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Hindawi Publishing CorporationInternational Journal of Distributed Sensor NetworksVolume 2012, Article ID 392515, 11 pagesdoi:10.1155/2012/392515

Research Article

A Cross-Layer-Based Clustered Multipath Routing withQoS-Aware Scheduling for Wireless Multimedia Sensor Networks

Islam T. Almalkawi,1 Manel Guerrero Zapata,1 and Jamal N. Al-Karaki2

1 Computer Architecture Department, Technical University of Catalonia, 08034 Barcelona, Spain2 Computer Engineering Department, The Hashemite University, Zarqa, Jordan

Correspondence should be addressed to Islam T. Almalkawi, [email protected]

Received 17 February 2012; Accepted 28 March 2012

Academic Editor: Paola Flocchini

Copyright © 2012 Islam T. Almalkawi 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.

Wireless multimedia sensor networks (WMSNs) can handle different traffic classes of multimedia content (video, audio streams,and still images) as well as scalar data over the network. To ensure correct delivery of real-time multimedia data and efficientresource utilization, a proposed solution should provide both quality of service (QoS) assurance and energy efficiency. In thispaper, we propose a cross-layer-based routing protocol that can utilize MAC-layer QoS-based scheduling for more efficient routingmechanism in WMSNs. Our proposed optimization is based on clustered multipath routing protocol and adaptive QoS-awarescheduling for the different traffic classes in WMSNs. Our design exploits the hierarchical structure of powerful cluster headsand the optimized multiple paths along with the adaptive scheduling to support reliable, high-throughput, and energy-efficientmultimedia transmission in WMSNs. Simulation results show a significant performance improvement of our proposed designwhen compared to other similar routing schemes.

1. Introduction

WMSNs [1, 2] are able to deliver multimedia content dueto the availability of inexpensive complementary Metal oxidesemiconductor (CMOS) cameras and microphones coupledwith the significant progress in distributed signal processingand multimedia source coding techniques. The additionalrequirements of delivering real-time multimedia data—suchas high bandwidth demand, tolerable end-to-end delay,proper jitter, and frame loss rate—along with many resourceconstraints in WMSNs should be considered probably atdifferent layers of the communication protocol stack. Mostof the existing proposed protocols designed for WMSNsfollow the classical layered structure of the communicationprotocol stack without taking into consideration the especialrequirements of handling real-time multimedia content overWMSNs. Some of these proposals may achieve a goodperformance in terms of some metrics related to each of theirintended individual layers, but these performance metricsare not jointly optimized to maximize the overall network

performance with minimum energy consumption. Never-theless, the correlation characteristics and interdependenciesamong the layers of the communication stack in WMSNcannot be neglected and should be exploited for betterperformance and efficient communication. Therefore, cross-layer optimization can be the solution to meet the especialrequirements of WMSN and its design challenges [3] in orderto provide enough support for multimedia applications andmaximize network performance.

Routing in WMSNs is very challenging and criticalbecause of their characteristics and constraints that makethem different from the existing communication and scalarwireless sensor networks [1, 4], such as (1) large number ofheterogeneous sensor nodes with different capabilities andfunctionalities is deployed; (2) careful resource managementfor multimedia transmissions is required as sensor nodes aretightly constrained in terms of battery energy, processingpower, storage capacity, and available bandwidth; (3) alsodelivering the collected multimedia data in WMSNs (videostreaming, still images, and audio) adds more constraints

2 International Journal of Distributed Sensor Networks

on the design of the routing protocols in order to meettheir QoS requirements such as end-to-end delay, SNR(signal-to-noise ratio) level, and packet (frame) loss rate;(4) in addition, the use of densely deployed nodes providessignificant redundancy in the collected sensor data, forexample, overlapping of FoVs (Field of Views) of camerasensors. Such redundancy needs to be exploited to improveenergy and bandwidth utilization, and for more accurate androbust observation results.

In general, two types of WMSNs architecture are widelyused [1]: flat and hierarchical (cluster-based) network archi-tecture as shown in Figure 1. In flat architecture, the networkis deployed with homogeneous sensor nodes of the samecapabilities and functionalities, which can perform any taskfrom image capturing through multimedia processing topacket relaying toward the sink in multihop basis. Onthe other hand, at cluster-based architecture, the networkis divided into clusters. Heterogeneous sensor nodes aredeployed in each cluster, where camera, audio, and scalarsensors relay data to a cluster head that has more resourcesand is able to perform intensive data processing. The clusterhead is wirelessly connected with the sink or the gatewayeither directly or through other cluster heads in multi-hopfashion. For WMSNs, cluster-based network architecture hasmore advantages than a flat network especially for image pro-cessing and transmissions. In the homogeneous flat network,all the nodes should have the same hardware capabilities andfunctionalities for multimedia processing and transmission,and this leads to increase the energy consumption andthe cost of the deployed network. Also, a single-tier flatarchitecture can cause the sink to overload with the increasein sensors density, which can affect the performance of thenetwork and cause latency in communication and trackingevents. Moreover, in cluster-based network, cluster heads canperform data aggregation and filtering to reduce the amountof transmitted data and do better scheduling among thenodes within clusters.

