TY - GEN
T1 - HMCRA
T2 - 2nd International Conference on Smart Systems and Inventive Technology, ICSSIT 2019
AU - Srinidhi, N. N.
AU - Nagarjun, E.
AU - Dilip Kumar, S. M.
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/11
Y1 - 2019/11
N2 - Opportunistic networks in Internet of Things (IoT) scenario, nodes will have limited time to exchange data and they don't have a pre-established route between them, therefore nodes have to collect the information about IoT network like location of the neighboring nodes and network topology dynamically. These dynamic characteristics pose challenges for routing of data in opportunistic IoT network. Despite multi-copy routing improves delivery probability and reduces number of message retransmission but it suffers from higher latency and overhead due multiple message copies in the network. Hence in this paper, Hybrid Multi-Copy Routing Algorithm (HMCRA) is propounded which classifies potential nodes based on optimal values exhibited by the nodes with respect to energy, speed and distance using fuzzy logic. Genetic Algorithm (GA) is used in fusion with fuzzy logic to form hybrid algorithm in order to obtain optimal route with lesser hop count. The simulation results delineate that the proposed HMCRA algorithm outperforms with respect to delivery probability, hop count, overhead ratio and latency in par with similar multi-copy routing algorithms. The uniqueness of this paper lies in selecting potential nodes and to find optimal path by applying fuzzy logic and GA.
AB - Opportunistic networks in Internet of Things (IoT) scenario, nodes will have limited time to exchange data and they don't have a pre-established route between them, therefore nodes have to collect the information about IoT network like location of the neighboring nodes and network topology dynamically. These dynamic characteristics pose challenges for routing of data in opportunistic IoT network. Despite multi-copy routing improves delivery probability and reduces number of message retransmission but it suffers from higher latency and overhead due multiple message copies in the network. Hence in this paper, Hybrid Multi-Copy Routing Algorithm (HMCRA) is propounded which classifies potential nodes based on optimal values exhibited by the nodes with respect to energy, speed and distance using fuzzy logic. Genetic Algorithm (GA) is used in fusion with fuzzy logic to form hybrid algorithm in order to obtain optimal route with lesser hop count. The simulation results delineate that the proposed HMCRA algorithm outperforms with respect to delivery probability, hop count, overhead ratio and latency in par with similar multi-copy routing algorithms. The uniqueness of this paper lies in selecting potential nodes and to find optimal path by applying fuzzy logic and GA.
UR - http://www.scopus.com/inward/record.url?scp=85080060470&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85080060470&partnerID=8YFLogxK
U2 - 10.1109/ICSSIT46314.2019.8987796
DO - 10.1109/ICSSIT46314.2019.8987796
M3 - Conference contribution
AN - SCOPUS:85080060470
T3 - Proceedings of the 2nd International Conference on Smart Systems and Inventive Technology, ICSSIT 2019
SP - 370
EP - 375
BT - Proceedings of the 2nd International Conference on Smart Systems and Inventive Technology, ICSSIT 2019
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 27 November 2019 through 29 November 2019
ER -