Scalable Routing Protocol Research Articles

Software Defined Multicast Using Segment Routing in LEO Satellite Networks

The emerging low earth orbit (LEO) broadband satellite networks are creating new opportunities to enable superior video distribution. With numerous satellites deployed, broadband constellations are capable of distributing videos across the globe by efficient multicasting techniques. However, existing work only studied IP multicast for broadband constellations, which suffer from limited scalability and tree performance. With recent breakthroughs in software defined networking, novel software defined multicasting (SDM) techniques manage to achieve efficient data transfer through intelligent and granular management, outperforming traditional IP Multicast. This paper leverages software defined multicasting in the promising broadband constellations to empower satellite-based Internet video distribution. Based on rectilinear Steiner trees, this paper proposes a novel software defined multicasting framework for broadband satellite networks. In addition, this paper designs simple, agile, and scalable multicast segment routing protocols implementing source routing and equal cost multipath routing. The proposed protocols also adapt to frequent member updates and network failures with efficient tree recovery and local rerouting mechanisms. Comprehensive experiments demonstrate the effectiveness and efficiency of our approach when compared with traditional algorithms.

The measurement and monitoring of Quality of service based on security analysis in wireless sensor network using deep learning architecture

Wireless sensor networks comprise of unattended little sensor hubs having low energy and low scope of correspondence. Machine learning has demonstrated its effectiveness in creating proficient cycles to deal with complex issues in different organization perspectives. This exploration propose novel procedure in wireless sensor network routing and security improvement by network observing utilizing profound learning model. The organization routing is done utilizing cluster based scalable hierarchical energy routing protocol (CSHERP) and the organization checking is completed utilizing fuzzy Boltzmann adversarial learning (FBAL). This routing protocol adopts an information driven strategy, with moderate hubs collecting information and sending it to a sink hub. The arrangement gave is valuable to additional investigation of expanded WSN networks. The trial examination is completed as far as energy efficiency, throughput, end-end delay, latency, QoS. The proposed technique attained energy efficiency of 96%, throughput of 91%, end-end delay of 86%, latency of 85%, QoS of 96%.

A social relationship-based energy efficient routing scheme for Opportunistic Internet of Things

Opportunistic Internet of Things (OppIoT) combines Opportunistic Networks and the Internet of Things to provide opportunistic communication between IoT devices and human-created communities in order to improve network connectivity, reliability, and longevity. This is significant because it introduces a new approach to connect and communicate smart devices in situations where there is no end-to-end connectivity. Due to the non-stable existence of connectivity between nodes, building a scalable, flexible, interoperable, and energy efficient routing protocol is a difficult issue. This study presents a new routing protocol for the Opportunistic Internet of Things called Social relationship based Energy Efficient Routing (SEER), which bases routing decisions on the forwarding feasibility degree, residual energy, and buffer capacity of nodes. SEER surpasses EBR and EDR in terms of delivery probability, hop count, and overhead ratio, according to simulation results utilizing the Opportunistic Network Environment (The ONE) simulator.

Neural Network-based Dynamic Clustering Model for Energy Efficient Data Uploading and Downloading in Green Vehicular Ad-hoc Networks

Green VANET is an emerging field of research that spurs interest in energy consumption management for the development of smart cities. It also presents a unique variety of research problems for developing trustworthy and scalable routing protocols as vehicles are susceptible to the restrictions of road geometry and the barriers which limit networking capabilities in urban environments. Clustering is a process of assembling vehicle nodes to create a powerful and effective network infrastructure. According to recent studies, clustering-based routing algorithms in green VANET may significantly improve networking effectiveness and lower infrastructure costs. However, sometimes the vehicle nodes are unaware of their OBU energy consumption, which causes network execution issues and topological alterations. In such instances, the energy consumption of onboard sensors becomes a major problem in the clustering-based routing protocol. Hence, this paper proposes a self-organizing map neural network (SOMNN) based dynamic clustering model to identify energy-efficient nodes from each cluster for vehicular data uploading and downloading applications. The simulation results demonstrate that the proposed model solves network lifetime issues and provides superior network effectiveness with enhanced communication stability. The suggested dynamic clustering model reduces network energy consumption by 26% and 18% in comparison to k – means (KM) and fuzzy c – means (FCM) based clustering model.