Design of an efficient QoS-aware MAC protocol [5, 6]is another important step for correct delivery of real-timemultimedia data and for end-to-end QoS provisioning overWMSNs. It is desirable that the MAC layer provides reliableand error-free data transfer with minimum retransmissionswhile meeting the QoS requirements with efficient resourceutilization. The existing sensory MAC protocols are mostlybased on variants of the carrier sense multiple accesswith collision avoidance (CSMA/CA) [7] and time divisionMultiple Access (TDMA) [6]. Contention-based approach,such as CSMA/CA, is preferred when network traffic loadis not very intensive, and the channel condition is relativelyunreliable because the probability of potential collision andcongestion is low. However, for heavier traffic loads as thecase of WMSNs, contention-based approach leads to increasewasted energy and delays due to idle listening and collisionsproduced with large preamble and hidden node problems.On the other side, contention-free approach, like TDMA, ismore appropriate for multimedia applications with reliablechannel conditions and heavier traffic load. However, itsuffers from clock synchronization problem, in addition to

Network architecture

(a) Flat network architecture (b) Hierarchical network architecture

Sink Sink

Cluster

Powerful multimedia nodeNormal multimedia node

Single-hop communicationMultihop communication

Figure 1: Flat versus hierarchical network architecture.

channel underutilization and fixed time-slot assignments incase of static slotted scheduling.

A quick look into the existing proposals in routingprotocols in sensor networks reveals that they are followingthe standard structure of the communication protocol stackand do not pay attention for the interdependencies andjoint functionalities among the layers especially the routingand MAC layers. Therefore, in this paper, a cross-layerdesign is proposed between the routing and MAC layerswhere a clustered multipath routing protocol is pursuedin conjunction with an adaptive QoS-aware scheduling tooptimize the performance of the routing and reliable deliverywith minimum resource consumption.

Our proposed routing protocol aims to cluster the nodesusing clustering algorithm based on the received signalstrength, in a way that keeps strong connections among thenodes with maximum number of multiple paths suitablefor the different requirements of handling different trafficclasses. In each cluster, powerful cluster heads have thecapability to do some intensive multimedia processing andaggregation in order to reduce the transmitted amountof data for saving energy consumption and bandwidthusage. Our proposed scheduling mechanism is based onadaptive QoS-aware TDMA approach used at two levels inthe network: within clusters and among cluster heads. Ouralgorithm uses flexible time-slot assignment where a clusterhead is responsible to schedule the traffic toward the sinkfrom the sensor nodes based on the type of data and itsavailability.

The rest of the paper is organized as the follow-ing: Section 2 introduces an overview of existing relatedworks. Section 3 provides network architecture and systemmodel and assumptions. Section 4 describes the cluster-based multipath routing protocol in details. Section 5presents the adaptive QoS-aware scheduling mechanism.Section 6 presents the performance evaluation. Finally,Section 7 concludes the paper.

International Journal of Distributed Sensor Networks 3

2. Related Work

Several cross-layer and communication protocols were devel-oped to address the aforementioned issues for WMSNs andsurveyed in [8]. Here in this section, we focus on cross-layeroptimization proposals that include routing and schedulingfunctionalities, and we summarize them in Table 1.

A routing protocol, DHCT [9], is proposed for WMSNsto support multipath routing and to reduce interferencesbetween close paths by using a performance metric (calledCostp), which is product of expected transmission countand the delay. Using Costp metric allows selecting pathswith minimum interferences to each other, hence it willincrease throughput. Also DHCT reinforces multiple linksat the sink to obtain disjoint path from the source formultipath routing. However, this routing protocol does notconsider the bandwidth as QoS metric for routing decisionor prioritizes the incoming packets to schedule them as thecase in CMRP, but it does consider the playout deadlinein a sense that the packet arrives after the deadline willbe discarded. Also having only disjoint paths means notconsidering interconnecting paths that can be effectively usedalong with packet scheduling to utilize the available capacityand increase throughput.

COM-MAC [10] is a multichannel multipath MACprotocol with packet scheduling to meet the bandwidth anddelay requirements in WMSNs. The routing protocol usesmultiple paths, multiple channels, and QoS packet schedul-ing technique based on the dynamic bandwidth adjustmentand path-length-based proportional delay differentiation(PPDD) techniques. These requirements (bandwidth anddelay) are adjusted locally at each node based on the path-length and incoming traffic in static flat wireless networkwhere all the nodes are homogeneous multimedia sensornodes for the same capabilities (video, audio, and scalar data)and equipped with single radio interface and multichannels.However, unlike CMRP, it uses static time slots at controlchannel and does not propose any mechanism for passivenodes for better channel utilization. CMRP uses adaptivetime slots assignment that can be changed dynamically de-pending on data availability, data type, and number of activenodes.

Another multiconstrained routing algorithm, MCRA[11], is proposed to provide end-to-end delay and packetloss ratio suitable for multimedia content and balance theenergy consumption. In MCRA, routing discovery starts atthe sink node that floods the network with interest messages.The source node that receives these interest messages andmatches the needed query selects the path of minimum hopcount to send its data. When receiving data packet, the sinknode calculates the coordinates of the source node using thelogical coordinates (hop count). MCRA tries to reduce theamount of flooding by either not forwarding the interestmessages already received them before, or by merging multi-ple interests in one message. However, the routing dependson flooding the network with interest messages from sinkto sources using all nodes to find the paths, not only usingsome powerful nodes to discover the routes as in CMRP.Also, the selection of the paths by the sources in MCRA is

based only on minimum hop count without considering thequality of the link that can be estimated from the receivedsignal strength as in the case of CMRP.

