scholarly journals Toward Improved RPL: A Congestion Avoidance Multipath Routing Protocol with Time Factor for Wireless Sensor Networks

2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Weisheng Tang ◽  
Xiaoyuan Ma ◽  
Jun Huang ◽  
Jianming Wei

Designing routing protocols in Low power and Lossy Networks (LLNs) imposes great challenges. In emergency scenarios, the large and rapid data traffic caused by emergencies will lead to network congestion and bring about significant packet loss and delay. Routing protocol for LLNs (RPL) is the IETF standard for IPv6 routing in LLNs. The basic version of RPL uses Expected Transmission Count (ETX) as the default routing metric; it cannot solve the problem of sudden large data traffic. In this paper, we propose a congestion avoidance multipath routing protocol which uses composite routing metrics based on RPL, named CA-RPL. A routing metric for RPL that minimized the average delay towards the DAG root is proposed, and the weight of each path is computed by four metrics. The mechanism is explained and its performance is evaluated through simulation experiments based on Contiki. Simulation results show that the proposed CA-RPL reduces the average time delay by about 30% compared to original RPL when the interpacket interval is short and has almost 20% reduction in packet loss ratio. The CA-RPL can effectively alleviate the network congestion in the network with poor link quality and large data traffic and significantly improve the performance of LLNs.

Sensors ◽  
2019 ◽  
Vol 19 (24) ◽  
pp. 5486 ◽  
Author(s):  
Sankar Sennan ◽  
Sathiyabhama Balasubramaniyam ◽  
Ashish Kr. Luhach ◽  
Somula Ramasubbareddy ◽  
Naveen Chilamkurti ◽  
...  

Energy conservation is one of the most critical problems in Internet of Things (IoT). It can be achieved in several ways, one of which is to select the optimal route for data transfer. IPv6 Routing Protocol for Low Power and Lossy Networks (RPL) is a standardized routing protocol for IoT. The RPL changes its path frequently while transmitting the data from source to the destination, due to high data traffic in dense networks. Hence, it creates data traffic across the nodes in the networks. To solve this issue, we propose Energy and Delay Aware Data aggregation in Routing Protocol (EDADA-RPL) for IoT. It has two processes, namely parent selection and data aggregation. The process of parent selection uses routing metric residual energy (RER) to choose the best possible parent for data transmission. The data aggregation process uses the compressed sensing (CS) theory in the parent node to combine data packets from the child nodes. Finally, the aggregated data transmits from a downward parent to the sink. The sink node collects all the aggregated data and it performs the reconstruction operation to get the original data of the participant node. The simulation is carried out using the Contiki COOJA simulator. EDADA-RPL’s performance is compared to RPL and LA-RPL. The EDADA-RPL offers good performance in terms of network lifetime, delay, and packet delivery ratio.


2016 ◽  
Vol 2016 ◽  
pp. 1-13 ◽  
Author(s):  
Chuang Ma ◽  
Jang-Ping Sheu ◽  
Chao-Xiang Hsu

In wireless sensor networks (WSNs), the presence of congestion increases the ratio of packet loss and energy consumption and reduces the network throughput. Particularly, this situation will be more complex in Internet of Things (IoT) environment, which is composed of thousands of heterogeneous nodes. RPL is an IPv6 routing protocol in low power and lossy networks standardized by IETF. However, the RPL can induce problems under network congestion, such as frequently parent changing and throughput degradation. In this paper, we address the congestion problem between parent nodes and child nodes in RPL-enabled networks, which typically consist of low power and resource constraint devices. To mitigate the effect of network congestion, we design a parent-change procedure by game theory strategy, by which the child nodes can change next hop neighbors toward the sink. Comparing to the ContikiRPL implementation, the simulation results show that our protocol can achieve more than two times improvement in throughput and reduce packet loss rate with less increasing of average hop count.


2020 ◽  
Vol 26 (11) ◽  
pp. 1366-1381
Author(s):  
Sathishkumar Natesan ◽  
Rajakumar Krishnan

The Routing Protocol for Low Power and Lossy Networks (RPL) is operated by gadgets comprised of many devices of embedded type with limited energy, memory as well as resources that do their process. The improvements in the life of the network and energy conservation are the key challenging features in Low Power and Lossy Networks (LLN). Obviously, the LLN has a key strategic part in routing. The Internet of Things (IoT) device is expected to make the apt choice. In LLN, the poor routing choice leads to traffic congestion, reduction in power as well as packet loss ratio. The task in the proposal analyzes Delay (D), Load (L) and Battery Discharge Index (BDI) pivoted Energy Efficient Composite Metric Routing (EECMR) protocol for LLN. The performance of the work in the proposal is evaluated by the COOJA simulator. It outperforms with respect to Network Lifetime (NL), Delay as well as Packet Delivery Ratio (PDR) contrasted to the routing metrics like Traffic Load (TL), Link Quality (LQ), Residual Energy (RE), RE-Battery Discharge Index (RE-BDI) and Hop Count (HC).


