Review Article Routing Protocols for Wireless Multimedia ...in wireless multimedia sensor network. e...

Hindawi Publishing CorporationJournal of SensorsVolume 2013, Article ID 469824, 11 pageshttp://dx.doi.org/10.1155/2013/469824

Review ArticleRouting Protocols for WirelessMultimedia Sensor Network: A Survey

Mohammed Abazeed, Norshiela Faisal, Suleiman Zubair, and Adel Ali

Faculty of Electrical Engineering, University Technology Malaysia, 81310 Johor Bahru, Johor Darul Ta’zim, Malaysia

Correspondence should be addressed to Mohammed Abazeed; [email protected]

Received 17 May 2013; Accepted 3 November 2013

Academic Editor: Christos Riziotis

Copyright © 2013 Mohammed Abazeed et al. This is an open access article distributed under the Creative Commons AttributionLicense, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properlycited.

Multimedia applications have become an essential part of our daily lives, and their use is flourishing day by day.The area of wirelesssensor network is not an exception where the multimedia sensors are attracting the attention of the researchers increasingly, and ithas shifted the focus from traditional scalar sensors to sensors equipped with multimedia devices.Themultimedia sensors have theability to capture video, image, audio, and scalar sensor data and deliver the multimedia content through sensors network. Due tothe resource constraints nature ofWSN introducingmultimedia will addmore challenges, so the protocols designed formultimediawireless sensor network should be aware of the resource constraints nature ofWSN andmultimedia transmission requirement.Thispaper discusses the design challenges of routing protocols proposed for WMSN. A survey and comprehensive discussion are givenfor proposed protocols of WMSN followed by their limitations and features.

1. Introduction

Wireless multimedia sensor networks (WMSNs) are a newlydeveloped type of sensor network which has the sensor nodesequipped with cameras, microphones, and other sensors pro-ducing multimedia data content. The development towardsthe wireless multimedia sensor network has been the resultof progress in the CMOS technology which leads to devel-opment of single chip camera modules that could be easilyintegrated with senor nodes. This integration between multi-media sources and cheap communication devices motivatesthe researches in wireless sensor network. WMSN enhancesexisting WSN applications and enables a new large rangeof applications, like multimedia surveillance, traffic man-agement, automated assistance, environmental monitoring,and industrial process control.WMSNs havemore additionalfeatures and requirements thanWSN, such as high bandwidthdemand, bounded delay, acceptable jitter, and low packet lossratio.These characteristics impose more resource constraintsthat involve energy consumption, memory, buffer size, band-width, and processing capabilities [1]. Meeting the qualityof service requirements for multimedia data within afore-mentioned constraints is a real challenge. These mentioned

characteristics, challenges, and requirements of designingWMSNs open many research issues and future researchdirections to develop protocols, algorithms, architectures,devices, and test beds to maximize the network lifetimewhile satisfying the quality of service requirements of thevarious applications. Routing protocols designed for WSMNmust take into consideration the requirements and resourceconstraints nature of WMSN, in order to meet the tight QoSrequirements. Designing routing protocol for WMSN is stillan open research area in spite of many routing protocolsproposed for WSN. According to the direction of currentresearch we can classify the routing protocols into differentcategories, for example, depending on the type and the num-ber of constrained QoS they consider [2]. A classification ofdifferent routing protocols for WMSNs is shown in Figure 1.

2. Design Challenge and Resource Constraints

WMSN requirements impose more challenge and resourceconstraints to the routing protocols design. In this section themain challenges we need to deal with to improve communi-cation efficiency in WMSN are discussed.

2 Journal of Sensors

Routing protocols in WMSN

Data delivery modelCommunication model Layered architecture QoS requirements

Single path Multipath

Multichannel

Single layer Multiple layers

Mixed

Latency Multiple QoS

Type of multimedia Class of algorithm

Soft Hard

VideoImage Query driven Event driven

Continuous ACOClustered

Figure 1: Classification of routing protocols for WMSN.

2.1. Energy Consumption. Multimedia applications producehigh volume of traffic which requires high transmission rateand processing capabilities which lead to consuming moreenergy than WSN. While energy consumption is one of themost important performance metrics in WMSN the routingprotocols designed for WMSN should be aware of energyconsumption to prolong the network lifetime [3].

2.2. QoS Requirements. QoS requirements differ according todifferent types of multimedia applications. QoS metrics suchas delay, bandwidth, reliability, and jitter must be disparatelytaken into account as needed. For example many multimediaapplications are time critical: need to be reported with alimited time [4].

