The document presents a new routing protocol called TFUZZY-OF for load balancing in low-power and lossy networks (LLNs) using fuzzy logic and multi-criteria decision making. It proposes using a combination of hop count, expected transmission count, and received signal strength indicator as routing metrics. The method uses fuzzy logic to integrate the node and link metrics and the TOPSIS technique to select the best parent node. Simulations show the approach can increase packet delivery ratio and decrease average end-to-end delay compared to existing routing protocols for LLNs.
Energy and Load Aware Routing Protocol for Internet of ThingsIJAAS Team
The document proposes an Energy and Load aware Routing Protocol (EL-RPL) for Internet of Things networks. EL-RPL is an enhancement of the Routing Protocol for Low Power and Lossy Networks (RPL) that uses a composite metric for route selection. The composite metric is calculated based on expected transmission count (ETX), load, and battery depletion index (BDI). The simulation results show that EL-RPL improves network lifetime by 8-12% and packet delivery ratio by 2-4% compared to other similar RPL protocols.
Congestion and Energy Aware Multipath Load Balancing Routing for LLNSIJCNCJournal
The Internet of Things (IoT) is presently in its golden era with its current technological evolution towards digital transformation. Low-power and Lossy Networks (LLNs) form the groundwork for IoT, where the IPv6 Routing Protocol for Low-Power and Lossy Networks (RPL) is designated by Internet Engineering Task Force as the benchmark protocol for routing. Although RPL, with its unique capabilities, has addressed many IoT routing requirements, Load balancing and Congestion control are the outliers. This paper builds on the RPL protocol and proposes a multipath Congestion and Energy Aware RPL (CEARPL) that alleviates the load balancing and congestion concerns associated with RPL and improves the network performance. For congestion avoidance, a Congestion and Energy Aware Objective Function (CEA-OF) is suggested during parent selection that considers multiple metrics like Child Count metric, Estimated Lifetime metric, and Queue Occupancy metric, to equally distribute the traffic in LLNs. The Queue Occupancy metric is used to detect congestion in the network, and a Multipath routing strategy is utilized to mitigate the congestion in the network. A comparison of the performance of CEA-RPL was made against the existing Objective Functions of RPL, OFO, and MRHOF, as well as COM-OF, utilizing Contiki OS 3.0's Cooja emulator. CEA-RPL projected superior results with power consumption lowering by 33%, end-to-end delay decreasing by 30%, queue loss ratio reducing by 49%, and packet receiving rate and network lifetime improving by 7% and 49%, on an average, respectively.
CONGESTION AND ENERGY AWARE MULTIPATH LOAD BALANCING ROUTING FOR LLNSIJCNCJournal
The Internet of Things (IoT) is presently in its golden era with its current technological evolution towards
digital transformation. Low-power and Lossy Networks (LLNs) form the groundwork for IoT, where the
IPv6 Routing Protocol for Low-Power and Lossy Networks (RPL) is designated by Internet Engineering
Task Force as the benchmark protocol for routing. Although RPL, with its unique capabilities, has
addressed many IoT routing requirements, Load balancing and Congestion control are the outliers. This
paper builds on the RPL protocol and proposes a multipath Congestion and Energy Aware RPL (CEARPL)
that alleviates the load balancing and congestion concerns associated with RPL and improves the network
performance. For congestion avoidance, a Congestion and Energy Aware Objective Function (CEA-OF) is
suggested during parent selection that considers multiple metrics like Child Count metric, Estimated
Lifetime metric, and Queue Occupancy metric, to equally distribute the traffic in LLNs. The Queue
Occupancy metric is used to detect congestion in the network, and a Multipath routing strategy is utilized
to mitigate the congestion in the network. A comparison of the performance of CEA-RPL was made against
the existing Objective Functions of RPL, OFO, and MRHOF, as well as COM-OF, utilizing Contiki OS
3.0's Cooja emulator. CEA-RPL projected superior results with power consumption lowering by 33%, endto-end delay decreasing by 30%, queue loss ratio reducing by 49%, and packet receiving rate and network
lifetime improving by 7% and 49%, on an average, respectively.
A hybrid objective function with empirical stability aware to improve RPL for...IJECEIAES
The diverse applications of the internet of things (IoT) require adaptable routing pro- tocol able to cope with several constraints. Thus, RPL protocol was designed to meet the needs for IoT networks categorized as low power and lossy networks (LLN). RPL uses an objective function based on specific metrics for preferred parents selection through these packets are sent to root. The single routing metric issue generally doesn’t satisfy all routing performance requirements, whereas some are improved others are degraded. In that purpose, we propose a hybrid objective function with empirical stability aware (HOFESA), implemented in the network layer of the embedded operating system CONTIKI, which combines linearly three weighty metrics namely hop count, RSSI and node energy consumption. Also, To remedy to frequent preferred parents changes problems caused by taking into account more than one metric, our proposal relies on static and empirical thresholds. The designed HOFESA, evaluated under COOJA emulator against Standard-RPL and EC-OF, showed a packet delivery ratio improvement, a decrease in the power consumption, the convergence time and DIO control messages as well as it gives network stability through an adequate churn.
Low Power and Lossy Networks Routing Protocols for IoT Environment: A SurveyBRNSSPublicationHubI
This document summarizes a survey of routing protocols for low power and lossy networks (LLNs) used in internet of things (IoT) environments. The routing protocol for LLNs (RPL) standardized by IETF in 2009 aims to address routing challenges in LLNs, but studies have found limitations that restrict its efficiency. Several proposed solutions aim to address RPL's limitations, but the survey found they are still inadequate. Analyzing problems, drawbacks, challenges and how to avoid pitfalls can help establish better routing strategies for LLNs in the future.
AN EXPERIMENTAL STUDY OF IOT NETWORKS UNDER INTERNAL ROUTING ATTACKIJCNCJournal
Internet of Things (IoT) deployments mostly relies on the establishment of Low-Power and Lossy Networks (LLNs) among a large number of constraint devices. The Internet Engineering Task Force (IETF) provides an effective IPv6-based LLN routing protocol, namely the IPv6 Routing Protocol for Low Power and Lossy Network (RPL). RPL provides adequate protection against external security attacks but stays vulnerable to internal routing attacks such as a rank attack. Malicious RPL nodes can carry out a rank attack in different forms and cause serious network performance degradation. An experimental study of the impact of the decreased rank attack on the overall network performance is presented in this paper. In also besides, it is
important to understand the main influencing factors in this context. In this study, several some many network scenarios were considered with varying network sizes, attacker properties, and topological setups. The experimental results indicate a noticeable adverse effect of the rank attack on the average PDR, delay, ETX, and beacon interval. However, such impact was varied according to network size, attacker position,
attacker neighbor count, number of attack-affected nodes, and overall hops increase. The results give a practical reference to the overall performance of RPL networks under rank attacks.
An Experimental Study of IoT Networks Under Internal Routing AttackIJCNCJournal
This document describes an experimental study of the impact of internal routing attacks on RPL networks. The study focuses specifically on the decreased rank attack. Several network scenarios were simulated using the Contiki OS, varying parameters like network size, attacker position and properties, and number of affected nodes. The results showed that the rank attack noticeably degraded key network performance metrics like packet delivery ratio, delay, and routing cost. However, the impact varied based on the scenario parameters. The results provide insight into how RPL network performance is affected under rank attacks.
A Hybrid Routing Protocol to Support Mobility in LLNsIRJET Journal
The document proposes a Hybrid Routing Protocol (HRP) to support mobility in low power and lossy networks (LLNs) without increasing overhead. HRP divides the network into subtrees using subroot nodes and employs proactive routing within subtrees and reactive routing between subtrees. This hybrid approach aims to efficiently route packets while considering node mobility. The HRP protocol utilizes various control messages like NIS, NIO and NAO to construct the network topology and maintain routing tables with localized updates when nodes move. Simulation results showed HRP improved efficiency by minimizing routing updates and overhead compared to other protocols.
Energy and Load Aware Routing Protocol for Internet of ThingsIJAAS Team
The document proposes an Energy and Load aware Routing Protocol (EL-RPL) for Internet of Things networks. EL-RPL is an enhancement of the Routing Protocol for Low Power and Lossy Networks (RPL) that uses a composite metric for route selection. The composite metric is calculated based on expected transmission count (ETX), load, and battery depletion index (BDI). The simulation results show that EL-RPL improves network lifetime by 8-12% and packet delivery ratio by 2-4% compared to other similar RPL protocols.
Congestion and Energy Aware Multipath Load Balancing Routing for LLNSIJCNCJournal
The Internet of Things (IoT) is presently in its golden era with its current technological evolution towards digital transformation. Low-power and Lossy Networks (LLNs) form the groundwork for IoT, where the IPv6 Routing Protocol for Low-Power and Lossy Networks (RPL) is designated by Internet Engineering Task Force as the benchmark protocol for routing. Although RPL, with its unique capabilities, has addressed many IoT routing requirements, Load balancing and Congestion control are the outliers. This paper builds on the RPL protocol and proposes a multipath Congestion and Energy Aware RPL (CEARPL) that alleviates the load balancing and congestion concerns associated with RPL and improves the network performance. For congestion avoidance, a Congestion and Energy Aware Objective Function (CEA-OF) is suggested during parent selection that considers multiple metrics like Child Count metric, Estimated Lifetime metric, and Queue Occupancy metric, to equally distribute the traffic in LLNs. The Queue Occupancy metric is used to detect congestion in the network, and a Multipath routing strategy is utilized to mitigate the congestion in the network. A comparison of the performance of CEA-RPL was made against the existing Objective Functions of RPL, OFO, and MRHOF, as well as COM-OF, utilizing Contiki OS 3.0's Cooja emulator. CEA-RPL projected superior results with power consumption lowering by 33%, end-to-end delay decreasing by 30%, queue loss ratio reducing by 49%, and packet receiving rate and network lifetime improving by 7% and 49%, on an average, respectively.
CONGESTION AND ENERGY AWARE MULTIPATH LOAD BALANCING ROUTING FOR LLNSIJCNCJournal
The Internet of Things (IoT) is presently in its golden era with its current technological evolution towards
digital transformation. Low-power and Lossy Networks (LLNs) form the groundwork for IoT, where the
IPv6 Routing Protocol for Low-Power and Lossy Networks (RPL) is designated by Internet Engineering
Task Force as the benchmark protocol for routing. Although RPL, with its unique capabilities, has
addressed many IoT routing requirements, Load balancing and Congestion control are the outliers. This
paper builds on the RPL protocol and proposes a multipath Congestion and Energy Aware RPL (CEARPL)
that alleviates the load balancing and congestion concerns associated with RPL and improves the network
performance. For congestion avoidance, a Congestion and Energy Aware Objective Function (CEA-OF) is
suggested during parent selection that considers multiple metrics like Child Count metric, Estimated
Lifetime metric, and Queue Occupancy metric, to equally distribute the traffic in LLNs. The Queue
Occupancy metric is used to detect congestion in the network, and a Multipath routing strategy is utilized
to mitigate the congestion in the network. A comparison of the performance of CEA-RPL was made against
the existing Objective Functions of RPL, OFO, and MRHOF, as well as COM-OF, utilizing Contiki OS
3.0's Cooja emulator. CEA-RPL projected superior results with power consumption lowering by 33%, endto-end delay decreasing by 30%, queue loss ratio reducing by 49%, and packet receiving rate and network
lifetime improving by 7% and 49%, on an average, respectively.