The cross-layer design described in [12] jointly optimizesthe source coding techniques for multimedia processing andcompression in the application layer with the network codingalong with the routing functions to minimize the distortionwith maximum network lifetime following multiple paths.However, this approach does not provide any proposal forcontrolling node channel access or scheduling process amongthe nodes based on the data type, and thus interferences andcollisions cannot be avoided which leads to degrade networkthroughput and the quality of received data.

Another cross-layer design for WMSNs is implementedin [13] where an extension of a geographical routing protocolis presented for multipath routing along with path priorityscheduling algorithm for efficient communication of real-time video over WMSNs. Using hop-by-hop deviation angleadjustment method, a path can be established using anyinitial deviation angle specified at the source node, andthen other disjoint paths are constructed by changing thevalue of the deviation angle. If there is no path satisfyingthe required data rate, video coding parameters are adaptedalong with using frame skipping, reference frame selecting,and intraframe refreshing techniques in order to lower thebandwidth consumption. To meet the delay constraint ofvideo frames, a path priority scheduling algorithm is usedthat gives a weight for each path calculated based on theestimated available bandwidth, path delay, and path energylevel. Then, by using path weight along with packet prior-ity, shorter delay paths will be used for time-constrainedpackets, while other paths are used for balancing energyand bandwidth usage for other traffic. However, like mostgeographical routing protocols, the proposed cross-layerdesign assumes that nodes are location aware and that thedensity of nodes is high.

A cross-layer system is presented in [14] to provideQoS for WMSN applications based on the time-hoppingimpulse radio ultrawideband (TH-IR-UWB) transmissiontechnique. This architecture tries to solve the shortcomingsof using CSMA/CA for the MAC layer and to provide QoSfor WMSNs. Routing process starts at the source nodesby sending request packets describing their requirementsto their neighbors, and among the replies, a source nodeselects the one who has the most positive advance toward thesink and is able to satisfy the needed requirements, and thiscontinues iteratively until the end-to-end path is establishedto the sink. The cross-layer system also provides dynamicchannel coding and receiver-centric scheduling based ontime hopping sequence of impulse radio of ultrawidebandMAC and physical layer. This allows for multiple paralleltransmissions, prevents collisions at the receiver node (byusing unique TH sequence for each receiver), and savesenergy by avoiding idle listening and wasteful transmissions(by turning on exactly the incoming transmission). However,this cross-layer system is based on end-to-end resource reser-vation that causes higher overhead, and it does not considerthe source rate adaptation with the network conditions.


Table 1: Cross-layer design and communication protocols for WMSNs.

Protocol Network Modality Operational Layer Performance Metric

DHCT [9] Standard Routing Transmission-count/delay

COM-MAC [10] Cross-layer Routing/MAC Bandwidth/delay

MCRA [11] Standard Routing hop count/delay

Li et al. [12] Cross-layer Application/Routing Distortion

Chen et al. [13] Cross-layer Routing/MAC Bandwidth/delay/path energy

UWB-based Protocol [14] Cross-layer Routing/MAC/ Physical end-to-end resource reservation

MPMP [15] Cross-layer Transport/Routing Distance/delay/data type

QoS-SDMR [16] Cross-layer Application/Routing/MAC Bandwidth/delay/distortion

CMRP Cross-layer Routing/MAC hop count/RSSI

In [15], a context-aware cross-layer multipath multi-priority (MPMP) transmission scheme is proposed wherealgorithms in routing and transport layers are used. In thisscheme, a multipath geographic routing protocol is used toexplore maximum number of node-disjoint routing paths.Also, a context-aware multipath selection algorithm in thetransport layer is used to choose the maximum number ofpaths from all found node-disjoint paths for maximizingthe delivery of the important data to the sink. The selectionalgorithm selects the proper routing paths that are suitablefor each type of multimedia content based on two typesof priority: end-to-end transmission delay-based priorityfor constraint real-time video communication and context-aware multimedia-based priority (image versus audio) forthe most valuable information to the sink. However, theunderlying routing protocol considers only the distancebetween the nodes and the sink to discover the routes anddoes not take into account other important parameters suchas link quality and bandwidth. Also, this protocol does notsupport different type of traffic (video and scalar data at thesame time).

A cross-layer framework is presented in [16] for QoSsupport in WMSNs, which optimizes the functionalitiesof communication protocols to maximize the number ofvideo stream requests to be delivered without affectingtheir quality. The proposed design uses a source-directedmultipath routing (SDMR) protocol that interacts withenhanced IEEE 802.11e MAC standard for QoS scheduling,and data link layer for multirate transmission modes. Alsothe cross-layer design is capable of interacting with theapplication layer to choose an appropriate group of picture(GoP) size according to network conditions and the feed-backs received from the sink. However, the SDMR routingprotocol assumes a flat network with dense deployment forsensor nodes for estimating the upper bound number ofhops in order to calculate the required end-to-end delay.Also SDMR establishes only disjoint paths (maximum threenoninterfering paths) from a source to the sink.

