Sensors 2010, 10, 10506-10523; doi:10.3390/s101210506sensorsISSN 1424-8220www.mdpi.com/journal/sensorsReviewA Comparative Study of Wireless Sensor Networks and TheirRouting ProtocolsDebnath Bhattacharyya 1, Tai-hoon Kim 1,* and Subhajit Pal 21 Department of Multimedia Engineering, Hannam University, Daejeon, Korea;E-Mail: email@example.com Heritage Institute of Technology, Kolkata-700107, India; E-Mail: firstname.lastname@example.org* Author to whom correspondence should be addressed; E-Mail: email@example.com;Tel.: +82-42-629-8373; Fax: +82-42-629-8383; Mobile: +82-10-8592-4900.Received: 10 October 2010; in revised form: 10 November 2010 / Accepted: 15 November 2010 /Published: 24 November 2010Abstract: Recent developments in the area of micro-sensor devices have acceleratedadvances in the sensor networks field leading to many new protocols specifically designedfor wireless sensor networks (WSNs). Wireless sensor networks with hundreds to thousandsof sensor nodes can gather information from an unattended location and transmit thegathered data to a particular user, depending on the application. These sensor nodes havesome constraints due to their limited energy, storage capacity and computing power. Dataare routed from one node to other using different routing protocols. There are a number ofrouting protocols for wireless sensor networks. In this review article, we discuss thearchitecture of wireless sensor networks. Further, we categorize the routing protocolsaccording to some key factors and summarize their mode of operation. Finally, we provide acomparative study on these various protocols.Keywords: wireless sensors; protocols; routing; energy efficiency; clustering1. IntroductionA wireless sensor network (WSN) consists of hundreds to thousands of low-powermulti-functional sensor nodes, operating in an unattended environment, and having sensing,computation and communication capabilities. The basic components  of a node are a sensor unit, anADC (Analog to Digital Converter), a CPU (Central processing unit), a power unit and aOPEN ACCESSSensors 2010, 10 10507communication unit. Sensor nodes are micro-electro-mechanical systems  (MEMS) that produce ameasurable response to a change in some physical condition like temperature and pressure. Sensornodes sense or measure physical data of the area to be monitored. The continual analog signal sensedby the sensors is digitized by an analog-to-digital converter and sent to controllers for furtherprocessing. Sensor nodes are of very small size, consume extremely low energy, are operated in highvolumetric densities, and can be autonomous and adaptive to the environment. The spatial density ofsensor nodes in the field may be as high as 20 nodes/m3.As wireless sensor nodes are typically verysmall electronic devices, they can only be equipped with a limited power source . Each sensor nodehas a certain area of coverage for which it can reliably and accurately report the particular quantity thatit is observing. Several sources of power consumption in sensors are: (a) signal sampling andconversion of physical signals to electrical ones; (b) signal conditioning, and (c) analog-to-digitalconversion.There are three categories of sensor nodes:(i) Passive, Omni Directional Sensors: passive sensor nodes sense the environment withoutmanipulating it by active probing. In this case, the energy is needed only to amplify theiranalog signals. There is no notion of “direction” in measuring the environment.(ii) Passive, narrow-beam sensors: these sensors are passive and they are concerned about thedirection when sensing the environment.(iii) Active Sensors: these sensors actively probe the environment.Since a sensor node has limited sensing and computation capacities, communication performanceand power, a large number of sensor devices are distributed over an area of interest for collectinginformation (temperature, humidity, motion detection, etc.). These nodes can communicate with eachother for sending or getting information either directly or through other intermediate nodes and thusform a network, so each node in a sensor network acts as a router  inside the network. In directcommunication routing protocols (single hop), each sensor node communicates directly with a controlcenter called Base Station (BS) and sends gathered information. The base station is fixed and locatedfar away from the sensors. Base station(s) can communicate with the end user either directly orthrough some existing wired network. The topology of the sensor network changes very frequently.Nodes may not have global identification. Since the distance between the sensor nodes and basestation in case of direct communication is large, they consume energy quickly. In another approach(multi hop), data is routed via intermediate nodes to the base station and thus saves sending nodeenergy. A routing protocol  is a protocol that specifies how routers (sensor nodes) communicatewith each other, disseminating information that enables them to select routes between any two nodeson the network, the choice of the route being done by routing algorithms. Each router has a prioriknowledge only of the networks attached to it directly. A routing protocol shares this information firstamong immediate neighbors, and then throughout the network. This way, routers gain knowledge ofthe topology of the network. There are mainly two types of routing process: one is static routing andthe other is dynamic routing.Dynamic routing  performs the same function as static routing except it is more robust. Staticrouting allows routing tables in specific routers to be set up in a static manner so network routes forpackets are set. If a router on the route goes down, the destination may become unreachable. DynamicSensors 2010, 10 10508routing allows routing tables in routers to change as the possible routes change. In case of wirelesssensor networks dynamic routing is employed because nodes may frequently change their position anddie at any moment. The advantages and disadvantages of wireless sensor networks can be summarizedas follows:Advantages: Network setups can be done without fixed