2.3. Multimedia Coding Techniques. Transmission of multi-media content has for long been associated with multimediasource coding techniques because of the large amounts oftraffic generated by multimedia sources such as cameras.Thecompression techniques certainly decrease the informationto be transmitted. This compression, however, comes at thecost of degradation of the multimedia quality that is usuallyreferred to as distortion. Effective compression techniqueswhich developed so far result in good rate-distortion levelsto efficientmultimedia transmission. Despite their significantcompression capabilities and good rate-distortion perfor-mance, traditional source coding techniques are not directlyapplicable to resource constrained WMSNs. This is mainlyrelated to the fact that predictive encoding requires com-plex encoders and powerful processing algorithms, whichsignificantly increase the energy consumption. Multimediaencoding techniques focus on two main goals for efficienttransmission of multimedia data. Firstly, the correlationbetween pixels of an image/frame or between frames of avideo stream can be exploited to significantly reduce theinformation content to be transmitted without major qualitydegradation.This is usually referred to as source coding. Sec-ondly, the compressed data should be efficiently representedto allow reliable transmission over bad channels. This isusually referred to as channel coding or error-resilient coding[3]. consequently, the main design objectives of a multimediaencoder for WMSNs are as follows.

2.3.1. High Compression Efficiency. It is necessary to achieve ahigh ratio of compression to effectively limit bandwidth andenergy consumption.

2.3.2. Low Complexity. The resource constraints of multime-dia sensors in terms of processing and energy consumptionrequire encoder techniques to be of low complexity to reducecost and form factors and low power to prolong the lifetimeof the sensor nodes.

2.3.3. Error Resiliency. Low-power wireless communicationincreases the errors in the channel. As a result, the encodersshould be designed to account for these effects and providerobust and error-resilient coding [1, 5].

2.4. Multimedia In-Network Processing. WMSN performmultimedia in-network processing algorithm on the rawdata transmitted from environment. In-network processingrequires new network architecture resource constrained pro-cessing that makes filtering and extract the useful informa-tion at the edge of network. The scalability will increaseby reducing redundant data transmission and combined datacoming from different sensors. It is important to enhance theapplications independently and self-organizing architectureto perform flexibly in-network processing.

2.5. High Bandwidth Demand. Multimedia traffic demandshigh bandwidth which requires new transmission techniquesto provide the required bandwidth with acceptable energyconsumption level to optimize the resource constraintsnature of WMSN. Anyhow, using multipath or multichannelcan be a solution to this issue.

3. Routing Protocols for WMSNS

The network layer is important to QoS support for multime-dia application because it is responsible for providing energyefficient path that meets QoS requirements and it serves asintermediate for the exchange of performance parametersbetween application and MAC layer [6].

In this section various routing protocols proposed forWMSN are surveyed and the features and limitations of eachare discussed. Then a general comparison between them ismade. These protocols, in fact, lie under the following cate-gories.

3.1. Swarm Intelligence Routing Protocol. ASAR [7] is a QoSrouting protocol for multimedia wireless sensor network

Journal of Sensors 3

based on traditional ant algorithm. The ASAR selects opti-mal paths to meet QoS requirements for different types ofservices. These services are called

(i) R: event driven service mode, where delay and errorare intolerant; this requires less bandwidth and highsignal to noise ratio path;

(ii) D: query driven service mode, where the error isintolerant, while delay is tolerant; a congestion andhigh signal to noise ratio path may be used for thisservice;

(iii) S: stream query service mode, where delay is intol-erant but error is tolerant so the less traffic and lowsignal-to-noise ratio path will be acceptable for thisservice.

The proposed protocol is a cluster based architecture andonly addresses the routing scheme between the cluster headsand the sink node. Each cluster head generates ants for eachtype of service (R/D/S) to find different service aware paths,from source to destination, which meet QoS requirementsand is suitable for the traffic type. A probabilistic ruledepending on the pheromone value of the paths is defined todetermine the moving from a current node to the next. Thepheromone value is calculated based on delay, rate of packetloss, bandwidth, and energy consumption. All cluster headswill have three optimal path tables for different services, threepheromone tables for the three kinds of services, and alsoa real time pheromone value and a transition probability ofthe next hop. The simulation results show that the efficiencyof the proposed protocol depends on the service type wheresome types perform well in some QoS metrics while othertypes are still suffering specially in delay and energy con-sumption.There are also some drawbacks, like the bottleneckproblemof hierarchicalmodel and the optimal path setup dueto congestion which requires extra calculations that affect thenetwork performance.

