Routing Metrics Research Articles

Customized novel routing metrics for wireless mesh-based swarm-of-drones applications

With the proliferation of drones, there is an increasing interest on utilizing swarm-of-drones in numerous applications from surveillance to search and rescue. While a swarm-of-drones (a.k.a flying ad hoc networks (FANETs)) is essentially a special form of mobile ad-hoc networks (MANETs) which has been studied for many years, there are unique requirements of drone applications that necessitate re-visiting MANET protocols. These challenges stem from 3-D environments the drones are deployed in, and their specific way of mobility which adds to the wireless link management challenges among the drones. To tackle these challenges, in this paper, we propose adopting the current mesh standard, namely IEEE 802.11s, in its routing capabilities to provide improved performance. Specifically, we propose two new link quality routing metrics called SrFTime and CRP as an alternative to the IEEE 802.11s default Airtime routing metric to meet network throughput requirements for FANET applications. Basically, SrFTime improves network performance of stationary FANETs, while CRP is designed to fit the transient link characteristics of mobile drones and enable more efficient routes from drones to their destinations. To be able to test these metrics, we also introduce a group mobility model adaptation for FANET’s needs. The evaluations in the actual 802.11s standard using ns-3 simulator and introduced 3-D mobility models indicate that our proposed metrics outperform the existing one consistently under various conditions.

An interference aware energy efficient data transmission approach for smart cities healthcare systems

New and integrated smart cities concept have envisioned more smart and efficient networks for people's health, education, business, and living. Sustainable smart cities always looking for smart and more advanced systems. Smart healthcare is one of the prominent area and domain of smart cities where different types of applications are used for people's health and comfort. Smart health systems are further divided into different areas, such as e-health, e-medicine, personal assistant monitoring, and body area networks. Wireless Body Area Networks (WBAN) is one of the popular research area due to its impending use in emergencies such as monitoring and diagnosis patient’s health. Sensor nodes are placed on or inside the human body where the implanted sensor performs the operations for a long time without any replacement of the battery. To avoid frequent change/replacement of the battery, energy management is essential and one of major concern. Facts show that most of the sensor networks use multi-hop and utilizes more resources. Energy-efficient routing protocols play a significant role in energy consumption. Due to the number of sensor nodes attached to the patient body, interference among sensors is one of the reasons for energy wastage. The co-channel interference increases the energy consumption because of the higher number of retransmission efforts required for successful transmission in the presence of interference. The main objective of this paper is to develop an Interference Aware Energy Efficient Transmission Protocol (IEETP) by utilizing the most appropriate routing metrics for smart health systems in smart cities. The proposed protocol selects the next forwarder node based on the residual energy of nodes, distance, node’s position, and node density. The proposed protocol is a multi-hop protocol in which each source node forwards the data towards the coordinator node. The proposed protocol has evaluated with state-of-the-art protocols where the IEETP has higher performance in the network.

Mobility management for RPL protocol in internet of things

<p>The IPv6 Routing Protocol for Low Power and Lossy Networks (RPL) was proposed for various applications of IPv6 low power wireless networks. While RPL supports various routing metrics and is designed to be suitable for wireless sensor network environments, it does not consider the mobility of nodes. Therefore, there is a need for a method that is energy efficient and that provides stable and reliable data transmission by considering the mobility of nodes in RPL networks. In this paper a new heuristic flabellum algorithm inspired by physical and biological behaviour of flabella in the sea is presented, and bottleneck and swarm problems are resolved through managing the moving nodes by flabellum algorithm. Finally, the proposed algorithm’s performance is evaluated using the Cooja simulator. The proposed algorithm;Flabellum RPL; shows significant improvements with regards to packet delivery, and convergence and lifetime.</p>

EBOF: A New Load Balancing Objective Function for Low-power and Lossy Networks

The IPv6-based Routing Protocol for Low-Power and Lossy Networks (RPL) is a new routing protocol designed to satisfy constrained networks such as 6LoWPAN. The default route selection technique of RPL takes into account a single metric, which is unable to recognize the load balancing problem in the network. As a consequence, energy may drain rapidly from overloaded nodes, and the nodes that die first can cause a partition in the network. To resolve this problem, we propose a new RPL-compliant objective function named the Energy Balance Objective Function (EBOF). It combines two different routing metrics, which are the Expected Transmission Count (ETX) and the Child Count (CC). Then, the Destination Oriented Directed Acyclic Graph (DODAG) Information Object (DIO) message format is amended to disseminate the CC information among neighbor nodes. Two metrics are utilized to select the best path and to construct a balanced network. The proposed scheme is examined through simulation tests and evaluated against the Minimum Rank with Hysteresis Objective Function (MRHOF), the Load Balancing Model for RPL (ALABAMO), and Load Balanced Objective Function (LB-OF). The resulting analysis shows that the proposed EBOF significantly achieves the energy balance among intermediate nodes, which in turn prolongs the network lifetime.

