25-08-2017, 09:32 PM
Link Estimation and Routing in Sensor Network Backbones: Beacon-based or Data-driven
[attachment=23498]
ABSTRACT
In the context of IEEE 802.11b network testbeds, we examine the differences between unicast and broadcast link properties, and we show the inherent difficulties in precisely estimating unicast link properties via those of broadcast beacons even if we make the length and transmission rate of beacons be the same as those of data packets. To circumvent the difficulties in link estimation, we propose to estimate unicast link properties directly via data traffic itself without using periodic beacons. To this end, we design a data-driven routing protocol Learn on the Fly (LOF). LOF chooses routes based on ETX/ETT-type metrics, but the metrics are estimated via MAC feedback for unicast data transmission instead of broadcast beacons. Using a realistic sensor network traffic trace and an 802.11b testbed of ∼195 Stargates, we experimentally compare the performance of LOF with that of beacon-based protocols, represented by the geography-unaware ETX and the geography-based PRD.We find that LOF reduces end-to-end MAC latency by a factor of 3, enhances energy efficiency by a factor up to 2.37, and improves network throughput by a factor up to 7.78, which demonstrate the feasibility and the potential benefits of data-driven link estimation and routing.
EXISTING SYSTEM
In existing routing protocols that use link quality estimation, beacons are exchanged periodically. Therefore, energy is consumed unnecessarily for the periodic beaconing when there is no data traffic. This is especially true if the events of interest are infrequent enough that there is no data traffic in the network most of the time
PROPOSED SYSTEM
To deal with the shortcomings of beacon-based link quality estimation and to avoid unnecessary beaconing, new mechanisms for link estimation and routing are desired. In this project, to address the drawbacks of beacon-based estimation, we propose to estimate link properties via MAC feedback for unicast data transmissions themselves. To this end, we define data-driven routing metrics that, using MAC latency for data transmissions, are similar to ETX/ETT but are estimated via unicast MAC feedback instead of broadcast beacons.
MODULE DESCRIPTION
1. Network Formation
We will formulate a network node by using simple assumption of creating a node window. For each node will having the unique number starts with LER. Then we will provide the distance units like 5, 10, 15… to every node and update the neighbor nodes.
2. Data-driven routing
In this approach, it may not be always feasible when the length of data packets is changing; or even when the approach is feasible, it still does not guarantee that link properties experienced by periodic beacons reflect those in the presence of data traffic, especially in event-driven sensor network applications. Moreover, the existing method for estimating metrics such as ETX does not take into account the temporal correlations in link properties (partly due to the difficulty of modeling the temporal correlations themselves), which further decreases its estimation fidelity.
3. Node mobility. Given that nodes in most sensor networks are static, LOF is not designed to support high degree of mobility. Nevertheless, LOF can deal with infrequent movement of nodes in the following simple manner:
• If the base station moves, the new location of the base station is diffused across the network If a node other than the base station moves, it first broadcast M copies of message packets, then it restarts its routing process.
[attachment=23498]
ABSTRACT
In the context of IEEE 802.11b network testbeds, we examine the differences between unicast and broadcast link properties, and we show the inherent difficulties in precisely estimating unicast link properties via those of broadcast beacons even if we make the length and transmission rate of beacons be the same as those of data packets. To circumvent the difficulties in link estimation, we propose to estimate unicast link properties directly via data traffic itself without using periodic beacons. To this end, we design a data-driven routing protocol Learn on the Fly (LOF). LOF chooses routes based on ETX/ETT-type metrics, but the metrics are estimated via MAC feedback for unicast data transmission instead of broadcast beacons. Using a realistic sensor network traffic trace and an 802.11b testbed of ∼195 Stargates, we experimentally compare the performance of LOF with that of beacon-based protocols, represented by the geography-unaware ETX and the geography-based PRD.We find that LOF reduces end-to-end MAC latency by a factor of 3, enhances energy efficiency by a factor up to 2.37, and improves network throughput by a factor up to 7.78, which demonstrate the feasibility and the potential benefits of data-driven link estimation and routing.
EXISTING SYSTEM
In existing routing protocols that use link quality estimation, beacons are exchanged periodically. Therefore, energy is consumed unnecessarily for the periodic beaconing when there is no data traffic. This is especially true if the events of interest are infrequent enough that there is no data traffic in the network most of the time
PROPOSED SYSTEM
To deal with the shortcomings of beacon-based link quality estimation and to avoid unnecessary beaconing, new mechanisms for link estimation and routing are desired. In this project, to address the drawbacks of beacon-based estimation, we propose to estimate link properties via MAC feedback for unicast data transmissions themselves. To this end, we define data-driven routing metrics that, using MAC latency for data transmissions, are similar to ETX/ETT but are estimated via unicast MAC feedback instead of broadcast beacons.
MODULE DESCRIPTION
1. Network Formation
We will formulate a network node by using simple assumption of creating a node window. For each node will having the unique number starts with LER. Then we will provide the distance units like 5, 10, 15… to every node and update the neighbor nodes.
2. Data-driven routing
In this approach, it may not be always feasible when the length of data packets is changing; or even when the approach is feasible, it still does not guarantee that link properties experienced by periodic beacons reflect those in the presence of data traffic, especially in event-driven sensor network applications. Moreover, the existing method for estimating metrics such as ETX does not take into account the temporal correlations in link properties (partly due to the difficulty of modeling the temporal correlations themselves), which further decreases its estimation fidelity.
3. Node mobility. Given that nodes in most sensor networks are static, LOF is not designed to support high degree of mobility. Nevertheless, LOF can deal with infrequent movement of nodes in the following simple manner:
• If the base station moves, the new location of the base station is diffused across the network If a node other than the base station moves, it first broadcast M copies of message packets, then it restarts its routing process.