5,569 research outputs found
TFUZZY-OF: a new method for routing protocol for low-power and lossy networks load balancing using multi-criteria decision-making
The internet of things (IoT) based on a network layer perspective includes low-power and lossy networks (LLN) that are limited in terms of power consumption, memory, and energy usage. The routing protocol used in these networks is called routing over low-power and lossy networks (RPL). Therefore, the IoT networks include smart objects that need multiple routing for their interconnections which makes traffic load balancing techniques indispensable to RPL routing protocol. In this paper, we propose a method based on fuzzy logic and the technique for the order of prioritization by similarity to the ideal solution (TOPSIS) as a well-known multi-criteria decision-making method to solve the load balancing problem by routing metrics composition. For this purpose, a combination of both link and node routing metrics namely hop count, expected transmission count, and received signal strength indicator is used. The results of simulations show that this method can increase the quality of services in terms of packet delivery ratio and average end-to-end delay
A Novel Cryptography-Based Multipath Routing Protocol for Wireless Communications
Communication in a heterogeneous, dynamic, low-power, and lossy network is dependable and seamless thanks to Mobile Ad-hoc Networks (MANETs). Low power and Lossy Networks (LLN) Routing Protocol (RPL) has been designed to make MANET routing more efficient. For different types of traffic, RPL routing can experience problems with packet transmission rates and latency. RPL is an optimal routing protocol for low power lossy networks (LLN) having the capacity to establish a path between resource constraints nodes by using standard objective functions: OF0 and MRHOF. The standard objective functions lead to a decrease in the network lifetime due to increasing the computations for establishing routing between nodes in the heterogeneous network (LLN) due to poor decision problems. Currently, conventional Mobile Ad-hoc Network (MANET) is subjected to different security issues. Weathering those storms would help if you struck a good speed-memory-storage equilibrium. This article presents a security algorithm for MANET networks that employ the Rapid Packet Loss (RPL) routing protocol. The constructed network uses optimization-based deep learning reinforcement learning for MANET route creation. An improved network security algorithm is applied after a route has been set up using (ClonQlearn). The suggested method relies on a lightweight encryption scheme that can be used for both encryption and decryption. The suggested security method uses Elliptic-curve cryptography (ClonQlearn+ECC) for a random key generation based on reinforcement learning (ClonQlearn). The simulation study showed that the proposed ClonQlearn+ECC method improved network performance over the status quo. Secure data transmission is demonstrated by the proposed ClonQlearn + ECC, which also improves network speed. The proposed ClonQlearn + ECC increased network efficiency by 8-10% in terms of packet delivery ratio, 7-13% in terms of throughput, 5-10% in terms of end-to-end delay, and 3-7% in terms of power usage variation
Evaluation of RPL’s Single Metric Objective Functions
In this paper, we evaluate the performance of RPL
(IPv6 Routing Protocol for Low Power and Lossy Networks)
based on the Objective Function being used to construct the
Destination Oriented Directed Acyclic Graph (DODAG). Using
the Cooja simulator, we compared Objective Function Zero (OF0)
with the Minimum Rank with Hysteresis Objective Function
(MRHOF) in terms of average power consumption, packet loss
ratio, and average end-to-end latency. Our study shows that RPL
performs better in terms of packet loss ratio and average endto-end
latency when MRHOF is used as an objective function.
However, the average power consumption is noticeably higher
compared to OF0
RPL routing protocol performance under sinkhole and selective forwarding attack: experimental and simulated evaluation
To make possible dream of connecting 30 billion smart devices assessable from anywhere, anytime and to fuel the engine growth of Internet of things (IoT) both in terms of physical and virtual things, Internet Engineering Task Force (IETF) came up with a concept of 6LoWPAN possessing characteristics like low power, bandwidth and cost. To bridge the routing gap and to collaborate between low power private area network and the outside world, IETF ROLL group proposed IPv6 based lightweight standard RPL (Routing protocol for low power and lossy networks). Due to large chunks of random data generated on daily basis security either externally or internally always remain bigger threat which may lead to devastation and eventually degrades the quality of service parameters affecting network resources. This paper evaluates and compare the effect of internal attacks like sinkhole and selective forwarding attacks on routing protocol for low power and lossy network topology. Widely known IoT operating system Contiki and Cooja as the simulator are used to analyse different consequences on low power and lossy network
Comparative Analysis of Objective Functions in Routing Protocol for Low Power and Lossy Networks
Internet-of-Things (IoT), a new paradigm, has led to the extensive increase in communication among the tiny and embedded network devices. Majority of those devices are power, memory, and energy constrained and are made to work in lossy environments, thus forming an important part of Low Power and Lossy Networks (LLNs). Routing Protocol for Low Power and Lossy Networks (RPL) designed by Internet Engineering Task Force (IETF) is proved to be an effective candidate for routing in such networks. RPL defines the Objective Functions (OFs) in which a set of routing metrics (like hop count, ETX and so on) are used either in an individual or combined manner for optimal path selection between the nodes of the network in terms of various performance factors like power consumed, Packet Delivery Ratio (PDR), reliability and so on. There are two standard Objective Functions- Objective function Zero (OF0) and Minimum Rank Hysteresis Objective Function (MRHOF). The former uses the hop count and the latter uses the Expected Transmission Count (ETX) as the default routing metrics to select the optimal paths. But both of them are single metric Objective Functions (OFs) and have to face various issues regarding the energy consumed, network lifetime and so on. So a number of RPL optimizations incorporating the different routing metrics in a combined way have been proposed to enhance the performance in all respects. This paper gives the comparative analysis of existing Objective Functions that are based on different routing metrics and concludes that the use of a combination of multiple metrics will further improve the RPL performance in future