infrastructure. Ideal for the non-reachable places such as across the sea, mountains, rural areas or deep forests. Flexible if there is ad hoc situation when additional workstation is required. Implementation cost is cheap.Disadvantages: Less secure because hackers can enter the access point and get all the information. Lower speed compared to a wired network. More complex to configure than a wired network. Easily affected by surroundings (walls, microwavea, large distances due to signal attenuation,etc.).A Wireless Sensor Network structure is shown in Figure 1.Figure 1. A wireless sensor network structure.2. Recent WorksMartin Merck , in 2010, in his paper has described function of IceCube installed at South Pole.As per his observation IceCube is the largest Neutrino observatory currently in operations. Located atthe geographical South Pole, the detector modules are deployed up to 2,450 m deep into the Antarcticice. A combination of intelligent sensor modules and a farm of industry standard servers are used tooperate the detector and reduce the data to accommodate the limited connectivity from the South Poleto the northern hemisphere. He has given a detailed description of the technical implementation of thesensor modules, data acquisition system and filtering farm used in the IceCube experiment.Sensors 2010, 10 10509You-Chiun Wang, et al, in March 2010, considered a hybrid wireless sensor network with static andmobile nodes. Static sensors monitor the environment and report events occurring in the sensing field.They scheduled the mobile sensors’ traveling paths in an energy-balanced way so that their overalllifetime could be maximized and they shown that it has been a NP-complete problem. They proposed acentralized and a distributed heuristics to schedule mobile sensors’ traveling paths. Their heuristicsallowed arbitrary numbers of mobile sensors and event locations in each round and had anenergy-balanced concept in mind. The centralized heuristic tries to minimize mobile sensors’ movingenergy while keeping their energy consumption balanced .Kunjan Patel, et al., presented a reliable and lightweight routing protocol for wireless sensornetworks in their paper. They claimed more than 90% savings in number of transmissions compared tothe message flooding scheme when the same route was used to transmit data messages. This savingincreased exponentially as the number of transmissions increased over a same route. The protocoloccupied only 16% of total available RAM and 12% of total program memory in MICAz platformwhich maked it very lightweight to implement in wireless sensor networks .Mohamed Hafeeda and Hossein Ahmadi, 2007, proposed  a new probabilistic coverage protocol(denoted by PCP) that considered probabilistic sensing models. PCP was fairly general and used withdifferent sensing models. In particular, PCP required the computation of a single parameter from theadopted sensing model, while everything else remained same. They showed how this parameter couldbe derived in general, and the calculations for two example sensing models: (i) the probabilisticexponential sensing model, and (ii) the commonly-used deterministic disk sensing model. Theycompared their protocol with two existing protocols and claimed for the better performance as theyproposed.3. ApplicationsThe applications for WSNs involve tracking, monitoring and controlling. WSNs are mainly utilizedfor habitat monitoring, object tracking, nuclear reactor control, fire detection, and traffic monitoring.Area monitoring is a common application of WSNs, in which the WSN is deployed over a region wheresome incident is to be monitored. For example, a large quantity of sensor nodes could be deployed overa battlefield to detect enemy intrusions instead of using landmines. When the sensors detect the eventbeing monitored (heat, pressure, sound, light, electro-magnetic field, vibration, etc.), the event needs tobe reported to one of the base stations, which can than take some appropriate action (e.g., send amessage on the internet or to a satellite). Wireless sensor networks are used extensively within thewater/wastewater industries. Facilities not wired for power or data transmission can be monitored usingindustrial wireless I/O devices and sensor nodes powered by solar panels or battery packs. Wirelesssensor networks can use a range of sensors to detect the presence of vehicles for vehicles detection.Wireless sensor networks are also used to control the temperature and humidity levels insidecommercial greenhouses. When the temperature and humidity drops below specific levels, thegreenhouse manager can be notified via e-mail or a cell phone text message, or host systems can triggermisting systems, open vents, turn on fans, or control a wide variety of system responses. Because somewireless sensor networks are easy to install, they are also easy to move when the needs of theapplication change.Sensors 2010, 10 105104. ClassificationRouting techniques are required for sending data between sensor nodes and the base stations forcommunication. Different routing protocols are proposed for wireless sensor network. These protocolsare classified according to different parameters. Protocols can be classified as proactive, reactive andhybrid, based on their mode of functioning and type of target applications. In a proactive protocol thenodes switch on their sensors and transmitters, sense the environment and transmit the data to a BSthrough the predefined route. The Low Energy Adaptive Clustering hierarchy protocol (LEACH)utilizes this type of protocol . In case of a reactive protocol if there are sudden changes in the sensedattribute beyond some pre-determined threshold value, the nodes immediately react. This type ofprotocol is used in time critical applications. The Threshold sensitive Energy Efficient sensor Network(TEEN)  is an example of a reactive protocol. Hybrid protocols like Adaptive Periodic TEEN(APTEEN) incorporate both proactive and reactive concepts . They first compute all routes and thenimprove the routes at the time of routing. Further, routing protocols can be classified as directcommunication, flat