# Implementation of Energy Efficient Adaptive Load Balancing Algorithm by Rainbow Mechanism in Wireless Sensor Networks

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4 Fig 2.ALBA handshake. B. Rainbow mechanism with ALBA: Rainbow mechanism used by ALBA to handles the connectivity holes. To avoid the dead ends the nodes are forward the packet away from the destination but when the relay is chosen towards the sink this cannot find in the ALBA mechanism. The Rainbow mechanism is used to search the relay in the direction of the sink or in the opposite direction. In this mechanism every node is labelled by a color and this color is chosen by an order in the list. To find the relay among the nodes is searched based on its own color or the color is immediately before in the list. Hence color of each node is able to route towards the sink is shown in figure 3. Fig 3.The F and F C region. Let t be a busy node in packet forwarding, the transmission area of t is divided into F and F C regions. The F and F C region as the neighbors to offer the positive and negative advancement towards the sink. The t node wants to transmit the packet, it seeks a relay in positive or negative advancement based on colorsc n, and it is selected from the set of colors {C 0, C 1, C 2, C 3, C 4.}. The nodes with even colors C 0, C 2.. Search for neighbors in F region and the nodes with odd colors C 1, C 3 search for neighbors in F C region. Nodes with the colorc n, n 0 it chose the relay only for nodes with colorc n or C n+1, if the node with colorc n, n>0 it can only takes the color C n-1 or C n. In this mechanism initially all the nodes are colored as C 0 to perform the greedy forwarding. The nodes at the boundary holes it cannot find the relay to offer the positive advancement after the fixed number of N hsk consecutive failed attempts. Hence the node may be a dead end, it correspondingly increase their color to C 1. According to the Rainbow concept the C 1 node sends the packet away from the destination by searching for C 0 or C 1 nodes in F C region. If the node C 1 cannot find the C 0 or C 1 in F C region it changes the color to C 2 after the N hsk failed attempts. Therefore node C 2 searching C 2 or C 1 the relay in F region. Similarly node C 2 cannot find C 2 or C 1 relay in F it turns to C 3 and it start searching for C 3 or C 2 node in F C. This process continues until it reaches to their final color. At this point the any node has color C 0 it can find the greedy to route to the destination. The nodes which finally reach to the C 0 node the routing performed based on the ALBA greedy forwarding. Fig 4.Rainbow mechanism. Copyright to IJIRCCE DOI: /ijircce

5 The figure 4 shows that the numbers in the node indicates the color is assumed. Higher colors are shown by darker shade. This mechanism is performed in finite time and it is loop freedom of route determining at the dead end. C. EALBA-R Protocol. The EALBA-R protocol is a cross-layer solution for convergecasting in wireless sensor network. In this protocol packet forwarding takes place between awake/asleep schedules with a fixed duty cycle d. In the case of packet transmission if busy node occurs, it uses the Rainbow coloring mechanism to perform the routing. This EALBA-R is designed by using the concept of ALBA-R. The source node sends the RTS (Request to send) packet to the destination, the transmission takes place via user defined intermediate node address and it calculates how much energy consumed by each intermediate nodes that is called sending energy. After receiving RTS message sink node replies with CTS (clear to send) through the user defined intermediate nodes to the sender and it calculates how much energy consumed by each intermediate nodes, it is called as receiving energy. The sender finally calculates the total energy of user defined intermediate nodes. i.e. (sending energy + receiving energy). The energy calculation of each node is calculated by using the formula After calculating total energy consumed by user defined intermediate node, which node consumes less energy among user defined intermediate nodes, that path is established. Finally source node transmits data packet to the sink node using best path and it is acknowledged. The energy calculation of each node is calculated by using this formula. Where, E TXe = The energy needed by the transmitter. (3) E TXa (r) = The energy required to cover the transmission range r. Fig 5.The source node sending RTS and CTS packet through three intermediate nodes. Fig 6.Transmission of data packet source to destination using EALBA-R. Figure 5 explains performance of EALBAR protocol. Here node 4 is assumed as source node and node 19 is assumed as destination. The node 20, 3 and 12th are user defined nodes, first source node sending the RTS packet to the destination and source node receives the CTS packet from destination through the 20, 3 and 12th node. After receiving CTS message the energy calculation has done. The 3rd node is chosen as intermediate node for transmission of data from source to the destination because, the 3rd node consumes less energy based on energy calculation is explained by figure 6 In the figure straight line indicates transmission of data is on progress and dotted line indicates that there is no transmission in the network. An EALBA-R protocol is designed by using NS2.33 simulator. The simulated results shows that when compared to ALBA-R, EALBA-R protocol is requires less time to transmission of packet from source to sink node. The performance metrics achieves better performance in packet delivery ratio, energy consumption and end to end latency. An EALBA-R achieves better performance when compared to IRIS and GeRaF protocol. Copyright to IJIRCCE DOI: /ijircce