3. System Model

The network is divided into clusters using our proposed rout-ing protocol, called CMRP, where each cluster is deployedwith heterogeneous sensors (camera, audio, and scalar sen-sors) that communicate directly in a certain schedule with a

cluster head and relay their sensed data to it. However, theseheterogeneous sensor nodes have the same radio interfaceand propagation range. A cluster head has more resources,and it is able to perform intensive data processing. Thesepowerful nodes, cluster heads, are deployed uniformly in thenetwork, and they are wirelessly connected with the sinkeither directly (in case of 1st-level cluster heads) or throughother cluster heads in multihop fashion.

CMRP is based on hop count and received signal strengthindex (RSSI) of the sensory message as an indication of thelink quality and distance between the nodes. RSSI can becalculated in a large-scale wireless sensor network using thefollowing propagation model:

Pr = PtGtGr(hthr)2d−4L−1, (1)

where Pt and Pr are the power level of transmitted andreceived message, respectively, Gt and Gr are the transmitter(Tx) and receiver (Rx) antenna gain, respectively, ht and hrare antenna height for the Tx and Rx, respectively, d is thedistance between the Tx and the Rx, and L is system lossfactor. Then,

RSS = PrPt−→ RSS = GtGr(hthr)

2d−4L−1. (2)

If we assumed that antenna gain of the Tx and Rx is equalto 1, antenna height of the Tx and Rx is equal to 1, and Lalso equals 1, then RSSI can be approximated as a functionof distance between the Tx and Rx as a dominating factoraffecting its value RSS ≈ 1/d4.

For more accurate propagation model, signal-to-noiseratio (SNR) and bit error rate (BER) should be taken intoaccount along with the received signal strength in order toconsider noises (from receiver and environment) and inter-ferences from other packets arrived simultaneously:

SNR = 10 log

(Pr

Np +∑n−1

i Pr

),

BER = 0.5× erfc

(√Pr × BWNp × R

),

(3)

where BW is the channel bandwidth, Np is noise power, n isnumber of interfering packets, and R is data rate.


4. Cluster-Based Multipath Routing in WMSN

This section describes the routing operation of our proposedclustered multipath routing protocol for WMSNs, CMRP,which is based on the hierarchical structure of multiplepaths established depending on hop count and receivedsignal strength (along with measured SNR and BER) asan indication of the link quality and distance between thenodes. CMRP depends on the local information exchangedamong the nodes to establish the routes to the sink and doesnot require any coordination measurement equipments orposition message exchange.

4.1. Route Discovery. Here, we explain our proposed clus-tered multipath routing protocol, CMRP, and then we dem-onstrate the scheduling algorithm in the next section. We areusing two performance metrics: hop count (as indication fordistance from the sink and delay) and received signal strengthindex RSSI (combined with SNR & BER) as indication forlink quality (interference and noise level) and distance fromthe sender. Two thresholds (upper and lower) are used tocompare with the packet’s RSSI.

The selection of the values of the two thresholds isvery critical in clustering the network and connecting themtogether. The upper threshold is used to determine the 1st-level cluster heads and group member nodes (as describedbelow). The upper threshold should be adjusted in a way thatit should not be very large value (close to the max value)so that you will not find any node receives your messagein this power level or only a few nodes. In this case, thecluster size will be very small with many chances of havingonly singleton clusters, and the load will be high on few 1st-level cluster heads for serving many paths passing throughthem. Also if the upper threshold is low (below the midvalueclose to the lower threshold), the cluster size will be veryhigh and cause cluster heads to overload with many groupmembers and suffer high interferences in both inside clustersand at the sink side. The lower threshold is used to establishthe links between cluster heads. Having a relatively highvalue of the lower threshold (close to the midvalue) mayprevent connecting the cluster heads in different levels andthis leads to have a weak network connectivity. Also if thelower threshold is very low (close to the midvalue), then thenetwork can have low link quality links between cluster headswith high possibility of packet drops.

In the initializing phase of CMRP, the base station startssending periodic broadcast messages, called BS-Msg, to thesurrounding powerful nodes. The nodes that receive BS-Msgs compare the RSSI with the upper threshold (Thr-High). If RSSI is greater than Thr-High, these nodesrespond to the base station by sending back acknowledgmentmessages informing their joining the base station as theirparent. Then, they start acting as 1st-level cluster heads (1stCH)—as shown in an example in Figure 2—and broadcastperiodically control messages called CH-Msg to their neigh-boring nodes. CH-Msg contains the ID of the CH, numberof hops between the CH and the sink in the current foundpath, and IDs of the nodes joining this path up to the currentCH. For each CH-Msg received by the surrounding nodes of

Base station

Cluster

1st-level cluster head2nd-level cluster head

Group member

Figure 2: An example of clustered multipath WMSN.

the 1st CHs, RSSI is measured and compared with the twothresholds, Thr-High and Thr-Low.