and clustering protocols, according to the participation style of the nodes. In directcommunication protocols, any node can send information to the BS directly. When this is applied in avery large network, the energy of sensor nodes may be drained quickly. Its scalability is very small.SPIN is an example of this type of protocol. In the case of flat protocols, for example Rumor Routing,if any node needs to transmit data, it first searches for a valid route to the BS and then transmits thedata. Nodes around the base station may drain their energy quickly. Its scalability is average.According to the clustering protocol, the total area is divided into numbers of clusters. Each and everycluster has a cluster head (CH) and this cluster head directly communicates with the BS. All nodes in acluster send their data to their corresponding CH (example: TEEN). Furthermore, depending on thenetwork structure, protocols can be classified as hierarchical, data centric and location based.Hierarchical routing (examples: LEACH, TEEN, APTEEN) is used to perform energy efficientrouting, i.e., higher energy nodes can be used to process and send the information; low energy nodesare used to perform the sensing in the area of interest. Data centric protocols are query based and theydepend on the naming of the desired data, thus it eliminates much redundant transmissions. The BSsends queries to a certain area for information and waits for reply from the nodes of that particularregion. Since data is requested through queries, attribute based naming is required to specify theproperties of the data. Depending on the query, sensors collect a particular data from the area ofinterest and this particular information is only required to transmit to the BS and thus reducing thenumber of transmissions.SPIN  was the first data centric protocol. Location based routing protocols  need some locationinformation of the sensor nodes. Location information can be obtained from GPS (Global PositioningSystem) signals, received radio signal strength, etc. Using location information, an optimal path can beformed without using flooding techniques. GEAR is an example of a location based routing protocol.The present review discusses the intricate details of the roles of different routing protocols.Furthermore it provides a comparative analysis between these.Sensors 2010, 10 105115. Sensor Network Architecture and Design IssuesThe main design goal of wireless sensor networks is to transmit data by increasing the lifetime ofthe network and by employing energy efficient routing protocols. Depending on the applications used,different architectures and designs have been applied in sensor networks. Again, the performance of arouting protocol depends on the architecture and design of the network, so the architecture and designof the network is very important features in WSNs. The design of the wireless sensor network isaffected by many challenging factors which must be overcome before an efficient network can beachieved in WSNs. In the following section we try to describe the architectural issues and challengesfor WSNs.Node Distribution: Node distribution  in WSNs is either deterministic or self-organizing andapplication dependant. The uniformity of the node distribution directly affects the performance of therouting protocol used for this network. In the case of deterministic node distribution, the sensor nodesare mutually placed and gathered data is transmitted through pre-determined paths. In the other case,the sensor nodes are spread over the area of interest randomly thus creating an infrastructure in anad hoc manner.Network Dynamicity: Since the nodes in WSNs may be static or dynamic, dynamicity of thenetwork is a challenging issue. Most of the routing protocols assume that the sensor nodes and the basestations are fixed i.e., they are static, but in the case of dynamic BS or nodes routes from one node toanother must be reported periodically within the network so that all nodes can transmit data via thereported route. Again depending on the application, the sensed event can be dynamic or static. Forexample, in target detection/tracking applications, the event is dynamic, whereas forest monitoring forearly fire prevention is an example of a static event. Monitoring static events works in reactive mode.On the other hand, dynamic events work in proactive mode.Energy efficiency: The sensor nodes in WSNs have limited energy and they use their energy forcomputation, communication and sensing, so energy consumption is an important issue in WSNs.According to some routing protocols nodes take part in data fusion and expend more energy. Since thetransmission power is proportional to distance squared, multi-hop routing consumes less energy thandirect communication, but it has some route management overhead. In this regard, directcommunication is efficient. Since most of the times sensor nodes are distributed randomly, multi-hoprouting is preferable. In some applications nodes sense environment periodically and lose more energythan the nodes used in some applications where they sense environment when some event occurs.Data Transmission: Data transmission in WSNs is application specific. It may be continuous orevent driven or query-based or hybrid. In case of continuous data transmission, sensor nodes send datato the base station periodically. In event driven and query-based transmission they send data to thebase station when some event occurs or a specific query is generated by the base station. Hybridtransmission uses a combination of continuous, event driven and query-based transmission, so forarchitecture and design of WSNs data transmission is a very significant issue.Scalability: A WSN consists of hundreds to thousands of sensor nodes. Routing protocols must beworkable with this huge number of nodes i.e., these protocols can be able to handle all of thefunctionalities of the sensor nodes so that the lifetime of the network can be stable.Sensors 2010, 10 10512Data Fusion: Data fusion  is a process of combining of data from different sources according tosome function. This is achieved by signal