S-Octopus: A Novel Scalable Secure Position-Based Routing Protocol for MANETs

Mobile Ad-Hoc Networks (MANET) are self-organized wireless networks that are becoming progressively popular. Determining an efficient route leading from a source to a specific destination in these networks is an essential issue since nodes are continuously moving. Furthermore, finding a secure route is a difficult area to deal with since adversaries might insert themselves into these routes unless a strict secure routing procedure is implemented. In this paper, a novel scalable secure routing protocol called S-Octopus has been proposed. Via dividing the network area into sectors and utilizing restricted directional flooding, our protocol intents to achieve improved scalability. Moreover, S-Octopus seeks to enhance robustness against the single point of failure and compromise by introducing several Sector Certificate Authority servers. Together with S-Octopus a location service and a misbehavior detection system have been proposed. Using GloMoSim simulator, S-Octopus security and performance have been evaluated and compared with the basic Authenticated Routing for Ad-Hoc Networks (ARAN) as well as Zone-based Authenticated Routing for Ad-Hoc Networks (ARANz). Simulation results assure that S-Octopus is able to effectively initiate and maintain secure routes in MANETs. Results also confirm that S-Octopus has significantly mitigated the scalability problem by achieving the maximum packet delivery fraction and the minimum network and routing loads within fairly large networks with high-mobility nodes and large malicious node percentage. Thus, S-Octopus is a good choice for MANET established among students on a campus or peers at a conference, where keys and certificates might be previously deployed.

SGMRP-Utilizing a Mobile Ad Hoc Network to Develop a Scalable Geographic Multicast Routing Protocol for Localization

Group’s communications using Mobile Ad hoc Networks (MANETs) have recently drawn a lot of interest. Information is delivered to a group of receivers simultaneously through a process known as multipath. Therefore, to enable team communication activities, an effective and efficient multipath routing protocol is essential. Enhancing multicast routing has been the subject of numerous initiatives. However, they don't account for scalability. A scalable geographic multicast routing protocol was proposed in this research (SGMRP). This protocol's primary goal is to create a compact, adaptable multipath routing strategy that works regardless of the number of broadcast participants or the magnitude of the network. Using a prediction model and cross-validation techniques, the model performance evaluation tool assesses model effectiveness. The satisfaction with the service was also evaluated using a question. In addition to reducing the number of participating nodes in localization, the proposed method also gets rid of duplicate packets between clusters. The article introduces the framework's fundamental idea, details its transparent implementations, and finishes with a preliminary assessment of the framework based on typical mobile software kinds.

Fast and scalable routing protocols for data center networks

Data center networks may comprise tens or hundreds of thousands of nodes, and, naturally, suffer from frequent software and hardware failures as well as link congestions. Packets are routed along the shortest paths with sufficient resources to facilitate efficient network utilization and minimize delays. In such dynamic networks, links frequently fail or get congested, making the recalculation of the shortest paths a computationally intensive problem. Various routing protocols were proposed to overcome this problem by focusing on network utilization rather than speed. Surprisingly, the design of fast shortest-path algorithms for data centers was largely neglected, though they are universal components of routing protocols. Moreover, parallelization techniques were mostly deployed for random network topologies, and not for regular topologies that are often found in data centers. The aim of this paper is to improve scalability and reduce the time required for the shortest-path calculation in data center networks by parallelization on general-purpose hardware. We propose a novel algorithm that parallelizes edge relaxations as a faster and more scalable solution for popular data center topologies.

An Individual Node Delay Based Efficient Power Aware Routing Protocol for Wireless Heterogeneous Sensor Networks

Miscellaneous node transmission ranges builds up Wireless Heterogeneous Sensor Networks (WHSNs). Designing an efficient, reliable and scalable routing protocol for WHSNs with intermittent asymmetric links is a challenging task. In this paper, we propose an efficient power aware routing scheme for WHSNs, which can provide loop-free, stateless, source-to-sink routing scheme without using prior information about neighbor. It uses both symmetric and asymmetric links to forward data from source to sink. The source node broadcasts location information to all its neighbor nodes. Each neighbor node calculates a delay slot based on the information obtained from the source to forward its power value to it. The node that has a minimum delay slot forwards the power earlier than the other nodes during contention phase and the delay slot is used to suppress the selection of unsuitable low-power nodes at that time. We also prove that our protocol is loop-free assuming no failures in greedy forwarding. By simulations we show that our protocol significantly outperforms the existing protocols in WHSNs.