IETF standardization in the field of the Internet of Things (IoT): a survey
Smart embedded objects will become an important part of what is called the Internet of Things. However, the integration of embedded devices into the Internet introduces several challenges, since many of the existing Internet technologies and protocols were not designed for this class of devices. In the past few years, there have been many efforts to enable the extension of Internet technologies to constrained devices. Initially, this resulted in proprietary protocols and architectures. Later, the integration of constrained devices into the Internet was embraced by IETF, moving towards standardized IP-based protocols. In this paper, we will briefly review the history of integrating constrained devices into the Internet, followed by an extensive overview of IETF standardization work in the 6LoWPAN, ROLL and CoRE working groups. This is complemented with a broad overview of related research results that illustrate how this work can be extended or used to tackle other problems and with a discussion on open issues and challenges. As such the aim of this paper is twofold: apart from giving readers solid insights in IETF standardization work on the Internet of Things, it also aims to encourage readers to further explore the world of Internet-connected objects, pointing to future research opportunities
History-based consistency algorithm for the trickle-timer with low-power and lossy networks
Recently, the internet of things (IoT) has become an important concept which has changed the vision of the Internet with the appearance of IPv6 over low power and lossy networks (6LoWPAN). However, these 6LoWPANs have many drawbacks because of the use of many devices with limited resources; therefore, suitable protocols such as the Routing Protocol for low power and lossy networks (RPL) were developed, and one of RPL's main components is the trickle timer algorithm, used to control and maintain the routing traffic frequency caused by a set of control messages. However, the trickle timer suffered from the short-listen problem which was handled by adding the listen-only period mechanism. This addition increased the delay in propagating transmissions and resolving the inconsistency in the network. However, to solve this problem we proposed the history based consistency algorithm (HBC), which eliminates the listen-only period based on the consistency period of the network. The proposed algorithm showed very good results. We measured the performance of HBC trickle in terms of convergence time; which was mainly affected, the power consumption and the packet delivery ratio (PDR). We made a comparison between the original trickle timer, the E-Trickle, the optimized trickle and our HBC trickle algorithm. The PDR and the power consumption showed in some cases better results under the HBC trickle compared to other trickle timers and in other cases the results were very close to the original trickle indicating the efficiency of the proposed trickle in choosing optimal routes when sending messages
Performance Comparison of the RPL and LOADng Routing Protocols in a Home Automation Scenario
RPL, the routing protocol proposed by IETF for IPv6/6LoWPAN Low Power and
Lossy Networks has significant complexity. Another protocol called LOADng, a
lightweight variant of AODV, emerges as an alternative solution. In this paper,
we compare the performance of the two protocols in a Home Automation scenario
with heterogenous traffic patterns including a mix of multipoint-to-point and
point-to-multipoint routes in realistic dense non-uniform network topologies.
We use Contiki OS and Cooja simulator to evaluate the behavior of the
ContikiRPL implementation and a basic non-optimized implementation of LOADng.
Unlike previous studies, our results show that RPL provides shorter delays,
less control overhead, and requires less memory than LOADng. Nevertheless,
enhancing LOADng with more efficient flooding and a better route storage
algorithm may improve its performance
Evolving SDN for Low-Power IoT Networks
Software Defined Networking (SDN) offers a flexible and scalable architecture
that abstracts decision making away from individual devices and provides a
programmable network platform. However, implementing a centralized SDN
architecture within the constraints of a low-power wireless network faces
considerable challenges. Not only is controller traffic subject to jitter due
to unreliable links and network contention, but the overhead generated by SDN
can severely affect the performance of other traffic. This paper addresses the
challenge of bringing high-overhead SDN architecture to IEEE 802.15.4 networks.
We explore how traditional SDN needs to evolve in order to overcome the
constraints of low-power wireless networks, and discuss protocol and
architectural optimizations necessary to reduce SDN control overhead - the main
barrier to successful implementation. We argue that interoperability with the
existing protocol stack is necessary to provide a platform for controller
discovery and coexistence with legacy networks. We consequently introduce
{\mu}SDN, a lightweight SDN framework for Contiki, with both IPv6 and
underlying routing protocol interoperability, as well as optimizing a number of
elements within the SDN architecture to reduce control overhead to practical
levels. We evaluate {\mu}SDN in terms of latency, energy, and packet delivery.
Through this evaluation we show how the cost of SDN control overhead (both
bootstrapping and management) can be reduced to a point where comparable
performance and scalability is achieved against an IEEE 802.15.4-2012 RPL-based
network. Additionally, we demonstrate {\mu}SDN through simulation: providing a
use-case where the SDN configurability can be used to provide Quality of
Service (QoS) for critical network flows experiencing interference, and we
achieve considerable reductions in delay and jitter in comparison to a scenario
without SDN
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