processing methods. This technique is used by some routingprotocols for energy efficiency and data transfer optimization. Since sensor nodes get data frommultiple nodes, similar packets may be fused generating redundant data. In data fusion or dataaggregation process awareness is needed to avoid this redundant data.6. Existing Routing Protocols6.1. LEACH (Low Energy Adaptive Clustering Hierarchy)LEACH  is a self-organizing, adaptive clustering protocol. It uses randomization for distributingthe energy load among the sensors in the network. The following are the assumptions made in theLEACH protocol:a. All nodes can transmit with enough power to reach the base station.b. Each node has enough computational power to support different MAC protocols.c. Nodes located close to each other have correlated data.According to this protocol, the base station is fixed and located far from the sensor nodes and thenodes are homogeneous and energy constrained. Here, one node called cluster-head (CH) acts as thelocal base station. LEACH randomly rotates the high-energy cluster-head so that the activities areequally shared among the sensors and the sensors consume battery power equally. LEACH alsoperforms data fusion, i.e. compression of data when data is sent from the clusters to the base stationthus reducing energy dissipation and enhancing system lifetime. LEACH divides the total operationinto rounds—each round consisting of two phases: set-up phase and steady phase.In the set-up phase, clusters are formed and a CH is selected for each cluster. The CH is selectedfrom the sensor nodes at a time with a certain probability. Each node generates a random number from0 to 1. If this number is lower than the threshold node [T(n)] then this particular node becomes a CH.T(n) is given as follows:[ mod( 1 )],1( )prppT n nG = 0, otherwisewhere p is the percentage of nodes that are CHs, r is the current round and G is the set of nodes thathave not served as cluster head in the past 1/p rounds.Then the CH allocates time slots to nodes within its cluster. LEACH clustering is shown inFigure 2.In steady state phase, nodes send data to their CH during their allocated time slot using TDMA. Whenthe cluster head gets data from its cluster, it aggregates the data and sends the compressed data to theBS. Since the BS is far away from the CH, it needs high energy for transmitting the data. This affectsonly the nodes which are CHs and that’s why the selection of a CH depends on the remaining energyof that node.Sensors 2010, 10 10513Figure 2. Clustering in LEACH Protocol.6.2. TEEN (Threshold sensitive Energy Efficient sensor Network)TEEN  is a cluster based hierarchical routing protocol based on LEACH. This protocol is usedfor time-critical applications. It has two assumptions : The BS and the sensor nodes have same initial energy The BS can transmit data to all nodes in the network directly.In this protocol, nodes sense the medium continuously, but the data transmission is done lessfrequently. The network consists of simple nodes, first-level cluster heads and second-level clusterheads. TEEN uses LEACH’s strategy to form cluster. First level CHs are formed away from the BSand second level cluster heads are formed near to the BS.A CH sends two types of data to its neighbors—one is the hard threshold (HT) and other is softthreshold (ST). In the hard threshold, the nodes transmit data if the sensed attribute is in the range ofinterest and thus it reduces the number of transmissions. On the other hand, in soft threshold mode, anysmall change in the value of the sensed attribute is transmitted. The nodes sense their environmentcontinuously and store the sensed value for transmission. Thereafter the node transmits the sensedvalue if one of the following conditions satisfied:a. Sensed value > hard threshold (HT).b. Sensed value ~ hard threshold >= soft threshold (ST).TEEN has the following drawbacks: A node may wait for their time slot for data transmission. Again time slot may be wasted if anode has no data for transmission. Cluster heads always wait for data from nodes by keeping its transmitter on.6.3. APTEEN (Adaptive Threshold TEEN)APTEEN  is an improved version of TEEN which has all the features of TEEN. It was developedfor hybrid networks and captures both periodic data collection and reacts to time critical events.APTEEN supports queries like: Historical analysis of past data values A snapshot of the current network view. Persistent monitoring of an event for a period of time.Sensors 2010, 10 10514In each round, after deciding the cluster head, the cluster head broadcasts the following parameters: Attributes (interested physical parameters), Thresholds (hard threshold value and soft threshold value), time schedule (time slot using TDMA) and count time (maximum time period between two successive reports sent by a node).It allows the user to set threshold values and also a count time interval. If a node does not send datafor a time period equal to the count time, it is forced to sense and retransmit the data thus maintainingenergy consumption. Since it is a hybrid protocol, it can emulate a proactive network or a reactivenetwork depending on the count time and threshold value. Figure 3 shows TEEN and APTEEN. It hasthe disadvantage that additional complexity is required to implement the threshold function and counttime features.Figure 3. Hierarchical clustering in TEEN and APTEEN Protocols.6.4. PEGASIS (Power efficient Gathering Sensor Information System)PEGASIS  is a near optimal chain-based power efficient protocol based on LEACH .According to this protocol, all the nodes have information about all other nodes and each has thecapability of transmitting data to the base station directly. PEGASIS assumes that all the sensor nodeshave the same level of energy and they are likely to die at the same time. Since all nodes are immobileand have global knowledge of the network, the chain can be constructed easily by using greedyalgorithm. Chain creation is started at a node far from BS. Each node transmits and receives data fromonly one closest node of its neighbors. To locate the closest