Routing In Internet Of Things Research Articles

VLA-CR: A Variable Action-set Learning Automata-based Cognitive Routing Protocol for IoT

Internet of Things (IoT) is a heterogeneous, mixed, and uncertain ubiquitous network, which has significantly affected the concept of wireless networking. A large number of wireless devices have connected through the IoT and shared large amounts of data. So, efficient routing and forwarding data packets from the wireless devices toward gateways, which have connected to the Internet, is one of the most important issues in IoT. This paper has focused on routing and forwarding data packets in IoT. Firstly, a learning automata-based cognitive framework has been applied to integrate cognition into IoT; because current IoT lacks intelligence and cannot satisfy the increasing application performance requirements, and also adding cognition into IoT equips it with a brain and high level intelligence. Then, a new routing and forwarding protocol, which benefits from cross-layer optimization between routing and Media Access Control (MAC) layer protocols, has been proposed. In the proposed protocol a network of variable action-set learning automata establishes a route between source nodes and a corresponding gateway, by making a directed acyclic graph toward the gateway. Then, using a set of learning automata, MAC layer protocol parameters are configured to properly forward data packets hop by hop. The proposed protocol has been named VLA-CR (Variable Action-set Learning Automata-based Cognitive Routing Protocol). Based on Martingale theorem, the convergence of VLA-CR has been proved. Finally, extensive simulation experiments have been conducted to show the performance of the proposed protocol. Simulation results show the superiority of VLA-CR over several existing routing protocol in terms of end-to-end reliability, end-to-end delay, power consumption, and routing time.

Improving the Network Life Time in Smart Grid Sensor Nodes by Considering Nodes Usage

Our modern world is involved with technology and internet more than any time. Internet of things has been invented for the comfort of humans. Smart grid is one of the most highlighted aspects of internet of things. Routing of these networks is a significant point and the aim in this article is to find an algorithm which is based on internet of things routing and it may reduce the path between source and destination to decrease power consumption of nodes. In this paper, we introduce an algorithm which find out the shortest path between source and destination. It notices number of hop and packet delivery rate that each node pass. This shortest path presents packets transfer from source to destination in a way which use the least amount of remaining energy of sensor batteries. This cause to reduce the energy consumption and helps to increase network’s life time. Moreover, we improve the effect of number of hops between source to destination to 33% in minimum and average and also 34% for maximum case. Furthermore, by considering the effect of send and receive between middle nodes minimum state became 17%, average about 41% and maximum case became 42%.

SD-MIoT: A Software-Defined Networking Solution for Mobile Internet of Things

The Internet of Things (IoT) brings new potentials in humans’ everyday life activities through enabling applications with stringent communication demands, including mobile IoT applications. State-of-the-art routing protocols for the IoT, such as IPv6 routing protocol for low-power and lossy networks (RPL), have not been originally designed for such challenging applications. Recent proposals blend the software-defined networking (SDN) paradigm with IoT, enabling better-informed and bespoke routing control, matching the application requirements. In this article, we propose SD-MIoT , an open-source SDN solution for mobile IoT environments that consists of a modular SDN controller and an OpenFlow-like protocol. SD-MIoT detects passively in real-time, the network’s mobile nodes through mobility detector (MODE), an intelligent algorithm that utilizes the connectivity graph of the SDN controller. It incorporates novel mobility-aware topology discovery mechanisms, routing policies, and flow-rule establishment methods, all of them balancing control overhead with routing robustness, according to nodes’ mobility behavior detected by MODE. We provide extensive evaluation results over two realistic scenarios, further confirming the suitability of SD-MIoT for mobile IoT environments and demonstrating reliable operation in terms of successful data packet delivery with low control overhead.

INTEGRATING PRIVACY PRESERVING IN INTERNET OF THINGS TO ENSURE DATA SECURITY USING VERTICAL PARTITIONING APPROACH

Guaranteeing security and data privacy are key issues in the Internet of Things (IoT). For the management of numerous security services, privacy plays a significant role. Devices which capable of being utilized anywhere any place, any device anything, any context anytime, anybody anytime, any business any service, in any network any path is the definition of IoT. Routing for IoT needs to be energy efficient. For multimodal problems, traditional evolutionary algorithms commonly result in population convergence towards a search space’s restricted area, hence, disregarding the local optima’s remainder. The Ant Colony Optimization (ACO) algorithm has garnered much interest and has been researched extensively since it is one of the most efficient techniques for the resolution of optimization problems. This is a population-based heuristic evolution algorithm that is influenced by the results of research of actual ants’ natural collective behaviour. Multimodal optimization’s Evolutionary algorithms can generally identify many optima within a single run and also retain their diversity of population throughout a run. Hence, for multimodal functions, these algorithms have the capability of global optimization. In this work, a hybrid ACO-Evolutionary Multimodal is proposed for energy-efficient routing. The data collected are stored in a vertically partitioned dataset to maintain the privacy of the data.