A hybrid objective function with empirical stability aware to improve RPL for...IJECEIAES
The diverse applications of the internet of things (IoT) require adaptable routing pro- tocol able to cope with several constraints. Thus, RPL protocol was designed to meet the needs for IoT networks categorized as low power and lossy networks (LLN). RPL uses an objective function based on specific metrics for preferred parents selection through these packets are sent to root. The single routing metric issue generally doesn’t satisfy all routing performance requirements, whereas some are improved others are degraded. In that purpose, we propose a hybrid objective function with empirical stability aware (HOFESA), implemented in the network layer of the embedded operating system CONTIKI, which combines linearly three weighty metrics namely hop count, RSSI and node energy consumption. Also, To remedy to frequent preferred parents changes problems caused by taking into account more than one metric, our proposal relies on static and empirical thresholds. The designed HOFESA, evaluated under COOJA emulator against Standard-RPL and EC-OF, showed a packet delivery ratio improvement, a decrease in the power consumption, the convergence time and DIO control messages as well as it gives network stability through an adequate churn.
Low Power and Lossy Networks Routing Protocols for IoT Environment: A SurveyBRNSSPublicationHubI
This document summarizes a survey of routing protocols for low power and lossy networks (LLNs) used in internet of things (IoT) environments. The routing protocol for LLNs (RPL) standardized by IETF in 2009 aims to address routing challenges in LLNs, but studies have found limitations that restrict its efficiency. Several proposed solutions aim to address RPL's limitations, but the survey found they are still inadequate. Analyzing problems, drawbacks, challenges and how to avoid pitfalls can help establish better routing strategies for LLNs in the future.
AN EXPERIMENTAL STUDY OF IOT NETWORKS UNDER INTERNAL ROUTING ATTACKIJCNCJournal
Internet of Things (IoT) deployments mostly relies on the establishment of Low-Power and Lossy Networks (LLNs) among a large number of constraint devices. The Internet Engineering Task Force (IETF) provides an effective IPv6-based LLN routing protocol, namely the IPv6 Routing Protocol for Low Power and Lossy Network (RPL). RPL provides adequate protection against external security attacks but stays vulnerable to internal routing attacks such as a rank attack. Malicious RPL nodes can carry out a rank attack in different forms and cause serious network performance degradation. An experimental study of the impact of the decreased rank attack on the overall network performance is presented in this paper. In also besides, it is
important to understand the main influencing factors in this context. In this study, several some many network scenarios were considered with varying network sizes, attacker properties, and topological setups. The experimental results indicate a noticeable adverse effect of the rank attack on the average PDR, delay, ETX, and beacon interval. However, such impact was varied according to network size, attacker position,
attacker neighbor count, number of attack-affected nodes, and overall hops increase. The results give a practical reference to the overall performance of RPL networks under rank attacks.
An Experimental Study of IoT Networks Under Internal Routing AttackIJCNCJournal
This document describes an experimental study of the impact of internal routing attacks on RPL networks. The study focuses specifically on the decreased rank attack. Several network scenarios were simulated using the Contiki OS, varying parameters like network size, attacker position and properties, and number of affected nodes. The results showed that the rank attack noticeably degraded key network performance metrics like packet delivery ratio, delay, and routing cost. However, the impact varied based on the scenario parameters. The results provide insight into how RPL network performance is affected under rank attacks.
A Hybrid Routing Protocol to Support Mobility in LLNsIRJET Journal
The document proposes a Hybrid Routing Protocol (HRP) to support mobility in low power and lossy networks (LLNs) without increasing overhead. HRP divides the network into subtrees using subroot nodes and employs proactive routing within subtrees and reactive routing between subtrees. This hybrid approach aims to efficiently route packets while considering node mobility. The HRP protocol utilizes various control messages like NIS, NIO and NAO to construct the network topology and maintain routing tables with localized updates when nodes move. Simulation results showed HRP improved efficiency by minimizing routing updates and overhead compared to other protocols.
RPL routing protocol performance under sinkhole and selective forwarding atta...TELKOMNIKA JOURNAL
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.
Best strategy to control data on internet-of-robotic-things in heterogeneous ...IJECEIAES
1. The document proposes a new routing strategy called Routing Information and Distance Vector (RIDV) to improve data transmission in heterogeneous networks used for Internet of Robotic Things (IoRT) applications.
2. The RIDV strategy activates the Routing Information Protocol version 2 (RIPv2) on routers in wired networks and the Ad-hoc On-demand Distance Vector (AODV) protocol in wireless networks. It unifies their routing tables to reduce congestion.
3. Simulation results show that RIDV improved quality of service over other strategies and individual protocols by reducing data and traffic drop, queue delay, and increasing throughput.
IRJET- A Survey on Mobility in RPL for IoT ApplicationsIRJET Journal
This document summarizes a research paper that surveys mobility extensions for the Routing Protocol for Low-Power and Lossy Networks (RPL) in Internet of Things (IoT) applications. It begins by introducing RPL, a routing protocol designed for low-power and lossy networks. It then discusses various proposed methods for extending RPL to support node mobility, including methods that use signal strength to detect mobility and predict new parent nodes, and methods that introduce temporary parents to reduce routing failures during mobility. The document surveys these different RPL mobility extensions and their approaches to handling mobility in low-power and lossy networks.
This document discusses challenges encountered when implementing the RPL routing protocol for low-power and lossy networks. RPL is designed to construct destination-oriented directed acyclic graphs (DODAGs) for routing in IPv6-based wireless sensor networks. The implementation study found issues like neighbor unreachability, instability from varying link qualities, and potential routing loops. Solutions proposed include defining a new objective function to improve stability and defining transmission intervals for control messages to reduce overhead and collisions. The modified RPL implementation showed improved efficiency and stability.
Multiple intrusion detection in RPL based networks IJECEIAES
Routing Protocol for Low Power and Lossy Networks based networks consists of large number of tiny sensor nodes with limited resources. These nodes are directly connected to the Internet through the border router. Hence these nodes are susceptible to different types of attacks. The possible attacks are rank attack, selective forwarding, worm hole and Denial of service attack. These attacks can be effectively identified by intrusion detection system model. The paper focuses on identification of multiple intrusions by considering the network size as 10, 40 and 100 nodes and adding 10%, 20% and 30% of malicious nodes to the considered network. Experiments are simulated using Cooja simulator on Contiki operating system. Behavior of the network is observed based on the percentage of inconsistency achieved, energy consumption, accuracy and false positive rate. Experimental results show that multiple intrusions can be detected effectively by machine learning techniques.
Abstract
The rapid growth in the Internet of Things (IoTs)
has change our life to be more intelligent and smart,
the development in the Wireless Sensors Networks
(WSNs), besides the wide use of the embedded devices
in different area like industry, home automation,
transport, agriculture and health care, which was led
the Routing Over Low-power and Lossy-network
(ROLL) working group to introduce the IPv6 Routing
Protocol for Low-Power and Lossy Networks (RPL),
therein the RPL nodes have organized topology as a
Directed Acyclic Graph (DAG) and terminated at one
root to form the Destination Oriented DAGs
(DODAGs). In this paper by using InstantContiki3.0
and CoojaGUI we analyze the DODAG formations,
the RPL control messages that are send downward
and upward routes to construct and maintain
DODAG and the Rank computation by Objective
Function (OF) for inconsistency and loop detection,
also we evaluate the performance of the RPL based
on the Expected Transmission Count (ETX) OF that
enable RPL to select and optimize routes within RPL
instance, as well as we evaluate the following metrics:
The ETX Reliability Object (ETX), Radio Duty Cycle
(RDC), energy consumption, the received packets by
the motes and neighbor count. The simulation results
show that the RPL control messages flow in consistent
manner, the DODAG root able to connect to all of the
neighbor motes, also Rank illustration shows no loops
and DODAG topology consistent, as well as the ETX
can essentially take control over DODAG formations
and it has an effects in the RDC ratio, furthermore
most of the motes show reasonable low power
consumption, also the motes show acceptable number
of the received packets.
Comparative Performance Analysis of RPL for Low Power and Lossy Networks base...Kashif Mehmood
The Internet of Things (IoT) is an extensive
network between people-people, people-things and things-things.
With the overgrown opportunities, then it also comes with a lot of
challenges proportional to the number of connected things to the
network. The IPv6 allows us to connect a huge number of things.
For resource-constrained IoT devices, the routing issues are very
thought-provoking and for this purpose an IPv6 Routing
Protocol for Low-Power and Lossy Networks (RPL) is proposed.
There are multi-HOP paths connecting nodes to the root node.
Destination Oriented Directed Acyclic Graph (DODAG) is
created taking into account different parameters such as link
costs, nodes attribute and objective functions. RPL is flexible
and it can be tuned as per application demands, therefore, the
network can be optimized by using different objective functions.
This paper presents a novel energy efficient analysis of RPL by
performing a set of simulations in COOJA simulator. The
performance evaluation of RPL is compared by introducing
different Objective functions (OF) with multiple metrics for the
network.
An Efficient Machine Learning Optimization Model for Route Establishment Mech...IJCNCJournal
Internet of Things (IoT) provides interconnection of various wireless communication devices, which offers both ubiquitous accessibility of devices and in-built intelligence capacity. IoT offers interaction with devices and provides sufficient capability advantages of networking and socialization with consideration of intermediate devices. RPL (Routing Protocol for low-power and Lossy Networks) is an attractive model for effective routing techniques in the wireless medium. The increase in demand for wireless systems in terms of energy, reliability, stability, and scale routing IPv6 over 6L0WPAN is being adopted. This research developed an optimized machine learning model (WOABC) routing protocol for route establishment in IoT networks. The constructed RPL routing protocol incorporates an optimization approach for the identification of the best and worst routes in the network. The proposed WOABC evaluates the routing path for data transmission between nodes through optimization techniques for effective route establishment. The optimization of routes is performed with whale optimization techniques. The developed whale optimization technique is incorporated in machine learning networks. Also, the proposed WOABC utilizes an optimization membership function for the identification of the optimal path in the network. The performance of the proposed WOABC is compared with existing techniques such as RPL and Speed – IoT. The comparative analysis showed that the performance of the proposed WOABC is ~3% increased throughput. The performance of the proposed WOABC is significant compared with the existing RPL routing protocol.
AN EFFICIENT MACHINE LEARNING OPTIMIZATION MODEL FOR ROUTE ESTABLISHMENT MECH...IJCNCJournal
Internet of Things (IoT) provides interconnection of various wireless communication devices, which offers
both ubiquitous accessibility of devices and in-built intelligence capacity. IoT offers interaction with
devices and provides sufficient capability advantages of networking and socialization with consideration of
intermediate devices. RPL (Routing Protocol for low-power and Lossy Networks) is an attractive model for
effective routing techniques in the wireless medium. The increase in demand for wireless systems in terms
of energy, reliability, stability, and scale routing IPv6 over 6L0WPAN is being adopted. This research
developed an optimized machine learning model (WOABC) routing protocol for route establishment in IoT
networks. The constructed RPL routing protocol incorporates an optimization approach for the
identification of the best and worst routes in the network. The proposed WOABC evaluates the routing path
for data transmission between nodes through optimization techniques for effective route establishment. The
optimization of routes is performed with whale optimization techniques. The developed whale optimization
technique is incorporated in machine learning networks. Also, the proposed WOABC utilizes an
optimization membership function for the identification of the optimal path in the network. The
performance of the proposed WOABC is compared with existing techniques such as RPL and Speed – IoT.