Rahman et al. [8] propose biologically inspired rout-ing protocol which is a swarm-intelligent-based algorithmexploiting the concept of ant colony optimization to opti-mize the QoS metrics like delay, jitter, energy consumption,and packet survival rate. The protocol does not need tomaintain the global state of the sensor nodes. The routingdecision is based on neighborhood information only. Theeffects of both the distance from the current node to thenext hop and the remaining distance from next hop tosink are considered in the routing decision. The proposedprotocol uses two types of ants to find the shortest pathwith QoS requirements and the forwarding decision to nexthop based on probability equation. The node with highprobability is chosen as a forwarding node. At first the sourcenode sends forward ant which uses probability equationto find the probabilities of each neighbor and the packetforwards to neighbor with high probability. Same steps arerepeated till reaching the destination. The forward ant willbe killed if it visits more than half of the number of nodeswhich means that the path has a loop or is nonconvergent.When the forward ant reaches the destination successfully,the backward ant is created to reinforce the visited nodes

by increasing the probability value. The proposed protocolcan be configured for both acknowledgment-based and non-acknowledgment-based approach. The backward ant willacknowledge the path which is chosen by forward ant. Thesource node will send a new forwarding node if the earlierpacket is lost or the acknowledgment does not reached thesource within a certain period of time.The simulation resultsof the proposed protocol were not compared with relatedprotocols, while it shows good performance in jitter and delayand for the most time it finds the shortest path which leadsto consuming less energy. The load balancing between nodesis not considered, which causes holes when energy of somenodes is depleted earlier than others. The protocol requiresaccurate geographic information of the node which increasesthe cost of deployment. In addition, while the network scalesincrease the overhead is also increased making the protocolinefficiently scalable.

ALCOLBR [9] is a routing protocol based on ant colonyoptimization for load balancing and addressing the QoSrequirements for WMSN. The intracluster routing is builtby minimum spanning tree then intercluster routing whichis built by proposed ant colony optimization algorithm tofind optimal and suboptimal paths. Constructing hierarchicalrouting tree to cluster head with cluster members is done byusing MST algorithm. Intercluster routing is to find optimaland suboptimal paths using ACO algorithm. Suboptimalpaths will be used when the amount of data exceeds pathflow threshold. Forward ants and backward ants are used.Theforward ants will die when reaching its limit. While movingfrom one node to the next the forward nodes update thepheromone using local pheromone update rule. The highestprobability node will be chosen as next hope node. The sameprocess is repeated till second and third suboptimal pathsare found. To reinforce the optimal paths the backward antreleases more pheromone in these paths based on globalpheromone rule.Then the transmissionwill start from sourceto destination. In case of node failure, the neighbor node willset the pheromone value to zero and send an errormessage tosource node. Then the source node will stop transmission inthis path and enable an alternate path for transmission. Theprotocol determines the congestion occurred by monitoringthe end to end delay from source to destination. If it exceedsthe threshold a congestion message will be sent to the sourcenode. When the source node gets this message it will reducethe data amount sent in this path and enable an alternate pathwhich increases the reliability. The simulation results showthat the performance of the protocol is better than relevantprotocols such as AGRA andMIAR, in delay, nodes life time,and scalability and reliability.The draw backs of the proposedwork are the hierarchical model which introduces bottleneckproblem and the optimal path selection that requires extracalculation which may decrease network performance.

Ke et al. [10] propose a routing protocol using gametheory and ant colony algorithm to meet QoS challengein wireless multimedia sensor network. The standard gametheory has three elements: players, payoff, and strategies. Theauthors assume the players to try to maximize their payoffwith minimum cost. The sensor node uses local informationto build a routing path depending on the game result and


the residual energy. Ant routing algorithm is used basedon [11]. The forward ants are sent to explore the path todestination node. The routing decision takes place based onthe pheromone trails left by ants. The probability calculationfor forward decision uses residual energy, delay, and band-width. When the forward ants successfully reach the sink,a backward ant is generated and takes the path found byforward ants toward the source.

