worksrdquo IEEE Transactions on Vehicular Technology vol 63 no5 pp 2407ndash2419 2014

[26] I Chatzigiannakis A Kinalis and S Nikoletseas ldquoEfficient datapropagation strategies inwireless sensor networks using a singlemobile sinkrdquoComputer Communications vol 31 no 5 pp 896ndash914 2008

[27] G Wang T Wang W Jia M Guo and J Li ldquoAdaptive locationupdates for mobile sinks in wireless sensor networksrdquo TheJournal of Supercomputing vol 47 no 2 pp 127ndash145 2009

[28] J Luo and J-P Hubaux ldquoJoint sink mobility and routing tomaximize the lifetime of wireless sensor networks the case ofconstrained mobilityrdquo IEEEACM Transactions on Networkingvol 18 no 3 pp 871ndash884 2010

[29] P Ciciriello L Mottola and G P Picco ldquoEfficient routingfrom multiple sources to multiple sinks in wireless sensornetworksrdquo in Wireless Sensor Networks pp 34ndash50 SpringerBerlin Germany 2007

[30] D Puthal B Sahoo and S Sharma ldquoDynamic model forefficient data collection in wireless sensor networks withmobilesinkrdquo International Journal of Computer Science and Technologyvol 3 no 1 pp 623ndash628 2012

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Protocol for Secure Communication in Mobile Sinks Secur-ing wireless sensor networks [WSN] is the primary and adaunting task because of its characteristics such as unreliablewireless communication constraints with respect to theresources unknown topology and unprotected environmentThe primary security goals here would be to maintain dataconfidentiality by not leaking data to neighboring node toprovide data freshness and to provide high availability andauthenticity by verifying that the data is always sent by anauthentic source

2 Related Literature

Kim et al [9] proposed Intelligent Agent-Based Routing(IAR) protocol for providing data delivery efficiently to themobile sink The IAR protocol is evaluated using mathe-matical analysis Results proved that the protocol supportsmobility of sink with less overhead and an improvement overthe triangular routing problem

Similarly [10] have highlighted the difference between amobile relay and the mobile sink Amobile relay collects datawhenever it is closer to sensor nodes Mechanical movementis employed to transport the data to the sink As it doesnot use the wireless links for transmission to the sink thelatency in delivering data is significant In contrast mobilesink performs various operations like distributing the loadamong the sensor nodes collecting data continuously fromthe nodes and moving slowly and discontinuously in datagathering process

In one attempt the mobile sink is a moving strategybased on remaining energy of the sensor nodes whichbalance the network workload and increase the network lifetime [11] Consequently [12] proposed a query-based datacollection scheme in which mobile sink issues queries in thesensing field and the response is received through multihopcommunicationTheproblemwith such query-based systemsis that the sink mobility causes the query and responsepackets to take different routes Query-based data collectionscheme (QBDCS) consumes lesser energy and deliveredpacket with minimum latency Moreover QBDCS selects theoptimal time for sending its query packet and tailored therouting process for sensor nodes for forwarding packets Theperformance of theQBDCSwas evaluated by comparingwitha ldquoNaiverdquo scheme using the OMNeT++ simulation tool

Reference [13] proposes RECPE a collection protocolwhich is reliable in a significant high scale WSN for aggre-gating packets from the source to sinkThis protocol has suc-cessfully covered all the routes in the network by employingexpected transmission count for forward links (ETF)methodfor constructing a collection tree thereby reducing the con-sequence of the asymmetric link in the entire networkMore-over the proposed protocol also utilized Trickle algorithmand pipeline mechanismThis mechanismminimizes controlinformation and increases the effectiveness of data deliveryReference [14] proposed a Mobile Sink Based Reliable andEnergy Efficient Data Gathering (MSREEDG) technique forgathering data in tree-shaped network topology in WSN andcompared with constant pause time method

Reference [15] uses an agent-based architecture that savesthe bandwidth and segregates SAPID (self-organized agent-based architecture for power-aware intrusion detection)in two phases This agent architecture principally uses aKohonen Self-Organizing Map to recognize the patterns andidentify anomalies appropriately for unauthorized users Ref-erence [16] tackles the hotspot problem and presents amobilesink based Routing Protocol (MSRP) for extending networklifetime for cluster based architecture in WSN MSRP movesto gather the data which in turn reduces the hotspot problemSimilarly various protocols are discussed in [17ndash19]