Congestion Control and Traffic Differentiation for Heterogeneous 6TiSCH Networks in IIoT.

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

Routing Protocols for UAV-Aided Wireless Sensor Networks

Recently, unmanned aerial vehicles (UAVs) attracted significant popularity in both military and civilian domains for various applications and services. Moreover, UAV-aided wireless sensor networks (UAWSNs) became one of the interesting hot research topics. This is mainly because UAWSNs can significantly increase the network coverage and energy utilization compared to traditional wireless sensor networks (WSNs). However, the high mobility, dynamic path, and variable altitude of UAVs can cause not only unforeseen changes in the network topology but also connectivity and coverage problems, which can affect the routing performance of the network. Therefore, the design of a routing protocol for UAWSNs is a critical task. In this paper, the routing protocols for UAWSNs are extensively investigated and discussed. Firstly, we classify the existing routing protocols based on different network criteria. They are extensively reviewed and compared with each other in terms of advantages and limitation, routing metrics and policies, characteristics, difference performance factors, and different performance optimization factors. Furthermore, open research issues and challenges are summarized and discussed.

Link reliability-based multi-hop directional location routing in vehicular ad hoc network

The vehicular ad hoc network (VANET) is a self-organized and decentralized wireless ad hoc network formed by the mobile vehicles on demand to communicate the traffic-related valuable information among the vehicles. The mobile vehicles work as a node because they use to either send or receive traffic-related information in the network. The vehicles can communicate within restricted distance but mobility nature causes they frequently switch from one network to another network topology; therefore, the links among the vehicles seldom vanish. Therefore, in the multi-hop VANET delivery of the messages at the anticipated destination is problematic. In this paper, a routing mechanism namely link reliability-based multi-hop directional location routing (MHDLR) has proposed to overcome the link vanish problem. The MHDLR decides a link reliability-based next-hop node to create a strongly durable path from the source to destination. In multi-hop VANET, the inter-vehicle distance directly impacts on the connectivity of the vehicles. Therefore, to estimate the link reliability of vehicles their inter-vehicle distance and relative velocity have considered. The geometry-based localization mechanism (G-BLM) has been proposed to estimate the inter-vehicle distance of the vehicles. The performance of MHDLR has estimated for routing metrics i.e. path vanish, message broadcasting time in the group, packet delivery ratio and throughput. The simulated outcomes of the proposed model MHDLR have shown, its performance is better as compared to the existing fuzzy-logic based directional location routing (FLDLR), directional location aided routing (D-LAR) and location aided routing (LAR) protocols.

RESDN: A Novel Metric and Method for Energy Efficient Routing in Software Defined Networks

Software-defined networking (SDN) paradigm, with the flexible and logically centralized control, enables dynamically minimizing the network energy consumption by redirecting paths of packets. However, the links and switches are designed to accommodate maximum traffic volume and their power consumption is not traffic proportional. Moreover, there exists a trade-off between energy efficiency and network performance that need to be considered together. Addressing these issues, we propose an energy efficiency metric named Ratio for Energy Saving in SDN (RESDN) that quantifies energy efficiency based on link utility intervals. We provide integer programming formulation and method for maximizing the RESDN of the network. To the best of our knowledge, RESDN approach is novel as it measures how links are profitably utilized in terms of the amount of energy they consume with respect to their utility. We analyze our approach considering various metrics of interest, and different types of SDN enabled switches. Experiments show that maximizing the RESDN value improves energy efficiency while maintaining acceptable network performance. In comparison to state-of-the-art utility-based heuristics, RESDN method achieves up to 30% better ratio for energy saving, 14.7 watts per switch power saving, 38% link saving, 2 hops decrease in average path length, 5% improved traffic proportionality.