3.2. Geographic Routing Protocol. TPGF [12] is a two-phasegeographic greedy forwarding algorithm for WMSN. Thefirst phase is responsible for exploring the possible routingpaths while the second phase is responsible for optimizingthe found routing paths with the least number of hops. Theprotocol assumes that eachnode is aware of its location and itsone hop neighbor node location. Each node has three states:(1) active and available, (2) active but unavailable, and (3)dead.The links have two states: available and unavailable.Therouting paths should be through active and available nodesand available links to avoid the holes and then optimize thefound routing paths with least number of hops. For thesetwo phases’ geographic forwarding and path optimizationis proposed. The geographic forwarding is responsible offinding routing paths with bypassing holes and consists oftwo methods: (1) greedy forwarding chooses the next hopnode which is the closest to the sink among all neighbornodes; (2) step back and mark: if the node has no next nodeexcept its previous node, then it will mark itself as a blocknode and the previous node will try to find other availablenode. The path optimization is to optimize the routing pathswith least number of nodes and eliminate the path circle.Thelabel based optimization is used to add other functions to theforwarding phase. Each node chosen for forwarding will havea label including path number and a digressive node number.An acknowledgment will be sent back when the routing pathreaches the destination. The acknowledgment will be sent tothe node which has the same path number and the largestnode number. The results show that the average numbers ofpaths found by TPGF are more and shorter than the numberof paths found by relevant protocols like GG and RNG. Thedrawback of TPGF is that it needs to build a complete map ofthe network topology which limits its scalability.

GEAMS [13] is a geographical multipath routing protocoldesigned to prolong the network lifetime. The proposedprotocol is an enhancement of the GPSR protocol [14] wherethe feature of load balancing is added, to reduce the queuesize and increase the life time of the network.The forwardingdecision policy is taken based on the remaining energy, num-ber of hops, distance between node and its neighbors, and thehistory of the packet forwarded belonging to the same stream.There are two modes used by the proposed protocol, thesmart greedy forwarding and the walking back forwarding.The first mode is used when there is always a neighbor closerto the destination than the current node. The second modeis used to deal with blocking situation, where the forwardingnode cannot find the next hop node toward the destination.Each sensor node stores some information about it on hopneighbor, which includes distance, link rate, and remainingenergy. The simulation results show that the GEAMS is more

suitable for WMSN than GPSR protocol. It ensures uniformenergy consumption and meets QoS constraints.

3.3. Routing Protocols Addressing Different Types of Algo-rithms. Yao et al. [15] propose a routing protocol that usesmetadata to construct multipath routing to meet QoS met-rics.The proposed protocol uses advancedDijkstra algorithmand cost function to make routing decision. The advancedDijkstra algorithm reduces the number of neighbor nodesby excluding the nodes with insufficient remaining energyand uses more than one factor such as delay, bandwidth, andremaining energy. The cost function is calculated based ondelay and energy consumption for multipath, and then theoptimized path will be selected. End to end delay calculationdepends not only on the distance between nodes but also onthe processing and queuing delay of relay nodes. To reducequeue delay, a classified queue model is introduced at eachnode to classify real time data and nonreal time data. Themetadata is used to describe the packet. Ordinary data packetis described by ID and time stamp, while themultimedia datais described by ID, time, and location coordinator to avoidrepeating the same data, which consumes more energy. Theproposed protocol is simulated and the result shows that it isbetter than SAR protocol in delaying and energy consuming.The protocol does not consider reliability and bandwidth.The metadata is inappropriate for multimedia data becauseit increases the overhead and energy consumption.

Guannan et al. [16] propose a routing protocol forwirelessmultimedia sensor network usingmultipath and load balanc-ing, aiming to increase the reliability, save more energy, andcontrol the congestion situation.The proposed protocol is flatand event driven. No global topology is required, and thesensor node is only aware of its neighbor nodes which reducethe overhead. Three full disjoint paths are built from sourcenode to sink called primary, alternate, and backup paths.Theprimary path is the least delay path, then the alternate andbackup paths. By default the backup path will be used incase the primary or alternative paths fail. The transmissionon these paths will be on stable rate and in round robinfashion butwith specific time control called time slice control.Each sensor node will use two paths for transmission. As theprimary path has less time delay it will get more time than thealternate path.The congestion controlmechanism is designedfor the major node (joint node) which is a node used by twopaths as a relay node and is done by monitoring the queueof this node if the receiver queue reaches the threshold. Acongestion notification is sent back to the source then it willstop transmitting in this path and switch to the another path.The simulation result shows that the protocol enhances thelife time and throughput but under higher transmission ratethe receiving rate and the network life time drop fast. Theredundancy is low which affects the reliability. The work didnot discuss the delay and bandwidth which havemore impacton multimedia transmission.

Mande and Yuanyan [17] propose multipath routingprotocol to support hole bypassing, load balancing, andcongestion control. The proposed algorithm consists of twophases. The first one determines a set of multiple paths whilethe second selects a routing path from the found paths.


