On Bit-Rate Selection for Opportunistic Routing

Gray, Chase; Santhapuri, Naveen; Nelakuditi, Srihari

doi:10.1109/sahcnw.2008.17

Cited by 6 publications

(5 citation statements)

References 18 publications

(27 reference statements)

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“…Zeng et al [15] and Gray et al [16] proposed multirate opportunistic schemes, but their routing algorithms are not provably optimal and they use a different routing metric. Radunovic et al [17] presents an optimization framework to derive routing, scheduling, and rate adaptation schemes for wireless mesh networks.…”

Section: Resultsmentioning

confidence: 99%

Multirate Anypath Routing in Wireless Mesh Networks

2009

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Abstract-In this paper, we present a new routing paradigm that generalizes opportunistic routing in wireless mesh networks. In multirate anypath routing, each node uses both a set of next hops and a selected transmission rate to reach a destination. Using this rate, a packet is broadcast to the nodes in the set and one of them forwards the packet on to the destination. To date, there is no theory capable of jointly optimizing both the set of next hops and the transmission rate used by each node. We bridge this gap by introducing a polynomial-time algorithm to this problem and provide the proof of its optimality. The proposed algorithm runs in the same running time as regular shortest-path algorithms and is therefore suitable for deployment in link-state routing protocols. We conducted experiments in a 802.11b testbed network, and our results show that multirate anypath routing performs on average 80% and up to 6.4 times better than anypath routing with a fixed rate of 11 Mbps. If the rate is fixed at 1 Mbps instead, performance improves by up to one order of magnitude.

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Section: Resultsmentioning

confidence: 99%

Multirate Anypath Routing in Wireless Mesh Networks

2009

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“…• Expected Medium Time (EMT): EMT [117] is another recursive opportunistic metric that shares several similarities with other opportunistic metrics such as EAX [111], EATT [118] and ExACT [116]. EMT models the expected transmission time from node i to dst as follows:…”

Section: Or Metrics: a Complete Classification Treatmentmentioning

confidence: 99%

Opportunistic routing metrics: A timely one-stop tutorial survey

Abdollahi

Eshghi

Kelarestaghi

et al. 2020

Journal of Network and Computer Applications

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High-speed, low latency, and heterogeneity features of 5G, as the common denominator of many emerging and classic wireless applications, have put wireless technology back in the spotlight. Continuous connectivity requirement in low-power and wide-reach networks underlines the need for more efficient routing over scarce wireless resources, in multi-hp scenarios. In this regard, Opportunistic Routing (OR), which utilizes the broadcast nature of wireless media to provide transmission cooperation amongst a selected number of overhearing nodes, has become more promising than ever. Crucial to the overall network performance, which nodes to participate and where they stand on the transmission-priority hierarchy, are decided by userdefined OR metrics embedded in OR protocols. Therefore, the task of choosing or designing an appropriate OR metric is a critical one. The numerousness, proprietary notations, and the objective variousness of OR metrics can cause the interested researcher to lose insight and become overwhelmed, making the metric selection or design effort-intensive. While there are not any comprehensive OR metrics surveys in the literature, those who partially address the subject are non-exhaustive and lacking in detail. Furthermore, they offer limited insight regarding related taxonomy and future research recommendations. In this paper, starting with a custom tutorial with a new look to OR and OR metrics, we devise a new framework for OR metric design. Introducing a new taxonomy enables us to take a structured, investigative, and comparative approach to OR metrics, supported by extensive simulations. Exhaustive coverage of OR metrics, formulated in a unified notation, is presented with sufficient details. Self-explanatory, easy-to-grasp, and visual-friendly quick references are provided, which can be used independently from the rest of the paper. Finally, a new insightful framework for future research directions is developed. This tutorial-survey has been organized to benefit both generalists and OR specialists equally, and to be used not only in its entirety but selectively as well.

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“…Then based on the coordinates of source and destinations, it would calculate expected transmission hops, using the message headerTTL entries according to the formula (13) to calculateγ . Finally, using equation (15) to calculate F , and select the path with the smallest path as the optimal path, transmission the acknowledgement to the source node along the reverse of the optimal path. Assuming the grid of the highest priority node N located is i g , the upstream region of which is defined as 1 i g − , downstream region 1 i g + , in 1 i g − the highest priority node denoted by X, in 1 i g + the highest priority node as Y.…”

Section: Optimal Route Selection 1) Energy Modelmentioning

confidence: 99%

“…If the current grid neither in GridList , nor a neighbor of grid in GridList , then the nodes in the current grid discard the data packets listened. After nodes decode the packet, extract ETCost and RTCost from the data frame and then use the formula(13)( 14) (15) to calculate F . When the destinations receive multicast messages from several different regions, they will have several values, then only store the link information with the smallest value.…”

Section: Optimal Route Selection 1) Energy Modelmentioning

confidence: 99%

“…Literature [12] describes the different opportunistic routing methods, from different point of view, each method design the rational routing metrics to ensure reliable message transmission and reducing the cost of the link. In order to make several key parameters of network to achieve a balance, Changhun Bae et al [13] [14] uses mathematical methods between energy and delay, energy and bandwidth obtain the optimal value, ensure the messages more efficiently transmission between links, Jean-Marie Gorce et al [15] have studied the energy, bandwidth and latency, and calculated their optimum values to…”

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confidence: 99%

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Energy-Efficient Opportunistic Routing Protocol in Wireless Sensor Networks

Zhang

Wen

Yang

et al. 2014

AMM

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The paper presents energy-efficiency opportunistic multicast routing protocol (EOMR) for the multicast energy consumption minimization problem in wireless sensor networks. The protocol divides the network into single grids, so each node determines their own coordinates according to the grid, which they locate in a certain period of time. The nodes only need to know the topology of their own grid, instead of the topology of the entire network. Nodes in the same grid determine the priority in light of the upstream and downstream links metrics, and use the opportunistic routing to send messages to the next hop. The destinations calculate the optimal path in accordance with the hops and links cost, and transmission acknowledgement to source along the optimal path selected. If all nodes in the current grid transmission messages failure, the neighbor grids are in charge of retransmission. The results of simulation show that, compared with traditional multicast routing, EOMR is effective in reducing the consumption of links cost, so that it improves the link reliability and reduces the delay.

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On Bit-Rate Selection for Opportunistic Routing

Cited by 6 publications

References 18 publications

Multirate Anypath Routing in Wireless Mesh Networks

Multirate Anypath Routing in Wireless Mesh Networks

Opportunistic routing metrics: A timely one-stop tutorial survey

Energy-Efficient Opportunistic Routing Protocol in Wireless Sensor Networks

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