A Comprehensive Survey of the Routing Schemes for IoT applications

Internet of Things (IoT) is with a perception of ‘anything’, ‘anywhere’ and provides the interconnection among devices with a remarkable scale and speed. The prevalent intention of IoT is the datatransmission through the internet without the mediation of humans. An efficient routing protocol must be included in the IoT network for the accomplishment of its objectives and securing data transmission. Accordingly, the survey presents various routing protocols for secure data communication in IoT for providing a clear vision as the major issue in the IoT networks is energy consumption. Therefore, there is a need for devising an effective routing scheme to provide superior performance over the other existing schemes in terms of energy consumption. Thus, this review article provides a detailed review of 52 research papers presenting the suggested routing protocols based on the contentbased, clustering-based, fuzzy-based, Routing Protocol for Low power and Lossy Networks, tree-based and so on. Also, a detailed analysis and discussion are made by concerning the parameters, simulation tool, and year of publication, network size, evaluation metrics, and utilized protocols. Finally, the research gaps and issues of various conventional routing protocols are presented for extending the researchers towards a better contribution of routing protocol for the secure IoT routing.

An architecture for resilient intrusion detection in ad-hoc networks

We study efficient and lightweight Intrusion Detection Systems (IDS) for ad-hoc networks via the prism of IPv6-enabled Wireless Sensor Actuator Networks. These networks consist of highly constrained devices able to communicate wirelessly in an ad-hoc fashion, thus following the architecture of ad-hoc networks. Current state-of-the-art (IDS) has been developed taking into consideration the architecture of conventional computer networks, and as such they do not efficiently address the paradigm of ad-hoc networks, that is highly relevant in emergent networks, such as the Internet of Things (IoT). In this context, the network properties of resilience and redundancy have not been studied yet. In this work, we firstly identify a trade-off between the communication overhead and energy consumption of an IDS (as captured by the number of active IDS agents in the network) and the performance of the system in terms of successfully identifying attacks. In order to fine tune this trade-off, we model such networks as Random Geometric Graphs; a rigorous approach that allows us to capture underlying structural properties of the network. We then introduce a novel IDS architectural approach that consists of a central IDS agent a set of distributed IDS agents deployed uniformly at random over the network area. These nodes are able to efficiently detect attacks at the networking layer in a collaborative manner by monitoring locally available network information provided by IoT routing protocols such as RPL. Our detailed experimental evaluation demonstrates significant performance gains in terms of communication overhead and energy consumption while maintaining high detection rates. We also show that the performance of our IDS in ad-hoc networks does not rely on the size of the network but on fundamental underling network properties, such as the network topology and the average degree of the nodes. Conducted experiments show that our proposed IDS architecture is resilient against frequent topology changs due to nodes failures.

Enhancing Energy Saving in Smart Farming through Aggregation and Partition Aware IoT Routing Protocol.

Internet of things (IoT) for precision agriculture or Smart Farming (SF) is an emerging area of application. It consists essentially of deploying wireless sensor networks (WSNs), composed of IP-enabled sensor nodes, in a partitioned farmland area. When the surface, diversity, and complexity of the farm increases, the number of sensing nodes increases, generating heavy exchange of data and messages, and thus leading to network congestion, radio interference, and high energy consumption. In this work, we propose a novel routing algorithm extending the well known IPv6 Routing Protocol for Low power and Lossy Networks (RPL), the standard routing protocol used for IPv6 over Low-Power Wireless Personal Area Networks (6LoWPAN). It is referred to as the Partition Aware-RPL (PA-RPL) and improves the performance of the standard RPL. In contrast to RPL, the proposed technique builds a routing topology enabling efficient in-network data aggregation, hence dramatically reducing data traffic through the network. Performance analysis of a typical/realistic precision agriculture case, considering the potato pest prevention from the well-known late blight disease, shows that PA-RPL improves energy saving up to compared to standard RPL.