neighbor node, each node uses the signalstrength to measure the distance from the neighbors and then adjusts the signal strength so the only onenode cab is heard. Node passes token through the chain to leader from both sides. Each node fuses thereceived data with their own data at the time of constructing the chain. In each round, a randomlychosen node (leader) from the chain will transmit the aggregated data to the BS. Node i (mod N) is theleader in round i. The chain consists of those nodes that are closest to each other and form a path to thebase station. The aggregated data is sent to the base station by the leader.PEGASIS outperforms LEACH by eliminating the overhead of dynamic cluster information,minimizes the sum of distances and limits the number of transmission. Each node requires globalSensors 2010, 10 10515information about the network. This is a drawback of this protocol because at any time it can becollected from the network. PEGASIS is shown in Figure 4.Figure 4. Chaining in PEGASIS.6.5. SPIN (Sensor Protocols for Information via Negotiation)SPIN [16,17] is a family of adaptive protocols that use data negotiation and resource-adaptivealgorithms. SPIN is a data centric routing protocol. It assumes:a. all nodes in the network are base stations.b. nodes in close proximity have similar data.The key idea behind SPIN is to name the data using high-level descriptors or meta-data. Since allnodes can be assumed as base stations all information is broadcasted to each node in the network. Souser can query to any node and can get the information immediately. Nodes in this network use a highlevel name to describe their collected data called meta-data. Figure 5 shows how SPIN works.Figure 5. Data Transmission in SPIN.Before transmission, meta-data are exchanged among sensors nodes (meta-data negotiation) via adata advertisement procedure, thus avoiding transmission of redundant data in the network. Afterreceiving the data each node advertises it to its neighbors and interested neighbors get this data bySensors 2010, 10 10516sending a request message. The format of this meta-data is not specified in SPIN and it depends on theused applications. This meta-data negotiation solves the classic problem of flooding and thus itachieves energy efficiency. SPIN uses three types of messages: ADV, REQ, and DATA forcommunication with each other. ADV is used for adverting new data, REQ is used for requesting fordata and DATA is the actual message. According to this protocol first a node gets some new data andthe node wants to distribute that data throughout the network, so it broadcasts an ADV messagecontaining meta-data. The interested nodes request that data by sending a REQ message and the data issent to the requesting nodes.The neighboring node repeats this process until the entire network gets the new data. The SPINprotocols include many other protocols. The main two protocols are SPIN-1 and SPIN-2. These twoprotocols incorporate negotiation before transmitting data so that only useful information will betransferred. Each node has its own resource manager that keeps track of resource consumption. TheSPIN-1 protocol is a 3-stage protocol, as described above. SPIN-2 is an extension of SPIN-1, whichincorporates threshold-based resource awareness mechanism in addition to negotiation. When energyin the nodes is abundant, SPIN-2 communicates using the 3-stage protocol of SPIN-1.One of the advantages of SPIN is that topological changes are localized since each node only needsto know its single-hop neighbors. SPIN provides much more energy savings than flooding andmeta-data negotiation almost halves the redundant data. However, SPINs data advertisementmechanism cannot guarantee the delivery of data. To see this, consider the application of intrusiondetection where data should be reliably reported over periodic intervals and assume that nodesinterested in the data are located far away from the source node and the nodes between source anddestination nodes are not interested in that data, such data will not be delivered to the destination at all.6.6. DD (Directed Diffusion)Directed diffusion [17,18] is a data-centric (DC) and application-aware protocol in which datagenerated by sensor nodes is named by attribute-value pairs. It consists of four elements:  interests,data messages, gradients and reinforcements. An interest (a list of attribute value pairs) describes atask. Data messages are named using attribute value pairs. A gradient specifies data rate as well as thedirection of event and reinforcement selects a particular path from a number of paths. In the DCprotocol data coming from different sources are combined and thus eliminating redundancy,minimizing the number of transmissions, saving network energy and prolonging its lifetime. DCrouting searches for a destination from multiple sources. In directed diffusion, a base station diffuses aquery towards nodes in the interested region. The query or interest is diffused through the networkhop-by-hop. Each sensor receives the interest and sets up a gradient toward the sensor nodes fromwhich it receives the interest. This process continues until gradients are set up from the sources back tothe BS. The sensed data are then returned to the BS along that reverse path. The intermediate nodesmay aggregate their data depending on the data message (data’s name and attribute value pair) thusreducing the communication cost. Since in this case data transmission is not reliable the BSperiodically refreshes and resends the interest when it starts to receive data from the source(s).Directed Diffusion protocols are application specific and hence can save energy by selecting optimalpaths by caching and processing data in the network. It has some drawbacks . First of all, for dataSensors 2010, 10 10517aggregation it needs time synchronization technique that is not very easy to achieve in WSNs. Anotherproblem is associated with the overhead involved in recording information thus increasing the cost of asensor node. The DD Protocol is described in Figure 6.Figure 6. Directed Diffusion Protocol.6.7. Rumor RoutingRumor routing [19,20] is