Particle Swarm Based Resource Optimized Geographic Routing for Improved Network Lifetime in MANET

C, Nallusamy; Sabari, A.

doi:10.1007/s11036-017-0911-0

Cited by 13 publications

(10 citation statements)

References 15 publications

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“…Because the performance of the P2R2 method [19] is affected by the node's mobility. Moreover, the energy consumption of AODV-BBO methodology is 452.43J for 250 nodes, it is less when compared to the PS-ROGR [20]. The reason behind the lesser delay and energy consumption of AODV-BBO methodology is the BBO route optimization in AODV.…”

Section: Comparative Analysismentioning

confidence: 99%

“…There are three parameters such as channel capacity, link quality and residual energy of the nodes used to select the nodes in the multi-hop path. Moreover, these parameters are used to avoid the route failure [20] presented the Particle Swarm based Resource Optimized Geographic Routing (PS-ROGR) technique to prolong the network lifetime. The local best position is used to control the particle's (i.e.…”

Section: Literature Surveymentioning

confidence: 99%

“…The efficiency of the AODV-BBO methodology is evaluated by comparing this AODV-BBO methodology with existing methods namely P2R2 method [19] and PS-ROGR technique [20]. Table 2 and Table 3 shows the comparison of AODV-BBO methodology with P2R2 method [19] and PS-ROGR technique [20] respectively. The comparison is made in terms of end to end delay and energy consumption.…”

Section: Comparative Analysismentioning

confidence: 99%

“…The Table 2 shows the end to end delay comparison of the AODV-BBO methodology with P2R2 method [19]. Additionally, the Table 3 shows the energy consumption comparison for PS-ROGR [20] and AODV-BBO methodology. The performance of the Table 2 is taken when the mobility is 20m/s.…”

Section: Comparative Analysismentioning

confidence: 99%

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Delay Aware Routing Protocol Using Optimized AODV with BBO for MPLSMANET

Jayaramu¹,

Banga²

2020

IJIES

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Mobile Ad Hoc Network (MANET) is a wireless network that does not have any fixed structure. MANET is a collection of independent mobile nodes that can communicate with each other through radio waves. In conventional Internet Protocol (IP) forwarding, each router creates forwarding decision on the basis of IP header information. The router has to analyse the packet and routing table at each hop to take the decision for data transmission. Since, inappropriate decisions in data transmission causes delay in packet delivery. This can be overcome with the help of a special feature of Multiprotocol Label Switching (MPLS) called Label switching. MPLS is a switching mechanism that plays a good role in routing, switching and forwarding using small labels. The MPLS is integrated into MANET to improve network performance. In this paper, an effective routing strategy is introduced to reduce the transmission time between routers during the data transmission. Here the Ad Hoc On-Demand Distance Vector (AODV) with Biogeography Based Optimization (BBO) based routing method is used to identify the optimal route among the routers of the MPLS based MANET. The proposed methodology is named as AODV-BBO. Three different objective functions are considered in this routing strategy viz., residual energy, distance and number of hops. Moreover, the rerouting is performed when the node or link failure occurs in the network. This rerouting is used to overcome the packet drop through the MPLS based MANET. The performance of AODV-BBO methodology is analysed in terms of percentage of alive nodes, dead nodes, energy consumption, end to end delay and bandwidth. The performance of the AODV-BBO methodology is compared with two existing methods P2R2 and PS-ROGR. Result showed that, the energy consumption of the AODV-BBO methodology with 400 nodes is 536.52 J, which is less compared to the PS-ROGR method.

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Section: Comparative Analysismentioning

confidence: 99%

Section: Literature Surveymentioning

confidence: 99%

Section: Comparative Analysismentioning

confidence: 99%

Section: Comparative Analysismentioning

confidence: 99%

See 2 more Smart Citations

Delay Aware Routing Protocol Using Optimized AODV with BBO for MPLSMANET

Jayaramu¹,

Banga²

2020

IJIES

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“…For routing the data to the destination, the Noureddine et al 25 proposed a greedy and contention-based forwarding approach without any prior information regarding the end-to-end route. To enrich the network lifetime and resource optimization in MANET, the Nallusamy and Sabari 26 proposed an efficient particle swarm-based resource optimized geographic routing (PS-ROGR) approach. However, energy-efficient routing is not certainly guaranteed.…”

Section: Related Workmentioning

confidence: 99%

Geographic routing with hybrid firefly algorithm and galactic swarm optimization for efficient ‘void’ handling in mobile ad hoc networks

Kaliyamurthi

Anandhakumar

2020

Int J Communication

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Summary Geographic routing in mobile ad hoc network (MANET) has gained much attention even though it fails to find a route when a node meets a void zone (hole). Therefore, an efficient approach is required to avoid the void issues and to effectively transfer the data packets if a path is available between the source and destination nodes. For such, a hybrid evolutionary algorithm is introduced with geographical routing protocol (GRP) for avoiding the void, which selects the shortest route for routing from the source to the destination by combining firefly (FF) algorithm and galactic swarm optimization (HFFGSO). This proposed algorithm exploits the strengths of both the FF algorithm and galactic swarm mechanisms. In this paper, the cross‐layer design approach is implemented, which contains data link and network layer. The proposed hybrid FFGSO‐GRP algorithm improves the routing process within these layers. The implementation process for this proposed technique is carried out in NS2 simulator. From the simulation results, it is observed that our hybrid protocol when compared with the existing approaches proves its significance in terms of packet delivery ratio (PDR), delay, throughput, energy efficiency, power consumption, routing overhead and hop count.

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Optimal Cluster Head Selection Using Vortex Search Algorithm with Deep Learning-Based Multipath Routing in MANET

Venkatasubramanian¹

2022

IoT Based Control Networks and Intelligent Systems

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Particle Swarm Based Resource Optimized Geographic Routing for Improved Network Lifetime in MANET

Cited by 13 publications

References 15 publications

Delay Aware Routing Protocol Using Optimized AODV with BBO for MPLSMANET

Delay Aware Routing Protocol Using Optimized AODV with BBO for MPLSMANET

Geographic routing with hybrid firefly algorithm and galactic swarm optimization for efficient ‘void’ handling in mobile ad hoc networks

Optimal Cluster Head Selection Using Vortex Search Algorithm with Deep Learning-Based Multipath Routing in MANET

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