Multiple constrained QoS routing with RPL

Khallef, Walid; Molnar, Miklos; Benslimane, Abderrahim; Durand, Sylvain

doi:10.1109/icc.2017.7997081

Cited by 32 publications

(22 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Patrick et al [48] also utilize the concept of fuzzy logic to combine several routing metrics that include ETX, delay, and energy cost of the path. Regarding multiple metrics, Walid et al propose a new OF which is based on the non-linear length (NL-OF) [49]. The NL-OF is a greedy approach that considers any number of metrics and all input constraints for quality of service (QoS).…”

Section: Related Workmentioning

confidence: 99%

Routing protocol for Low-Power and Lossy Networks for heterogeneous traffic network

Musaddiq

Zikria

Zulqarnain

et al. 2020

J Wireless Com Network

View full text Add to dashboard Cite

In a real network deployment, the diverse sensor applications generate a heterogeneous traffic pattern which may include basic sensing measurements such as temperature readings or high-volume multimedia traffic. In a heterogeneous traffic network, the two standardized objective functions (OFs), i.e., objective function zero (OF0) and the Minimum Rank with Hysteresis Objective Function (MRHOF) for routing protocol for Low-Power and Lossy Networks (RPL) perform poor routing decisions by selecting an already congested parent node and cause more retransmissions across the network. Therefore, careful consideration is required in designing a new OF for heterogeneous traffic scenarios. In this study, we examine the RPL protocol under a heterogeneous traffic pattern and proposed a new protocol based on queue and workload-based condition (QWL-RPL). The aim of the proposed protocol is to achieve a reliable path with better overall performance. The proposed OF model considers the link workload in addition to mapping the congestion status of the node using the packet queue. We implement the proposed routing model in the Contiki operating system (OS) Cooja environment to compare with the existing technique. The simulation results show that QWL-RPL can improve the performance of a heterogeneous traffic network as compared with both OF0 and MRHOF, specifically in terms of the amount of overhead, packets reception ratio (PRR), average delay, and jitter. Final results indicate that on average, there is a 5%-30% improvement in PRR, 25%-45% reduction in overheads, 12%-30% reduction in average delay, and 20%-40% reduction in jitter.The Internet of Things (IoT) is a large system of interconnected heterogeneous devices to sense our physical environment and communicate the sensed information. Each sensor detects its vicinity and transmits the sensed information to the sink node via its neighboring nodes using multihop communication [1]. The practical applications of such a system include smart cities [2] [3], industrial and building automation, disaster management [4], smart grid, and smart healthcare [5]. A sensor discovers its neighbors, builds the topology, and routes the sensed data. An IoT system requires an efficient networking mechanism to facilitate such an interconnected heterogeneous flow of traffic. An efficient routing mechanism must consider these device characteristics and constrained resources. Furthermore, the IoT sensors usually face unfavorable environmental factors. Thus, designing of such routing protocols is a complicated task due to the resource limitations of these devices, such as limited energy, limited memory, and limited processing power [6]. For any pair of communicating nodes, a reasonable goal for such a protocol is to improve communication performance while maintaining energy consumption at a minimum level. However, achieving this goal requires careful consideration of the lossy nature of the network, fluctuating traffic patterns, varying link qualities, routing loops, and convergence time [7].Several rou...

show abstract

Section: Related Workmentioning

confidence: 99%

Routing protocol for Low-Power and Lossy Networks for heterogeneous traffic network

Musaddiq

Zikria

Zulqarnain

et al. 2020

J Wireless Com Network

View full text Add to dashboard Cite

show abstract

“…Simulation results will show that this solution outperforms several algorithms. Compared to [7], our proposition yields better results in terms of PDR by up to 14% (section IV-B) and throughput by up to 15% (section IV-C).…”

Section: Introductionmentioning

confidence: 87%

“…Another example is the Non-Linear Objective Function [7] (NL-OF) which can use any number of additive metrics. Each metric value is divided by a predetermined Quality of Service (QoS) requirement used to normalize it.…”

Section: A Existing Objective Functionsmentioning

confidence: 99%

“…More specific to RPL, this [6] proposition uses queue utilization to load balance packets in the network in order to improve Packet Delivery Ratio (PDR). Another algorithm [7] (see section II-A) that considers all available metrics to focus on the most problematic one to improve performance has also been developed and yields good results (see section IV). However, these algorithms ultimately focus on either one metric, aim at improving one aspect of the network's performance or do not take energy into account.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Fuzzy-Based Objective Function for Routing Protocol in the Internet of Things

Fabian

Rachedi

Gueguen

et al. 2018

2018 IEEE Global Communications Conference (GLOBECOM)

View full text Add to dashboard Cite

The amount of data represented by the Internet of Things (IoT) is continually growing and is expected to reach more than one third of the total amount of Internet traffic by 2020. Wireless sensors pose a great challenge because of the varying radio conditions and the limited energy and computational capabilities they have. This is why we have developed an Objective Function (OF) that uses fuzzy logic to dynamically adapt to variable environments in wireless networks. Simulation results will show that the proposed algorithm increases performance compared to other solutions by up to 15% in terms of throughput and by up to 14% in terms of Packet Delivery Ratio (PDR) without compromising energy consumption.

show abstract

“…As explained in [22,24,27,31,[34][35][36], there are also other routing metrics used for a different purpose. However, none of them take into account the difference between the current queue length and the last-round queue occupancy.…”

Section: Proposed Approachmentioning

confidence: 99%

A Resource Oriented Route Selection Framework Using Contextual Information Based on Fuzzy Logic

Bhandari

Cho

2019

Electronics

View full text Add to dashboard Cite

Internet of Things (IoT) is expected to have a significant impact on city’s service provisioning and make a smart city more accessible and pragmatic since the deployment of heterogeneous smart devices in each infrastructure of cities is increasing. So far, the IPv6 routing protocol for low power and lossy networks (RPL) is considered to fit on IoT infrastructure for achieving the expected network requirements. While RPL meets the IoT network requirements quite well, there are some issues that need to be addressed, such as adaptability to network dynamics. This issue significantly limits the use of RPL in many smart city application scenarios, such as emergency alerts with high traffic flows. As part of a smart city vision, IoT applications are becoming more diverse, which requires context-awareness in routing protocols to support the behavior of the network. To address this issue, we design an objective function that performs the route selection based on fuzzy logic techniques while using contextual information from the application. For this, we present a new context-oriented objective function (COOF) that comprises both nodes as well as link metrics. Further, we suggest two new routing metrics, known as queue fluctuation index (QFI) and residual energy index (REI), which consider the status of queue utilization and remaining energy, respectively. The metrics used are designed to respond to the dynamic needs of the network. The proposed approach has been examined and evaluated in different scenarios when compared to other similar approach and default RPL objective functions. Simulation experiments are conducted in Cooja network simulator for Contiki OS. The evaluation results show that COOF can cope with network dynamics and IoT-based smart city application requirements.

show abstract

Multiple constrained QoS routing with RPL

Cited by 32 publications

References 10 publications

Routing protocol for Low-Power and Lossy Networks for heterogeneous traffic network

Routing protocol for Low-Power and Lossy Networks for heterogeneous traffic network

Fuzzy-Based Objective Function for Routing Protocol in the Internet of Things

A Resource Oriented Route Selection Framework Using Contextual Information Based on Fuzzy Logic

Contact Info

Product

Resources

About