2017 ◽  
Vol 13 (2) ◽  
pp. 87 ◽  
Author(s):  
Jose V. V. Sobral ◽  
Joel J. P. C. Rodrigues ◽  
Neeraj Kumar ◽  
Chunsheng Zhu ◽  
Raja W. Ahmad

LOADng (Lightweight On-demand Ad hoc Distance-vector Routing Protocol - Next Generation) is an emerging routing protocol that emerged as an alternative to RPL (IPv6 Routing Protocol for Low power and Lossy Networks). Although some work has been dedicated to study LOADng, these works do not analyze the performance of this protocol with different routing metrics. A routing metric is responsible for defining values for paths during the route creation process. Moreover, based on these metrics information a routing protocol will select the path to forward a message. Thus, this work aims to realize a performance assessment study considering different routing metrics applied to LOADng. The scenarios under study consider different traffic patterns and network sizes. The routing metrics are evaluated considering the packet delivery ratio, average energy spent per bit delivered, average latency, and number of hops. The results reveals that routing metrics used by this protocol may influence (directly) the network performance.


2018 ◽  
Vol 7 (2.22) ◽  
pp. 39 ◽  
Author(s):  
A Sebastian ◽  
S Sivagurunathan ◽  
. .

IETF ROLL working Group standardized the IPv6 Routing protocol (RPL) for applications over low-power and lossy networks (LLNs). RPL constructs a Destination Oriented Direction Acyclic Graph (DODAG) to organize network topology. RPL shows fast network setup and good scalability. However, it may suffer from load imbalance due to diverse network traffic and heavy load on preferred or forwarding parents. To optimize the load balancing of routes in RPL, this paper proposes load balancing metric based routing protocol called lbRPL. We introduce a new routing metric for RPL called load balancing index (LBI), which exploits load balancing characteristics of RPL nodes to select more load balanced parents and routes. LBI includes ETX, Parent count (Pc) and Remaining Parent Energy (Pe) metrics to make routing decisions. Simulation results show that lbRPL improves network performance, stability and improved network life time to RPL.  


2011 ◽  
Vol 2011 ◽  
pp. 1-8 ◽  
Author(s):  
Martin Krogmann ◽  
Mike Heidrich ◽  
Daniel Bichler ◽  
Daniel Barisic ◽  
Guido Stromberg

We present a novel Reliable, Real-time Routing protocol (3R) based on multipath routing for highly time-constrained Wireless Sensor and Actuator Networks (WSANs). The protocol consists of a newly designed routing metric and a routing algorithm utilizing this metric. Our routing metric enables strong Quality-of-Service (QoS) support based on parallel transmissions which significantly reduces transmission delays in WSANs. A routing algorithm utilizing this metric is presented based on Dijkstra's shortest path. A novel Medium Access Control (MAC) layer that supports dynamical adjustments of retransmission limits, reduces traffic overhead in multipath routing protocols. Thorough simulations have been performed to evaluate the routing protocol, and the results show that real-time performance of WSANs can be vastly improved.


Sensors ◽  
2020 ◽  
Vol 20 (12) ◽  
pp. 3508
Author(s):  
Hossam Farag ◽  
Patrik Österberg ◽  
Mikael Gidlund

The Routing Protocol for Low power and lossy networks (RPL) has been introduced as the de-facto routing protocol for the Industrial Internet of Things (IIoT). In heavy load scenarios, particular parent nodes are likely prone to congestion, which in turn degrades the network performance, in terms of packet delivery and delay. Moreover, there is no explicit strategy in RPL to prioritize the transmission of different traffic types in heterogeneous 6TiSCH networks, each according to its criticality. In this paper, we address the aforementioned issues by introducing a congestion control and service differentiation strategies to support heterogeneous 6TiSCH networks in IIoT applications. First, we introduce a congestion control mechanism to achieve load balancing under heavy traffic scenarios. The congestion is detected through monitoring and sharing the status of the queue backlog among neighbor nodes. We define a new routing metric that considers the queue occupancy when selecting the new parent node in congestion situations. In addition, we design a multi-queue model to provide prioritized data transmission for critical data over the non-critical ones. Each traffic type is placed in a separate queue and scheduled for transmission based on the assigned queue priority, where critical data are always transmitted first. The performance of the proposed work is evaluated through extensive simulations and compared with existing work to demonstrate its effectiveness. The results show that our proposal achieves improved packet delivery and low queue losses under heavy load scenarios, as well as improved delay performance of critical traffic.


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