A Novel Approach to Support Scalable Multicast Routing in Wireless Ad Hoc Networks

Nowadays, group communications over Mobile Ad hoc Networks (MANETs) have received significant attention. Multicasting plays an important role in simultaneous delivery of information to group of receivers. Thus, it is necessary to design efficient and effective multicast routing protocol to support group communication applications. Several efforts have been put to improve multicast routing. However, they do not consider scalability issue. This paper introduces a a novel Scalable Geographic Multicast Routing Protocol (SGMRP). The main objective of this protocol is to design a lightweight scalable multicast routing scheme irrespective of the number of multicast members and network size. To achieve this, a virtual clustering strategy has been introduced. This strategy based on partitioning the network into sectorial zones. The proposed solution performs efficient packet forwarding with reduced communication overhead. The proposed scheme eliminates the duplicate packets between clusters and reduces the number of participating nodes

SGMRP: Scalable Geographic Multicast Routing Protocol for Mobile Ad Hoc Networks

Recently, group communications over Mobile Ad hoc Networks (MANETs) have received considerable attention. Group communication needs support of multicast routing protocols for simultaneous delivery information of group of receivers. Thus, designing effective and efficient multicast routing protocol is necessary to support this kind of applications. Several efforts have been adopted to improve multicast routing. However, most of them did not consider the scalability issue. In this paper, we propose a novel Scalable Geographic Multicast Routing Protocol (SGMRP) to improve the scalability of multicast routing with reduced overhead. SGMRP uses virtual clustering strategy to implement scalable routing and efficient group management. This scheme based on partitioning the network into sectorial zones. The proposed solution performs efficient packet forwarding with reduced communication overhead. This scheme reduces the number of participating nodes and eliminates the duplicate packets. Compared with on Demand Multicast Routing Protocol (ODMRP) and Efficient Geographic Multicast Protocol (EGMP), simulation results show that SGMRP delivers more packets with significantly reduced overhead regardless of the network size, mobility speed and number of multicast members.

Performance analysis of multi-hop routing protocols in SDN-based wireless networks

Wireless cellular networks have rapidly evolved to be software-defined in nature. This has created opportunities to improve their performance. One such opportunity is through enabling programming and integration of multi-hop device-to-device (MD2D) at the edge. However, efficient integration of MD2D at the edge requires a highly adaptable and scalable routing protocol, where its development is underpinned through understanding of which type of current routing characteristics and architectures are suitable over dynamic networking conditions. To develop such understanding, we conducted a detailed analysis and performance study on three routing protocols, namely virtual ad-hoc routing protocol-source based (VARP-S) Abolhasan et al. (2018), SDN-based multi-hop device-to-device routing protocol (SMDRP) Abdollahi et al. (2019) and hybrid SDN architecture for wireless distributed networks (HSAW) Abolhasan et al. (2015). Our investigations illustrate that VARP-S and SMDRP perform best in terms of energy consumption and cellular routing overhead. However, HSAW shows better performance in terms of end-to-end (E2E) delay and packet loss over lower network and traffic densities.

Scalable and Reliable Data Center Networks by Combining Source Routing and Automatic Labelling

Today, most user services are based on cloud computing, which leverages data center networks (DCNs) to efficiently route its communications. These networks process high volumes of traffic and require exhaustive failure management. Furthermore, expanding these networks is usually costly due to their constraint designs. In this article, we present enhanced Torii (eTorii), an automatic, scalable, reliable and flexible multipath routing protocol that aims to accomplish the demanding requirements of DCNs. We prove that eTorii is, by definition, applicable to a wide range of DCNs or any other type of hierarchical network and able to route with minimum forwarding table size and capable of rerouting around failed links on-the-fly with almost zero cost. A proof of concept of the eTorii protocol has been implemented using the Ryu SDN controller and the Mininet framework. Its evaluation shows that eTorii balances the load and preserves high-bandwidth utilization. Thus, it optimizes the use of DCN resources in comparison to other approaches, such as Equal-Cost Multi-Path (ECMP).

Scalable and efficient routing protocol for internet of things by clustering cache and diverse paths

This paper proposes SENR, a scalable and efficient named-based routing protocol for the internet of things (IoT). SENR explores semantic notification and opportunistic caching strategy to enhance the data retrieval efficiency for smart systems. First, SENR performs data aggregation according to the hierarchy of namespace, and stores data over in-network storage node. It also marks each route notification at the edge nodes, and allows the interest with the same name prefix to choose the same edge routing node towards to the storage node. Second, SENR adopts link-state routing protocols to collect network topology and compute the shortest path to the content source nodes, moreover, it uses distance-vector routing protocols to select multiple alternative paths to cope with node failures. Third, SENR employs partial routing update to explicit support of dynamic paths and caching capabilities. Simulation results demonstrate that SENR can significantly reduce the content retrieval delay and routing overheads.

