IJRIT International Journal of Research in Information Technology, Volume 3, Issue 4, April 2015, Pg. 134-149

International Journal of Research in Information Technology (IJRIT) www.ijrit.com

ISSN 2001-5569

An Energy Aware Tree based Routing (EATR) in Zigbee Wireless Sensor Network (ZWSN) for Efficient Multimedia Transmission Kavita Malav

Deepak Gupta

M.Tech Scholer,Gov Engg College(Ajmer)

Asst. Professor,Gov.Engg. College(Ajmer)

[email protected]

[email protected]

Abstract—The development of wireless sensor networks can be originally indorsed by military applications such as battlefield surveillance and now used in many civilian application expanses. The IEEE 802.15.4 protocol is anintensifying standard for WSN applications because it pays precise consideration to energy efficiency and communication overheads. Among the existing topologies, even though cluster-tree network is effective for WSNs within multimedia applications, the topology suffers from restricted routing and prevents the use of many potential routing paths, which means, only a considerable amount of bandwidth is utilized efficiently in total bandwidth and rest is kept idle. This paper proposed an energy efficient cluster based routing scheme for zigbee WSN for proper utilization of network resources. Proposed work use different energy criteria for route selection in ZWSN. Performance are measured in terms of network lifetime, throughput, end-to-end delay etc. and outperform the traditional approaches. Keywords: Zigbee Standard, IEEE 802.15.4 protocol, Wireless sensor network, Energy efficient routing, On-tree Selfpruning Rebroadcast. I.

INTRODUCTION

Wireless

Sensor Network (WSN) is usually deployed with a great number of sensor nodes to cover a large range of area to monitor events, collect data from environment, etc. The data collected by sensor nodes is usually transmitted to sink nodes, which are gateways to outside world, for further processing by a multi-hop network. Node failures and relocations should not hinder the successful transmission of data to the sinks. Consequently, WSN needs to be capable of adapting to changes in network topology caused by node failures, relocations and so on. Initially, research interest is focused on single sink WSN [1] and [2]. However, scalability of single sink WSN is not good enough to satisfy the demand of transmitting data from a large number of nodes to a single sink. As the number of nodes increases, network congestion due to hot spot phenomenon will be so severe that transmission cannot continue. Recently, interest is changed toward to multi-sink WSN [3]-[5]. In a multi-sink WSN, the mean number of hops between nodes and sinks can be reduced remarkably; network congestion can be relieved by using appropriate routing method to balance traffic load among the sinks evenly. ZigBee is a specification of high level communication protocols built on top of IEEE 802.15.4 standard. Because of its low cost low power consumption properties and ability to support mesh network topology, ZigBee is an ideal technology for implementation of WSN. ZigBee [6] is a wireless “standard” of ZigBee alliance based on IEEE 802.15.4 standard [7] for Personal Area Networks. It defines the network and application layers on the top of physical and data link layers normalized in IEEE 802.15.4. ZigBee stack offers a wireless communication solution coupled with low cost, low energy consumption characteristics. It can be used in consumer electronics, industrial controls, PC peripherals, toys and games, etc. However, one of the potential applications of this standard is in Wireless Sensor Networks (WSN). In fact, IEEE 802.15.4 is designed to achieve a very low power consumption through several optimizations in Physical layer and Medium Access Control (MAC) sub-layer like the use

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IJRIT International Journal of Research in Information Technology, Volume 3, Issue 4, April 2015, Pg. 52-56

of low duty cycles. The network layer uses a modified AODV (Ad Hoc on Demand Distance Vector) by default and Hierarchical Tree Routing (HTR) as last resort. WSN have focused on Quality of Service (QoS) support to improve the reliability and performance under severe energy constraints. The improvement of QoS can be tackled in any layer. For instance several research work has been carried out on improving real time support in MAC sub-layer using GTS (Guaranteed Time Slot) mechanism of IEEE 802.15.4 [8]. This improves only real time QoS in single hop networks. In network layer, which provides end to end real time QoS in multi hop networks, this is done by adding and improving the QoS support to the routing algorithm. However, before doing that we need to analyze the performance of the existing routing algorithms. It is clear that our aim in long term is to provide real time support in ZigBee Routing Protocol (ZRP). A. Background of ZigBee The ZigBee specification identifies three kinds of devices that incorporate ZigBee radios, with all three found in a typical ZigBee network: · A coordinator, which organizes the network and maintains routing table. · Routers, which can also have the routing capacity for maintaining routes and talk to all kinds of devices. · End devices, which can talk to routers and the coordinator, but not to each other. The ZigBee mesh routing adopts the well-studied public domain algorithm AODV [9]. As AODV is a pure on-demand protocol, route discovery is based on a route request and route reply query cycle. Route discovery begins when a source node desires to send data to some destination. As shown in Figure 1, the source node first broadcasts a route request (RREQ) packet to its neighbours. When a node receives the RREQ, it then checks whether it has an unexpired route to the destination node. If not, it creates a route entry and a route discovery entry. The information stored in the route entry includes destination address, status, and next-hop address. Next, the route discovery entry contains Route Request ID, Source Address, SenderAddress, Forward Cost, Residual Cost, and ExpirationTime. The Route Request ID is incremented for every RREQ the node initiates, and together with the source address, uniquely identifies a RREQ.

