Hybrid Algorithm for Efficient node and Path in Opportunistic IoT Network

Document Type : Special Issue: Big Data Analytics and Management in Internet of Things.

Authors

1 Department of Computer Science and Engineering, University Visvesvaraya College of Engineering, Bangalore.

2 Department of Computer Science and Engineering, University Visvesvaraya College of Engineering,

Abstract

Opportunistic networks in the Internet of Things (IoT) scenario, also known as OppIoT, espouse IoT devices interactions opportunistically in order to improve connectivity, the lifetime of the network, and network reliability. An increase in opportunistic utilization is fostered by IoT applications to find communication opportunities whenever possible to route and deliver data efficiently. In this opportunistic scenario, devising an efficient path for data delivery is a challenging work due to uncertainty in the connection between the nodes and the selection of intermediate forwarder nodes for data delivery towards the destination. Considering the scenario of uncertainty in device location and exploiting IoT devices opportunistically, this paper propounds a routing algorithm for OppIoT called Hybrid Multi-Copy Routing Algorithm (HMCRA). The proposed algorithm finds potential forwarder nodes by using fuzzy logic wherein residual energy, distance, and speed of the nodes are considered as input values while preparing fuzzy rules. Genetic Algorithm (GA) is considered along with fuzzy logic to select an efficient path for data delivery. In GA, the delay is taken as the fitness function to select a reliable path for data delivery. Simulation results of the proposed algorithm perform well in contrast with relative existing routing algorithms with respect to latency, overhead ratio, delivery probability, and hop count. The work uniqueness lies in the selection of potential nodes and finding path having less hop count in an opportunistic IoT network scenario.