a kind of directed diffusion and is used for applications where geographicrouting is not feasible. It combines query flooding and event flooding protocols in a random way. Ithas the following assumptions: The network is composed of densely distributed nodes. Only bi-directional links exits. Only short distance transmissions are allowed. It has fixed infrastructure.In case of directed diffusion flooding is used to inject the query to the entire network. Sometimesthe requested data from the nodes are very small and thus the flooding is unnecessary, so we can useanother approach which is to flood the events when the number of events is small and the number ofqueries is large. The queries are rooted to that particular nodes that are belongs to the interested region.In order to flood events through the network, the rumor routing algorithm employs long-lived packets,called agents. When a node detects an event, it adds such event to its local table (events table), andgenerates an agent. Agents travel the network on a random path with related event information. Thenthe visited nodes form a gradient towards the event. When a node needs to initiate a query, it routes thequery to the initial source. If it gets some nodes lying on the gradient before its TTL expires, it will berouted to the event, else the node may need to retransmit, give up or flood the query. Unlike directeddiffusion, where data can be routed through multiple paths at low rates, Rumor routing only maintainsone path between source and destination. Rumor routing performs well only when the number ofevents is small. For a large number of events, the cost of maintaining agents and event-tables in eachnode becomes infeasible if there is not enough interest in these events from the BS. Moreover, theSensors 2010, 10 10518overhead associated with rumor routing is controlled by different parameters used in the algorithmsuch as time-to-live (TTL) pertaining to queries and agents.6.8. Geographic and Energy-Aware Routing (GEAR)Location based routing protocols for sensor network need location information of all the sensornodes to calculate the distance between any two nodes. GEAR [17,21] is a location based routingprotocol which uses GIS (Geographical Information System) to find the location of sensor nodes in thenetwork. According to this protocol, each node stores two types of cost of reaching the destination:estimated cost and learning cost. The estimated cost is a combination of residual energy  anddistance to destination. The learned cost is a modified estimated cost and it accounts the routingaround holes in the network. When a node does not have any closure neighbours towards the targetregion, a hole occurs. In case where no holes exit, the estimated cost is equal to the learned cost. TheGEAR protocol only considers a certain region rather than sending the interests to the whole networkas happens in Directed Diffusion  and thus restricting the number of interests. There are twophases in this protocol:Phase-I: In this phase, packets are forwarded towards the target region. After receiving a packet, anode searches for a neighbor which is closer to the target region then itself. The neighbor is thenselected as the next hop. If there are more than one suitable nodes then there exists a hole and in thiscase one node is picked to forward the packet based on the learning cost function.Phase-II: In this phase, the packets are forwarded within the region. If the packet reaches the region,it is diffused in that region by either recursive geographic forwarding or restricted flooding. If thesensors are not densely deployed, then restricted flooding is used and if the node density is high, thengeographic flooding is used. In geographic flooding, the region is divided into four sub regions andfour copies of the packet are created. This process continues until the regions with only one node areleft.6.9. Geographic Adaptive Fidelity (GAF)GAF is an energy efficient location-based routing protocol. This protocol was initially conceivedfor mobile ad hoc networks, but it can also be applied to sensor networks. GAF can be implementedboth for non-mobile and mobile nodes. Although GAF is a location based protocol, it may also beimplemented as a hierarchical protocol where the clusters are based on geographic location.Initially the area of interest is split into some fixed zones forming a virtual grid for the covered area.Nodes in each zone have different functionalities and each node uses its GPS-indicated location toassociate itself with a point in the grid. Nodes which are positioned at the same point on the grid areconsidered equivalent in terms of the cost of packet routing. Such equivalence is exploited in keepingsome nodes located in a particular grid area in a sleeping state in order to save energy. Thus GAF canincrease the network lifetime as the number of nodes increases. GAF conserves energy by turning offunnecessary nodes in the network without affecting the level of routing fidelity. GAF defines threestates: discovery, active, sleep. The ‘discovery’ state is used for determining the neighbors in the grid;the ‘active’ state participates in routing process and at the time of ‘sleep’ state, the radio is turned off.In order to handle the mobility, each node in the grid estimates it’s leaving time of grid and sends thisSensors 2010, 10 10519to its neighbors. The sleeping neighbors adjust their sleeping time accordingly in order to keep therouting fidelity. Before the leaving time of the active node expires, sleeping nodes wake up and one ofthem becomes active.7. Comparative StudyNow we compare the above mentioned routing protocols according to their performance dependingon different parameters. Table 1 shows the comparison.Table 1. Comparison of different routing protocols. ProtocolsMobilityPowermanagementNetworklifetimeScalabilityResourceawarenessClassificationDataaggregationQuerybasedMultipathLEACHFixed BSMaximumVery goodGoodYesClusteringNoNoNoTEENFixed BSMaximumVery goodGoodYesReactive/ClusteringYesNoNoAPTEENFixed BSMaximumVery goodGoodYesHybridYesNoNoPEGASISFixed BSMaximumVery