Figure. 1: Basic routing discovery Along with its own sequence number and the Route Request ID, the source node includes in the RREQ the most recent sequence number it has for the destination. In order to respond to the RREQ, the node must be the destination itself. If neither of this condition is met, the node rebroadcasts the RREQ. The latest ZigBee specification, officially named ZigBee 2012, offers full wireless mesh networking capable of supporting more than 64,000 devices on a single network. It’s designed to connect the widest range of devices, in any industry, into a single control network. ZigBee supports the largest number of interoperable standards including ZigBee Building Automation, ZigBee Health Care, ZigBee Home Automation, ZigBee Light Link, ZigBee Smart Energy, ZigBee Telecom Services, and the forthcoming ZigBee Retail Services. Desirable properties of a router are as follows: • Correctness and simplicity: The packets are to be correctly delivered. Simpler the routing algorithm, it is better. • Robustness: Ability of the network to deliver packets via some route even in the face of failures. • Stability: The algorithm should converge to equilibrium fast in the face of changing conditions in the network. • Fairness and optimality: obvious requirements, but conflicting. • Efficiency: Minimum overhead B. Classification of wireless sensor networks In this subdivision a simple classification of the sensor networks based on their mode of the functioning & the type of target application is obtainable.

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· Proactive networks · Reactive networks · Hybrid networks C. The · · · · · · · · ·

Applications of wireless sensor network using ZigBee ZigBee Alliance developed the following application profiles: Smart energy Commercial building automation Industrial control and monitoring Military Surveillance Home automation Personal, home, and hospital care (PHHC) Environmental Remote Sensing Remote control for consumer electronics Industrial process monitoring and control

D. Routing Procedure ZigBee Cluster Label Routing Protocol-To simplify our study, we make the following assumptions in this paper. • A Coordinator and Routers are constantly turned on for relaying data packets. • End devices do not have routing capacity. Hence, they cannot relay data packets. • A link between neighbour nodes is symmetry. • Network topology is static without any movement. Taking into account their procedures, routing protocols can be roughly classified according to the following criteria. Hierarchy Role of Nodes in the Network In the flat schemes, all sensor nodes participate with the same role in the routing procedures. On the other hand, the hierarchical routing protocols classify sensor nodes according to their functionalities [13]. The network is then divided into groups or clusters. A leader or a cluster head is selected in the group to coordinate the activities within the cluster and to communicate with nodes outside the own cluster. The differentiation of nodes can be static or dynamic. Data Delivery Model Depending on the application, data gathering and interaction in wireless sensor networks could be accomplished on several ways. The data delivery model indicates the flow of information between the sensor nodes and the sink [12]. The data delivery models are divided into the following classes: continuous, event-driven, and query-driven or hybrid. II. RELATED WORK In 1981, Baker and Ephremides proposed a clustering algorithms called “Linked cluster algorithm (LCA)” [19] for wireless networks. To improve network manageability, channel proficiency & energy economy of MANETS, Clustering algorithms have been examined in the previous. Lin and Gerla investigated actual methods to sustenance multimedia applications in the common multi-hop mobile ad-hoc networks using CDMA based medium arbitration in [20]. Random competition based clustering (RCC) [21] is related both to mobile ad hoc networks & WSN. RCC generally attentions at cluster constancy in order to support mobile nodes. The RCC algorithm relates the First Declaration Wins rule, in which any node can “govern” the rest of the nodes in its radio coverage if it is the first to claim being a CH. Some of well-known clustering algorithms for mobile ad hoc networks offered in the works are Cluster Gateway Switch Routing Protocol (CGSR) [22], Cluster-Based Routing Protocol (CBRP) [23], Weighted Clustering Algorithm (WCA) [24]. A review of clustering algorithms for mobile ad hoc networks has been discussed in [25]. In recent years, insect sensory organizations have been inspiring to new communications & calculating models like bio inspired routing. It is due to their capability to provision characteristics like autonomous, & self-organized adaptive