During exploring the path, the node that belonged to FCS(set of nodes that is nearer to destination and farther from thesource than the current node) with less DEF (Decisive EnergyFactor) (energy consumption for transmitting data packet)value is selected as next forwarding node. The proposedprotocol uses amazing search algorithm which consists ofwave front expansion and path back tracking. In wave frontall valid nodes from source to destination are labeled in adecreasing tag number till reaching the destination. Duringpath backtracking, the algorithm starts from destination tosource and selects the node whose tag number is greaterthan the current node. When the source node is successfullyreached, then the path is built. After multiple paths aredetermined, selecting paths randomly and independentlyfrom different sources increases the congestion and energyconsumption in some nodes. To overcome these problems apath selection strategy is designed. To manage energy con-sumption, aDecisive EnergyRatioChangeRequest (DERCR)message is introduced which is sent by node to sourceto update the energy consumption value on the path. Forcongestion avoidance a control message is introduced whichcontains node andpath ID;when the queue exceeds thresholdspecified by user the node sends this message to all nodes inrouting tables; then two adjustment strategies are used, (1)gradual increase strategy based on the path and (2) gradualincrease strategy based on flows.The work was not simulatedto show the protocol performance. Delay, bandwidth, and jit-ter, which are tight requirements of multimedia transmissionin wireless sensor network, are not considered.

Hamid et al. [18] present multichannel multipath QoSaware routing protocol.The routing decision in the proposedprotocol is made according to dynamic adjustment of therequired bandwidth and proportional delay differentiationfor real time data. To efficiently utilize the bandwidth usingmultiple frequencies a Mutual Orthogonal Latin Square(MOLS) based scheduling is applied to assign transmissionand reception activities. Packet scheduling policy is intro-duced, where every node has a classifier to send data intodifferent queues according to their bandwidth and delayrequirement. Initially, the sink node will specify the band-width value depending on delay of time critical packets andsend this value to all nodes, and then all nodes will dynami-cally calculate their bandwidth value considering the distanceto sink. The PPDD will calculate the delay for each packetin queue along the path. The PPDD (path-length-based pro-portional delay differentiation) schedulers service packets inclasses and realize proportional average hop queuing delaysamong them locally at each node in the path. The proposedwork defines that the packet has less number of hops to sink;it will allow higher delay than the packet coming away fromthe sink. To maximize the bandwidth of nonreal time trafficthe sink will observe the delay; if it is increased it will increasethe bandwidth for real time traffic and vice versa.The routingfrom source to destinationwill be done through the paths andchannels that meet the bandwidth and delay requirements.Packets that do notmeet theQoS requirements are discarded.The best effort traffic will be routed through alternativepaths for balancing the distribution of remaining traffic. Thesimulation result shows that the proposed protocol has a good

performance in delay, throughput, and lifetime comparedto single r and multi-r proposed in [19] while reliabilityand energy are still not studied well. In addition switchingbetween different frequencies introduces more delay.

MCRA [20] is a multiconstrained routing protocoldesigned to provide end to enddelay, packet loss ratio guaran-tee, and balance the energy consumption in sensor nodes.Theproposed protocol is query driven and query flooding datamode. The interest message is sent from source node to allneighbors.When a certain node receives themessage and canmeet theQoS requirements, it will broadcast the interest to allof its neighbors, otherwise it will be discarded. Same steps arerepeated till the interest reaches the source node. When thesource node receives multiple interests from different pathsit will choose the optimum path. The differentiation servicein MAC layer can be used to classify the real-time dataand best effort data into different priorities. To decreasethe redundancy and retransmission caused by collision, theproposed work introduces message suppression technique,which consists of two aspects: restraining forwarding anddeferring one.The idea in restraining forwarding is to reducethe number of interests by restraining some nodes fromforwarding, while the idea of deferring forwarding involvesdeferring forwarding action, so these nodes have enoughtime to collect and merge interests from different sources.The authors design a localization approach based on hop-count information attained from the routing process andsupposing that the network nodes are distributed on a planeof rectangle “m” units in length and “n” units in width orany other known shapes. The simulation result shows thatthe packet loss ratio in MCRA is the best compared to DDand speed protocols. End to end delay is closest to speed,while the energy consumption is shown to be better thanspeed protocol, in case that the numbers of nodes are morethan 70. The proposed work does not consider the reliabilityand bandwidth while still there is broadcasting in everynode from source to destination which increases energyconsumption.

