Lightweight On-demand Ad hoc Distance-vector Routing - Next Generation (LOADng): Protocol, extension, and applicability

Routing protocol is a critical component of Low-power and Lossy Networks for Smart Grid The protocols are used for data forwarding, which includes data acquisition, information dissemination, etc This paper evaluates two main routing protocols used for Low-power and Lossy Networks: RPL and LOADng, to understand their strengths and limitations Observations are provided based on analysis of specification and experimental experience, regarding the protocol's routing overhead, traffic pattern, resource requirement, fragmentation, etc Simulations are further launched to study the performance in different traffic patterns, which include sensor-to-sensor traffic, sensor-to-root traffic and root-to-sensor bidirectional traffic By evaluating those protocols, the readers could have better understanding of the protocol applicability, and choose the appropriate protocol for desired applications

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Evaluation of routing protocol for low power and Lossy Networks: LOADng and RPL

The Internet of Things (IoT) is an emerging paradigm that proposes the connection of objects to exchange information in order to reach a common objective. In IoT networks, it is expected that the nodes will exchange data between each other and with external Internet services. However, due to deployment costs, not all the network devices are able to communicate with the Internet directly. Thus, other network nodes should use Internet-connected nodes as a gateway to forward messages to Internet services. Considering the fact that main routing protocols for low-power networks are not able to reach suitable performance in the displayed IoT environment, this work presents an enhancement to the Lightweight On-demand Ad hoc Distance-vector Routing Protocol—Next Generation (LOADng) for IoT scenarios. The proposal, named LOADng-IoT, is based on three improvements that will allow the nodes to find Internet-connected nodes autonomously and dynamically, decreasing the control message overhead required for the route construction, and reducing the loss of data messages directed to the Internet. Based on the performed assessment study, which considered several number of nodes in dense, sparse, and mobility scenarios, the proposed approach is able to present significant results in metrics related to quality-of-service, reliability, and energy efficiency.

https://www.mdpi.com/1424-8220/19/1/150/pdf

LOADng-IoT: An Enhanced Routing Protocol for Internet of Things Applications over Low Power Networks

We investigate the performance of cross-layer optimized routing across distributed wireless body-to-body networks (BBNs), based on real-life experimental measurements. Two types of dynamic routing are analyzed: shortest path routing (SPR), and cooperative multi-path routing (CMR) associated with selection combining. An open-access experimental dataset incorporating ‘everyday’ mixed-activities is used for analyzing and comparing the cross-layer optimized routing protocols with different wireless sensor network protocols, i.e., ORPL and LOADng, and also with a standard star topology routing within a BBN (multiple, connected, body area networks). Negligible packet error rate is achieved by applying CMR and SPR techniques with reasonably sensitive receivers. Moreover, at 10% outage probability, CMR gains up to 12, 8, 7, and 6 dB improvements over star topology routing, ORPL, SPR, and LOADng, respectively. We show that CMR achieves the highest throughput (packets/s) while providing acceptable end-to-end delay with 95 ms maximum, at −100 dBm receive sensitivity. The use of an alternate path in CMR reduces retransmissions and increases the packet success rate, which significantly reduces the end-to-end delay and energy consumption for CMR with respect to the other protocols. It is also shown that the combined channel gains across SPR and CMR are gamma and Rician distributed, respectively.

Experimental Analysis of Cross-Layer Optimization for Distributed Wireless Body-to-Body Networks

Routing protocols represent an important issue on the Internet of Things (IoT) scenarios since they are responsible for creating paths and forwarding data packets among the network nodes. In mobile IoT scenarios, the topology changes caused by the movement of nodes makes the work of routing protocols more difficult. Thus, the current IoT routing solutions tend to present strong limitations and a poor performance in these scenarios, generally requiring complex additional improvement to better support the mobility of the devices. In this context, the Lightweight On-demand Ad hoc Distance-vector Routing Protocol - Next Generation (LOADng), is an emerging solution for IoT networks that despite being adequate for a mobile environment due to its reactive functioning still lacks in performance. Thus, this paper proposes a novel solution to enhance the performance of LOADng in mobile IoT networks. The improved version, LOADng-IoT-Mob, introduces a mechanism that permits nodes to be aware of the availability of their neighbors through the harnessing of control messages. As a result, these nodes can shorten paths and avoid sending data packets through broken routes due to the movement of the nodes. Additionally, a short periodical control message is introduced, allowing the nodes to update their routing table, even with a low control message frequency. Furthermore, a new routing metric is proposed for creating routes based on the reliability of the link and proximity of the neighboring nodes. Finally, through computational simulations, the performance of the LOADng-IoT-Mob is studied under multiple scenarios varying the network size, the number of mobile devices, and maximum nodes' speed. The results obtained demonstrate the efficiency of the proposed solution in terms of packet delivery ratio, latency, and power and overhead efficiency, with a slight increase in memory consumption.

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Improving the Performance of LOADng Routing Protocol in Mobile IoT Scenarios

A derivative of AODV, denoted LOADng, is proposed for use in very constrained environment, sacrificing a number of features from AODV for the benefit of smaller control messages and simpler processing logic. Among these sacrifices is intermediate route replies. This paper presents an alternative to intermediate router replies, denoted Smart Route Request, which provides an optimization similar to that attainable by intermediate route requests, but without imposing additional processing complexity or additional signaling. A performance study is presented, showing that the use of Smart Route Requests can effectively reduce the control traffic overhead from Route Requests, while retaining the simplicity of LOADng. LOADng with Smart Route Requests effectively reduces control traffic overhead and on-link traffic collisions, and this especially for multipoint-to-point traffic.

/pdf/smart-route-request-for-on-demand-route-discovery-in-2wpnyes94z.pdf

Smart Route Request for on-demand route discovery in constrained environments

This paper explores the cooperation between the new standards for "Low Power and Lossy Networks'' (LLNs): IETF RFC 6971, denoted "Depth-First Forwarding in Unreliable Networks'' (DFF) and the ITU-T standardised routing protocol "LOADng''. DFF is a data-forwarding mechanism for increasing reliability of data delivery in networks with dynamic topology and lossy links, using a mechanism similar to a "depth-first search'' for the destination of a packet. LOADng is a reactive on-demand routing protocol used in LLNs. The purpose of this study is to evaluate the benefit of using DFF conjointly with a routing protocol. To this end, the paper compares the performance of LOADng and LOADng+DFF using Ns2 simulations, showing a 20% end-to-end data delivery ratio increase at expense of expected longer path lengths.

/pdf/a-depth-first-forwarding-dff-extension-for-the-loadng-4dajywe1fm.pdf

Antonin Bas

Papers

Smart Route Request for on-demand route discovery in constrained environments

A Depth First Forwarding (DFF) Extension for the LOADng Routing Protocol