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IJRIT International Journal of Research in Information Technology, Volume 3, Issue 4, April 2015, Pg. 52-56

communication schemes for pervasive surroundings like WSN & mobile ad hoc networks. Biological synchronization occurrences have unlimited potential to allow circulated & scalable synchronization algorithms for WSN [26]. The first MANET routing algorithm in the document to take motivation from ants are Ant-Colony Based Routing Algorithm (ARA) [27], AntNet [28], AntHocNet [29] etc. In [30], an energy efficient & delay-aware routing algorithm is projected based on ant-colonybased algorithms. In [31], a bio-inspired accessible network organization protocol for large scale sensor networks is projected, which is encouraged by the simple organization strategies in biological phenomena such as flashing fireflies & spiking of neurons. A biologically encouraged circulated organization algorithm presented in [32] is based on a mathematical model. It clarifies how neurons & fireflies spontaneously synchronize. In [33], the principles of genetics & development are accepted to allow service-oriented, autonomous, & self-adaptive communication systems for universal surroundings such as WSN& mobile ad hoc networks. In [34], effectual bio-inspired communication example for WSN is projected based on the feedback loop apparatus established by motivation from the principles of cell biology. In [35], a clustering algorithm based on biological quorum sensing mechanism is stated. It helps the sensor nodes to form clusters conferring to spatial features of the experimental event signal. QoS is the capability of a network component (e.g. an application, host or router) to have certain level of declaration that its traffic & service supplies can be gratified. QoS manages bandwidth according to application demands & network management surroundings. QoS has been widely studied in wireless LANs & wired computer networks. A complete outline of the state of the field of QoS in networking was delivered by Chen in his thesis in 1999 [36]. Chakrabarti and Mishra [37] summarized the important QoS-related subjects in MANETs & the future work that required more attention is delivered in [38]. In 2004, Al-Karaki and Kamal [39] offered a full overview about the state of & the expansion trends in the arena of QoS. It characterized routing into the following categories of several methods: flat (all nodes play an equivalent role), hierarchical (some nodes are local cluster heads for instance), position based (consume position information), & power-aware (take battery usage & residual charge into consideration) QoS routing. Lastly, a complete overview of the added extensively established MAC & routing solutions for providing better QoS was offered in [40, 41]. III.

THE PROPOSED WORK

In this section we describe our model of a zigbee wireless sensor network with nodes heterogeneous in their initial amount of energy. We particularly present the setting, the energy model, and how the optimal number of clusters can be computed. Let us assume the case where a percentage of the population of sensor nodes within zigbee WSN is equipped with more energy resources than the rest of the nodes. Let ݉ be the fraction of the total number of nodes ݊, which is equipped with α times more energy than the others. We refer to these powerful nodes as advanced nodes, and the rest (1-m) ×n as normal nodes. We assume that all nodes are distributed uniformly over the wireless field. 1. Clustering Hierarchy We consider a zigbee wireless network that is hierarchically clustered. Our proposed algorithm maintains such clustering hierarchy. In our protocol, the clusters are re-established in each “round.” New cluster heads are elected in each round and as a result the load is well distributed and balanced among the nodes of the network. Moreover each node transmits to the closest cluster head so as to split the communication cost to the sink (which is tens of times greater than the processing and operation cost.)

Figure 2: Sensor Node placement in network environment (for 50 sensors placed randomly in the field of 10000 meter square area)

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IJRIT International Journal of Research in Information Technology, Volume 3, Issue 4, April 2015, Pg. 52-56

After the initialization and setup phase completed, the transmission phase is starts, in this phase, initially we calculate and update the energy values of every device and it will update at every transmission round. First thing to start a transmission round is the selection of cluster head, we defined a criteria based on certain energy values to select a node as cluster head, and the node will be selected as a cluster head only if it has a proper energy values to continue the round as cluster head. In the selection of cluster head a probability distribution is used based on probabilistic clustering, here classification of such devices is based on energy parameters like residual energy, initial energy, average energy, and the total energy. The considered network parameters are shown in table below. TABLE I. PARAMETER SETTINGS OF THE FIRST-ORDER RADIO MODEL