Design and analysis of RPL objective functions using variant routing metrics for IoT applications

The main objective of Internet of Things (IoT) is to connect almost all the devices anywhere and everywhere in the world. IoT network is heterogeneous in nature, hence routing the data packets in this network is a big challenge. Routing Protocol for Low Power Lossy Network (RPL), has been designed by Internet Engineering Task Force (IETF) for such type of network. The existing design of RPL Objective Function (OF) is insufficient to cover all the issues of IoT applications. In this paper, the proposed OFs designs using various routing metrics are used to enhance the performance of the IoT applications. The analysis for various scenarios for these designs shows that only traditional hop and Expected Transmission Count (ETX) routing parameters will not fit for the smart applications need. The routing metric selection according to the application requirement is the principal idea of the proposed design. Three metrics ETX, Content and Energy, single and combination with each other are used to enhance the design of objective function of RPL for IoT applications. The enhanced triggering technique is added in these designs for the improvement of RPL. This technique will eliminate the cumulative effect of the short-listen problem of default trickle timer. The result analysis done using Cooja simulator along with Contiki Operating System (OS) states that, all the designs are performing well in one or other manner than the traditional OF. Energy combined with Content (EC) and aggregation with Enhanced timer (EC_En_Timer) design gives better result for Packet Delivery Ratio (PDR) and Latency Delay (LD) as compared to default OF design. Residual Energy (RE) combined with ETX (EE) and conjunction with Enhanced timer (EE_En_Timer) design works well for energy consumption. Overhead is very less in RE and ETX design. Conversion time is reduced by almost 50% in an En_Timer design. Higher PDR and low delay values of EC and EC_En_Timer design encourages its use in health monitoring application where reliability is essential. Low energy consumption results of RE, EE and EE_En_Timer designs are comfortable for forest monitoring application, as energy is a crucial aspect. This comparative result outcome will help to fulfill the IoT application requirements.

A New Objective Function Based on Additive Combination of Node and Link Metrics as a Mechanism Path Selection for RPL Protocol

Since its development by IETF, the IPv6 routing protocol for low power and lossy networks (RPL) remains the subject of several researches. RPL is based on objective function as a mechanism selection of paths in the network. However, the default objective functions standardized selects the routes according to a single routing metric that leads to an unoptimized path selection and a lot of parent changes. Thus, we propose in this paper weighted combined metrics objective function (WCM-OF) and non-weighted combined metrics objective function (NWCM-OF) that are based both on additive link quality and energy metrics with equal weights or not to achieve a tradeoff between reliability and saved energy levels. The proposed objective functions were implemented in the core of Contiki operating system and evaluated with Cooja emulator. Results show that the proposed objective functions improved the network performances compared to default objective functions.

EAR: Energy-aware risk-averse routing for disaster response networks

Disaster Response Networks (DRNs) are specific delay-tolerant networks (DTNs) designed to support temporary communications during disaster recovery with limited energy resources. Existing research on DRNs routing addresses routing metrics like packet delivery delay (PDD), packet delivery ratio (PDR), and total transmission energy (TTE). However, the complex interplay among these metrics remains unclear and makes their control difficult. Moreover, the standard deviation of packet delivery delay (PDS), which is overlooked by the previous works, is an important metric in DRNs. In this paper, we propose the Energy-Aware Risk-averse routing framework (EAR) for DRNs. EAR models the mobility in DRNs using a stochastic multigraph and computes the risks associated with routing paths using the Mean-Risk and Max-Probability models. A “λ-optimal” algorithm is used for finding routing paths with the minimum risks. A parameter L restricting the number of packet replicas and a differentiated service model are utilized to improve packet delivery efficiency (PDE) while maintaining other metrics at an adequate level. We show via extensive simulations that EAR provides flexible control of the routing risks and delivers packets to the destinations in a more energy-efficient way (up to 8x higher PDE with 4% lower PDR) than well-known routing protocols Prophet, MaxProp, RAPID and Spray&Wait.

Performance Analysis of Denial of Service (DoS) and Distributed (DDoS) Attack of Application and Network Layer of IoT

In present days the Internet of Things (IoT) is fast-growing technology for the use of various internet services to connect with any component at anytime. This is used as a medium between the components that are self-organize; recognize themselves using (RFID) Radio frequency identification, Zig Bee and WSN etc. for efficient communication. IoT consists of the most unique features. IoT faces many complicated issues based on power, security, and connectivity. It is very important to adopt the IoT into various large networks which secure the personal data from the real threats. In this paper, analysis the DoS and DDoS attack of application and network layer of IoT. Moreover, this paper also analyze the performance with various metrics delay, number of packets lost, routing metrics that can improve the performance of the IoT.