The comparative analysis showed that the performance of the proposed WOABC is ~3% increased
throughput. The performance of the proposed WOABC is significant compared with the existing RPL
routing protocol.
The support of multipath routing in IPv6-based internet of things IJECEIAES
The development of IPv6-based network architectures for Internet of Things (IoT) systems is a feasible approach to widen the horizon for more effective applications, but remains a challenge. Network routing needs to be effectively addressed in such environments of scarce computational and energy resources. The Internet Engineering Task Force (IETF) specified the IPv6 Routing Protocol for Low Power and Lossy Network (RPL) to provide a basic IPv6-based routing framework for IoT networks. However, the RPL design has the potential of extending its functionality to a further limit and incorporating the support of advanced routing mechanisms. These include multipath routing which has opened the doors for great improvements towards efficient energy balancing, load distribution, and even more. This paper fulfilled a need for an effective review of recent advancements in Internet of Things (IoT) networking. In particular, it presented an effective review and provided a taxonomy of the different multipath routing solutions enhancing the RPL protocol. The aim was to discover its current state and outline the importance of integrating such a mechanism into RPL to revive its potentiality to a wider range of IoT applications. This paper also discussed the latest research findings and provided some insights into plausible follow-up researches.
Performance investigations of internet protocol versions for mobile Ad-hoc ne...nooriasukmaningtyas
A mobile ad hoc network (MANET) can be seen as a mobile nodes collection
having no support of fixed infrastructure and therefore its communication is
totally dependent on the network's nodes. As a result of the mobility of
nodes, rapid and unpredictable changes occur within the mobile ad hoc
network (MANET) arrangements. Therefore, this makes the analysis of
routing protocols very crucial so as to enhance efficient communication
between the wireless nodes. IPv4 and IpV6 within the MANET is another
issue of concern. IPv4 which has been traditionally used for ages and IPv6;
predicted to be the forthcoming network architecture model is investigated
because of its protection which has been improved as well as its enormous
address space provision. The analysis on Ad Hoc On Demand Vector and
Dynamic Manet On Demand routing protocols are performed using Qualnet
simulator under the IPv4 and IPv6 standards. A thorough evaluation of the
usability and functionality of the simulator software is carried out. The
metrics for performance are; Throughput, End-to-End Delay and Average
jitter. Afterwards, analyses and summary of the results is conducted and
summarized in order to make available an assessment of their performances.
Performance Analysis of Ad-hoc on Demand Distance Vector Routing (AODV) and D...ijceronline
International Journal of Computational Engineering Research (IJCER) is dedicated to protecting personal information and will make every reasonable effort to handle collected information appropriately. All information collected, as well as related requests, will be handled as carefully and efficiently as possible in accordance with IJCER standards for integrity and objectivity.
Network Lifetime Analysis of Routing Protocols of Short Network in QualnetIOSR Journals
Abstract: A Mobile Ad-Hoc Network (MANET) is a collection of wireless mobile nodes that communicates with each other without using any existing infrastructure, access point or centralized administration. Mobile ad-hoc network have the attributes such as wireless connection, continuously changing topology, distributed operation and ease of deployment. In this paper we have compared the energy consumption of reactive, proactive & hybrid routing protocol AODV,DSR,RIP & ZRP by using different mobility model. We have analyzed the Network lifetime of protocols by varying pay load, mobility, pause time and type of traffic (CBR). A detailed simulation has been carried out in qualnet. The metrics used for performance analysis are energy consumed & battery consumption. It has been observed that RIP has better network lifetime than other.
Network Lifetime Analysis of Routing Protocols of Short Network in QualnetIOSR Journals
A Mobile Ad-Hoc Network (MANET) is a collection of wireless mobile nodes that communicates with
each other without using any existing infrastructure, access point or centralized administration. Mobile ad-hoc
network have the attributes such as wireless connection, continuously changing topology, distributed operation
and ease of deployment. In this paper we have compared the energy consumption of reactive, proactive &
hybrid routing protocol AODV,DSR,RIP & ZRP by using different mobility model. We have analyzed the
Network lifetime of protocols by varying pay load, mobility, pause time and type of traffic (CBR). A detailed
simulation has been carried out in qualnet. The metrics used for performance analysis are energy consumed &
battery consumption. It has been observed that RIP has better network lifetime than other
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
A detailed study of routing protocols for mobile ad hoc networks usingIAEME Publication
This document discusses routing protocols for mobile ad hoc networks. It analyzes the performance of several routing protocols including OLSR, DSR, AODV, ZRP and LAR using Qualnet simulator 6.1. The protocols are classified as proactive, reactive or hybrid. Proactive protocols maintain up-to-date routing tables while reactive protocols discover routes on demand. The paper evaluates and compares the protocols based on metrics like average jitter, end-to-end delay, and throughput under different numbers of stationary and mobile nodes.
A detailed study of routing protocols for mobile ad hoc networks usingIAEME Publication
This document discusses and compares several routing protocols for mobile ad hoc networks (MANETs). It evaluates the performance of the Optimized Link State Routing protocol (OLSR), Dynamic Source Routing (DSR), Ad-hoc On-demand Distance Vector routing (AODV), Location Aided Routing (LAR) and Zone Routing Protocol (ZRP) using the Qualnet simulator. The performance is evaluated based on average end-to-end delay, average jitter, and throughput under scenarios with 45 stationary and mobile nodes. The results show that protocols perform differently depending on node mobility, with OLSR and AODV generally having better performance than DSR, LAR and ZRP in terms of lower delay and
The document summarizes the design of an HDLC controller with CRC generation using VHDL. It discusses:
1. HDLC is a standard protocol that organizes data into frames for point-to-point transmission with error detection. It includes address, control and CRC fields.
2. The design of the HDLC controller includes transmitter and receiver sections. The transmitter adds flag sequences and CRC to frames. The receiver detects flags, removes stuffing and checks the CRC.
3. Simulation results show the controller can generate and check CRC to detect errors for an example transmission of an 8-bit data byte and 8-bit address.
Comparative Performance Evaluation of Ad-hoc on Demand Distance Vector Routin...ijceronline
International Journal of Computational Engineering Research (IJCER) is dedicated to protecting personal information and will make every reasonable effort to handle collected information appropriately. All information collected, as well as related requests, will be handled as carefully and efficiently as possible in accordance with IJCER standards for integrity and objectivity.
Performance Evaluation AODV, DYMO, OLSR and ZRPAD Hoc Routing Protocol for IE...pijans
In VANET high speed is the real characteristics which leads to frequent breakdown, interference etc.
Therefore Performance of adhoc routing protocols is helpful to improve the Quality of Service (QOS). In
this paper we studied various adhoc routing protocols, Reactive, Proactive & Hybrid, taking in to
consideration parameters like speed, altitude, mobility etc in real VANET scenario. The AODV and DYMO
(Reactive), OLSR (Proactive) and ZRP (hybrid) protocols are compared for IEEE 802.11(MAC) and IEEE
802.11(DCF) standard using Qualnet as a Simulation tool. Since IEEE 802.11, covers both physical and
data link layer. Hence performance of the protocols in these layers helps to make a right selection of
Protocol for high speed mobility. Varying parameters of VANET shows that in the real traffic scenarios
proactive protocol performs more efficiently for IEEE 802.11 (MAC) and IEEE 802.11(DCF).
Redefining brain tumor segmentation: a cutting-edge convolutional neural netw...IJECEIAES
Medical image analysis has witnessed significant advancements with deep learning techniques. In the domain of brain tumor segmentation, the ability to
precisely delineate tumor boundaries from magnetic resonance imaging (MRI)
scans holds profound implications for diagnosis. This study presents an ensemble convolutional neural network (CNN) with transfer learning, integrating
the state-of-the-art Deeplabv3+ architecture with the ResNet18 backbone. The
model is rigorously trained and evaluated, exhibiting remarkable performance
metrics, including an impressive global accuracy of 99.286%, a high-class accuracy of 82.191%, a mean intersection over union (IoU) of 79.900%, a weighted
IoU of 98.620%, and a Boundary F1 (BF) score of 83.303%. Notably, a detailed comparative analysis with existing methods showcases the superiority of
our proposed model. These findings underscore the model’s competence in precise brain tumor localization, underscoring its potential to revolutionize medical
image analysis and enhance healthcare outcomes. This research paves the way
for future exploration and optimization of advanced CNN models in medical
imaging, emphasizing addressing false positives and resource efficiency.
Embedded machine learning-based road conditions and driving behavior monitoringIJECEIAES
Car accident rates have increased in recent years, resulting in losses in human lives, properties, and other financial costs. An embedded machine learning-based system is developed to address this critical issue. The system can monitor road conditions, detect driving patterns, and identify aggressive driving behaviors. The system is based on neural networks trained on a comprehensive dataset of driving events, driving styles, and road conditions. The system effectively detects potential risks and helps mitigate the frequency and impact of accidents. The primary goal is to ensure the safety of drivers and vehicles. Collecting data involved gathering information on three key road events: normal street and normal drive, speed bumps, circular yellow speed bumps, and three aggressive driving actions: sudden start, sudden stop, and sudden entry. The gathered data is processed and analyzed using a machine learning system designed for limited power and memory devices. The developed system resulted in 91.9% accuracy, 93.6% precision, and 92% recall. The achieved inference time on an Arduino Nano 33 BLE Sense with a 32-bit CPU running at 64 MHz is 34 ms and requires 2.6 kB peak RAM and 139.9 kB program flash memory, making it suitable for resource-constrained embedded systems.
More Related Content
Similar to TFUZZY-OF: a new method for routing protocol for low-power and lossy networks load balancing using multi-criteria decisionmaking
RPL routing protocol performance under sinkhole and selective forwarding atta...TELKOMNIKA JOURNAL
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.
Best strategy to control data on internet-of-robotic-things in heterogeneous ...IJECEIAES
1. The document proposes a new routing strategy called Routing Information and Distance Vector (RIDV) to improve data transmission in heterogeneous networks used for Internet of Robotic Things (IoRT) applications.
2. The RIDV strategy activates the Routing Information Protocol version 2 (RIPv2) on routers in wired networks and the Ad-hoc On-demand Distance Vector (AODV) protocol in wireless networks. It unifies their routing tables to reduce congestion.
3. Simulation results show that RIDV improved quality of service over other strategies and individual protocols by reducing data and traffic drop, queue delay, and increasing throughput.
IRJET- A Survey on Mobility in RPL for IoT ApplicationsIRJET Journal
This document summarizes a research paper that surveys mobility extensions for the Routing Protocol for Low-Power and Lossy Networks (RPL) in Internet of Things (IoT) applications. It begins by introducing RPL, a routing protocol designed for low-power and lossy networks. It then discusses various proposed methods for extending RPL to support node mobility, including methods that use signal strength to detect mobility and predict new parent nodes, and methods that introduce temporary parents to reduce routing failures during mobility. The document surveys these different RPL mobility extensions and their approaches to handling mobility in low-power and lossy networks.