After the selection of cluster head, a cluster region created around the particular cluster head, and nodes belong to that region is labelled as cluster members. In transmission phase, The Cluster members transmits their data to cluster head and cluster head transmit the collected data to the destination directly, with every data packets transmission, a signature is added with the data packets sent, this complex signature will try degrading the network efficiency but it’s the network design and routing which decreases the effect of authentication algorithm on routing performance. The Clustering and routing procedure continues till the network devices alive, the devices with a proper energy levels are selected as cluster head one after another every round. After every transmission round, device’s residual energy is calculated with the radio energy model for zigbee wireless communication network, this helps us in deciding a cluster head node to continue transmission in the next transmission round. In case of research work in zigbee wireless network, system efficiency can be calculated from the relation of input and output data packets. Hence the throughput, end to end delay, packet delivery fraction ratio, and network lifetime are the best suited parameters to show research efficiency. Algorithm I Network Initialization // A random zigbee WSN Field created and nodes are randomly placed, every node contains a specified amount of energy Setup Phase // Bisection between nodes through random model, and path-cost calculated through distance vector estimation Transmission phase ‫ݎ݋ܨ‬1: 1: ‫ݏ݀݊ݑ݋ݎ݊݋݅ݏݏ݅݉ݏ݊ܽݎݐ݉ݑ݉݅ݔܽܯ‬ Update Average Energy with respect to rounds, ‫( × ݐܧ‬ Check for Dead Criteria at every Start Up ‫ = ݅ݎ݋ܨ‬1: ݊ Check Nodes & Update Flags Update Dead & Alive Statistics End ‫ = ݅ݎ݋ܨ‬1: ݊ If Ea>0 (means checking if there’s maximum round reaches)

1−

௥ ோ௠௔௫

݊

)

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IJRIT International Journal of Research in Information Technology, Volume 3, Issue 4, April 2015, Pg. 52-56 Calculate probability of selection of Cluster Head ௉×௡×௖௨௥௥௘௡௧௘௡௘௥௚௬௫௧௢௧௔௟௘௡௘௥௚௬

P (i) =

௜௡௜௧௜௔௟௘௡௘௥௚௬௫௔௩௘௥௔௚௘௘௡௘௥௚௬

Here, ܲ is calculate through the genetic algorithm, based upon the optimum solution of our algorithm ‫)݅(ܵ(݂ܫ‬. ‫ > ܧ‬0) Temp= a temporary random number allotted to every node If temp<= ܶሺ‫ݏ‬௜ ሻ ௉

೔ ݂݅ ∈ ‫ܩ‬ భ Where, ܶሺ‫ݏ‬௜ ሻ = ൝ଵି௉೔ ൬௥௠௢ௗು೔ ൰ 0‫ݐ݋‬ℎ݁‫݁ݏ݅ݓݎ‬ Update Packet Counter as per selection as the set up phase completed Update Clusters Counter as per Sub-Destination Selection (We denote the methodology as cluster based because we first select a cluster head based on energy level and then assuming the region around it as a cluster and the selected sub-destination will be the head of that cluster) Update the selected node number value as an id number for cluster region formed Update Cluster Area (The Cluster Area is the area between the selected cluster head and the base station based on distance Vector calculated between them, and the devices between these Regions are called as cluster member) Data Transmission from Selected Cluster head based on Distance Vector Calculated ݈‫ܧ‬ௗ௘௖ + ݈ߝ௙௫݀ଶ , ݀ < ݀଴ ܵሺ݅ሻ. ‫ = ܧ‬ቊ ݈‫ܧ‬ௗ௘௖ + ݈ߝ௙௫݀ସ , ݀ ≥ ݀଴ Update Residual Energy for the selected cluster head from the formula above (All the Nodes & Future Cluster heads are not active during this time or we can say that they are in sleep mode) End End End

Residual energy can be calculated by radio energy model, the probability formula is based on certain energy values and zigbee cluster tree based structure, that’s why the selection of head nodes is optimum and we get an optimum results from the proposed approach, also the network design is such that, the delay produce in transmitting the data packets also decreases. 4.