Trust-aware and cooperative routing protocol for IoT security

The resource-constrained nature of IoT objects makes the Routing Protocol for Low-power and Lossy Networks (RPL) vulnerable to several attacks. Although RPL specification provides encryption protection to control messages, RPL is still vulnerable to internal attackers and selfish behaviours. To address the lack of robust security mechanisms in RPL, we design a new Metric-based RPL Trustworthiness Scheme (MRTS) that introduces trust evaluation for secure routing topology construction. Extensive simulations show that MRTS is efficient in terms of packet delivery ratio, energy consumption, nodes’ rank changes, and throughput. In addition, a mathematical modelling analysis shows that MRTS meets the requirements of consistency, optimality, and loop-freeness and that the proposed trust-based routing metric has the isotonicity and monotonicity properties required for a routing protocol. By using game theory concepts, we formally describe MRTS as a strategy for the iterated Prisoner’s Dilemma and demonstrate its cooperation enforcement characteristic. Both mathematical analysis and evolutionary simulation results show clearly that MRTS, as a strategy, is an efficient approach in promoting the stability and the evolution of the Internet of Things network.

Joint Channel and Interference Aware Cooperative Routing for Cognitive Radio Network

Cognitive Radio based network technology provides a promising solution for various types of real-time wireless communication by offering better spectrum utilization and resource allocation. Generally, the dynamic network topology, interference, channel switching and under-utilization of resource can degrade the network performance. Therefore, development of promising solution to obtain the desired performance is a challenging research topic in CRNs. Several researches have been carried out which have focused on development of routing protocol for CRNs to improve the performance. These routing protocols are classified as local and global routing which are mainly focused on overhead reduction and optimal route selection respectively. However, the conventional approaches suffer from various issues such as interflow-interference, channel switching delay and node overhearing problems which can progress towards the poor network performance. In this paper, our objective is to focus on the inter-flow interference, channel switching delay, and develop a cooperative communication based approaches where inter-flow interference and overhearing issues are mitigated using cooperative communication. Furthermore, Switching Delay and Interference (SDI) routing metric is developed to reduce the switching delay and also finally, a cooperative scheme of packet transmission is developed where direct or cooperative communication is selected for successful packet transmission. The proposed approach jointly considers channel and interference issue, hence it is known as Joint Cooperative Channel and Interference Aware Routing (JCIAR). The performance of proposed approach is compared with the existing techniques such as Primary User Aware k-hop route discovery scheme (PAK), AODV, Cognitive- AODV, and Location-Aided Routing for CRN (LAUNCH) in terms of delay, packet delivery rate and throughput. The obtained result shows a significant improvement in network performance.

On Providing Differentiated Service Exploiting Multi-Instance RPL for Industrial Low-Power and Lossy Networks

The rapid proliferation of low-power wireless devices enables the industrial users to improve the productivity and safety of the plants as well as efficient management of the system. This can be achieved through significant increase in data collection, remote monitoring, and control of the plants and promoting the development of industrial Internet of Things (IoT) applications. However, the industrial environment is typically harsh causing high link quality variations and topology changes. The wireless devices used in this environment are also resource constrained in terms of energy, memory, and processing power. In spite of their low-power and lossy nature, these networks demand provisioning of differentiated services for various industrial applications having diverse quality of service (QoS) requirements. Considering the unique characteristics of low-power and lossy networks (LLN), routing for low-power and lossy networks (RPL) is devised which was standardized by IETF in 2012. To meet the demand of diverse traffic, RPL supports multiple instances in a single network. This paper proposes MI-RPL, a multi-instance solution of RPL for industrial low-power and lossy networks (LLNs). MI-RPL defines four instances for four distinct traffic classes of industrial monitoring applications in terms of delay and reliability. MI-RPL also introduces composite routing metrics and proposes an objective function (OF) to compute the most suitable path for each instance. The performance of MI-RPL is investigated through simulations that exhibit MI-RPL has better delay and packet delivery performance for delay- and reliability-constrained traffic along with lower energy consumption compared to the standard RPL.

Neo-hybrid Composite Routing Metric for RPL

Abstract Low power and Lossy Networks (LLN) are the backbone of the blooming Internet of Things (IoT) technology. The routing protocols play crucial role in the efficiency and management of the scarce resources of LLNs. RPL is the popular routing protocol for LLNs and its efficiency depends on the routing metrics used. The default objective functions of RPL use hop count and Expected Transmission Count (ETX). In denser networks, congestion is caused, and the objective functions require optimization. This paper aims at providing an optimization of RPL by creating a new strategy of amalgamating the existing sigma routing metric and enhanced routing metric. Contiki Cooja simulator is used for simulating the results. The results are evaluated with the default objective functions, sigma routing, and enhanced objective function. The neo-hybrid composite routing metric (NCRM) outperforms all the other in packet delivery ratio, network life time, end-to-end delay and energy consumption.