This document discusses challenges encountered when implementing the RPL routing protocol for low-power and lossy networks. RPL is designed to construct destination-oriented directed acyclic graphs (DODAGs) for routing in IPv6-based wireless sensor networks. The implementation study found issues like neighbor unreachability, instability from varying link qualities, and potential routing loops. Solutions proposed include defining a new objective function to improve stability and defining transmission intervals for control messages to reduce overhead and collisions. The modified RPL implementation showed improved efficiency and stability.
Multiple intrusion detection in RPL based networks IJECEIAES
Routing Protocol for Low Power and Lossy Networks based networks consists of large number of tiny sensor nodes with limited resources. These nodes are directly connected to the Internet through the border router. Hence these nodes are susceptible to different types of attacks. The possible attacks are rank attack, selective forwarding, worm hole and Denial of service attack. These attacks can be effectively identified by intrusion detection system model. The paper focuses on identification of multiple intrusions by considering the network size as 10, 40 and 100 nodes and adding 10%, 20% and 30% of malicious nodes to the considered network. Experiments are simulated using Cooja simulator on Contiki operating system. Behavior of the network is observed based on the percentage of inconsistency achieved, energy consumption, accuracy and false positive rate. Experimental results show that multiple intrusions can be detected effectively by machine learning techniques.
Abstract
The rapid growth in the Internet of Things (IoTs)
has change our life to be more intelligent and smart,
the development in the Wireless Sensors Networks
(WSNs), besides the wide use of the embedded devices
in different area like industry, home automation,
transport, agriculture and health care, which was led
the Routing Over Low-power and Lossy-network
(ROLL) working group to introduce the IPv6 Routing
Protocol for Low-Power and Lossy Networks (RPL),
therein the RPL nodes have organized topology as a
Directed Acyclic Graph (DAG) and terminated at one
root to form the Destination Oriented DAGs
(DODAGs). In this paper by using InstantContiki3.0
and CoojaGUI we analyze the DODAG formations,
the RPL control messages that are send downward
and upward routes to construct and maintain
DODAG and the Rank computation by Objective
Function (OF) for inconsistency and loop detection,
also we evaluate the performance of the RPL based
on the Expected Transmission Count (ETX) OF that
enable RPL to select and optimize routes within RPL
instance, as well as we evaluate the following metrics:
The ETX Reliability Object (ETX), Radio Duty Cycle
(RDC), energy consumption, the received packets by
the motes and neighbor count. The simulation results
show that the RPL control messages flow in consistent
manner, the DODAG root able to connect to all of the
neighbor motes, also Rank illustration shows no loops
and DODAG topology consistent, as well as the ETX
can essentially take control over DODAG formations
and it has an effects in the RDC ratio, furthermore
most of the motes show reasonable low power
consumption, also the motes show acceptable number
of the received packets.
Comparative Performance Analysis of RPL for Low Power and Lossy Networks base...Kashif Mehmood
The Internet of Things (IoT) is an extensive
network between people-people, people-things and things-things.
With the overgrown opportunities, then it also comes with a lot of
challenges proportional to the number of connected things to the
network. The IPv6 allows us to connect a huge number of things.
For resource-constrained IoT devices, the routing issues are very
thought-provoking and for this purpose an IPv6 Routing
Protocol for Low-Power and Lossy Networks (RPL) is proposed.
There are multi-HOP paths connecting nodes to the root node.
Destination Oriented Directed Acyclic Graph (DODAG) is
created taking into account different parameters such as link
costs, nodes attribute and objective functions. RPL is flexible
and it can be tuned as per application demands, therefore, the
network can be optimized by using different objective functions.
This paper presents a novel energy efficient analysis of RPL by
performing a set of simulations in COOJA simulator. The
performance evaluation of RPL is compared by introducing
different Objective functions (OF) with multiple metrics for the
network.
An Efficient Machine Learning Optimization Model for Route Establishment Mech...IJCNCJournal
Internet of Things (IoT) provides interconnection of various wireless communication devices, which offers both ubiquitous accessibility of devices and in-built intelligence capacity. IoT offers interaction with devices and provides sufficient capability advantages of networking and socialization with consideration of intermediate devices. RPL (Routing Protocol for low-power and Lossy Networks) is an attractive model for effective routing techniques in the wireless medium. The increase in demand for wireless systems in terms of energy, reliability, stability, and scale routing IPv6 over 6L0WPAN is being adopted. This research developed an optimized machine learning model (WOABC) routing protocol for route establishment in IoT networks. The constructed RPL routing protocol incorporates an optimization approach for the identification of the best and worst routes in the network. The proposed WOABC evaluates the routing path for data transmission between nodes through optimization techniques for effective route establishment. The optimization of routes is performed with whale optimization techniques. The developed whale optimization technique is incorporated in machine learning networks. Also, the proposed WOABC utilizes an optimization membership function for the identification of the optimal path in the network. The performance of the proposed WOABC is compared with existing techniques such as RPL and Speed – IoT. The comparative analysis showed that the performance of the proposed WOABC is ~3% increased throughput. The performance of the proposed WOABC is significant compared with the existing RPL routing protocol.
AN EFFICIENT MACHINE LEARNING OPTIMIZATION MODEL FOR ROUTE ESTABLISHMENT MECH...IJCNCJournal
Internet of Things (IoT) provides interconnection of various wireless communication devices, which offers
both ubiquitous accessibility of devices and in-built intelligence capacity. IoT offers interaction with
devices and provides sufficient capability advantages of networking and socialization with consideration of
intermediate devices. RPL (Routing Protocol for low-power and Lossy Networks) is an attractive model for
effective routing techniques in the wireless medium. The increase in demand for wireless systems in terms
of energy, reliability, stability, and scale routing IPv6 over 6L0WPAN is being adopted. This research
developed an optimized machine learning model (WOABC) routing protocol for route establishment in IoT
networks. The constructed RPL routing protocol incorporates an optimization approach for the
identification of the best and worst routes in the network. The proposed WOABC evaluates the routing path
for data transmission between nodes through optimization techniques for effective route establishment. The
optimization of routes is performed with whale optimization techniques. The developed whale optimization
technique is incorporated in machine learning networks. Also, the proposed WOABC utilizes an
optimization membership function for the identification of the optimal path in the network. The
performance of the proposed WOABC is compared with existing techniques such as RPL and Speed – IoT.
The comparative analysis showed that the performance of the proposed WOABC is ~3% increased
throughput. The performance of the proposed WOABC is significant compared with the existing RPL
routing protocol.
The support of multipath routing in IPv6-based internet of things IJECEIAES
The development of IPv6-based network architectures for Internet of Things (IoT) systems is a feasible approach to widen the horizon for more effective applications, but remains a challenge. Network routing needs to be effectively addressed in such environments of scarce computational and energy resources. The Internet Engineering Task Force (IETF) specified the IPv6 Routing Protocol for Low Power and Lossy Network (RPL) to provide a basic IPv6-based routing framework for IoT networks. However, the RPL design has the potential of extending its functionality to a further limit and incorporating the support of advanced routing mechanisms. These include multipath routing which has opened the doors for great improvements towards efficient energy balancing, load distribution, and even more. This paper fulfilled a need for an effective review of recent advancements in Internet of Things (IoT) networking. In particular, it presented an effective review and provided a taxonomy of the different multipath routing solutions enhancing the RPL protocol. The aim was to discover its current state and outline the importance of integrating such a mechanism into RPL to revive its potentiality to a wider range of IoT applications. This paper also discussed the latest research findings and provided some insights into plausible follow-up researches.
Performance investigations of internet protocol versions for mobile Ad-hoc ne...nooriasukmaningtyas
A mobile ad hoc network (MANET) can be seen as a mobile nodes collection
having no support of fixed infrastructure and therefore its communication is
totally dependent on the network's nodes. As a result of the mobility of
nodes, rapid and unpredictable changes occur within the mobile ad hoc
network (MANET) arrangements. Therefore, this makes the analysis of
routing protocols very crucial so as to enhance efficient communication
between the wireless nodes. IPv4 and IpV6 within the MANET is another
issue of concern. IPv4 which has been traditionally used for ages and IPv6;
predicted to be the forthcoming network architecture model is investigated
because of its protection which has been improved as well as its enormous
address space provision. The analysis on Ad Hoc On Demand Vector and
Dynamic Manet On Demand routing protocols are performed using Qualnet
simulator under the IPv4 and IPv6 standards. A thorough evaluation of the
usability and functionality of the simulator software is carried out. The
metrics for performance are; Throughput, End-to-End Delay and Average
jitter. Afterwards, analyses and summary of the results is conducted and
summarized in order to make available an assessment of their performances.
Performance Analysis of Ad-hoc on Demand Distance Vector Routing (AODV) and D...ijceronline
International Journal of Computational Engineering Research (IJCER) is dedicated to protecting personal information and will make every reasonable effort to handle collected information appropriately. All information collected, as well as related requests, will be handled as carefully and efficiently as possible in accordance with IJCER standards for integrity and objectivity.
Network Lifetime Analysis of Routing Protocols of Short Network in QualnetIOSR Journals
Abstract: A Mobile Ad-Hoc Network (MANET) is a collection of wireless mobile nodes that communicates with each other without using any existing infrastructure, access point or centralized administration. Mobile ad-hoc network have the attributes such as wireless connection, continuously changing topology, distributed operation and ease of deployment. In this paper we have compared the energy consumption of reactive, proactive & hybrid routing protocol AODV,DSR,RIP & ZRP by using different mobility model. We have analyzed the Network lifetime of protocols by varying pay load, mobility, pause time and type of traffic (CBR). A detailed simulation has been carried out in qualnet. The metrics used for performance analysis are energy consumed & battery consumption. It has been observed that RIP has better network lifetime than other.
Network Lifetime Analysis of Routing Protocols of Short Network in QualnetIOSR Journals
A Mobile Ad-Hoc Network (MANET) is a collection of wireless mobile nodes that communicates with
each other without using any existing infrastructure, access point or centralized administration. Mobile ad-hoc
network have the attributes such as wireless connection, continuously changing topology, distributed operation
and ease of deployment. In this paper we have compared the energy consumption of reactive, proactive &
hybrid routing protocol AODV,DSR,RIP & ZRP by using different mobility model. We have analyzed the
Network lifetime of protocols by varying pay load, mobility, pause time and type of traffic (CBR). A detailed
simulation has been carried out in qualnet. The metrics used for performance analysis are energy consumed &
battery consumption. It has been observed that RIP has better network lifetime than other
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
A detailed study of routing protocols for mobile ad hoc networks usingIAEME Publication
This document discusses routing protocols for mobile ad hoc networks. It analyzes the performance of several routing protocols including OLSR, DSR, AODV, ZRP and LAR using Qualnet simulator 6.1. The protocols are classified as proactive, reactive or hybrid. Proactive protocols maintain up-to-date routing tables while reactive protocols discover routes on demand. The paper evaluates and compares the protocols based on metrics like average jitter, end-to-end delay, and throughput under different numbers of stationary and mobile nodes.