ZigBee on-tree self-pruning Approach

An on-tree self-pruning broadcast algorithm for ZigBee networks is presented in this section. Upon reception of a broadcast packet, a node decides whether to rebroadcast or not. Basically, after a source broadcasts a packet, all its 1-hop neighbors receive it. If they all rebroadcast the packet at the same time, catastrophic packet collisions may happen and delay the whole process of broadcast. To avoid collisions, every forward node waits for a random period of time before rebroadcasting. During this waiting period, a node v may receive the duplicated broadcast packet from another node u. So node v only needs to cover ܰ(‫)ݑ(ܰ –)ݒ‬, provided v knows 1-hop neighbors ܰ(‫ )ݑ‬of node u. If node v learns that all its 1-hop neighbors have already been covered before time out, it does not need to rebroadcast. For a general ad hoc network, one issue with the above self-pruning algorithm is that the 2-hop neighbour information is assumed available to node v. When this assumption does not hold, node v can only know that the source node u of a duplicate packet has been covered so that v still need to cover ܰ(‫ݑ –)ݒ‬. Node v can be self-pruned only if it has received the broadcast packet from all its 1-hop neighbors in ܰ(‫)ݒ‬, which does not happen with a high probability during a short waiting period, especially when ܰ(‫ )ݒ‬is very large. As a result, the self-pruning broadcast algorithm would perform poorly when applied to ZigBee networks where the 2-hop neighbour information is not available. On the other hand, by exploiting the tree structure of ZigBee address space, a node can find addresses of a partial list of 2-hop neighbours without introducing any communication or storage overhead. In other words, given the address of a 1-hop neighbour in ܰ(‫ )ݒ‬and its number of children, one can determine the addresses of all its tree neighbours in ܶܰ(ܰ(‫))ݒ‬. Text gives the On-tree Self-pruning Rebroadcast (OSR) algorithm when a node v receives a broadcast packet from node u. The localized OSR algorithm actually guarantees that the whole network will be covered, as proven by Theorem 1. Algorithm 2. When every node in a ZigBee network runs the OSR algorithm, a broadcast packet from any source can reach all the other nodes, provided the network is physically connected.

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IJRIT International Journal of Research in Information Technology, Volume 3, Issue 4, April 2015, Pg. 52-56

_______________________________________________ On-tree Self-pruning Rebroadcast (OSR) Input: receiving node v and broadcasting node u Output: none ifit is the first time to receive a broadcast packet, Set an on-tree to-be-covered set: ܶܵ = ܶܰ(‫)ݑ(ܰܶ –)ݒ‬ if TS = Ø, Drop the packet. else Buffer the packet and record its broadcast ID. Start a timer with random timeout. end if else ifthe early copy of this packet is waiting, Update ܶܵ = ܶܵ– ܶܰ(‫)ݑ‬ if TS = Ø, Drop the packet and stop the timer. end if else Drop the duplicated broadcast packet. end if end if if the timer expires broadcast the packet. end if

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IV.

RESULTS & DISCUSSION

This work is apply Method in a simulated zigbee based Sensor Monitoring Field of Area 100×100 m. However one can change the field area as per the result variations. Also, the base Station or data fusion center is placed at the Centre of Zigbee based Wireless Field initially, however we can change the Position of base Station. Results are compared with the base work denoted by [107] in this paper. Initially the dissipated energy is Zero & residual energy is the Amount of initial energy in a Node, Hence Total energy ‫ܧ‬௧ also the Amount of residual energy because it is the sum of dissipated & residual energy. Simulations are carried out in MATLAB R2013b (Version 8.2.0.703) ‫ܮ‬. ‫ܧ‬௘௟௘௖ + ‫ܮ‬. ∈௙௦ . ݀ ଶ ݂݅݀ ≤ ݀଴ ‫்ܧ‬ଶ ሺ݈, ݀ሻ = ቊ ቋ ‫ܮ‬. ‫ܧ‬௘௟௘௖ + ‫ܮ‬. ∈௠௣. ݀ ସ ݂݅݀ > ݀଴ Here ‫ܧ‬௘௟௘௖ is energy debauched per bit to run the transmitter or the receiver circuit, ∈௙௦ &∈௠௣ rest on the transmitter amplifier model we employs, and d is the distance between the sender and receiver. By equating the two expressions at d = d0, we have݀଴ = ඥ∈௙௦ /∈௠௣. To receive an L-bit message the radio expends‫ܧ‬ோ௫ = ‫ܮ‬. ‫ܧ‬௘௟௘௖ . The performance of the protocols are tested using two setups: Setup 1: A 100x100 m of randomly dispersed homogeneous nodes, each with 0.5 J of energy and the BS located at the centre of the network system. Setup 2: A 100x100 m of randomly dispersed heterogeneous nodes with the initial energies varying between 0.5 J to 2.25 J and BS located at the centre of the network system. To be fair, the total energy of the system for each protocol are ensured to be the same; we use a total energy of 102.5 J. After starting a round, firstly it checks if there is a dead node in the ZIBEE BASED WSN Field, and repeats these criteria after every round. Election of Cluster Heads for member nodes and a cluster head node are done in different loops which depend on the Election Probability used. After a Cluster Head sent its Data to Sink, Energy dissipated is calculated, through energy models considered in the propose work, in order to calculate how much energy dissipated after a steady state and whether a Cluster head is eligible to transmit data in the next round too. This Energy thoroughly depends upon the distance between BS and CH for CH, and Member node to CH for Member node. The 100 Nodes are placed in the randomly manner in the whole field, the number of clusters directly depends upon the number of cluster head. A single cluster head is assigned to clusters which act as a sub-destination and route data from other cluster member nodes to the destination (Sink or Base Station).