Scalable and efficient routing protocol for internet of things by clustering cache and diverse paths

Scalable and efficient routing protocol for internet of things by clustering cache and diverse paths

A multi-tier based clustering framework for scalable and energy efficient WSN-assisted IoT network

The effectiveness of wireless sensor network (WSN) in Internet of Thing (IoT) based large scale application depends on the deployment method along with the routing protocol. The sensor nodes are an important component of WSN-assisted IoT network running on limited and non-rechargeable energy resource. The performance of WSN-assisted IoT is decreased, when network is deployed at large area. So, developing robust and energy-efficient routing protocol is a challenging task to prolong the network lifetime. In contrast to the state-of-the-art techniques this paper introduces Scalable and energy efficient routing protocol (SEEP). SEEP leverages the multi-hop hierarchical routing scheme to minimize the energy consumption. To achieve scalable and energy efficient network, SEEP employs a multi-tier based clustering framework. The network area in SEEP is divided into various zones with the help of proposed subarea division algorithm. The number of zones in the network are increased as the network size increases to avoid long-distance communication. Every zone is divided into certain number of clusters (sub-zones) and the number of clusters are increased towards the base station, whereas the zone width is decreased. In every cluster, some of the optimal nodes are promoted as a Relay Node (RN) and Cluster Head (CH). Normal nodes send their sensed data to the base station via local RN and CH in a multi-hop way. Furthermore, propose protocol provides a trade-off between distance and energy to prolong the network lifetime. In the proposed framework, static and mobile scenarios have been considered by applying Random walk and Random waypoint model for node mobility in simulation to make it more realistic as the various application of WSN-assisted IoT. The effectiveness of SEEP is examined against LEACH, M-LEACH, EA-CRP, TDEEC, DEEC, SEP, and MIEEPB, and result indicates that SEEP performs better for different network metrics: network lifetime, scalability, and energy efficiency.

Attestation-enabled secure and scalable routing protocol for IoT networks

Cybercrime in the past decade has experienced an all-time high due to the inclusion of so-called smart devices in our daily lives. These tiny devices with brittle security features are often dubbed as the Internet of Things (IoT). Their inclusion is not only limited to our daily lives but also in different fields, for example, healthcare, smart-industries, aviation, and smart-cities. Although IoT devices make our lives easy and perform our jobs in a smart way, but their fragile security mechanisms pose a severe challenge regarding safety and privacy of its users. Attacks like Stuxnet, and Mirai-botnet are the key examples of the damages that can be caused by maliciously controlling these devices. One effective tool to identify a malicious entity at a network device is to perform Remote Attestation (RA). However, performing RA over a large, heterogeneous IoT network is difficult tasks due to resource constrain nature of these networks. To this end, we propose a novel scheme called SARP, which is an attestation-assisted secure and scalable routing protocol for IoT networks. SARP performs attestation in large scale IoT networks by using Routing Protocol for Low Power and Lossy Networks (RPL) framework and exploiting the inbuilt features of RPL. In particular, SARP uses attestation technique that not only secures the network from internal attacks, but it also provides security to RPL’s data communication process, which helps to improve the overall network performance. Moreover, SARP supports network mobility, device heterogeneity, and network scalability, while it does not sacrifice the key requirements of IoT networks such as low energy and memory consumption, and low network overhead. The simulation results obtained in different IoT scenarios in presence of various types of attacks show the effectiveness of SARP, concerning energy consumption, packet delivery ratio, network overhead, data integrity, and communication security.

Classification of DoS Attacks in Smart Underwater Wireless Sensor Network

Due to deployment in sensitive military areas and other security applications, wireless networks are becoming a famous research spot in the field of computer science. To ratify the security and reliability in such kinds of application intrusion detection system can play an important role. There is a need of intrusion detection system, which has the capability to detect a large number of possible threats in wireless sensor networks. This article contains a customized dataset for smart underwater wireless sensor network that can be categorized into four types of DoS attacks (Blackhole, Grayhole, Flooding and Scheduling attacks). For the experimental purpose, since it is highly used in WSN, Low Energy Aware Cluster Hierarchy protocol has been used in this research work. Vector based forwarding provide scalable routing protocol to deploy smart underwater wireless sensor network. Using NS2 network simulator model a scheme has been defined to collect network traffic and create the dataset. Artificial Neural Network has been applied to train the dataset to classify it into different DoS attacks. Experimental work performed here gives high classification rate and accuracy for mentioning attacks with the help of proposed dataset. In future, suggested method can be useful for more attacks like Sybil/Wormhole presented in datalink layer as DoS attacks.