A detailed study of routing protocols for mobile ad hoc networks usingIAEME Publication
This document discusses and compares several routing protocols for mobile ad hoc networks (MANETs). It evaluates the performance of the Optimized Link State Routing protocol (OLSR), Dynamic Source Routing (DSR), Ad-hoc On-demand Distance Vector routing (AODV), Location Aided Routing (LAR) and Zone Routing Protocol (ZRP) using the Qualnet simulator. The performance is evaluated based on average end-to-end delay, average jitter, and throughput under scenarios with 45 stationary and mobile nodes. The results show that protocols perform differently depending on node mobility, with OLSR and AODV generally having better performance than DSR, LAR and ZRP in terms of lower delay and
The document summarizes the design of an HDLC controller with CRC generation using VHDL. It discusses:
1. HDLC is a standard protocol that organizes data into frames for point-to-point transmission with error detection. It includes address, control and CRC fields.
2. The design of the HDLC controller includes transmitter and receiver sections. The transmitter adds flag sequences and CRC to frames. The receiver detects flags, removes stuffing and checks the CRC.
3. Simulation results show the controller can generate and check CRC to detect errors for an example transmission of an 8-bit data byte and 8-bit address.
Comparative Performance Evaluation of Ad-hoc on Demand Distance Vector Routin...ijceronline
International Journal of Computational Engineering Research (IJCER) is dedicated to protecting personal information and will make every reasonable effort to handle collected information appropriately. All information collected, as well as related requests, will be handled as carefully and efficiently as possible in accordance with IJCER standards for integrity and objectivity.
Performance Evaluation AODV, DYMO, OLSR and ZRPAD Hoc Routing Protocol for IE...pijans
In VANET high speed is the real characteristics which leads to frequent breakdown, interference etc.
Therefore Performance of adhoc routing protocols is helpful to improve the Quality of Service (QOS). In
this paper we studied various adhoc routing protocols, Reactive, Proactive & Hybrid, taking in to
consideration parameters like speed, altitude, mobility etc in real VANET scenario. The AODV and DYMO
(Reactive), OLSR (Proactive) and ZRP (hybrid) protocols are compared for IEEE 802.11(MAC) and IEEE
802.11(DCF) standard using Qualnet as a Simulation tool. Since IEEE 802.11, covers both physical and
data link layer. Hence performance of the protocols in these layers helps to make a right selection of
Protocol for high speed mobility. Varying parameters of VANET shows that in the real traffic scenarios
proactive protocol performs more efficiently for IEEE 802.11 (MAC) and IEEE 802.11(DCF).
Similar to TFUZZY-OF: a new method for routing protocol for low-power and lossy networks load balancing using multi-criteria decisionmaking (20)
Redefining brain tumor segmentation: a cutting-edge convolutional neural netw...IJECEIAES
Medical image analysis has witnessed significant advancements with deep learning techniques. In the domain of brain tumor segmentation, the ability to
precisely delineate tumor boundaries from magnetic resonance imaging (MRI)
scans holds profound implications for diagnosis. This study presents an ensemble convolutional neural network (CNN) with transfer learning, integrating
the state-of-the-art Deeplabv3+ architecture with the ResNet18 backbone. The
model is rigorously trained and evaluated, exhibiting remarkable performance
metrics, including an impressive global accuracy of 99.286%, a high-class accuracy of 82.191%, a mean intersection over union (IoU) of 79.900%, a weighted
IoU of 98.620%, and a Boundary F1 (BF) score of 83.303%. Notably, a detailed comparative analysis with existing methods showcases the superiority of
our proposed model. These findings underscore the model’s competence in precise brain tumor localization, underscoring its potential to revolutionize medical
image analysis and enhance healthcare outcomes. This research paves the way
for future exploration and optimization of advanced CNN models in medical
imaging, emphasizing addressing false positives and resource efficiency.
Embedded machine learning-based road conditions and driving behavior monitoringIJECEIAES
Car accident rates have increased in recent years, resulting in losses in human lives, properties, and other financial costs. An embedded machine learning-based system is developed to address this critical issue. The system can monitor road conditions, detect driving patterns, and identify aggressive driving behaviors. The system is based on neural networks trained on a comprehensive dataset of driving events, driving styles, and road conditions. The system effectively detects potential risks and helps mitigate the frequency and impact of accidents. The primary goal is to ensure the safety of drivers and vehicles. Collecting data involved gathering information on three key road events: normal street and normal drive, speed bumps, circular yellow speed bumps, and three aggressive driving actions: sudden start, sudden stop, and sudden entry. The gathered data is processed and analyzed using a machine learning system designed for limited power and memory devices. The developed system resulted in 91.9% accuracy, 93.6% precision, and 92% recall. The achieved inference time on an Arduino Nano 33 BLE Sense with a 32-bit CPU running at 64 MHz is 34 ms and requires 2.6 kB peak RAM and 139.9 kB program flash memory, making it suitable for resource-constrained embedded systems.
Advanced control scheme of doubly fed induction generator for wind turbine us...IJECEIAES
This paper describes a speed control device for generating electrical energy on an electricity network based on the doubly fed induction generator (DFIG) used for wind power conversion systems. At first, a double-fed induction generator model was constructed. A control law is formulated to govern the flow of energy between the stator of a DFIG and the energy network using three types of controllers: proportional integral (PI), sliding mode controller (SMC) and second order sliding mode controller (SOSMC). Their different results in terms of power reference tracking, reaction to unexpected speed fluctuations, sensitivity to perturbations, and resilience against machine parameter alterations are compared. MATLAB/Simulink was used to conduct the simulations for the preceding study. Multiple simulations have shown very satisfying results, and the investigations demonstrate the efficacy and power-enhancing capabilities of the suggested control system.
Neural network optimizer of proportional-integral-differential controller par...IJECEIAES
Wide application of proportional-integral-differential (PID)-regulator in industry requires constant improvement of methods of its parameters adjustment. The paper deals with the issues of optimization of PID-regulator parameters with the use of neural network technology methods. A methodology for choosing the architecture (structure) of neural network optimizer is proposed, which consists in determining the number of layers, the number of neurons in each layer, as well as the form and type of activation function. Algorithms of neural network training based on the application of the method of minimizing the mismatch between the regulated value and the target value are developed. The method of back propagation of gradients is proposed to select the optimal training rate of neurons of the neural network. The neural network optimizer, which is a superstructure of the linear PID controller, allows increasing the regulation accuracy from 0.23 to 0.09, thus reducing the power consumption from 65% to 53%. The results of the conducted experiments allow us to conclude that the created neural superstructure may well become a prototype of an automatic voltage regulator (AVR)-type industrial controller for tuning the parameters of the PID controller.
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This research paper introduces an innovative modulation technique for controlling a 3-level flying capacitor multilevel inverter (FCMLI), aiming to streamline the modulation process in contrast to conventional methods. The proposed
simplified modulation technique paves the way for more straightforward and
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integration into modern power electronic systems. Through the amalgamation of
sinusoidal pulse width modulation (SPWM) with a high-frequency square wave
pulse, this controlling technique attains energy equilibrium across the coupling
capacitor. The modulation scheme incorporates a simplified switching pattern
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A review on features and methods of potential fishing zoneIJECEIAES
This review focuses on the importance of identifying potential fishing zones in seawater for sustainable fishing practices. It explores features like sea surface temperature (SST) and sea surface height (SSH), along with classification methods such as classifiers. The features like SST, SSH, and different classifiers used to classify the data, have been figured out in this review study. This study underscores the importance of examining potential fishing zones using advanced analytical techniques. It thoroughly explores the methodologies employed by researchers, covering both past and current approaches. The examination centers on data characteristics and the application of classification algorithms for classification of potential fishing zones. Furthermore, the prediction of potential fishing zones relies significantly on the effectiveness of classification algorithms. Previous research has assessed the performance of models like support vector machines, naïve Bayes, and artificial neural networks (ANN). In the previous result, the results of support vector machine (SVM) were 97.6% more accurate than naive Bayes's 94.2% to classify test data for fisheries classification. By considering the recent works in this area, several recommendations for future works are presented to further improve the performance of the potential fishing zone models, which is important to the fisheries community.
Electrical signal interference minimization using appropriate core material f...IJECEIAES
As demand for smaller, quicker, and more powerful devices rises, Moore's law is strictly followed. The industry has worked hard to make little devices that boost productivity. The goal is to optimize device density. Scientists are reducing connection delays to improve circuit performance. This helped them understand three-dimensional integrated circuit (3D IC) concepts, which stack active devices and create vertical connections to diminish latency and lower interconnects. Electrical involvement is a big worry with 3D integrates circuits. Researchers have developed and tested through silicon via (TSV) and substrates to decrease electrical wave involvement. This study illustrates a novel noise coupling reduction method using several electrical involvement models. A 22% drop in electrical involvement from wave-carrying to victim TSVs introduces this new paradigm and improves system performance even at higher THz frequencies.
Electric vehicle and photovoltaic advanced roles in enhancing the financial p...IJECEIAES
Climate change's impact on the planet forced the United Nations and governments to promote green energies and electric transportation. The deployments of photovoltaic (PV) and electric vehicle (EV) systems gained stronger momentum due to their numerous advantages over fossil fuel types. The advantages go beyond sustainability to reach financial support and stability. The work in this paper introduces the hybrid system between PV and EV to support industrial and commercial plants. This paper covers the theoretical framework of the proposed hybrid system including the required equation to complete the cost analysis when PV and EV are present. In addition, the proposed design diagram which sets the priorities and requirements of the system is presented. The proposed approach allows setup to advance their power stability, especially during power outages. The presented information supports researchers and plant owners to complete the necessary analysis while promoting the deployment of clean energy. The result of a case study that represents a dairy milk farmer supports the theoretical works and highlights its advanced benefits to existing plants. The short return on investment of the proposed approach supports the paper's novelty approach for the sustainable electrical system. In addition, the proposed system allows for an isolated power setup without the need for a transmission line which enhances the safety of the electrical network
Bibliometric analysis highlighting the role of women in addressing climate ch...IJECEIAES
Fossil fuel consumption increased quickly, contributing to climate change
that is evident in unusual flooding and draughts, and global warming. Over
the past ten years, women's involvement in society has grown dramatically,
and they succeeded in playing a noticeable role in reducing climate change.
A bibliometric analysis of data from the last ten years has been carried out to
examine the role of women in addressing the climate change. The analysis's
findings discussed the relevant to the sustainable development goals (SDGs),
particularly SDG 7 and SDG 13. The results considered contributions made
by women in the various sectors while taking geographic dispersion into
account. The bibliometric analysis delves into topics including women's
leadership in environmental groups, their involvement in policymaking, their
contributions to sustainable development projects, and the influence of
gender diversity on attempts to mitigate climate change. This study's results
highlight how women have influenced policies and actions related to climate
change, point out areas of research deficiency and recommendations on how
to increase role of the women in addressing the climate change and
achieving sustainability. To achieve more successful results, this initiative
aims to highlight the significance of gender equality and encourage
inclusivity in climate change decision-making processes.