Poojary and Pai [21] propose a routing protocol designedto be power aware, reliable, and having low latency.The rout-ing algorithmconsists of two steps: route setup phase anddatatransmission phase. In route setup phase a discovery messageis sent by source node to all neighbors to explore differentpaths. When the neighbor nodes receive the message it willforward it to next hop, in case that the number of paths builtthrough this node are less than threshold and the residualenergy of the node is more than required energy; otherwisethe node will send negative acknowledgment message. Thesame procedures are repeated till the message reaches thedestination. Then if the destination node is ready to receivedata it will send “ok” message to the source node. When“ok” message is received by the source node it will add “ok”message sender node ID to multipath set which consists ofthe nodes which are used as next hop nodes in transmission.In data transmission phase subset of paths is selected based onthe residual energy. The data split into “m” parts and send itinmultiple paths. To achieve reliability, the proposed protocoluses Reed-Solomon encoding to encode the transmitted data.Simulation results show that the energy consumption is less


than the conventional protocols. Packet loss ratio is decreasedin case that the number of transmission paths is increased.The main drawbacks in the proposed work are use of Reed-Solomon for reliability which increases energy consumptionand no consideration for end to end delay and bandwidthrequirements. Splitting data into different paths increases theoverload of data collection.

Li et al. [22] propose a multipath routing protocol basedon directed diffusion. The protocol tries to find multipledisjoint paths with high throughput and low end to end delay.For this purpose the protocol uses the pathmetric cost, whichis based on delay and expected transmission account, (ETX),and modifying directed diffusion protocol by (1) using costpath as ametric instead of pure delay; (2) reinforcingmultiplepaths at the sink to obtain disjoint paths from the source.When the source receives interest from the sink, exploratorydata packets are flooded. When receiving exploratory data,the relay nodes will read SNR from the packet. EXT of theprevious three upstream links is calculated from SNR andinserted into the packet header of ETX field. The cost of eachsubpath is kept in local table at intermediate nodes in ascend-ing order. Only the one with lowest cost is forwarded to thenext hop. For delay, the protocol only considers the packetswhose time stamps from source to sink before the deadline.The results show that the proposed protocol works better thanEDGE and directed diffusion protocols in throughput anddelay aspects, while there is still flooding in exploring timewhich increases energy consumption.The other QoS metricsare not considered, like reliability, bandwidth, and energyconsumption.

Kai and Min [23] propose reliable routing protocol basedon energy prediction of WMSN. This mechanism makes thesensors predict the energy level of other nodes, and thendepending on this, the protocol can balance the energy con-sumption of nodes by power allocationmechanism.Themaingoal of the proposed protocol is to increase the reliability andbalance the energy consumption. The increasing of reliabletransmission rate is done by increasing the power transmis-sion level which leads to consuming more energy. For savingenergy the authors use the power control algorithmpresentedin [24] which guarantees the reliability by gradually increas-ing the power level. If themaximum power level still does notmeet the reliable transmission request, it has to rebuild theother route.The energy prediction mechanism is achieved bydesigning a state conversation model for intracluster nodes,by assuming that there are seven working states for sensors:sleep, sense, idle, receive, transmit, process, and access. Thena Markov chain is used to simulate the working state. Tomake sure that all sensory data reaches the sink, the networkis divided into many concentric coronas. The coronas widthis equal to communication distance when using the lowesttransmission power level. At the beginning, the power levelis set to 1 for all nodes; if the node fails to find the next hop ordoes not meet the reliability requirements it will increase thepower level gradually till reaching the maximum power level.If it is still failed, it will stop the processing and try to findother route. For balancing the network energy consumptionthe transmit power level is adjusted dynamically according tothe remaining energy. The simulation results show that the

energy prediction mechanism increases the node life timeand enhances the reliability. The results are not comparedto relevant protocols. The energy prediction calculationsincrease the power consumption. There is no considerationfor delay and bandwidth.

LEAR [25] is energy aware multimedia routing protocolwhichmakesmodification onAOVDprotocol and offersQoSby assigning routes according to data type; these routes areless congested and have maximum power. The protocol alsooffers a hole bypassing technique. The protocol assumes thatthe network consists of scalar sensors and multimedia sen-sors. The scalar data is treated as the best effort data while formultimedia data special care must be taken. A bit is insertedinto request message to distinguish between scalar data andmultimedia data. When event occurs a request message isbroadcasted to all neighbors of the source node. The nodereceiving this message again sends it to their neighbors till itreaches the destination. The destination replies by sending arequest replymessage to the source.When the source receivesthis message the transmission will start in this path.The pathselection is based on route selection factor. The node withhigh selection factor value will be chosen as a forwardingnode. The selection factor calculation is based on remainingenergy and active routes used by the node. When the nodereaches 25% of its total energy it will be labeled as a swapnode and will not participate in the routing. The scalar datais routed like AODV protocol. The simulation results showthat the number of paths is increasing as multimedia datais increasing. The hop distance will increase but with highthroughput and the congestion will be reduced. The protocolstill uses broadcasting in all forwarding steps which increasesenergy consumption. Delay, bandwidth, and reliability arenot considered in the proposed protocol.