goodGoodYesReactive/ClusteringYesNoNoSPINSupportedLimitedGoodLimitedYesProactive/flatYesYesYesDDLimitedLimitedGoodLimitedYesProactive/flatYesYesYesRRVery limitedNot supportVery goodGoodYesHybrid/ flatYesYesNoGEARLimitedLimitedGoodLimitedYesLocationNoNoNoGAFLimitedLimitedGoodLimitedYesLocationNoNoNo BS: Base StationLEACH, TEEN, APTEEN and PEGASIS have similar features and their architectures are to someextent similar. They have fixed infrastructure. LEACH, TEEN, APTEEN are cluster based routingprotocols, whereas PEGASIS is a chain-based protocol. The performance of APTEEN lies betweenTEEN and LEACH with respect to energy consumption and longevity of the network . TEEN onlytransmits time-critical data, while APTEEN performs periodic data transmissions. In this respectAPTEEN is also better than LEACH because APTEEN transmits data based on a threshold valuewhereas LEACH transmits data continuously. Again PEGASIS avoids the formation of clusteringoverhead of LEACH, but it requires dynamic topology adjustment since sensor energy is not tracked.PEGASIS introduces excessive delay for distant nodes on the chain. The single leader can become abottleneck in PEGASIS. PEGASIS increases network lifetime two-fold compared to the LEACHprotocol.In directed diffusion the base station sends queries to sensor nodes by the flooding technique but inSPIN the sensor nodes advertise the availability of data so that interested nodes can query that data. InDirected diffusion each node can communicate with its neighbors, so it does not need the total networkinformation, but SPIN maintains a global network topology. SPIN halves the redundant data incomparison to flooding. Since SPIN cannot guarantee data delivery, it is not suitable for applicationsthat need reliable data delivery.SPIN, directed diffusion and rumor routing use meta-data whereas the other protocols don’t use it.Since they are flat routing protocols routes are formed in regions that have data for transmission, butfor the others, as they are hierarchical routing methods they form clusters throughout the network. Incase of hierarchical routing energy dissipation is uniform and it can’t be controlled; but in the case ofSensors 2010, 10 10520flat routing energy dissipation depends on the traffic pattern. For the previous case data aggregation isdone by cluster heads but in the later case, nodes on multi-hop path aggregates incoming data fromneighbours. GEAR limits the number of interests in Directed Diffusion by considering only a certainregion rather than sending the interests to the whole network. GEAR thus complements DirectedDiffusion and conserves more energy. According to simulation results , GAF performs at least aswell as a normal ad hoc routing protocol in terms of latency and packet loss and increases the lifetimeof the network by saving energy. Since the sensor networks are application specific, we can’t say aparticular protocol is better than other.8. ConclusionsThe past few years have witnessed a lot of attention on routing for wireless sensor networks andintroduced unique challenges compared to traditional data routing in wired networks. Routing insensor networks is a new area of research. Since sensor networks are designed for specificapplications, designing efficient routing protocols for sensor networks is very important. In our work,first we have gone through a comprehensive survey of routing techniques in wireless sensor networks.The routing techniques are classified as proactive, reactive and hybrid, based on their mode offunctioning and type of target applications. Further, these are classified as direct communication, flatand clustering protocols, according to the participating style of nodes. Again depending on the networkstructure, these are categorized as hierarchical, data centric and location based. In this document wehave discussed eight routing protocols and their comprehensive survey in Section 2. These eightprotocols are LEACH, TEEN, APTEEN, PEGASIS, SPIN, DD, RR and GEAR. Since the sensornetworks are application specific, we can’t say any particular protocol is better than other. We cancompare these protocols with respect to some parameters only. Future perspectives of this work arefocused towards modifying one of the above routing protocols such that the modified protocol couldminimize more energy for the entire system.References1. Lewis, F.L. Wireless Sensor Networks. Automation and Robotics Research Institute, TheUniversity of Texas at Arlington: Ft. Worth, Texas, USA, 2004; pp. 1-18.2. Younis, M.; Youssef, M.; Arisha, K. Energy-aware routing in cluster-based sensor networks. InProceedings of the 10th IEEE/ACM International Symposium on Modeling, Analysis andSimulation of Computer and Telecommunication Systems (MASCOTS2002), Fort Worth, TX,USA, October 2002.3. Schurgers, C.; Srivastava, M.B. Energy efficient routing in wireless sensor networks. In TheMILCOM Proceedings on Communications for Network-Centric Operations: Creating theInformation Force, McLean, VA, USA, 2001.4. Shah, R.; Rabaey, J. Energy aware routing for low energy ad hoc sensor networks. In Proceedingsof the IEEE Wireless Communications and Networking Conference (WCNC), Orlando, FL, USA,March 2002.5. Rodoplu, V.; Meng, T.H. Minimum energy mobile wireless networks. IEEE J. Sel. Area Commun.1999, 17, 133344.Sensors 2010, 10 105216. Li, L.; Halpern, J.Y. Minimum-energy mobile wireless networks revisited. IEEE Int. Conf.Commun. 