6 IV. SIMULATION RESULTS A. ALBA-R versus GeRaf and IRIS. The GeRaf protocol is the first cross layer protocols for geographic greedy forwarding. The other protocol is IRIS these perform as same as ALBA based on hop count metric and local cost function. But this GeRaf and IRIS protocol fails to achieve the performance in PDR, per packet energy consumption and end to end latency. The ALBA-R protocol achieves the best performance in the per packet energy consumption and end to end latency. The ALBA-R protocol achieves the best performance in per packet energy consumption, latency and packet delivery ratio. It gives the best performance in the increasing traffic and it is much better than other two protocols, because it uses the QPI based selection scheme for balancing the traffic among relays. Fig 8a.energy consumption for ALBA-R versus GeRaF and IRIS. Figure 8a explains packet per energy consumption for ALBA-R versus GeRaf and IRIS metrics. The IRIS protocol consumes more energy when increasing the packet per second. These simulated result shows that GeRaF and IRIS fails to achieve the per packet energy consumption when increase in load intensity per second. Fig 8b.Packet delivery ratio for ALBA-R versus GeRaF and IRIS. Figure 8b explains ALBAR achieves better performance in packet delivery ratio, when compared to the GeRaf and IRIS protocols. The packet delivery ratio for ALBAR when λ=4 packets per second it gives 98% of the packet transmitted successfully when compared to IRIS and GeRaF. But IRIS and GeRaF fails to achieve packet delivery ratio when increase in the load intensity. When increase in the load intensity GeRaF results worst performance when compared to the IRIS and ALBAR. GeRaF does not transmit packets from source to sink node successfully. Copyright to IJIRCCE DOI: /ijircce

7 Fig 8c. End to end latency for ALBA-R versus GeRaF and IRIS. An ALBAR and GeRaF protocol result requires less time to transmit packet from source to sink node, when increase in the load intensity. The IRIS protocol requires more time to transfer packet from source to sink node, it is explained by figure 8c. B. EALBA-R versus ALBA-R. The simulated graphs for EALBA-R versus ALBA-R. Both the protocol achieves good performance in energy consumption. These two protocols require less energy to transfer the packet from source to the destination. The comparison between enhanced ALBA-R with ALBA-R protocol. The enhanced ALBA-R achieves better performance in packet delivery ratio when compared to the ALBAR when increase in the load intensity (λ). The end to end latency explains that the EALBAR requires less to time to transfer the data packet from source to sink node when increase in the load intensity per second. But when compared to EALBAR the ALBAR protocol requires more time to transmission of packet from source to sink node. Fig 9a.Energy consumption for EALBA-R versus ALBA-R. Figure 6.9a explains the energy consumption of Enhanced ALBA-R versus ALBAR protocol. Both enhanced ALBA-R and ALBA-R protocol requires less energy to transmit data from source to destination. Copyright to IJIRCCE DOI: /ijircce