Voltage and frequency control of microgrid in presence of micro-turbine inter...IJECEIAES
The active and reactive load changes have a significant impact on voltage
and frequency. In this paper, in order to stabilize the microgrid (MG) against
load variations in islanding mode, the active and reactive power of all
distributed generators (DGs), including energy storage (battery), diesel
generator, and micro-turbine, are controlled. The micro-turbine generator is
connected to MG through a three-phase to three-phase matrix converter, and
the droop control method is applied for controlling the voltage and
frequency of MG. In addition, a method is introduced for voltage and
frequency control of micro-turbines in the transition state from gridconnected mode to islanding mode. A novel switching strategy of the matrix
converter is used for converting the high-frequency output voltage of the
micro-turbine to the grid-side frequency of the utility system. Moreover,
using the switching strategy, the low-order harmonics in the output current
and voltage are not produced, and consequently, the size of the output filter
would be reduced. In fact, the suggested control strategy is load-independent
and has no frequency conversion restrictions. The proposed approach for
voltage and frequency regulation demonstrates exceptional performance and
favorable response across various load alteration scenarios. The suggested
strategy is examined in several scenarios in the MG test systems, and the
simulation results are addressed.
Enhancing battery system identification: nonlinear autoregressive modeling fo...IJECEIAES
Precisely characterizing Li-ion batteries is essential for optimizing their
performance, enhancing safety, and prolonging their lifespan across various
applications, such as electric vehicles and renewable energy systems. This
article introduces an innovative nonlinear methodology for system
identification of a Li-ion battery, employing a nonlinear autoregressive with
exogenous inputs (NARX) model. The proposed approach integrates the
benefits of nonlinear modeling with the adaptability of the NARX structure,
facilitating a more comprehensive representation of the intricate
electrochemical processes within the battery. Experimental data collected
from a Li-ion battery operating under diverse scenarios are employed to
validate the effectiveness of the proposed methodology. The identified
NARX model exhibits superior accuracy in predicting the battery's behavior
compared to traditional linear models. This study underscores the
importance of accounting for nonlinearities in battery modeling, providing
insights into the intricate relationships between state-of-charge, voltage, and
current under dynamic conditions.
Smart grid deployment: from a bibliometric analysis to a surveyIJECEIAES
Smart grids are one of the last decades' innovations in electrical energy.
They bring relevant advantages compared to the traditional grid and
significant interest from the research community. Assessing the field's
evolution is essential to propose guidelines for facing new and future smart
grid challenges. In addition, knowing the main technologies involved in the
deployment of smart grids (SGs) is important to highlight possible
shortcomings that can be mitigated by developing new tools. This paper
contributes to the research trends mentioned above by focusing on two
objectives. First, a bibliometric analysis is presented to give an overview of
the current research level about smart grid deployment. Second, a survey of
the main technological approaches used for smart grid implementation and
their contributions are highlighted. To that effect, we searched the Web of
Science (WoS), and the Scopus databases. We obtained 5,663 documents
from WoS and 7,215 from Scopus on smart grid implementation or
deployment. With the extraction limitation in the Scopus database, 5,872 of
the 7,215 documents were extracted using a multi-step process. These two
datasets have been analyzed using a bibliometric tool called bibliometrix.
The main outputs are presented with some recommendations for future
research.
Use of analytical hierarchy process for selecting and prioritizing islanding ...IJECEIAES
One of the problems that are associated to power systems is islanding
condition, which must be rapidly and properly detected to prevent any
negative consequences on the system's protection, stability, and security.
This paper offers a thorough overview of several islanding detection
strategies, which are divided into two categories: classic approaches,
including local and remote approaches, and modern techniques, including
techniques based on signal processing and computational intelligence.
Additionally, each approach is compared and assessed based on several
factors, including implementation costs, non-detected zones, declining
power quality, and response times using the analytical hierarchy process
(AHP). The multi-criteria decision-making analysis shows that the overall
weight of passive methods (24.7%), active methods (7.8%), hybrid methods
(5.6%), remote methods (14.5%), signal processing-based methods (26.6%),
and computational intelligent-based methods (20.8%) based on the
comparison of all criteria together. Thus, it can be seen from the total weight
that hybrid approaches are the least suitable to be chosen, while signal
processing-based methods are the most appropriate islanding detection
method to be selected and implemented in power system with respect to the
aforementioned factors. Using Expert Choice software, the proposed
hierarchy model is studied and examined.
Enhancing of single-stage grid-connected photovoltaic system using fuzzy logi...IJECEIAES
The power generated by photovoltaic (PV) systems is influenced by
environmental factors. This variability hampers the control and utilization of
solar cells' peak output. In this study, a single-stage grid-connected PV
system is designed to enhance power quality. Our approach employs fuzzy
logic in the direct power control (DPC) of a three-phase voltage source
inverter (VSI), enabling seamless integration of the PV connected to the
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particularly in steady-state and varying weather conditions. For solar
irradiances of 500 and 1,000 W/m2
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method reduces the total harmonic distortion (THD) of the injected current
to the grid by approximately 46% and 38% compared to conventional
methods, respectively. Furthermore, we compare the simulation results with
IEEE standards to evaluate the system's grid compatibility.
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TFUZZY-OF: a new method for routing protocol for low-power and lossy networks load balancing using multi-criteria decisionmaking
1. International Journal of Electrical and Computer Engineering (IJECE)
Vol. 13, No. 3, June 2023, pp. 3474~3483
ISSN: 2088-8708, DOI: 10.11591/ijece.v13i3.pp3474-3483 3474
Journal homepage: http://ijece.iaescore.com
TFUZZY-OF: a new method for routing protocol for low-power
and lossy networks load balancing using multi-criteria decision-
making
Ali Kamil Ahmed1
, Behnam Farzaneh2
, Elahe Boochanpour3
, Emad Alizadeh2
, Shahin Farzaneh4
1
Department of Materials Engineering, University of Technology-Iraq, Baghdad, Iraq
2
Department of Electrical and Computer Engineering, Isfahan University of Technology, Isfahan, Iran
3
Department of Computer Engineering, Islamic Azad University South Tehran Branch, Tehran, Iran
4
Department of Civil Engineering, University of Mohaghegh Ardabili, Ardabil, Iran
Article Info ABSTRACT
Article history:
Received Jun 22, 2022
Revised Sep 19, 2022
Accepted Oct 1, 2022
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.
Keywords:
Fuzzy logic
Internet of thing
Load balancing
Multi criteria decision making
Objective function
Routing protocol
This is an open access article under the CC BY-SA license.
Corresponding Author:
Ali Kamil Ahmed
Department of Materials Engineering, University of Technology-Iraq
Al-Wehda Neighborhood, Baghdad, Iraq
Email: ali.k.ahmed@uotechnology.edu.iq
1. INTRODUCTION
The internet of things (IoT) as a new idea in the world of networks was introduced in [1]. IoT is a
system consisting of computing devices or objects including radio frequency identification (RFID), near-field
communication (NFC), sensors, actuators, and mobile phones that possess the capabilities for transferring
data over a network. The IoT and its services are used in a variety of areas such as agriculture, energy, home
and building, smart cities, healthcare, industry, transportation, and many other areas. One of the most
important features of IoT is the heterogeneity of objects. Given that many objects and physical and virtual
identities around us are interconnected in IoT, a large amount of heterogeneous data must be computed in IoT
networks [2]–[9].
One of the key components of IoT is the low-power and lossy networks (LLNs) [10], a set of
interconnected tiny, lossy, and low-powered devices which are limited in terms of energy, memory, and
computational power. To design a standard routing protocol for IoT, the internet engineering task force (IETF)
introduced a new 6LoWPAN-compliant routing protocol for LLN networks called routing over low-power and
lossy networks (RPL) [11]. The RPL routing protocol is a distance-vector protocol that organizes nodes as
destination-oriented directed acyclic graphs (DODAG) based on a collection of routing metrics in a network.
2. Int J Elec & Comp Eng ISSN: 2088-8708
TFUZZY-OF: A new method for routing protocol for low-power and lossy networks … (Ali Kamil Ahmed)
3475
Moreover, parent selection for each node in the network is done via objective functions (OF). As a default in
RPL, there are two OFs namely objective function zero (OF0) [12] and minimum rank with hysteresis
objective function (MRHOF) [13] for parent selection by a single routing metric that is unable to handle heavy
network traffic. Therefore, traffic load balancing problems in RPL-based networks are very important.
In this paper, we concentrate on load balancing in the RPL-based networks using fuzzy logic [14]
and multi-criteria decision-making (MCDM) [15] methods. The MCDM method can be used for load
balancing in RPL-based networks as an appropriate technique and promising approach. The major
contributions of our paper are that we i) represent a comprehensive study of load balancing in the RPL-based
networks based on various routing metrics, ii) introduce a novel objective function by combining three
routing metrics namely hop count (HC), received signal strength indicator (RSSI), and expected transmission
count (ETX), iii) use fuzzy logic and the technique for the order of prioritization by similarity to ideal
solution (TOPSIS) [16] method as a well-known MCDM technique for best parent selection in RPL, and
iv) implement and evaluate the proposed method using Cooja [17] simulator based on Contiki-NG operating
systems in terms of two performance metrics: packet delivery ratio (PDR), average end-to-end delay (E2ED).
The idea behind the usage of mixed link and node metrics arrives from the constraints that a single
metric supplies. The best parent selection is one advantage of the objective function with a single metric, but
it also has certain restrictions. It is obvious that a single metric technique increases some performances but
may decrease others, leading to the conclusion that the single metric approach does not fully meet the needs
of the application. For this purpose, we proposed a combination of both link and node metrics namely hop
count, RSSI and ETX. The rest of this paper is structured as follows. The RPL protocol and objective
function in RPL are introduced in section 2. Section 3 presents the related works. The proposed method is
described in section 4 and evaluated in section 5 and finally, the conclusion is discussed in section 6.
2. PRELIMINARIES
2.1. The RPL routing protocol
The RPL is a distance-vector routing protocol according to the destination-oriented directed acyclic
graphs (DODAG). There is some basic terminology, and key concepts in RPL must be described as follows
[4], [10]. A directed acyclic graph (DAG) refers to a graph that has no cycle in the network. DODAG root
(Sink) manages LLN nodes and gathers local data, and finally connects LLN nodes to the internet as an edge
router. Destination-oriented DAG (DODAG) is a loop-free tree structure of nodes forming a network which
have a single border router connecting the network to an IPv6 backbone, this network is identified by a
DODAGID tag. The objective function (OF) is a set of rules and policies that a node uses to select the
optimal path with respect to the application requirements such as minimum energy consumption or residual
energy. RPL instance is a network comprised of one or more DODAGs that have identical OF and are
identified by RPLInstanceID. Rank is the distance from the root (sink) node. For each node, the distance
must be greater than the Rank of its parent node to avoid routing loops in the DODAG. The DODAG version
is a tag manipulated by a border router in DODAG. Goal refers to where a DODAG demands to attain and
may be a wired or wireless network. Grounded is when a DODAG attained its goal. Floating is when a DODAG
does not reach its goal. A storing mode keeps a downward routing table at each node of DODAG, while a
non-storing mode sends all traffic to the root node, and finally, it sends traffic to the children’s nodes. DODAG
parent means that a parent of a node (child) is another node on a path toward the root node. The parent has a
lower rank than its children’s nodes. DODAG sibling means that a sibling of a node in the DODAG is any
neighbor node that is placed at the same rank. Sub-DODAG refers to every subtree belong a DODAG.