If the signal strength of the received CH-Msg is greaterthan Thr-High, the receiving node will start behaving as agroup member (GM) and send back an acknowledgmentmessage informing its joining to the corresponding CH.Receiving a CH-Msg with RSSI greater than Thr-Highindicates that the sender (CH) is in near region and thequality of the link is good, and thus, this CH can better servethe communication toward the base station. In case a nodereceives more than one message from different CHs withRSSI larger than Thr-High, the node selects the cluster headof the highest RSSI value, as shown in pseudocode of CMRPin Algorithm 1.

The powerful nodes that only receive messages with RSSIbetween Thr-High and Thr-Low will start acting as newcluster heads, in this case 2nd-level CHs, and respond backto the sender informing their selection of him as one oftheir possible parents toward the base station. New CHsmay receive different CH-Msgs from previous-level CHs.In this case, new CHs consider these messages in order toconstruct multiple paths toward base station and sort thesepaths based on certain criterions (such as link quality, end-to-end delay, bandwidth, or number of hops in the path).Paths with good conditions, like high link quality, short end-to-end delay, enough bandwidth, or less number of hops,are reserved for multimedia communication that requirescertain level of quality of service requirements. Other pathswill be used for other types of data that does not require strictQoS requirements such as scalar data. If the RSSI is less thanThr-Low, the message is considered as lost or ignored. Thisprocess continues in the same manner to build the networkuntil all nodes join the network and determine their roles,that is, cluster head or group member, and all possible pathsare found.


(1) Broadcasting authenticated BS-Msg periodically(2) For each node i receives BS-Msg−→Calculate RSSI

if RSSI > Thr-Highact as (1st-level) CHsend authenticated CH-Msg periodically

elseignore BS-Msg

End ifEnd for

(3) For each node i receives CH-Msg −→Calculate RSSIif RSSI > Thr-High

act as GMadd sender to CH-tablestart selectMyCH timer

elseif RSSI > Thr-Low

act as CHadd sender to parent table & add path to available paths tablestart selectMyParent timer

elseignore CH-Msg

End ifEnd for

(4) After selectMyCH timer or selectMyParent timer expired:For each CH −→select parent from parent table &

select corresponding path from available paths tablesuitable for each traffic class

For each GM −→ select CH from CH-table with max RSSI

Algorithm 1: The pseudocode of the main routing process of CMRP.

In case that cluster heads do not receive any message fromother nodes informing joining them as group members (i.e.,singleton clusters), then these cluster heads will behave eitheras (1) forwarder nodes to relay data toward the sink, if theyreceive messages from other powerful nodes informing theirjoining as next-level cluster heads, or (2) temporarily normalnodes, group members, and join any other closer clustersbased on RSSI. These nodes can create later on their ownclusters when new group members nodes are deployed intheir vicinity.

After the network is established and all possible routesare found, base station and cluster heads will reduce the rateof sending broadcast control messages (BS-Msg, CH-Msg) inorder to save channel capacity and energy. We keep sendingthese broadcast messages even with lower rate, which has anegligible effect on the network performance, for the sake ofadding new nodes to the network.

4.2. Route Optimization. In order to optimize the foundroutes in route discovery phase, path loops and path cyclesshould be prevented. For path loops, each CH that receivesCH-Msg from other nodes checks first the IDs of the nodesjoining the path to know whether it already joined this pathbefore or not. If a CH receives CH-Msg belongs to one ofthe paths already found before, it checks the conditions andthe status of the given path in order to update its routinginformation about this path and reflects these changes (if

any) on its decision of selecting the proper path for eachtype of data. Moreover, for path optimization with minimumnumber of hops, a CH checks for every given path whetherit is a child for any participating node in this path (except ofcourse its direct parent in this path). In this case, it is betterfor the CH to communicate directly to that parent instead ofmaking a path cycle. Thus, if a path cycle is found, the clusterhead deletes this path from its routing information and keepsthe shorter path.

4.3. Local Repair. The acknowledgment system is criticalfor WMSNs to achieve a low frame loss rate that affectsthe quality of video perception and to detect any nodeor link failure. After receiving a certain number of datapackets, a CH sends an acknowledgment message (Ack-Msg) to the sender (lower-level CH or GM) and in thesame manner waits an Ack-Msg from its parent (higher-levelCH or sink) confirming receiving the data packets. So, ifa node did not receive an Ack-Msg from its parent, it willassume that there is a node failure or link failure, and it willselect another parent (i.e., another path)—depending on itsrouting information tables—suitable with the current typeof data. There is no need to initialize the entire networkfor establishing the routes again in order to overcome theexisting failure; it just affects the nodes along the failed pathand because of that it is called local repair. If the parentis the sink, and there is no response from its side, then


the node should communicate with other reachable 1st-levelCHs, based on RSSI, to deliver data packets through them.If this node cannot communicate with any 1st-level CH,then it should send negative Ack-Msg to its children nodes(lower-level CHs and GMs) informing about this link failure.Then children nodes will have to select another parent CHaccording to their routing information table.

The same procedure is used with GMs to check their CH.After sending a certain number of data packets, a GM waitsan Ack-Msg from its CH confirming receiving those packets.If the GM did not receive Ack-Msg, then it assumes that thereis a link failure or node failure and joins another CH basedon its routing information table.