Self-Organizing and Scalable Routing Protocol (SOSRP) for Underwater Acoustic Sensor Networks.

Underwater Acoustic Sensor Networks (UASN) have two important limitations: a very aggressive (marine) environment, and the use of acoustic signals. This means that the techniques for terrestrial wireless sensor networks (WSN) are not applicable. This paper proposes a routing protocol called “Self-Organizing and Scalable Routing Protocol” (SOSRP) which is decentralized and based on tables residing in each node. A combination of the hop value to the collector node and the distance is used as a criterion to create routes leading to the sink node. The expected functions of the protocol include self-organization of the routes, tolerance to failures and detection of isolated nodes. Through the implementation of SOSRP in Matlab and a model of propagation and energy being appropriate for marine environment, performance results are obtained in different scenarios (varying both nodes and transmission range) that include parameters such as end-to-end packet delay, consumption of energy or length of the created routes (with and without failure). The results obtained show a stable, reliable and suitable operation for the deployment and operation of nodes in UASN networks.

A novel multi-featured metric for adaptive routing in mobile ad hoc networks

The design of adaptive, scalable, and low cost routing protocols presents one of the most challenging research problems in mobile ad hoc networks (MANETs). Many routing protocols for MANETs have been proposed in the literature, which are based mainly on selecting the shortest path between communication endpoints. In this paper, a new evolution-based routing metric called EVO is proposed. This metric is generated automatically by means of genetic programming. In the evolution process of this metric, mobility- and traffic-related features are employed. In this study, the metric is applied to the Ad hoc On-Demand Distance Vector (AODV) protocol, one of the most popular on-demand routing algorithms for MANETs. The modified version of AODV, called EVO-AODV, ranks and selects routes according to the evolved multi-featured metric between communication endpoints. The performance of the proposed metric has been tested on networks with varying mobility and traffic patterns. The metric is also compared with AODV and two recently proposed routing metrics, the hop change metric (HOC) (Zangabad 2014) and encounter-based routing metric (PER) (Son et al. in Ad Hoc Netw 14:2–14, 2014). The extensive simulation results demonstrate that the proposed approach improves the packet delivery ratio significantly and also decreases the packet drop rate, routing overhead, and end-to-end delay, especially on networks under medium traffic.

A Centralized Routing Protocol With a Scheduled Mobile Sink-Based AI for Large Scale I-IoT

Extensive efforts have been undertaken to enhance the centralized monitoring-based software-defined network (SDN) concept of the large-scale intelligent-Internet of Things (I-IoT). Furthermore, the number of IoT devices in vast environments is increasing and a scalable routing protocol has therefore become essential. However, due to associated resource restrictions, only very small functions can be configured using IoT nodes, principally those related to the power supply. One solution for increasing network scalability and prolonging the life of the network is to use the mobile sink (MS). However, determining the optimal set of data gathering points ( $S_{\mathrm{ DG}}$ ), optimal path, scheduling the entire network with MS in an energy efficient manner and prolonging the life of the network present huge challenges, particularly in large-scale networks. This paper therefore proposes an energy efficient routing protocol based on artificial intelligence (AI), i.e., particle swarm optimization and genetic algorithm, for large scale I-IoT networks under the SDN and cloud architecture. The basic premise is to exploit cloud resources, such as storage and data-center units by using a centralized SDN controller-based AI to calculate: a load-balanced table of clusters, an optimal $S_{\mathrm{ DG}}$ , and an optimal path for the MS (MSopath). Moreover, the proposed new routing technique will prevent significant energy dissipation by the cluster head and by all nodes in general by scheduling the whole network. Consequently, the SDN controller essentially balances energy consumption by the network during the routing construction process as it considers both the $S_{\mathrm{ DG}}$ and the movement of the MS. Simulation results demonstrate the effectiveness of the suggested model by improving the network lifespan up to 54%, volume of data aggregated by the MS up to 93% and reducing the delay of the MSopath by 61% in comparison with other approaches.