Figure 5: Network view of ZigBee wireless network designed. The network is created in the field area of 10,000 square meters. In figure above, 100 nodes deployed in network based on random distribution (shown with red circle). The base station is placed at the centre of field area (shown in green square). However, its position can be change for experimental purpose in order to test the robustness of proposed scheme. Node distance between the cells The distance vector calculation is a very important process while developing a communication protocol for ZigBee wireless network, as energy is directly dependent to distance, so it is necessary for a system to calculate the distance between all devices

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with each other. Let assume that the node position in the cell is(x୬, y୬ ). It can be defined the distance between nodeiand the other node (xୡ , yୡ ) as: D[୧] = ඥ(xୡ − x୬ )ଶ + (yୡ − y୬)ଶ 100 90 80 70 60 50 40 30 20 10 0

0

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Figure 6: Figure above shows the open view of ZigBee wireless network designed. The network is created in the field area of 10000 square meters. In figure above, 100 nodes deployed in network based on random distribution. Here, blue circle shows the base station is placed at the centre of field area shown by a cross sign. However, its position can be change for experimental purpose in order to test the robustness of proposed scheme. The red circles shows the coverage area of different cluster heads randomly between some communication periods, this snap is taken at an instant and its change regularly with every instant and every round. We know a simple relation: For all‫ => ܦ‬0, ‫ܦ‬ଶ>= ‫ܦ‬ଶଵ + ‫ܦ‬ଶଶ Where, ‫ܦ = ܦ‬1 + ‫ܦ‬2 Since, energy consumed in transmitting a signal to distance is D is proportional to the square of distance transmitted. We can easily concede that for the same set of parameters and targets, network equipped with Direct Communication protocol will run out of energy faster than rest of the types of networks. Because for a long range transmission sensor located far from base station will die very soon in order to send signals to the base station. So this kind of network is not efficient in a remote wide area.

Figure 7: Shows the distance vector calculation between different Sensor (within ZigBee based WSN) devices. This distance information is very useful for data communication based on distance in case of energy saving schemes.

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IJRIT International Journal of Research in Information Technology, Volume 3, Issue 4, April 2015, Pg. 52-56 5

5

x 10

4.5

y(Throughput of network (bits))

4 3.5 3 2.5 Proposed Protocol Energy Efficient Zigbee mechanism [107] LEACH based Routing

2 1.5 1 0.5 0

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4000 5000 6000 7000 x(Number of Rounds)

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Figure 8: The graph above shows a comparative view of obtained network throughput from both the proposed scheme and the LEACH and Energy Efficient Scheme [107]. The throughput obtained with respect to number of rounds or communication period. It is measured in terms of bits/second. Although, the base station received the data in terms of packets. A single packet consist of 8 bit of data. Above experiment are done for 100 Sensor (within ZigBee based WSN) nodes in the field area. It is clear from the figure[107] that,SasiNagarajan, in proposed “Energy approach Efficient a throughput Zigbee Cluster-Tree of approximately Wireless Sensor 479000 Network bits Using is calculated Modified Distributed which much Algorithm”, higher International on Communication and Signal Processing, than the approach proposed by Conference LEACH and Energy Efficient Scheme [107].April 3-5, 2014, India. Throughput of receiving bits: It is the ratio of the total number of successful packets in bits received at the sink or base station in a specified amount of time.  ൌ ෍ ‘—–‘ˆ‘—–‹‰ƒ…‡–•”‡…‹‡˜‡†ƒ––Š‡„ƒ•‡•–ƒ–‹‘ Proposed Protocol Energy Efficient Zigbee mechanism [107] LEACH based Routing