4.4. CMRP Life Time Analysis. In this subsection, we areinterested in analyzing the effect of multipath routing in theexpected life time of a link between a CH and BS. Accordingto CMRP, a link (P) consists of multiple paths where eachpath (pi) contains a certain number of intermediate CHs (n).A path will be broken once the battery energy (Ei) of anyintermediate node residing on it depleted. Ei is independentrandom variable distributed uniformly between 0 and Emax

(full battery energy), and for simplification, we can expressCi = Ei/Emax where Ci now is an independent random vari-able uniformly distributed between 0 and 1. Then, we candefine the following parameters.

Path life time:

pi = min(C1,C2, . . . ,Cni

). (4)

Link life time:

P =N∑i=1

(pi), (5)

where n is the number of nodes in the path i, and N is thenumber of paths in the link P.

Then the expected (average) life time of the link (P) is

E{P} =N∑i=1

E(pi). (6)

Since all node energy indexes (Ci) are random variablesuniformly distributed between 0 and 1, then the minimumrandom variable along one path pi follows a Beta distributionwith parameters 1 and n. The probability density function ofBeta distribution is as follows:

f(x;α,β

) = xα−1(1− x)β−1

B(α,β

) , (7)

where B(α,β) is the beta function:

B(α,β

) =∫ 1

0tα−1(1− t)β−1dt. (8)

Then substituting α = 1 and β = n gives us the probabilitydensity function of the path life time:

P{pi = x

} = n · (1− x)n−1. (9)

As the mean value of the Beta distribution is {X} = α/(α+β),then the expected path life time of this probability functioncan be expressed as

E{pi} = 1

n + 1. (10)

Finally, the average link life time can be calculated as:

E{P} = N

n + 1. (11)

5. Two-Level QoS-Aware Scheduling

After establishing the network and before data transmission,we introduce two-level QoS-aware scheduling as shown inFigure 3: low-level scheduling within each cluster among theGMs and high-level scheduling among the cluster heads inorder to increase the packet delivery ratio and throughputfor multimedia data.

Besides their low energy efficiency, most contention-based protocols are generally not designed for sending real-time multimedia data and are not suitable for delay-sensitiveWMSNs because each node has to contend for mediumaccess to send every packet; thus, the delay for data deliverycould be potentially unbounded. The needed time requiredto resolve collision is based on the load condition of thenetwork and number of nodes in clusters, which makes itvery difficult to guarantee a bounded delay. Therefore, weprefer to adopt TDMA protocol to access the channel as it hasa natural advantage of collision-free medium access, and it ismore appropriate for transmitting multimedia applicationswith QoS at reliable channel conditions and heavier trafficload. In order to avoid channel underutilization and todecrease the delay, dynamic time slot is assigned to the nodesdepending on the amount of data to be transmitted and thetime for sending Ack-Msgs if needed.

At low level, each CH should schedule the data trans-missions among its GMs within the cluster in order to givehigher priority to the nodes that demand higher or strictQoS requirements for their data and to avoid collisions andinterferences.

The low-level scheduling process is initiated by the CH bysending a broadcast message asking each GM in the clusterto send their requests informing about the type of data tobe transmitted, its amount, and its requirements (such asplayout deadline, BW, etc.). This broadcast message, Assign-Msg, contains the control slot assignment (i.e., time slot toeach GM) in the cluster. The duration of the control slot isenough to any node in the cluster to send its request message(Req-Msg), and the time slot is unique for each GM to avoidcollisions. During the request phase, each GM sends a Req-Msg to its CH at the allocated time slot informing about thedata to be sent (if available) and its QoS requirements.

Then based on the collected information from therequest phase, each CH generates a transmission schedule forthe active GMs and distributes it in the cluster. The resultingschedule is sent to all GMs by broadcasting a schedulingmessage, Sched-Msg, to inform each GM with the specifiedtime schedule for sending each type of data. The duration of


Parent CH

Cluster

Child CH

GM

GM

GM

GM

Parent CH

Child CH

CH2

CH3 CH4

Cluster

CH1

Direction of data transferMultimedia dataScalar data

Cluster head

Group memberCluster boundary

Figure 3: A simple example of two-level scheduling.

Assignment phaseRequest phase

Scheduling phaseData transmission phase

ΔT1 ΔT2 ΔT3

Figure 4: A cluster time intervals for scheduling process.

the time slot depends on the amount and type of data to betransmitted as requested by each GM.

By this way, multimedia streaming and time-critical datacan be transmitted first, then less priority data such as stillimages and then scalar data can be sent later. Moreover,for better energy efficiency, GMs can turn off their radiotransceiver when the schedule has been received until thetime slot for transmitting a certain data type approaches orto the end of the data transmission phase if they are passivenodes. After receiving the schedule, each GM will transmit itsdata during the assigned time slots for each data type and theCH sends, after receiving a certain number of data packets,an Ack-Msg to the sender as described before. When the datatransmission phase completes, a CH sends again the Assign-Msg to its GMs to send their requests. The time intervals ofthe scheduling operation in a cluster are shown in Figure 4.

At higher level, each intermediate cluster head—in thesame manner done at low level—schedules the traffic towardthe sink from other cluster heads (its children) based on thetype of the data and its QoS requirements.