An alternative protocol to minimize the energy con-sumption and overhead during the data retrieval process isproposed in [20] Adaptive mobile strategy is implementedfor hierarchical networks in a large scale that are presentedin [21] The trajectory of mobile sink is planned in such away that no multihop relays are required for transmissionof data to the sink Reference [22] presents using multihopforwarding forming a cluster around the expected position ofa mobile sink guaranteeing minimum energy consumptionwith packet delay is discussed in [23]

A new data gathering scheme named as MaximumAmount Shortest Path to increase the network throughputand to save energy by efficiently assigning the sensor nodesis discussed in [24] A weighted rendezvous planning (WRP)heuristic is presented in [25] in this each sensor node isassigned with a weight appropriate to its hop distance and thenumber of data packets it forwards In another attempt [26]mobility patterns for data collection of the sink are presentedFrequent location updates from mobile sinks increase theenergy consumption in wireless transmissions [27]

In [28] a model for investigating the joint sink mobilityis presented and routing problem is constrained by thesink with a predefined number of locations The routingprotocol between multiple source and sink is proposed in[29] Reference [30] proposed secure energy efficient datacollection for mobile sink using a session based symmetrickey cryptography method to increase the life time of thenetwork Among all other security goals only authenticationof the node and data fairness is considered in this paperseveral internal attacks are out of the scope of this paper

Based on the literature review of the mobile sinks thispaper proposes a protocol called relay node based securerouting protocol for multiple mobile sink which is usedfor data gathering and the simulation results are comparedwith IAR protocol The results are demonstrated in such away that the proposed protocol performs better in terms ofperformance metrics like delivery ratio and energy efficiencyand reduces the delay and overhead in the WSN

The reminder of the paper is prepared in such a way thatSection 3 discusses the problem formulation architecturedata gathering routing protocol relay node selection algo-rithm and security protocol in detail Section 4 discusses theexperimentation and simulation results in detail using theproposedmethod and also gives a detailed comparison of theresults to show the superiority of the proposed methodThenthe paper discusses the results and finally concludes


Sensor node Sink



























Then

119878P REQ997888997888997888997888997888rarr Neigh

119894

Neigh119894

P REP997888997888997888997888rarr 119878

(1)


nodeEnd if






119894

119863R REQ997888997888997888997888997888rarr Neigh

119894 (2)


Neigh119894

R REP997888997888997888997888997888rarr 119863 (3)



119863RP mes997888997888997888997888997888rarr IRN

119894

RP mes997888997888997888997888997888rarr RePmr (4)






119899which is



Then


119900 (5)



RP119900SEQ


119900state RP

119900state



proposed protocol





119894


119889



CSA =119867(119864(119873119894 119878119904))









119894= CT119889oplus CNA)









119894)


Start







End of joinrequest

Yes No

No

No


node




nodes


Stop

YesYes


Source Sink

CSA = H(E(Ni Ss))














0

2

4

6

8

10

12

14

16

21 41 61 81 101

Del

ay (m

s)

Nodes

Nodes versus delay

Sink 1

Sink 2

Sink 5


21 41 61 81 101

Nodes

Nodes versus drop

0

100

200

300

400

500

600

700

800

900

Dro

p (p

kts)

Sink 1

Sink 2

Sink 5








21 41 61 81 101

Nodes


0

2

4

6

8

10

12

14

16

Ener

gy (J

)

Sink 1

Sink 2

Sink 5


21 41 61 81 101

Nodes

Sink 1

Sink 2

Sink 5

0

5000

10000

15000

20000

25000

Ove

rhea

d










50 100 150 250200

Del

ay (s

)

Rate (kb)

Rate versus delay

0

05

1

15

2

25

3

35

4

45

Sink 1

Sink 2

Sink 5


50 100 150 200 250

Rate (kb)

Rate versus drop

0

50

100

150

200

250

300

350

400

450

Dro

p (p

kts)

Sink 1

Sink 2

Sink 5








0

5

10

15

20

25

50 100 150 200 250

Ener

gy (J

)

Rate (kb)


Sink 1

Sink 2

Sink 5


50 100 150 200 250

Rate (kb)


0

5000

10000

15000

20000

25000

Ove

rhea

d

Sink 1

Sink 2

Sink 5




024681012141618

Resid

ual e

nerg

y (J

)