8 Fig 9b.Packet delivery ratio for EALBA-R versus ALBA-R. The above figure 6.9b shows that the comparison between ALBA-R with ALBA-R protocol. The enhanced ALBA-R and ALBA-R protocol both achieves better performance in packet delivery ratio when increase in the load intensity (λ). Fig 9c. End to end latency for EALBA-R versus ALBA-R. Figure 9c shows that end-to-end latency comparison graphs for EALBA-R and ALBA-R. This graph explains that the EALBA-R requires less to time to transfer the data packet from source to sink node when increase in the load intensity per second when compared to ALBA-R protocol. V. CONCLUSION AND FUTURE WORK. Our simulation result gives ALBA-R protocol achieves the end to end latency and packet delivery ratio when compared to the IRIS and GeRaf protocol and it gives the better performance when increase in the load intensity. An Enhanced ALBA-R (EALBA-R) protocol is requires less time to transfer packet from source to destination when compared to ALBA-R protocol. Hence Enhanced ALBA-R is better than ALBA-R protocol. Further, the Enhanced ALBA-R protocol is needed to be designed for real-time applications and test in the presence of localization errors. Enhanced ALBA-R can be extended for mobile nodes and investigation must require based on packet delivery ratio, energy consumption and end to end latency. REFERENCES 1. P. CASARI, M. NATI, C. PETRIOLI, AND M. ZORZI, EFFICIENT NON-PLANAR ROUTING AROUND DEAD ENDS IN SPARSE TOPOLOGIES USING RANDOM FORWARDING, PROC. IEEE INT L CONF. COMM. (ICC 07), PP , JUNE FEBA ELIZABETH ABRAHAM AND KAVITHA MARGRET, SURVEY ON EFFICIENT ROUTING METHODS VIA GEOGRAPHICAL ROUTING WITH CONNECTIVITY HOLES IN WSNS, IJCST, VOL.2, ISSUE 5, SEP-OCT M. Zorzi, A New Contention-Based MAC Protocol for Geographic Forwarding in Ad Hoc and Sensor Networks, Proc. IEEE Int l Conf. Comm. (ICC 04), vol. 6, pp , June A. Camillo `, M. Nati, C. Petrioli, M. Rossi, and M. Zorzi, IRIS: Integrated Data Gathering and Interest Dissemination System for Wireless Sensor Networks, Ad Hoc Networks, Special Issue on Cross-Layer Design in Ad Hoc and Sensor Networks, vol. 11, no. 2, pp , Mar Copyright to IJIRCCE DOI: /ijircce

9 5. Chiara Petrioli, ALBA-R: Load-Balancing Geographic Routing Around Connectivity Holes in Wireless Sensor Networks, IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS, VOL. 25, NO. 3, MARCH SEADA, K., HELMY, A., AND GOVINDAN, R. On the effect of localization errors on geographic face routing in sensor networks. In Proceedings of the 3rd IEEE/ACM International Symposiumon Information Processing in Sensor Networks, IPSN 2004 (Berkeley, CA, Apr. 2004). 7. Stojmenovic, Position Based Routing in Ad Hoc Networks, IEEE Comm. Magazine, vol. 40, no. 7, pp , July Y.-J. Kim, R. Govindan, B. Karp, and S. Shenker, Geographic Routing Made Practical, Proc. Second Conf. Symp. Networked Systems Design and Implementation (NSDI 05), vol. 2, pp , May BIOGRAPHY GOWTHAMI.V.R., 4th Semester, M.Tech, Communication system, Department of Electronics and Communication, New Horizon College of Engineering, Outer Ring Road, Marathalli, Bengaluru, India. DIVYA SHARMA., Assistant Professor, Project Guide, Department of Electronics and Communication, New Horizon College of Engineering, Outer Ring Road, Marathalli, Bengaluru, India. Copyright to IJIRCCE DOI: /ijircce

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