RPL routing protocol uses four types of control messages [18], [19], which are DODAG information
object (DIO), DODAG information solicitation (DIS), DODAG advertisement object (DAO), destination
advertisement object acknowledgment (DAO-Ack). To construct DODAG, the sink or root starts to
propagate DIO messages through the network. The nodes receiving a DIO control message decide whether to
connect the DODAG or not based on the OF. Joint nodes re-propagate the DIO message, and this process
will take until all nodes join and construct a tree.
2.2. Objective function
As we mentioned in section 1, there are two different standard OFs namely OF0 and MRHOF. The
OF0 considers the hop count as a routing metric to find the shortest path to the root. Considering only hop
count as the only metric in OF0 may cause low link quality, short lifetime, or unreliable path in LLNs. To
overcome the mentioned problem in OF0, the MRHOF is proposed to select the path with the lowest cost. It
uses the ETX metric to calculate the cost of each path. The most popular routing metrics can be separated
into node metrics and link metrics groups [20]. The composite routing metrics should be well-defined and
scalable. Table 1 shows the classification of some routing metrics.
3. ISSN: 2088-8708
Int J Elec & Comp Eng, Vol. 13, No. 3, June 2023: 3474-3483
3476
Table 1. Classification of routing metrics in the RPL
Metric Group Metric Name Description
Node Metrics Hop count (HC) The number of hops among nodes in terms of the node's distance from the root.
Energy consumption (EC) This metric shows the energy spent in the network via sensor nodes.
Residual energy (RE) This metric refers to the remaining energy present in the network.
Buffer occupancy (BO) The data packets before forwarding in the wireless channel are stored in the buffer
of nodes. This metric refers to how much the buffer of the node is occupied.
Link Metrics Expected transmission
count (ETX)
The number of expected transmitted count for packets to successfully receive at the
destination, called ETX.
Expected transmission time
(ETT)
This metric refers to the expected time at the MAC layer for successful packet
forwarding.
Expected Lifetime (ELT) This metric is defined based on the energy consumption of nodes in listening and
transmitting modes (i.e., Rx and Tx).
Received signal strength
indicator (RSSI)
The RSSI is a famous radio link estimator and is defined as the power measurement
in received signals.
3. RELATED WORKS
Several research on load-balancing techniques and the enhancement of OFs performance in RPL
have been published recently. OF0 [12] uses hop count (HC) as a routing metric to carry out parent selection.
In other words, the shortest path is selected from each node to the root during DODAG construction. Using
hop count as the only metric may consider parents with poor connectivity. Thus, MRHOF [13] was proposed
to resolve this problem by using a hysteresis mechanism besides the selection of a low-rank path. On the
other hand, most previous versions of RPL use OF0 or MRHOF as their default OF, whereas other
researchers like Gaddour et al. [21] merge them with their proposed idea. Popular routing metrics such as
hop count or ETX or merging them are very common in research papers. In another work, the lexical metric
composition of two routing metrics is defined as follows: The first metric providing low or high value would
be used to choose the best parent among candidates. If the value of the first metric is equal for two or more
candidates, the second metric would be checked to choose the best parent. Additive metric composition is
another common technique in which a set of metrics are merged to provide one common metric. Many
researchers have used these two techniques, such as Nassar et al. [22], who presented an additive metric
called OFQS. The OFQS is the result of a combination of ETX, power state, and delay. Simulation results
showed that OFQS performed better than MRHOF and OF0 in terms of E2ED, network lifetime, and PDR. In
[23], a new load-balancing algorithm named smart energy efficient objective function (SEEOF) was
proposed. In SEEOF an additive metric constructed from drain rate with the residual energy is provided. The
simulation results depict that the SEEOF improves PDR and network lifetime in comparison with MRHOF
and OF0.
In [24], a modified trickle mechanism for RPL protocol is presented. Due to the balanced load and
optimized trickle mechanism, the network lifetime has increased in this method. Santiago et al. [25] proposed
a technique using the nested un-weighted pair group method with event rate (UPGM) to address the load
balancing problem of RPL. This method could enhance network lifetime, while scalability and overhead did
not examine. Taghizadeh et al. [26] concentrated on network lifetime and packet loss under dynamic and
heavy loads. The authors of this paper introduced the context-aware and load-balancing RPL (CLRPL) load-
balancing protocol, a context-aware load-balancing technique. First, the authors introduced a novel objective
function called context-aware objective function (CAOF) that uses a combination of remaining energy,
parent rank, and ETX routing metrics for the calculation of the node's rank. Second, for the sake of load
balancing, the authors introduced a novel metric called context-aware routing metric (CARF) which
considers the node's context and uses remaining energy and queue utilization. The results of simulation via
Cooja show that the CLRPL compared with the standard RPL improves the network lifetime and reduces
packet loss ratio and overhead
4. THE PROPOSED METHOD
In the RPL protocol, the objective function is responsible for topology construction via proper
parent selection in a DODAG. The routing metrics may be utilized in the defined objective function to
calculate the Rank of a node as a single or combined multiple metrics. Lexical, additive, and fuzzy logic are
common ways to combine different metrics. MCDM methods have become quite popular in network-related
fields in recent years. In this paper, we are going to use the MCDM and fuzzy logic methods. The MCDM is
an advanced tool in order to address complex decision problems involving multiple criteria goals. Lexical
and additive are simple ways to address decision-making problems compared to MCDM and fuzzy logic
approaches. The main goal of using the fuzzy logic method and TOPSIS technique is to integrate node and
4. Int J Elec & Comp Eng ISSN: 2088-8708
TFUZZY-OF: A new method for routing protocol for low-power and lossy networks … (Ali Kamil Ahmed)
3477
link metrics namely ETX, RSSI, and hop count. In our proposed method, the membership function is used to
enable a rigorous assessment of the quality of the selected neighbor nodes. In order to meet various LLN
requirements, including those for real-time and dependable applications, the TFUZZY-OF was designed.
4.1. Fuzzy logic
We were able to convert many input variables into a single output using the fuzzy logic approach
[27]. The fuzzy process model [28] is divided into four parts, as shown in Figure 1. We utilize the Mamdani
model [29] as the most prevalent fuzzy inference approach in this study, as follows. Fuzzification captures
predetermined input variables and computes membership degrees for appropriate fuzzy set values. Fuzzy
inference is the process of mixing fuzzified inputs and computing a fuzzy result. If the output is dependent on
more than one rule, aggregation unites all values into one. Defuzzification, based on the preceding step, turns
the fuzzy output to a precise value.
We define three metrics namely hop count, RSSI, and ETX for fuzzy logic composition. Figure 1
shows the fuzzy process model in which ETX and RSSI routing metrics as link metrics and hop count as
node metrics are taken into account, respectively. In fuzzy logic, variables can be in ranges of true or false
which are determined by linguistic values. To prepare one output, fuzzy logic uses linguistic variables to
indicate the degree of reliance across metrics. The fuzzy set values are introduced based on the input
variables' behavior [27]. The fuzzy values are entered into the fuzzy algorithm to decide on parent change.
In this method, the membership functions set for ETX, hop count, and RSSI are shown in Figures 2
to 4, respectively. A favorable path has to have high RSSI, low ETX, and low hop count. Figure 2 illustrates
the membership function graph for the reverse normalized ETX in the proposed method. Based on this figure,
a higher reverse normalized parameter value signifies a lower ETX for the route. As shown in the figure, the
range of membership function is considered as low, medium, and high. Figure 3 shows the membership
function graph for the reverse normalized hop count in the proposed method. If the reverse normalized hop
count is high, it is desirable. As shown in the figure, the range of the reverse of the normalized hop count in
membership functions is considered as low, medium, and high. Figure 4 displays the membership function
graph for RSSI. It is obvious that the route will be preferred if the normalization value is high. As shown in
the figure, the range of RSSI in membership functions is considered as low, medium, and high.
Figure 1. The fuzzy process model for the proposed method
Figure 2. The graph of ETX membership function
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Figure 3. The graph of hop count membership function
Figure 4. The graph of RSSI membership function
4.2. TOPSIS method
RPL uses the objective function to construct a path to the destination in order to effectively make
the connection, which is one of its key features. The designers can provide various metrics in accordance
with their requirements due to the inclusion of the objective function in the core of RPL. In this paper, we
used the TOPSIS method as a well-known MCDM approach that was proposed by Hwang and Yoon [16] for
the first time. For this purpose, we focus on the TOPSIS method to combine three routing metrics (i.e., hop
count, RSSI, and ETX) and design a novel objective function for the selection of the parents called
TFUZZY-OF. The TFUZZY-OF for solving the load balancing problem chooses the best parent node from a
set of available parents' sets that is considered as a less or non-congested parent in the network using multiple
routing metrics. Here, the best word refers to the best option for a node to be a parent in the network for
optimal route and better performance through specific routing metrics. The parents and routing metrics in
RPL are alternatives and criteria in the TOPSIS method, respectively. The TOPSIS method has 7 steps to
produce the comparison between the candidate parents [16].
a) The TOPSIS method gets the decision matrix as an input in which each node acts as a decision-maker.
This matrix contains m alternatives (candidate parents) A={𝑎𝑖, 𝑖 = 1, 2, . . . , 𝑚} and n criteria (routing
metrics). In this paper, we used 3 routing metrics C={𝐶𝑗, 𝑗 = 1, 2, 3} namely hop count, ETX, and RSSI
to find the best parent. The 𝑥𝑖𝑗 displays the numerical value of the jth
criteria for the ith
choice. To
determine the profits or costs of each criteria, the value of each must first be determined. It is self-evident
that qualitative criteria (measured on a scale) must be replaced by quantitative metrics. This approach also
contains an additional input that sets the relative relevance of each criterion to the others. The decision-
maker weights vector 𝑊 = {𝑤𝑗, 𝑗 = 1, 2, 3} where ∑ 𝑤𝑗 = 1
3
𝑗=1 is what it is called. Therefore, we have a
matrix (𝑥𝑖𝑗)mn as (1).
𝐷 = [
𝑥11 ⋯ 𝑥1𝑛
⋮ ⋱ ⋮
𝑥𝑚1 ⋯ 𝑥𝑚𝑛
] (1)
6. Int J Elec & Comp Eng ISSN: 2088-8708
TFUZZY-OF: A new method for routing protocol for low-power and lossy networks … (Ali Kamil Ahmed)
3479
Each alternative choice is treated as a point in space in the TOPSIS approach. Then, using the two crucial
points known as the positive ideal answer (𝐴+
) and the negative ideal answer (𝐴−
), each point's Euclidean
distance is determined. The next step is to rate the points based on their distance from the positive and
negative ideal answers.
b) The decision matrix (𝑥𝑖𝑗)mn is normalized using the vector approach. The vector normalizing is
determined as (2).