Data dissemination phase is used as the first step inmany different routing protocols designed forWMSN.Moha-jerzadeh et al. [26] propose data dissemination protocolfor WMSN named MLAF. The protocol aims to reduce theredundancy, prioritize the data according to their impor-tance, and give attention to delay and energy consumption.MLAF considers the network as a virtual grid and every nodeis aware of its geographical position. There are two types ofnodes defined in each cell: internal nodes where all theirneighbors are inside the cell and edge ones which have at leastone neighbor in another cell. Each packet has a field whichregisters the ID of the received nodes. If any node receivesthe packet and finds its ID in the list the packet is destroyed.The proposed protocol uses two mechanisms for routingdirectional forwarding and delay sensitive forwarding. Indirectional forwarding there are two priorities: low prioritydata where each grid cell should receive data from southerncell; the packet comes from other direction will be destroyed;For high priority data, each grid cell receives data from allits neighbors. In delay sensitive forwarding we have alsotwo different priorities but the forwarding way is different.For high priority traffic MLAF will decrease the number ofhops by increasing the transmission power while the lowpriority trafficwill follow the normal routes. Simulation resultshows that the performance of the proposed protocol isbetter compared to LAF protocol but the broadcasting at


Table1:Com

paris

onof

routingprotocolsfor

WMSN

s.

Protocol

Architecture

Datad

eliverm

odel

Locatio

naw

areness

Hole

bypassing

Metho

dology

Con

gestion

control

Classifi

catio

nservice

Energy

efficiency

QoS

parameters

arec

onsid

ered

Flat

Hierarchical

Query

driven

Event

driven

Stream

query

Multip

ath

Multichann

elGeographic

Other

Yaoetal.[15]√

√√

Metadata+

advanced

Dijxtra

√√

Delay

Guann

anetal.

[16]

√√

√√

√Re

liability

Mande

and

Yuanyan[17]√

√√

√Amazing

algorithm

√√

√Re

liability

Ham

idetal.

[18]

√√

√√

√Delay-

band

width

MCR

A[20]

√√

√Floo

ding

√√

Reliability

Poojaryand

Pai[21]

√√

√√

Reliability

Lietal.[22]√

√√

Basedon

direct

diffu

sion

Delay

Kaiand

Min

[23]

√√

Energy

predictio

nmechanism

√Re

liability

LEAR[25]

√√

√√

Basedon

AODV

√√

Reliability

MLA

F[26]

√√

√√

Basedon

LAF

√√

Reliability-delay

ASA

R[7]

√√

√√

√AC

O√

√Delay,packet

lossratio

-band

width

Rahm

anetal.

[8]

√√

ACO

√Delay-jitte

r

ALC

OLB

R[9]

√√

√AC

O√

Reliability

Keetal.[10]√

√AC

Oand

game

theory

√Delay-

band

width

TPGF[12]

√√

√√

√√

Delay-reliability

GEA

MS[13]√

√√

√Ba

sedon

GPS

R√

Delay-reliability


Table2:Simulationscenario

ofprop

osed

routingprotocolsfor

WMSN

s.

Protocol

Verifi

edmetho

dSimulator

type

Perfo

rmance

metric

sCom

paredto

Com

paris

onresult

Simulator

Testb

ed

Yaoetal.[15]

√Not

specified

Energy

consum

ption-

delay

-distance

SAR

TheR

EARalgorithm

prolon

gsthen

etworklift

mea

ndperfo

rmsm

uchbette

rthanSA

R

Guann

anetal.[16]

√OMNet++

PRR-networklifetim

eMHCandflo

oding

Achieveing

high

erdatarateandlonger

networklife

time.Bu

tund

erhigh

erpackagetransmittingratefro

msource,receiving

rate,and

networklifetim

ewill

drop

fast

Mande

andYu

anyan

[17]

——

——

——

Ham

idetal.[18]

√NS-2

Delay-nod

elife

time-throug

hput

Sing

le-rand

multi-r

mechanism

s

Providingsig

nificantp

erform

ance

improvem

entsin

term

sofaverage

delay

,average

lifetim

e,andnetwork

throug

hput

MCR

A[20]

√NS-2

Dela

y-packetloss

ratio

-con

trolm

essage

overhead

SPEE

D-D

DSh

owingthatithasa

good

overallp

erform

ance

PoojaryandPai[21]