6. Performance Evaluation

We simulate our proposal using NS-2 v2.34 [17] for over 100experiments with various random topologies. The networksize is 500 m × 500 m deployed with number of nodesranging from 50 to 175 in randomized grid for durationof 1000 s. The sink is located in the center of the network.The traffic is CBR of 600 packet/second, and the packet sizeis 316 bytes. We adopt IEEE802.11 for the MAC layer asshown in Table 2, which lists the parameters we used in our

Table 2: Simulation environment and used parameters.

Simulation parameter Value

Simulation time 1000 s

Network size 500× 500 m2

Node number 50–175

Link layer LL

MAC layer IEEE802.11

IFQ type Queue/DropTail/PriQueue

IFQ length 10

Antenna type Antenna/OmniAntenna

Physical type Phy/WirelessPhy

Channel type Channel/WirelessChannel

Energy model EnergyModel

Bandwidth 2 MB

Table 3: Features of Salvat Cluster and its picture.

Features Salvat Cluster

∗ USP 73 nodes XeonDual-Core 5148

∗Motherboard IntelS5000VCL∗ Intel SR1530chassis∗ Intel 5000 V∗ 2 Dual-Core IntelXeon 2.333 GHz,1333 MHz FSB, 4 MBCache∗ 12 GB RAM in 6modules of 2 GB∗ Hard Drive SeagateBarracuda 320 GBS-ATA-2∗ 2 IntelPRO/1000 GigabitEthernet networkcards

simulation. We used “Salvat Cluster” that has the featuresshown in Table 3 to run our simulation.

In the simulations, we focus on measuring the perfor-mance metrics after the network has set up to exclude thecommunication overhead of the most exchanged controlmessages. Control messages include broadcast messages (BS-Msg, CH-Msg) sent at very low rate and acknowledgmentmessages (Ack-Msg) used for data receiving notification andlocal repair. However, these control messages are consideredin measuring the energy consumption during simulationtime.

Figure 5 shows the end-to-end delay, which is one ofthe important QoS parameters as the real-time multimediapackets have strict playout deadlines. We compare theaverage end-to-end delay of our proposed routing pro-tocol combined with the two-level scheduling technique(CMRP+2 level scheduling) with the proposed routing


45

95

145

195

245

50 100 125 175

En

d-to

-en

d de

lay

(ms)

Network size

DHCTCMRP onlyMCRA

CMRP + 2 level scheduling

Figure 5: End-to-end delay performance of our protocol.

protocol only (CMRP only) and the other protocols (DHCTand MCRA). We select these protocols to compare with toshow how our proposed cross-layer design methodology willoutperform the other recent protocols that are based on theclassical layered structure of the communication stack.

It is shown clearly that our cross-layer design has theminimum end-to-end delay and outperforms the otherprotocols because it depends on selecting the path of betterlink quality and minimum hop count through powerfulcluster heads. Notice that CMRP only performs well at lownode density, but with dense deployment end-to-end delayincreases significantly due to the interferences and collisionswithin the clusters and among cluster heads which causeretransmission lost packets again.

Our proposed cross-layer protocol achieves higherthroughput, as shown in Figure 6, than the other protocolsby efficiently utilizing the wireless spectrum and distributingthe load via adopting adaptive TDMA-based scheduling andselecting multiple paths of better link quality and minimumdelay, respectively. Without implementing the schedulingscheme, we notice that CMRP-only’s performance is degrad-ing with increasing the number of nodes due to the timewasted for retransmitting lost packets and changing paths toovercome the interferences and collisions and hence lead todecrease number of received packets at the sink during thesimulation time.

Average packet delivery ratio (PDR) is shown in Figure 7where our proposed cross-layer design outperforms the otherprotocols, which confirms the previous result. We obtain thisresult due to the use of the two-level scheduling that preventscollisions and minimizes interference, besides the selectionof paths with better link quality based on the received signalstrength (along with SNR and BER). Also, the use of thefast mechanism of local repair through the acknowledgment

0

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100

150

200

250

50 100 125 175

Th

rou

ghpu

t (p

acke

t/s)

Network size

DHCT

CMRP onlyMCRACMRP + 2 level scheduling

Figure 6: Throughput performance of Our Protocol.

50

60

70

80

90

100

50 100 125 175

PD

R (

%)

Network size

DHCT


Figure 7: PDR of our protocol compared with other protocols.

system minimizes the effects of any node failure or link breakand hence decreases the number of lost packets.

With respect to the average energy consumption, ourproposed design has less energy consumption than the otherprotocols as shown in Figure 8 with different node numbers.Both CMRP-only and CMRP+2 level scheduling protocolshave good energy efficiency at low node density because ofthe many benefits that they get from the clustered networkarchitecture. First, they have less communication overheadas most of the nodes in the network are group membersand need only to communicate directly with their clusterheads regardless of the number of nodes in the cluster. Also,


15

18

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24

27

30

33

50 100 125 175

En

ergy

con

sum

ptio

n (

mW

H)

Network size

DHCT


Figure 8: Energy consumption of our protocol and other protocols.

minimum number of packet forwarding from a source tothe sink is needed as the paths found by CMRP routingprotocol are optimized in terms of number of hops alongwith preventing path loops and path cycles. In addition, theaggregation process and data fusion done at cluster headslevel reduce the size of correlated data within a cluster andthus decrease the needed amount of energy consumptionto deliver them. However, at higher node densities, wenotice that CMRP-only suffers from packet collisions andinterferences and consumes more energy for retransmittinglost packets, while our cross-layer design exploits the benefitsfrom the adaptive two-level scheduling to prevent suchproblem and hence has less energy consumption.