5 Conclusion






References








































Advances in

FuzzySystems


Volume 2014












Journal of

Journal of





Advances in

Multimedia


Biomedical Imaging



Advances in


RoboticsJournal of










Advances in




Sensor node Sink



























Then

119878P REQ997888997888997888997888997888rarr Neigh

119894

Neigh119894

P REP997888997888997888997888rarr 119878

(1)


nodeEnd if






119894

119863R REQ997888997888997888997888997888rarr Neigh

119894 (2)


Neigh119894

R REP997888997888997888997888997888rarr 119863 (3)



119863RP mes997888997888997888997888997888rarr IRN

119894

RP mes997888997888997888997888997888rarr RePmr (4)






119899which is



Then


119900 (5)



RP119900SEQ


119900state RP

119900state



proposed protocol





119894


119889



CSA =119867(119864(119873119894 119878119904))









119894= CT119889oplus CNA)









119894)


Start







End of joinrequest

Yes No

No

No


node




nodes


Stop

YesYes


Source Sink

CSA = H(E(Ni Ss))














0

2

4

6

8

10

12

14

16

21 41 61 81 101

Del

ay (m

s)

Nodes

Nodes versus delay

Sink 1

Sink 2

Sink 5


21 41 61 81 101

Nodes

Nodes versus drop

0

100

200

300

400

500

600

700

800

900

Dro

p (p

kts)

Sink 1

Sink 2

Sink 5








21 41 61 81 101

Nodes


0

2

4

6

8

10

12

14

16

Ener

gy (J

)

Sink 1

Sink 2

Sink 5


21 41 61 81 101

Nodes

Sink 1

Sink 2

Sink 5

0

5000

10000

15000

20000

25000

Ove

rhea

d










50 100 150 250200

Del

ay (s

)

Rate (kb)

Rate versus delay

0

05

1

15

2

25

3

35

4

45

Sink 1

Sink 2

Sink 5


50 100 150 200 250

Rate (kb)

Rate versus drop

0

50

100

150

200

250

300

350

400

450

Dro

p (p

kts)

Sink 1

Sink 2

Sink 5








0

5

10

15

20

25

50 100 150 200 250

Ener

gy (J

)

Rate (kb)


Sink 1

Sink 2

Sink 5


50 100 150 200 250

Rate (kb)


0

5000

10000

15000

20000

25000

Ove

rhea

d

Sink 1

Sink 2

Sink 5




024681012141618

Resid

ual e

nerg

y (J

)



5 Conclusion






References








































Advances in

FuzzySystems


Volume 2014












Journal of

Journal of





Advances in

Multimedia


Biomedical Imaging



Advances in


RoboticsJournal of










Advances in








119894

119863R REQ997888997888997888997888997888rarr Neigh

119894 (2)


Neigh119894

R REP997888997888997888997888997888rarr 119863 (3)



119863RP mes997888997888997888997888997888rarr IRN

119894

RP mes997888997888997888997888997888rarr RePmr (4)






119899which is



Then


119900 (5)



RP119900SEQ


119900state RP

119900state



proposed protocol





119894


119889



CSA =119867(119864(119873119894 119878119904))









119894= CT119889oplus CNA)









119894)


Start







End of joinrequest

Yes No

No

No


node




nodes


Stop

YesYes


Source Sink

CSA = H(E(Ni Ss))














0

2

4

6

8

10

12

14

16

21 41 61 81 101

Del

ay (m

s)

Nodes

Nodes versus delay

Sink 1

Sink 2

Sink 5


21 41 61 81 101

Nodes

Nodes versus drop

0

100

200

300

400

500

600

700

800

900

Dro

p (p

kts)

Sink 1

Sink 2

Sink 5








21 41 61 81 101

Nodes


0

2

4

6

8

10

12

14

16

Ener

gy (J

)

Sink 1

Sink 2

Sink 5


21 41 61 81 101

Nodes

Sink 1

Sink 2

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0

5000

10000

15000

20000

25000

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d










50 100 150 250200

Del

ay (s

)

Rate (kb)

Rate versus delay

0

05

1

15

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3

35

4

45

Sink 1

Sink 2

Sink 5


50 100 150 200 250

Rate (kb)

Rate versus drop

0

50

100

150

200

250

300

350

400

450

Dro

p (p

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Sink 1

Sink 2

Sink 5








0

5

10

15

20

25

50 100 150 200 250

Ener

gy (J

)

Rate (kb)


Sink 1

Sink 2

Sink 5


50 100 150 200 250

Rate (kb)


0

5000

10000

15000

20000

25000

Ove

rhea

d

Sink 1

Sink 2

Sink 5




024681012141618

Resid

ual e

nerg

y (J

)



