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On the number of candidates in opportunistic routing for multi-hop wireless networks

Published: 03 November 2013 Publication History

Abstract

Opportunistic Routing (OR) is a new paradigm that has been investigated as a new way to improve the performance of multihop wireless networks by exploiting the broadcast nature of the wireless medium. In contrast to traditional routing, in OR an ordered set of nodes is selected as potential next-hop forwarders (candidates). Using more number of candidates in OR decreases the number of transmissions in the network, but this comes at the cost of increasing the signaling overhead and also the possibility of having duplicated transmissions which in turn reduces the performance of the OR protocol. The number of candidates that each node can select is an issue which is not well investigated in the literature. In this paper, we propose a Distance-based MAximum number of Candidate Estimation (D-MACE) as an approach to find the number of candidates in each node. In contrast to the traditional approaches in OR which consider an identical number of candidates for all nodes, D-MACE reduces the number of candidates in each node according to the distance between the node and the destination. We evaluate the performance of our proposal, using two relevant candidate selection algorithms. Our results show that D-MACE reduces the number of selected candidates effectively in the network, which improves the network performance compared to the case with the same number of candidates in all nodes.

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Cited By

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  • (2023)A new on the fly energy-efficient opportunistic routing in wireless multi-hop networksJournal of the Chinese Institute of Engineers10.1080/02533839.2022.216193946:2(107-117)Online publication date: 23-Jan-2023
  • (2021)OMUS: Efficient Opportunistic Routing in Multi-Modal Underwater Sensor NetworksIEEE Transactions on Wireless Communications10.1109/TWC.2021.306911720:9(5642-5655)Online publication date: Sep-2021
  • (2020)Stochastic Modeling of Opportunistic Routing in Multi-Modal Internet of Underwater ThingsGLOBECOM 2020 - 2020 IEEE Global Communications Conference10.1109/GLOBECOM42002.2020.9348013(1-6)Online publication date: Dec-2020
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        cover image ACM Conferences
        MobiWac '13: Proceedings of the 11th ACM international symposium on Mobility management and wireless access
        November 2013
        168 pages
        ISBN:9781450323550
        DOI:10.1145/2508222
        Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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        Published: 03 November 2013

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        Author Tags

        1. candidate selection
        2. maximum number of candidates
        3. opportunistic routing
        4. wireless networks

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        MobiWac '13 Paper Acceptance Rate 21 of 68 submissions, 31%;
        Overall Acceptance Rate 83 of 272 submissions, 31%

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        Cited By

        View all
        • (2023)A new on the fly energy-efficient opportunistic routing in wireless multi-hop networksJournal of the Chinese Institute of Engineers10.1080/02533839.2022.216193946:2(107-117)Online publication date: 23-Jan-2023
        • (2021)OMUS: Efficient Opportunistic Routing in Multi-Modal Underwater Sensor NetworksIEEE Transactions on Wireless Communications10.1109/TWC.2021.306911720:9(5642-5655)Online publication date: Sep-2021
        • (2020)Stochastic Modeling of Opportunistic Routing in Multi-Modal Internet of Underwater ThingsGLOBECOM 2020 - 2020 IEEE Global Communications Conference10.1109/GLOBECOM42002.2020.9348013(1-6)Online publication date: Dec-2020
        • (2020)Normalized Advancement Based Totally Opportunistic Routing Algorithm With Void Detection and Avoiding Mechanism for Underwater Wireless Sensor NetworkIEEE Access10.1109/ACCESS.2020.29846528(67484-67500)Online publication date: 2020
        • (2016)An Estimation Method on the Number of Candidate Nodes in Opportunistic Routing2016 17th International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT)10.1109/PDCAT.2016.072(307-312)Online publication date: Dec-2016
        • (2016)Opportunistic Shortcut Tree Routing in ZigBee NetworksIEEE Sensors Journal10.1109/JSEN.2016.255734416:12(5107-5115)Online publication date: Jun-2016
        • (2016)Minimum-Cost Recruitment of Mobile Crowdsensing in Cellular Networks2016 IEEE Global Communications Conference (GLOBECOM)10.1109/GLOCOM.2016.7841988(1-7)Online publication date: Dec-2016
        • (2016)Constraint Free Preference Preserving Hashing for Fast Recommendation2016 IEEE Global Communications Conference (GLOBECOM)10.1109/GLOCOM.2016.7841687(1-6)Online publication date: Dec-2016
        • (2016)Analysis of Batched Opportunistic Data Forwarding in Wireless Mesh Networks2016 IEEE Global Communications Conference (GLOBECOM)10.1109/GLOCOM.2016.7841600(1-6)Online publication date: Dec-2016
        • (2016)Towards a novel trust-based opportunistic routing protocol for wireless networksWireless Networks10.1007/s11276-015-1010-422:3(927-943)Online publication date: 1-Apr-2016
        • Show More Cited By

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