Keywords

References

Fixed, V. G. (2016). Mobile Internet Traffic Forecasts. URL: https://www. cisco. com/c/en/us/solutions/service-provider/visualnetworking-index-vni/index. html, 328.
Ippisch, A., Sati, S., &Graffi, K. (2018, May). Optimal replication based on optimal path hops for opportunistic networks. In 2018 IEEE 32nd International Conference on Advanced Information Networking and Applications (AINA) (pp. 251-258). IEEE.
Jia, B., Li, W., & Zhou, T. (2017, July). A novel P2P service discovery algorithm based on Markov in internet of things. In 2017 IEEE International Conference on Computational Science and Engineering (CSE) and IEEE International Conference on Embedded and Ubiquitous Computing (EUC) (Vol. 2, pp. 26-31). IEEE.
Boldrini, C., Conti, M., Jacopini, J., &Passarella, A. (2007, June). Hibop: a history based routing protocol for opportunistic networks. In 2007 IEEE international Symposium on a world of wireless, mobile and multimedia networks (pp. 1-12). IEEE.
Sharma, D. K., Dhurandher, S. K., Woungang, I., Bansal, A., & Gupta, A. (2017, August). GD-CAR: a genetic algorithm based dynamic context aware routing protocol for opportunistic networks. In International Conference on Network-Based Information Systems (pp. 611-622). Springer, Cham.
Burgess, J., Gallagher, B., Jensen, D. D., & Levine, B. N. (2006, April). MaxProp: Routing for Vehicle-Based Disruption-Tolerant Networks. In Infocom (Vol. 6).
Makhlouta, J., Harkous, H., Hutayt, F., &Artail, H. (2011, October). Adaptive fuzzy spray and wait: Efficient routing for opportunistic networks. In 2011 international conference on selected topics in mobile and wireless networking (iCOST) (pp. 64-69). IEEE.
Ott, J., Hyytiä, E., Lassila, P., Vaegs, T., &Kangasharju, J. (2011, March). Floating content: Information sharing in urban areas. In 2011 IEEE International Conference on Pervasive Computing and Communications (PerCom) (pp. 136-146). IEEE.
Park, J., Lee, J., Kim, S. K., Jang, K., & Yang, S. B. (2016). A forwarding scheme based on swarm intelligence and percolation centrality in opportunistic networks. Wireless Networks, 22(8), 2511-2521.
Ahmad, K., Fathima, M., Jain, V., &Fathima, A. (2017). FUZZY-PRoPHET: a novel routing protocol for opportunistic network. International Journal of Information Technology, 9(2), 121-127.
Zadeh, L. A. (1965). Information and control. Fuzzy sets, 8(3), 338-353.
Lilien, L., Gupta, A., & Yang, Z. (2007, April). Opportunistic networks for emergency applications and their standard implementation framework. In 2007 IEEE International Performance, Computing, and Communications Conference (pp. 588-593). IEEE.
Srinidhi, N. N., Sagar, C. S., Chethan, S. D., Shreyas, J., & Kumar, S. D. (2019, December). Machine Learning Based Efficient Multi-copy Routing for OppIoT Networks. In International Conference on Computational Intelligence, Security and Internet of Things (pp. 288-302). Springer, Singapore.
Srinidhi, N. N., Nagarjun, E., & Kumar, S. D. (2019, November). HMCRA: Hybrid Multi-Copy Routing Algorithm for Opportunistic IoT Network. In 2019 International Conference on Smart Systems and Inventive Technology (ICSSIT) (pp. 370-375). IEEE.
Sok, P., Tan, S., & Kim, K. (2013, November). PRoPHET routing protocol based on neighbor node distance using a community mobility model in delay tolerant networks. In 2013 IEEE 10th International Conference on High Performance Computing and Communications & 2013 IEEE International Conference on Embedded and Ubiquitous Computing (pp. 1233-1240). IEEE.
Nelson, S. C., Bakht, M., &Kravets, R. (2009, April). Encounter-based routing in DTNs. In IEEE INFOCOM 2009 (pp. 846-854). IEEE.
Kumar, S. D., & Kumar, B. V. (2008, December). Energy-aware multicast routing in MANETs based on genetic algorithms. In 2008 16th IEEE International Conference on Networks (pp. 1-5). IEEE.
Borah, S. J., Dhurandher, S. K., Woungang, I., & Kumar, V. (2017). A game theoretic context-based routing protocol for opportunistic networks in an IoT scenario. Computer Networks, 129, 572-584.
Dhurandher, S. K., Sharma, D. K., &Woungang, I. (2013). Energy-based Performance Evaluation of Various Routing Protocols in Infrastructure-less Opportunistic Networks. J. Internet Serv. Inf. Secur., 3(1/2), 37-48.
Dhurandher, S. K., Borah, S. J., Woungang, I., Tibarewal, S., &Barolli, L. (2018). DEEP: distance and encounter based energy-efficient protocol for opportunistic networks. Journal of High Speed Networks, 24(2), 119-131.
Sisodiya, S., Sharma, P., & Tiwari, S. K. (2017, February). A new modified spray and wait routing algorithm for heterogeneous delay tolerant network. In 2017 International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud)(I-SMAC) (pp. 843-848). IEEE.
Srinidhi, N. N., Sunitha, G. P., Nagarjun, E., Shreyas, J., & Kumar, S. D. (2019, November). Lifetime Maximization of IoT Network by Optimizing Routing Energy. In 2019 IEEE International WIE Conference on Electrical and Computer Engineering (WIECON-ECE) (pp. 1-4). IEEE.
Srinidhi, N. N., Kumar, S. D., &Banu, R. (2017, December). Internet of things for neophytes: A survey. In 2017 International Conference on Electrical, Electronics, Communication, Computer, and Optimization Techniques (ICEECCOT) (pp. 234-242). IEEE.
Guan, X., Chen, M., &Ohtsuki, T. (2012). Epidemic theory based H+ 1 hop forwarding for intermittently connected mobile ad hoc networks. EURASIP Journal on Wireless Communications and Networking, 2012(1), 1-10.

Files

Share

How to cite

Statistics