A Cross-Layer Routing Metric with Link Prediction in Wireless Mesh Networks

Abstract Wireless Mesh Networks (WMNs) is one of the encouraging technologies for future-generation wireless network with diverse applications as it is undergoing rapid progress. WMNs are multi-hop networks which are beneficial in situations where there is little or no network infrastructure. WMNs consist of mesh nodes which interact with each other to establish a network connection. Mesh nodes include mesh clients and mesh routers. Mesh clients can be stationary or move from one place to another, whereas mesh routers have minimum movability and act as a backbone for WMNs. Due to the mobility of mesh nodes, the fundamental problem in WMNs is estimating the link quality. The efficiency of network protocols depends on the accuracy of link quality. Therefore, there is a need for an intelligent mechanism to find solutions to link quality problems in the wireless network. To address this problem, we apply machine learning prediction techniques. We evaluate the performance of prediction techniques like multiple linear regression, support vector regression and Gaussian regression. The experiments were conducted on various scenarios with cross-layer routing metric PCL-IDA to predict the link quality, which is embedded in OLSR routing protocol. Results using NS-2 simulations reveal that the link quality parameters throughput, average delay and packet loss are better when multiple linear regression prediction technique is applied.

Self-Assessment Based Clustering Data Dissemination for Sparse and Dense Traffic Conditions for Internet of Vehicles

Internet of Vehicle (IoV) is a sub class of vehicular ad hoc networks with more advanced cloud and Internet-enabled services. These networks offer various types of safety and infotainment services and provide comfortability and safety to passengers as well as to the drivers. Due to the high mobility of nodes, the nodes are out from its communication range and the information becomes outdated and causes link disconnections and packet dropping. Most feasible routing protocols are needed to provide in-time data communication, handle high mobility of nodes, dynamic topologies and unpredictable environments of these networks. In this paper, we proposed SACBR (Self-Assessment Cluster-based Routing) protocol in which the Cluster Heads (CHs) can communicate with other CHs. Every vehicle node initiates a self-assessment approach based on more appropriate routing metrics and elects the CH for every cluster and then collects the data from member nodes and further forward the data to other CHs. The CH is responsible to manage its own and member nodes’ data forwarding process. The proposed protocol provides more stability and less overhead compared to the aggregation method where every node exchanges its data with a one-hop neighbor. Proposed protocol suites sparse and dense traffic scenarios where most of the time vehicle nodes are moving in platoons or snaking structures. The experimental results show the better performance of SACBR compared to state-of-the-art protocols.

Investigation on optimisation, prioritising and weight allocation techniques for load balancing and controlling multimedia traffic in wireless mesh network

Wireless mesh network (WMN) is a type of wireless ad hoc network where radio nodes are wirelessly connected within sizable geographic area through mesh topology. The best path is identified by routing metrics to ensure efficient data transmission from source node to destination node. The performance of routing is concern with set of routing constraints such as bandwidth, network delay, energy consumption, load balancing and communication cost. The routing constraints are needed to be resolved to improve the WMN performance. In WSN, network load balancing plays a significant role to achieve effective routing without traffic. The energy consumption is an additional factor to provide high-quality data delivery at the destination end. Our research work is concentrated on developing the energy efficient and load balanced routing in WMN.

A Survey on Routing Protocols for Delay and Energy-Constrained Cognitive Radio Networks

The ever-growing demand for higher network data rates, lower delay, and conservative energy consumption at reduced costs, to support Internet-of-things (IoT) communications, has pushed wireless technologies into a new frontier. The growing demand for such technologies can be attributed to several factors, such as the massive number of the upcoming bandwidth-hungry IoT applications and the enormous number of - often battery-powered - devices expected to connect to the network. Cognitive Radio Networks (CRNs) can play a significant role in future generations of mobile-communication technologies by providing dynamic access to underutilized licensed bands. However, battery-operated devices, which communicate delay-sensitive data over multihop links, impose serious energy-delay limits. In such CRN-based IoT communications, as one device depletes its energy, network disconnectivity may arise, which can degrade the network efficiency. Therefore, building a reactive routing protocol to recover from any sudden link breakage is necessary to maintain prolonged network connectivity. This paper provides a comprehensive survey of CRN routing protocols that are based on two essential metrics, namely, packet delay, energy consumption, or both, while excluding all other CRN routing protocols. The survey is meant to support the designers of future CRN-based IoT communication frameworks with a detailed comparative survey, which targets the most relevant proposed routing protocols, including the specifics of the routing metrics, implemented spectrum awareness strategy, and employed medium-access control standard along with the simulator tool used for performance evaluation. In addition, this survey finds that the majority of cognitive radio routing protocols address either delay or energy consumption, but only a few consider a joint delay-energy metric, which suits delay-sensitive IoT applications running on energy-constrained devices.