√Qualnet

network

simulator

Energy

consum

ption-PR

RNot

specified

Prolon

ging

then

etworklifetim

eand

thep

acketd

rop

redu

cesa

sthe

numbero

fpaths

selected

forthe

data

transm

issionisincreased

Lietal.[22]

√NS-2

Throug

hput-delay-

good

put

EDGEandbasic

diffu

sion

Achievinghigh

throug

hput

anddesir

abledelay

tomeet

theQ

oSrequ

iremento

fmultim

ediastr

eaming

Kaiand

Min

[23]

√Not

specified

Energy

consum

ption-

reliability

Not

compared

Thee

nergyconsum

ptionisredu

cedby

usingthe

prop

osed

energy

predictio

nmechanism

LEAR[25]

√NS-2

Throug

hput

AODV

Thep

rotocolfi

ndsp

ossib

ledisjo

intp

aths

orpartial

disjo

intp

aths

form

ultim

ediatraffi

cfasterthanAO

DV

MLA

F[26]

√Opn

etEn

ergy

consum

ption-PR

RLA

FShow

inggood

resultin

energy

consum

ption,

reliability,

andendto

enddelay

ASA

R[7]

√NS-2

queuingdelay

,PRR

,anddrop

pedrate

Tradition

alant-

based-Dijk

stra-D

DSelecttheo

ptim

alpathstomeettheirindividu

alQoS

requ

irements.

Thus

improvingnetworkperfo

rmance

Rahm

anetal.[8]

√Java

Dela

y-jitter

Not

compared

M-IA

Rshow

sgoo

dperfo

rmance

which

achieves

acceptabledelay

,jitter,and

energy

consum

ption


Table2:Con

tinued.

Protocol

Verifi

edmetho

dSimulator

type

Perfo

rmance

metric

sCom

paredto

Com

paris

onresult

Simulator

Testb

ed

ALC

OLB

R[9]

√NS-2

Delay-nod

elife

time-PR

RAG

RAandM-IA

RAC

OLB

Rhasa

bette

radaptability;itcan

achieveload

balancing,redu

cethee

ndto

enddelay,andprolon

gthe

networklifetim

eKe

etal.[10]

——

——

——

TPGF[12]

√NetTo

poDelay-no.of

foun

dpaths

GPS

RHoles

canbe

efficiently

bypassed

comparedto

(GPS

R),

suitablefor

multim

ediatransm

ission

GEA

MS[13]

√OMNeT

++Dela

y-lost

packet-energy

distr

ibution

GPS

RMores

uitablefor

WMSN

sthanGPS

Ras

itensures

unifo

rmenergy

consum

ptionandmeetsthed

elay

and

packetlossconstraint


each node increases energy consumption, redundancy, andcongestion. The protocol requires grid arrangement which isnot suitable for all applications of sensor network.The resultsare not compared to known protocols forWMSN. Increasingthe reliability and decreasing the delay by increasing thetransmission power will increase energy consumption whichaffects the network performance.

Table 1 shows summary of comparison between afore-mentioned routing protocols for WMSN based on the QoSparameters considered: data delivery model, network archi-tecture, hole bypassing, energy aware, methodology used,congestion control mechanism, location awareness, and clas-sification service.

Table 2 shows the simulation scenario of proposed rout-ing protocols for WMSNs.

4. Conclusion

Appearing of WMSN has opened new large applicationsin our life and many researches issues emerged that needdifferent solutions. In this paper WMSN technologies areintroduced. Challenges and resource constraints are dis-cussed. Current routing protocols are classified according tothe existing researches direction. Also the routing protocolsproposed for multimedia transmission are surveyed and theperformance issues of each routing protocol are highlighted.In our survey, we can realize that the proposed protocols forwireless multimedia sensor network have different method-ologies and one goal which satisfies themultimedia transmis-sion requirements.The proposed protocols lie under differentcategories as mentioned, where the first class shows therouting protocols based on ant colony optimization.TheACOdisplays several features that make it particularly suitablefor wireless multimedia sensor networks. Additionally, antrouting has shown excellent performance to solve routingproblems in WSNs and ad hoc networks. The second classis geographic routing protocols like TPGF and GPSR. Theseprotocols achieve good performance in hole bypassing and itis suitable forWMSN as it ensures uniform energy consump-tion and meets the delay and packet loss constraint. The lastclass of the proposed protocols follows different algorithmtypes and addresses different QoS metrics that are requiredfor multimedia transmission with resource constraint natureof WMSN. We believe that the researches focus will increasein this area, while developing routing protocols will attractmore attention since they play the key roles behind thedevelopment of WSN.

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