6,885 research outputs found
Reliable routing scheme for indoor sensor networks
Indoor Wireless sensor networks require a highly dynamic, adaptive routing scheme to deal with the high rate of topology changes due to fading of indoor wireless channels. Besides that, energy consumption rate needs to be consistently distributed among sensor nodes and efficient utilization of battery power is essential. If only the link reliability metric is considered in the routing scheme, it may create long hops routes, and the high quality paths will be frequently used. This leads to shorter lifetime of such paths; thereby the entire network's lifetime will be significantly minimized. This paper briefly presents a reliable load-balanced routing (RLBR) scheme for indoor ad hoc wireless sensor networks, which integrates routing information from different layers. The proposed scheme aims to redistribute the relaying workload and the energy usage among relay sensor nodes to achieve balanced energy dissipation; thereby maximizing the functional network lifetime. RLBR scheme was tested and benchmarked against the TinyOS-2.x implementation of MintRoute on an indoor testbed comprising 20 Mica2 motes and low power listening (LPL) link layer provided by CC1000 radio. RLBR scheme consumes less energy for communications while reducing topology repair latency and achieves better connectivity and communication reliability in terms of end-to-end packets delivery performance
On Link Estimation in Dense RPL Deployments
The Internet of Things vision foresees billions of
devices to connect the physical world to the digital world. Sensing
applications such as structural health monitoring, surveillance or
smart buildings employ multi-hop wireless networks with high
density to attain sufficient area coverage. Such applications need
networking stacks and routing protocols that can scale with
network size and density while remaining energy-efficient and
lightweight. To this end, the IETF RoLL working group has
designed the IPv6 Routing Protocol for Low-Power and Lossy
Networks (RPL). This paper discusses the problems of link quality
estimation and neighbor management policies when it comes
to handling high densities. We implement and evaluate different
neighbor management policies and link probing techniques in
Contiki’s RPL implementation. We report on our experience
with a 100-node testbed with average 40-degree density. We show
the sensitivity of high density routing with respect to cache sizes
and routing metric initialization. Finally, we devise guidelines for
design and implementation of density-scalable routing protocols
Low Power, Low Delay: Opportunistic Routing meets Duty Cycling
Traditionally, routing in wireless sensor networks consists of
two steps: First, the routing protocol selects a next hop,
and, second, the MAC protocol waits for the intended destination
to wake up and receive the data. This design makes
it difficult to adapt to link dynamics and introduces delays
while waiting for the next hop to wake up.
In this paper we introduce ORW, a practical opportunistic
routing scheme for wireless sensor networks. In a dutycycled
setting, packets are addressed to sets of potential receivers
and forwarded by the neighbor that wakes up first
and successfully receives the packet. This reduces delay and
energy consumption by utilizing all neighbors as potential
forwarders. Furthermore, this increases resilience to wireless
link dynamics by exploiting spatial diversity. Our results
show that ORW reduces radio duty-cycles on average
by 50% (up to 90% on individual nodes) and delays by 30%
to 90% when compared to the state of the art
Traffic eavesdropping based scheme to deliver time-sensitive data in sensor networks
Due to the broadcast nature of wireless channels, neighbouring sensor nodes may overhear packets transmissions from each other even if they are not the intended recipients of these transmissions. This redundant packet reception leads to unnecessary expenditure of battery energy of the recipients. Particularly in highly dense sensor networks, overhearing or eavesdropping overheads can constitute a significant fraction of the total energy consumption. Since overhearing of wireless traffic is unavoidable and sometimes essential, a new distributed energy efficient scheme is proposed in this paper. This new scheme exploits the inevitable overhearing effect as an effective approach in order to collect the required information to perform energy efficient delivery for data aggregation. Based on this approach, the proposed scheme achieves moderate energy consumption and high packet delivery rate notwithstanding the occurrence of high link failure rates. The performance of the proposed scheme is experimentally investigated a testbed of TelosB motes in addition to ns-2 simulations to validate the performed experiments on large-scale network
Let the Tree Bloom: Scalable Opportunistic Routing with ORPL
Routing in battery-operated wireless networks is challenging, posing a tradeoff between energy and latency. Previous work has shown that opportunistic routing can achieve low-latency data collection in duty-cycled networks. However, applications are now considered where nodes are not only periodic data sources, but rather addressable end points generating traffic with arbitrary patterns.
We present ORPL, an opportunistic routing protocol that supports any-to-any, on-demand traffic. ORPL builds upon RPL, the standard protocol for low-power IPv6 networks. By combining RPL's tree-like topology with opportunistic routing, ORPL forwards data to any destination based on the mere knowledge of the nodes' sub-tree. We use bitmaps and Bloom filters to represent and propagate this information in a space-efficient way, making ORPL scale to large networks of addressable nodes. Our results in a 135-node testbed show that ORPL outperforms a number of state-of-the-art solutions including RPL and CTP, conciliating a sub-second latency and a sub-percent duty cycle. ORPL also increases robustness and scalability, addressing the whole network reliably through a 64-byte Bloom filter, where RPL needs kilobytes of routing tables for the same task
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