𝑟𝑖𝑗 =
𝑥𝑖𝑗
√∑ 𝑥𝑖𝑗
2
, 𝑖 = 1,2, … , 𝑚, 𝑗 = 1,2, … , 𝑛 (2)
The normalized matrix (rij)mn using the normalization method is computed as (3):
𝑅𝑖𝑗 = [
𝑟11 ⋯ 𝑟1𝑛
⋮ ⋱ ⋮
𝑟𝑚1 ⋯ 𝑟𝑚𝑛
] (3)
This is accomplished to rule out the problem's size, as each criteria may have its own unit of
measurement.
c) The weighted normalized decision matrix V is created by multiplying each criteria's weight by the column
in the normalized matrix that corresponds to that criterion as (4),
𝑣𝑖𝑗 = 𝑤𝑗𝑟𝑖𝑗 , 𝑖 = 1, 2, … , 𝑚, 𝑗 = 1,2, … , 𝑛 (4)
where 𝑤𝑗 is the original weight given to the indicator vj. Assume that 𝑊 = (𝑤1, 𝑤2, … , 𝑤𝑗, … , 𝑤𝑛) is the
weight matrix for the desired criteria, multiplying the first column by 𝑤1, and the second column by 𝑤2,
and therefore multiplying the 𝑛𝑡ℎ column by 𝑤𝑛, as (5):
𝑉 = [
𝑣11 ⋯ 𝑣1𝑛
⋮ ⋱ ⋮
𝑣𝑚1 ⋯ 𝑣𝑚𝑛
] (5)
d) Determining positive ideal options or benefits (A+) and negative ideal options or costs (A-), as shown in
(6) and (7),
𝐴+
= {(𝑚𝑎𝑥𝑣𝑖𝑗|𝑗 ∈ 𝐽), (𝑚𝑖𝑛𝑣𝑖𝑗|𝑗 ∈ 𝐽′)|𝑖 = 1, 2, 3, … , 𝑚} = {𝑣1
+
, 𝑣2
+
, … , 𝑣𝑛
+
} (6)
𝐴−
= {(𝑚𝑖𝑛𝑣𝑖𝑗|𝑗 ∈ 𝐽), (𝑚𝑎𝑥𝑣𝑖𝑗|𝑗 ∈ 𝐽′)|𝑖 = 1, 2, 3, … , 𝑚} = {𝑣1
−
, 𝑣2
−
, … , 𝑣𝑛
−
} (7)
where J is the profit criterion and J' is the cost criterion.
e) Determine the geometric distance of each alternative to 𝐴+
(benefits) and 𝐴−
(costs). The 2-dimensional
Euclidean distance is used to determine how far apart each ideal choice is, both positive and negative.
Assume 𝑆𝑖
+
is the ith
distance choice for 𝐴+
and 𝑆𝑖
−
for 𝐴−
as illustrated in (8) and (9).
𝑆𝑖
+
= √∑ (𝑣𝑖𝑗 − 𝑣𝑗
+
)2
𝑛
𝑗=1 , 𝑖 = 1,2, … , 𝑚 (8)
𝑆𝑖
−
= √∑ (𝑣𝑖𝑗 − 𝑣𝑗
−
)2
𝑛
𝑗=1 , 𝑖 = 1,2, … , 𝑚 (9)
f) For each option i, we calculate 𝑑𝑖 as (10).
𝑑𝑖 =
𝑆𝑖
−
𝑆𝑖
−+𝑆𝑖
+ , 𝑖 = 1,2, … , 𝑛, 0 ≤ 𝑑𝑖 ≤ 1 (10)
As can be seen, the relative distance weights between the ith
alternative and the negative ideal are
represented by this index. As a result, if the quantity of di for each choice is greater, the negative ideal
distance will be greater and the rate will be higher. 𝐴i
𝑖s positioned on 𝐴+
with 𝑑𝑖 = 0 in the best situation,
and on 𝐴−
with 𝑑𝑖 = 1 in the worst case. The objective function for the new DIO message is defined based
on three routing metrics including hop count, ETX, and RSSI based on (10) and using positive and negative
ideals and then, in step 7, rank is calculated according to the objective function.
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g) Rank the alternatives based on 𝑑𝑖, 𝑖 = 1,2, … , 𝑛. The quantities collected in step 6 are compared. When
the amounts are higher, it indicates that the situation is better. In this paper, according to the nature of the
TOPSIS method, all criteria values of each alternative must be available in the best choice selection
procedure. This causes increasing routing overhead because each node needs to send each criteria value to
its neighbors in the DIO message. So, we use a modified TOPSIS method, such that each node uses the
fixed positive and negative ideal.
5. RESULTS AND DISCUSSION
To implement TFUZZY-OF, we used the Cooja [17] simulator running on Contiki-NG Operating
System (version 3.0). It is an open-source emulator created for IoT purposes. In this paper, Z1 [30] mote is
used as the base node for simulation. The network's nodes have a communication range of 50 meters and an
interference range of 100 meters. Table 2 lists the parameters utilized in the simulations. For evaluation two
metrics are taken into account: E2ED (the average time it takes for a packet to go from a client to a server node
in a network is known as the average E2ED) and PDR, where the ratio of data packets successfully received at
the destination to the amount transmitted during simulation is used to measure network dependability.
Table 2. The parameters considered in simulation
Network Parameters Values
Sensor node OS Contiki-NG
Simulator Cooja
Routing protocol RPL
Radio medium model UDGM: distance loss
Deployment type Random, Grid
Range of nodes Rx and Tx: 50 m, Interference: 100 m
Mote type Z1
Deployment area size 100×100 m
Number of client nodes 10, 20, 30
Number of server 1
TX ratio 60%
RX ratio 60%
Simulation duration 10 min
To evaluate the performance of TFUZZY-OF, RPL networks with 10, 20, and 30 nodes (1 node as
server node and other nodes as client nodes) are considered that are located in two main topologies: random
and grid. Figure 5 depicts the two primary topologies in which the LLN nodes are distributed across the
experiment including random topology in Figure 5(a) and grid topology in Figure 5(b). As shown in the
figures, the green color indicates the server node and the yellow color represents the client nodes.
(a) (b)
Figure 5. Nodes distribution with 1 (ID:1) server based on two topologies (a) random topology and (b) grid
8. Int J Elec & Comp Eng ISSN: 2088-8708
TFUZZY-OF: A new method for routing protocol for low-power and lossy networks … (Ali Kamil Ahmed)
3481
The standardized OF-MRHOF, OF-fuzzy, and our novel TFUZZY-OF have all been compared. All
simulation figures demonstrate RPL performances by analyzing the PDR and E2ED. In Figure 6, TFUZZY-
OF has been compared to currently used OFs known as OF0 and MRHOF and also recently proposed OFs
OF-EC and OF-fuzzy. As its observable in this figure, TFUZZY-OF has a good PDR rate almost close to
100% (98%). It can also be seen that this proposed method has outperformed every other OF by at least
10 percent increase in the amount of PDR. In Figure 7, TFUZZY-OF is compared to MRHOF and OF0 based
on average E2ED. It is clear that the TFUZZY-OF has a lower average E2ED in comparison with both of
them. From this figure, it is observable that for more populated LLN networks (in this experiment, networks
with 20 and 30 nodes), TFUZZY-OF would outperform almost all the other objective functions since it
seems that the E2ED decreases with a sharper steep as the number of nodes increases in a network.
With various network sizes, an OF with a single metric supplies high control messages than OF with
combined metrics. As a result, the network should update, taking into account the available nodes, in the case
of a link failure or a bottleneck node. However, in the network with combined metrics, link failures or
bottleneck nodes are reduced because of using link and node metrics in the parent selection procedure.
Figure 6. Comparison of PDR for three OFs
Figure 7. Comparison of E2ED for three OFs
6. CONCLUSION
The load balancing techniques play a crucial role in RPL routing protocol. In order to meet various
LLN requirements, including those for real-time and dependable applications, the TFUZZY-OF as a new
method was designed. In this paper, the TFUZZY-OF for load balancing of route establishments in RPL
routing protocol has been proposed which uses the composition of a set of network metrics, here ETX, RSSI,
and hop count, and a decision-making algorithm named TOPSIS. The proposed routing protocol is able to
balance loads of traffic in a dense network and increase the lifetime of the network. To evaluate the proposed
routing protocol, Cooja simulator is used, and the result is compared with standard RPL using MRHOF and
also OF-EC and OF-fuzzy in terms of PDR and E2ED. Simulation results show that the TFUZZY-OF can
increase the quality of service for LLN networks. For future work, the TFUZZY-OF will extend by using
artificial intelligence techniques such as machine learning and deep learning methods, especially
reinforcement learning to acquire more precision.
0
20
40
60
80
100
TFUZZY-OF ETX OF0 OF-EC OF-FUZZY
PDR
10 NODE
20 NODE
30 NODE
0
50
100
150
200
250
300
350
TFUZZY-OF ETX OF0 OF-EC OF-FUZZY
E2ED
10 NODE
20 NODE
30 NODE
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BIOGRAPHIES OF AUTHORS
Ali Kamil Ahmed was born in Baghdad, Iraq, in 1982. He received his B.Sc.
degree in computer technology engineering from Electrical Engineering Technical College-
Middle Technical University, and his M.Sc. degree in computer systems architecture from
Isfahan University of Technology, Iran. He is currently a lecturer in Department of Materials
Engineering, University of Technology, Iraq. His current research interests include IoT,
wireless networks, artificial neural networks, and image processing. He can be contacted at
ali.k.ahmed@uotechnology.edu.iq.
Behnam Farzaneh received his B.Sc. degree in computer engineering (software
engineering) from Payame Noor University, Ardabil, Iran in 2012 and his M.Sc. degree in
computer engineering (computer architecture) from Isfahan University of Technology, Isfahan,
Iran in 2018. His research interests include the internet of things (IoT), 5G network slicing,
computer networks, network security, machine learning, and optimization. He can be
contacted at b.farzaneh@ec.iut.ac.ir.
Elahe Boochanpour was born in Kermanshah, Iran in 1987. She received her
B.Sc. degree in information technology engineering in 2012 and her M.Sc. degree in a
computer network in information technology engineering in 2019 from South Tehran
University, Iran. Her recent research activities are telecommunication. She can be contacted at
elaheboochanpour@ymail.com.
Emad Alizadeh was born in 1993 in Gachsaran, Iran. He received a B.Sc. in
electrical engineering (communications) from Yazd University, in 2014. He also received his
M.Sc. degree in electrical engineering (telecommunication networks) from Isfahan University
of Technology (IUT), Isfahan, in 2018. Since 2018, he has been pursuing his Ph.D. program in
telecommunication networks at IUT. His major research interest is applied mathematics, social
networks, complex networks, software-defined networks, network function virtualization, and
the Internet of things. He also is experienced in applied mathematics, and complex and social
networks. He can be contacted at e.alizadeh@ec.iut.ac.ir.
Shahin Farzaneh received his B.Sc. degree in civil engineering in 2017 from the
University of Mohaghegh Ardabili (UMA), Iran. Currently, he is a research assistant in Civil
Engineering Department, UMA. To date, his interdisciplinary research activities are focused
on seismic design, structural health monitoring, machine learning, the Internet of things, data
analytics, and optimization algorithms. He can be contacted at b_farzaneh@uma.ac.ir.