2001, 1, 278-283.7. Heinzelman, W.; Chandrakasan, A.; Balakrishnan, H. Energy–efficient communication protocolfor wireless microsensor networks. In Proceedings of the 33rd Annual Hawaii InternationalConference on System Sciences(HICSS), Big Island, HI, USA, January 2000; pp. 3005-3014,8. Manjeswar, A.; Agrawal, D.P. TEEN: A protocol for enhanced efficiency in wireless sensornetworks. In Proceedings of 1st International Workshop on Parallel and Distributed ComputingIssues in Wireless Networks and Mobile Computing, San Francisco, CA, USA, 2001; p. 189.9. Manjeswar, A.; Agrawal, D.P. APTEEN: A hybrid protocol for efficient routing andcomprehensive information retrieval in wireless sensor networks. In Proceedings of 2ndInternational Workshop on Parallel and Distributed Computing Issues in Wireless Networks andMobile Computing, Fort Lauderdale, FL, USA, April 15–19, 2002; pp. 195-202.10. Kulik, J.; Rabiner, W.; Balakrishnan, H. Adaptive protocols for information dissemination inwireless sensor networks. In Proceedings of the 5th Annual ACM/IEEE International Conferenceon Mobile Computing and Networking (MobiCom_99), Seattle, WA, USA, August 1999.11. Barati, H.; Movaghar, A.; Barati, A.; Azizi Mazresh, A. A review of coverage and routing forwireless sensor networks. World Acad. Sci. Eng. Tech. 2008, 37, 296-302.12. Goodman, D. Wireless Personal Communications Systems; Addison-Wesley: Reading, MA, USA,1997.13. Heinzelman, W.B. Application-Specific Protocol Architectures for Wireless Networks. PhD.thesis, Massachusetts Institute of Technology. Cambridge, MA, USA, June 2000.14. Jiang, Q.F.; Manivannan, D. Routing protocols for sensor networks. In Proceedings of Conferenceon Consumer Communications and Networking, Las Vegas, NV, USA, January 5–8, 2004;pp. 93-98.15. Lindsey, S.; Raghavendra, C.S. PEGASIS: Power Efficient gathering in sensor informationsystems. In Proceedings of IEEE Aerospace Conference, Big Sky, MT, USA, March 2002.16. Martorosyan, A.; Boukerche, A.; Nelem Pazzi, R.W. A taxonomy of cluster-based routingprotocols for wireless sensor networks. In International Symposium on Parallel Architectures,Algorithms, and Networks, Sydney, NSW, Australia, May 7–9, 2008; pp. 247-253.17. Jamal, N.; E. Kamal, A.-K.A. Routing techniques in wireless sensor networks: A survey. IEEEWirel. Commun. 2004, 11, 6-28.18. Intanagonwiwat, C.; Govindan, R.; Estrin, D. Directed difusion: A scalable and robustcommunication paradigm for sensor networks. In Proceedings of ACM MobiCom’ 00, Boston,MA, USA, 2000; pp. 56-67.19. Braginsky, D.; Estrin, D. Rumor routing algorithm for sensor networks. In Proceedings of theFirst Workshop on Sensor Networks and Applications (WSNA), Atlanta, GA, USA, October 2002.20. Akkaya, K.; Younis, M. A survey on routing protocols for wireless sensor networks. J. Ad HocNetw. 2005, 3, 325-349.21. Y. Yu, Estrin, D.; Govindan, R. Geographical and Energy Aware Routing: A Recursive DataDissemination Protocol for Wireless Sensor Networks. UCLA Computer Science DepartmentTechnical Report, UCLA-CSD TR-01-0023. UCLA: Los Angeles, CA, USA, May 2001.Sensors 2010, 10 1052222. Capkun, S.; Hamdi, M.; Hubaux, J. GPS-free positioning in mobile ad-hoc networks. InProceedings of the 34th Annual Hawaii International Conference on System Sciences,Maui, HI, USA, January 3–6, 2001; pp. 3481-3490.23. Li, Q.; Aslam, J.; Rus, D. Hierarchical power-aware routing in sensor networks. In Proceedings ofthe DIMACS Workshop on Pervasive Networking, DIMACS Center, Rutgers University:Piscataway, NJ, USA, May 21, 2001.24. Chang, J.-H.; Tassiulas, L. Maximum lifetime routing in wireless sensor networks. In Proceedingsof Advanced Telecommunications and Information Distribution Research Program (ATIRP2000),College Park, MD, USA, March 2000.25. Rahul, C.; Rabaey, J. Energy aware routing for low energy ad hoc sensor networks. InProceedings of IEEE Wireless Communications and Networking Conference (WCNC), Orlando,FL, USA, March, 2002; pp. 350-355.26. Bandyopadhyay, S.; Coyle, E. An energy efficient hierarchical clustering algorithm for wirelesssensor networks. In Proceedings of Infocom 2003, San Francisco, CA, USA, March 30–April 3,2003; Volume 3, pp. 1713-1723.27. Karp, B.; Kung, H.T. GPSR: Greedy perimeter stateless routing for wireless sensor networks. InProceedings of the 6th Annual ACM/IEEE International Conference on Mobile Computing andNetworking, Boston, MA, USA, August 2000.28. Rappaport, T.S. Wireless Communication; Prentice-Hall: Bergen County, NJ, USA, 199629. Sohrabi, K.; Gao, J.; Ailawadhi, V.; Pottie, C.J. Protocols for self-organization of a wirelesssensor network. IEEE Personal Commun. 2000, 7950, 16-17.30. Scott K.; Bambos, N. Routing and Channel Assignment for Low Power Transmission in PCS. In5th IEEE International Conference on Universal Personal Communications, Cambridge, MA,USA, September 9–October 2, 1996; Volume 2, pp. 498-502,31. Meng T.; Volkan, R. Distributed network protocols for wireless communication. In InternationalSymposium on Circuits and Systems, Monterey, CA, USA, May 31–June 3, 1998; Volume 4, pp.600-603.32. Loren, P.C.; Pottieb, G.J.; Jonathan, R.A. Self-organizing distributed sensor networks. In SPIEConference on Unattended Ground Sensor Technologies and Applications, Orlando, FL, USA,April 1999; pp. 229-237.33. The Network Simulator—ns-2. Available online: http://www.isi.edu/nsnam/ns/ (accessed on 5November 2010).34. Park, V.; Corson, S. A highly adaptive distributed routing algorithm for mobile wireless netowrks.In Proceedings of IEEE International Conference on Computer Communications, Kobe, Japan,April 7–12, 1997; Volume 3, pp. 1405-1413.35. Raman, S.; Mccanne, S. Scalable data naming for application level framing in reliable multicast.In Proceedings of the Sixth ACM International Conference on Multimedia, ACM Multimedia:Bristol, UK, September 13–16, 1998.36. Merck, M. The icecube detector: A large sensor network at the south pole. IEEE Pervasive Comput.2010, 9, 43-47.37. Wang, Y.-C.; Peng, W.-C.; Tseng, Y.-C. Energy-balanced dispatch of mobile sensors in a hybridwireless sensor network. IEEE Trans. Parallel Distrib. Syst. 2010, 21, 1836-1850.Sensors 2010, 10 1052338. Patel, K.; Chern, L.J.; Bleakley, C.J.; Vanderbauwhede, W. MAW: A reliable lightweightmulti-hop wireless sensor network routing protocol. In Proceedings of International Conferenceon Computational Science and Engineering, Vancouver, BC, Canada, August 29–31, 2009;Volume 2, pp. 487-493.39. Hafeeda, M.; Ahmadi, H. A probabilistic coverage protocol for wireless sensor networks.ICNP-2007; Beijing, China, October 16–19, 2007; pp. 41-50.© 2010 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access articledistributed under the terms and conditions of the Creative Commons Attribution license(http://creativecommons.org/licenses/by/3.0/).
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