7. Conclusions

In this paper, we presented a cross-layer communicationarchitecture for WMSNs between the routing and MAC lay-ers, where a cluster-based multipath routing protocol hasbeen pursued in conjunction with an adaptive QoS-awarescheduling. Our design aims to exploit correlation character-istics and functionalities between the two layers to maximizethe overall network performance with minimum energyconsumption in order to handle the additional requirementsof delivering reliable multimedia data. Our proposed routingprotocol provides load balancing by establishing multiplepaths based on the hop count and received signal strength asan indication of the link quality, delay, and distance betweenthe nodes. Our proposed scheduling protocol is based onTDMA approach with flexible time slot assignment thatadaptively assigns slots to various traffics from active nodes.It maintains minimum end-to-end delay suitable for differ-ent traffic classes to meet their playout deadline and achieveshigh throughput and packet delivery ratio by selecting thepaths with better link quality and avoiding collisions andinterferences. The simulation results demonstrate that ourcross-layer design can achieve better performance than the

preexisting ones (CMRP only, DHCT, and MCRA) in termsof average end-to-end delay, throughput, packet deliveryratio, and battery power consumption. In future work, wewill focus on optimizing the threshold values based on net-work configuration both in mathematical representation andin simulation. This will result in better cluster distributionand network connectivity. Also, studying in more details theeffect of the communication overhead and synchronizationproblem in our scheduling protocol is planned.

Acknowledgments

This work was partially supported by the EuroNF NoEand Spanish Grants TIN2010-21378-C02-01 and 2009-SGR-1167.

References

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[2] I. F. Akyildiz, T. Melodia, and K. R. Chowdhury, “A surveyon wireless multimedia sensor networks,” Computer Networks,vol. 51, no. 4, pp. 921–960, 2007.

[3] I. T. Almalkawi, M. Alaei, M. Guerrero Zapata, J. M. Barcelo-Ordinas, and J. Morillo-Pozo, “Energy efficiency in wirelessmultimedia sensor networks,” IEEE COMSOC MMTC E-Letter Special Issue on Multimedia Sensor Networks in Sustain-able Systems, vol. 6, no. 12, pp. 17–20, 2011.

[4] S. Ehsan and B. Hamdaoui, “A survey on energy-efficient rout-ing techniques with QoS assurances for wireless multimediasensor networks,” IEEE Communications Surveys and Tutorials,no. 99, pp. 1–14, 2011.

[5] K. Kredo II and P. Mohapatra, “Medium access control inwireless sensor networks,” Computer Networks, vol. 51, no. 4,pp. 961–994, 2007.

[6] M. A. Yigitel, O. D. Incel, and C. Ersoy, “QoS-aware MACprotocols for wireless sensor networks: a survey,” ComputerNetworks, vol. 55, no. 8, pp. 1982–2004, 2011.

[7] N. Saxena, A. Roy, and J. Shin, “Dynamic duty cycle andadaptive contention window based QoS-MAC protocol forwireless multimedia sensor networks,” Computer Networks,vol. 52, no. 13, pp. 2532–2542, 2008.

[8] D. G. Costa and L. A. Guedes, “A survey on multimedia-basedcross-layer optimization in visual sensor networks,” Sensors,vol. 11, no. 5, pp. 5439–5468, 2011.

[9] S. Li, R. Neelisetti, C. Liu, and A. Lim, “Delay-constrainedhigh throughput protocol for multi-path transmission overwireless multimedia sensor networks,” in Proceedings of the9th IEEE International Symposium on Wireless, Mobile andMultimedia Networks (WoWMoM ’08), pp. 1–8, NewportBeach, Calif, USA, June 2008.

[10] C. Li, P. Wang, H. H. Chen, and M. Guizani, “A clusterbased on-demand multi-channel MAC protocol for wirelessmultimedia sensor networks,” in Proceedings of the IEEEInternational Conference on Communications (ICC ’08), pp.2371–2376, Beijing, China, May 2008.

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[13] M. Chen, V. Leung, S. Mao, and M. Li, “Cross-layer and pathpriority scheduling based real-time video communicationsover wireless sensor networks,” in Proceedings of the IEEEVehicular Technology Conference (VTC ’08), pp. 2873–2877,Marina Bay, Singapore, May 2008.

[14] T. Melodia and I. F. Akyildiz, “Cross-layer quality of servicesupport for UWB wireless multimedia sensor networks,” inProceedings of the 27th IEEE Communications Society Confer-ence on Computer Communications (INFOCOM ’08), pp. 121–125, Phoenix, Ariz, USA, April 2008.

[15] L. Shu, Y. Zhang, Z. Yu, L. T. Yang, M. Hauswirth, and N.Xiong, “Context-aware cross-layer optimized video streamingin wireless multimedia sensor networks,” Journal of Supercom-puting, vol. 54, no. 1, pp. 94–121, 2010.

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