0.45

y(End to End Delay in network)

0.4 0.35 0.3 0.25 0.2 0.15 0.1 0.05 0

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Figure 9: The graph obtained shows a comparative view of end to end delay measured at the base station or delay introduced by the routing scheme in delivering data packets to the base station from both the proposed scheme and the LEACH and Energy Efficient Scheme [107]. The End-to-end delay obtained with respect to number of rounds or communication period. It is measured in terms of milliseconds. Above experiment are done for 100 Sensor (within ZigBee based WSN) nodes in the field area. It is clear from the figure that, in proposed approach the end-to-end delay is much lower and about 0.022 which is lower than the approach proposed by LEACH and Energy Efficient Scheme [107]. End-to-End Delay: It is the delay that could be caused by buffering during route discovery, queuing delays at interface queues, retransmission delays at the media, and propagation and transfer times.  ൌ

—””‡–”ƒ•‹••‹‘’‡”‹‘† ‘–ƒŽ—„‡”‘ˆƒ–ƒƒ…‡–•‡…‹‡˜‡†

In Proposed model, a Node will becomes Cluster Head, if a Temporary number (between 0 to 1) assigned to it is less than the Probability Structure Below,

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IJRIT International Journal of Research in Information Technology, Volume 3, Issue 4, April 2015, Pg. 52-56

ܲ௜ ܶሺ‫ݏ‬௜ ሻ ൌ ൞ͳ െ ܲ௜ ቀ‫ ݀݋݉ݎ‬ଵ ቁ

݂݅ ‫ܩ א‬

௉೔

Ͳ‫݁ݏ݅ݓݎ݄݁ݐ݋‬ Here, Pi is come out from New Expression for Optimum Probability P (i), Pi is the optimum probability for the selection of heads, developed in proposed methodology. After a higher weight node becomes Cluster Head, Energy Models are applied to calculate the Amount of Energy Spent by it on that Particular Round and complete the round of steady state phase. ݈‫ܧ‬ௗ௘௖ ൅ ݈ߝ௙௫ ݀ ଶ ǡ ݀ ൏ ݀଴ ‫்ܧ‬௑ ሺ݈ǡ ݀ሻ ൌ ቊ ݈‫ܧ‬ௗ௘௖ ൅ ݈ߝ௙௫ ݀ ସ ǡ ݀ ൒ ݀଴ When this dissipated energy is subtracted from the initial energy, then the amount of energy remain is called residual energy. When a node residual energy is zero then the node is called dead and is terminated from the network environment. Hence, only the nodes with higher weight amongst the other nodes can fulfil the criteria above and hence a node can transmit data as a cluster head for a longer period which results in increment of network lifetime and throughput. After a higher weight node becomes Cluster Head, Energy Models are applied to calculate the Amount of Energy Spent by it on that Particular Round and complete the round of steady state phase. When a node residual energy is zero then the node is called dead and is terminated from the network environment. The statistics of dead nodes with respect to transmission rounds is shown in figure below: 100

y(Lifetime of Zigbee Wireless Network)

90 80 70 60 50 40 30 20

Proposed Protocol Energy Efficient Zigbee mechanism [107] LEACH based Routing

10 0

0

1000

2000

3000

4000 5000 6000 x(Number of Rounds)

7000

8000

9000

10000

Figure 10: Figure above shows a comparative view of death of Sensor (within ZigBee based WSN) nodes with each round for both the proposed scheme and the LEACHand Energy Efficient Scheme [107]. Node dead statistics are obtained with respect to number of rounds or communication period. Above experiment are done for 100 Sensor (within ZigBee based WSN) nodes in the field area. Result is taken when the base station is placed at the centre of Sensor (within ZigBee based WSN) field and the selection probability is defined through the energy values considered. It is clear from the figure that both the network lifetime [107] of SasiNagarajan, Efficient Zigbee Cluster-Tree WirelessAlso, SensoritNetwork Using Modified Distributed Algorithm”, and stability of lifetime network is“Energy achieved through proposed protocol. was observed that the technique network International Conference on Communication and Signal Processing, April 3-5, 2014, India. proposed in LEACH and Energy Efficient Scheme [107] completely stopped functioning at an earlier simulation rounds compared to our proposed technique. We saw that the functional capacity for LEACH and Energy Efficient Scheme [107] created network lasted till an estimated value of ~1300 and ~4900 rounds of simulation, while the functional capacity of the proposed approach lasted till an estimated value of ~5900 rounds of simulation.