5 Conclusion






References








































Advances in

FuzzySystems


Volume 2014












Journal of

Journal of





Advances in

Multimedia


Biomedical Imaging



Advances in


RoboticsJournal of










Advances in




Start







End of joinrequest

Yes No

No

No


node




nodes


Stop

YesYes


Source Sink

CSA = H(E(Ni Ss))














0

2

4

6

8

10

12

14

16

21 41 61 81 101

Del

ay (m

s)

Nodes

Nodes versus delay

Sink 1

Sink 2

Sink 5


21 41 61 81 101

Nodes

Nodes versus drop

0

100

200

300

400

500

600

700

800

900

Dro

p (p

kts)

Sink 1

Sink 2

Sink 5








21 41 61 81 101

Nodes


0

2

4

6

8

10

12

14

16

Ener

gy (J

)

Sink 1

Sink 2

Sink 5


21 41 61 81 101

Nodes

Sink 1

Sink 2

Sink 5

0

5000

10000

15000

20000

25000

Ove

rhea

d










50 100 150 250200

Del

ay (s

)

Rate (kb)

Rate versus delay

0

05

1

15

2

25

3

35

4

45

Sink 1

Sink 2

Sink 5


50 100 150 200 250

Rate (kb)

Rate versus drop

0

50

100

150

200

250

300

350

400

450

Dro

p (p

kts)

Sink 1

Sink 2

Sink 5








0

5

10

15

20

25

50 100 150 200 250

Ener

gy (J

)

Rate (kb)


Sink 1

Sink 2

Sink 5


50 100 150 200 250

Rate (kb)


0

5000

10000

15000

20000

25000

Ove

rhea

d

Sink 1

Sink 2

Sink 5




024681012141618

Resid

ual e

nerg

y (J

)



5 Conclusion






References








































Advances in

FuzzySystems


Volume 2014












Journal of

Journal of





Advances in

Multimedia


Biomedical Imaging



Advances in


RoboticsJournal of










Advances in




0

2

4

6

8

10

12

14

16

21 41 61 81 101

Del

ay (m

s)

Nodes

Nodes versus delay

Sink 1

Sink 2

Sink 5


21 41 61 81 101

Nodes

Nodes versus drop

0

100

200

300

400

500

600

700

800

900

Dro

p (p

kts)

Sink 1

Sink 2

Sink 5








21 41 61 81 101

Nodes


0

2

4

6

8

10

12

14

16

Ener

gy (J

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Sink 1

Sink 2

Sink 5


21 41 61 81 101

Nodes

Sink 1

Sink 2

Sink 5

0

5000

10000

15000

20000

25000

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50 100 150 250200

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ay (s

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1

15

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45

Sink 1

Sink 2

Sink 5


50 100 150 200 250

Rate (kb)

Rate versus drop

0

50

100

150

200

250

300

350

400

450

Dro

p (p

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Sink 1

Sink 2

Sink 5








0

5

10

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50 100 150 200 250

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gy (J

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Sink 1

Sink 2

Sink 5


50 100 150 200 250

Rate (kb)


0

5000

10000

15000

20000

25000

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Sink 1

Sink 2

Sink 5




024681012141618

Resid

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)



5 Conclusion






References








































Advances in

FuzzySystems


Volume 2014












Journal of

Journal of





Advances in

Multimedia


Biomedical Imaging



Advances in


RoboticsJournal of










Advances in




50 100 150 250200

Del

ay (s

)

Rate (kb)

Rate versus delay

0

05

1

15

2

25

3

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4

45

Sink 1

Sink 2

Sink 5


50 100 150 200 250

Rate (kb)

Rate versus drop

0

50

100

150

200

250

300

350

400

450

Dro

p (p

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Sink 1

Sink 2

Sink 5








0

5

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Sink 2

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024681012141618

Resid

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5 Conclusion






References








































Advances in

FuzzySystems


Volume 2014












Journal of

Journal of





Advances in

Multimedia


Biomedical Imaging



Advances in


RoboticsJournal of










Advances in







References








































Advances in

FuzzySystems


Volume 2014












Journal of

Journal of





Advances in

Multimedia


Biomedical Imaging



Advances in


RoboticsJournal of










Advances in

















Advances in

FuzzySystems


Volume 2014












Journal of

Journal of





Advances in

Multimedia


Biomedical Imaging



Advances in


RoboticsJournal of










Advances in



research article modeling and simulation of a novel relay...

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