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IJRIT International Journal of Research in Information Technology, Volume 3, Issue 4, April 2015, Pg. 52-56

y(Lifetime of Zigbee Wireless Network)

25

20

15

10

Proposed Protocol Energy Efficient Zigbee mechanism [107] LEACH based Routing

5

0

0

1000

2000

3000

4000 5000 6000 x(Number of Rounds)

7000

8000

9000

10000

Figure 11: Figure above shows a comparative view of death of sensor nodes with each round for both the proposed scheme and LEACH and Energy Efficient Scheme [42] schemes. Node dead statistics are obtained with respect to number of rounds or communication period. Above experiment are done for 25 Sensor (within ZigBee based WSN) nodes in the field area. TABLE II: MEAN AND VARIANCE OF RESIDUAL ENERGY IN BOTH THE PROPOSED METHOD AND THE TRADITIONAL [107] METHOD

Range (J)

Mean residual energy (J)

Variance residual energy (J)

Proposed

98.5569

43.9161

38.5569

[107]

29.7538

13.1419

11.7406

TABLE III. COMPARISONS OF NETWORK LIFETIMES (NUMBER OF ROUNDS)

TABLE IV. COMPARISONS OF NETWORK THROUGHPUT (BITS)

The deployed ZigBee routers represent the clusters that cover different sensing regions. We assume that the deepest cluster covers the region of interest that yields additional information suddenly. The region of interest has a traffic load with a mean that ranges from 4-8 packets per second, while the remaining areas have a light average traffic load of 0.01 packets per second. The packet interarrival times follow an exponential distribution. In the proposed adoptive-parent-based framework,

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multiple adoptive parents can be associated with a router. However, in the experiment, each ancestor router of the cluster of interest only associates with one additional adoptive parent.

Figure 12:Networking of 2,000 FFDs randomly deployed in a circular area. As a result, we can observe the performance improvement over the original approach conservatively. In the performance evaluation, we analyze the throughput and transmission latency of the packets generated in the region of interest. Specifically, the throughput metric used in the experiments is normalized as a fraction of the achieved throughput over the ideal throughput (i.e., without any packet loss). Fig. 12 depicts a snap shot of node connection when the two networking schemes are applied to a WSN comprising 2,000 FFD nodes, where red dot denotes the network coordinator, blue dots denote the routers, purple dots denote the end devices, and orange colored dots denote the orphan nodes which fail to join the network. It can be seen that the conventional protocol makes node connection biased, yielding 433 orphan nodes. On the other hand, the proposed scheme yields no orphan node, significantly improving the node connectivity. [107] SasiNagarajan, “Energy Efficient Zigbee Cluster-Tree Wireless Sensor Network Using Modified Distributed Algorithm”, International Conference on Communication and Signal Processing, April 3-5, 2014, India.

V.

CONCLUSION AND DISCUSSION

Wireless sensor networks are conceived to monitor a certain application or physical phenomena and are supposed to function for several years without any human intervention for maintenance. Thus, the main issue in sensor networks is often to extend the lifetime of the network by reducing energy consumption. When the network topology does not change very often, a clustering technique can be used to manage the network activity. Some applications have high priority traffic that needs to be transferred with bounded end-to-end delay. The IEEE 802.15.4 standard defines a MAC protocol that saves energy by putting nodes periodically in sleep mode. The ZigBee protocol defines a hierarchical addressing mechanism by creating cluster-tree based on regrouping the star topology of the IEEE 802.15.4 standard. This paper work deal with energy constraints to select a head route in zigbee tree based architecture. The result section conclude that and also here results shows that, this protocol successfully extends the stable region to more than 2000 rounds by being aware of heterogeneity through assigning probabilities of cluster-head election weighted by the relative initial energy of nodes, also the lifetime of network extended to more than 4500 rounds in this protocol. The protocol defines a genetic algorithm and energy based criteria for the selection of cluster heads in cluster based communication. The results clearly show that, the network lifetime and the stability period in terms of more nodes to stay alive (for additional number of rounds) and in terms of reduced energy consumption, our proposed protocol is better than the compared protocol [107]. It also provides reduced delay in transmitting packets to the network towards the destination which, makes it a feasible protocol for the networks where there is no room for huge delay. VI.

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