An Unconventional Routing Method using Particle Swarm Optimization for the Internet of Things

The study introduces novel analytical modeling of a multipath fault-tolerant routing approach where the design principle is formulated based on a bio-inspired optimization modeling of swarm optimization principles. The prime objective of this novel approach is to deal with network failures of Internet-of-Things (IoT) in a faster manner and recover the network operations as early as possible without compromising much energy. This way, the network becomes more reliable and sustainable even if any events occur that make the senor node functionally disabled and even if any types of path failures take place, regardless of energy consumption factors in IoT routing scenarios. However, the approach also capable of handling energy problems during the IoT routing scenario to a significant extent. Further, the outcome of the study shows that the fault-tolerance routing approach based on unconventional particle swarm optimization (FT-PSO) attains better results as compared to the existing baselines.

QoS Routing in Internet of Things (IoT) by Context Aware Agent priority by Meta Computational Intelligence for Evidence-based E-Health Services

Internet of Things (IoT) having taken giant leaps has emerged as one of the most promising fields with a plethora of E- Health applications. Due to burgeoning demands in data rates and Internet-enabled services, an evidence-based e-health is required in network traffic .Sudden and unforeseeable large-scale anomalies cause packet collisions and constant or sporadic interferences between multiple transmitters. Developing a ‘‘One-Queue-fits-all’’ solution is a great challenge. However, priority analysis for data services bolsters QoS. The proposed Context Aware Agent priority by Meta computational intelligence in IoT for evidence-based E- Health data service (CAAM -EH) aims to assign priority for packets from diverse networks based on their criticality levels. Data are estimated using attributes such as task, temporal, spatial and customized estimation. A Quad Tree structure is employed to organize the estimated data into various levels and priority is eventually set for transmission to the IoT. The Computational intelligence used to support event, time as well as query-based E health data from IoT.

A secure multipath reactive protocol for routing in IoT and HANETs

In numerous Internet of Things (IoT) scenarios (such as Intelligent Transportation System (ITS) or environment sensing), the ad hoc mode is widely used. Ad-hoc networks have several benefits including infrastructureless and spontaneous deployment, and the opportunity to set up temporary and dynamic networks cost-effectively. However, some of their characteristics such as the unreliability of wireless links, dynamic topology and resource constraints in energy and processing power of objects, make new protocols’ development ignore security requirements of applications in order to satisfy some quality of service. Consequently, there is a lack of standardization works in the field of secure routing among IoT devices. Furthermore, recently proposed secure routing approaches (mostly from the academic community) do not meet the current needs and requirements of secure routing for IoT applications. In this context, we propose a lightweight and secure routing scheme that combines multipath routing and trust management, that can adapt to different scenarios in the IoT environment. To analyze and evaluate our scheme, we propose a probabilistic model that considers two types of events that affect routing performance for a given node: mobility and uncooperative behavior. Based on this mathematical model, we compared the performance of our proposed routing scheme with two other multipath routing protocols namely, SMORT and DMRP. Our performance results show that our scheme is highly scalable, more efficient, and resilient compared with previous related works and is particularly suitable for insecure large and dense IoT networks.

Security Issues and Challenges in IoT Routing over Wireless Communication

The participation of Internet devices in different communications through embedded technologies and the adaptive and interactive nature of each communication affects future development tools and applications. The majority of IoT devices are able to communicate over a wireless network, improving their usability and scalability quickly. But these usability improvements drew the attackers' attention to their personal advantages and created numerous security challenges for detection and protection. Because devices are exposed to the Internet to deliver services, they are particularly vulnerable to various threats to security and privacy.Therefore, a major concern on the Internet of Things (IoT) is the discovery of such abnormal activities that pose a security threat so that appropriate solutions can be provided with a high level of reliability. This paper will be based on a detailed overview of IoT wireless security issues and abnormal activity detection methods. It also provided an overview of the various anomaly detection models and security challenges for launching the IoT connection to the wireless network.

Proposing a Secure RPL based Internet of Things Routing Protocol: A Review

Nowadays, the Internet of Things (IoT) research domain attracts the researchers, due to its extensive collection of applications and ease in deploying in several domains of real life, particularly for environments that are considered critical such as E-health, smart homes, and smart cities. Things in smart cities are intractable via the Internet. These things are naturally deployed in a distributed environment wirelessly. They become vulnerable to the diverse security attacks that can adversely influence their proper functionalities at any time. The stated problem severity even becomes higher when they are deployed in smart cities. In addition, it is very likely to compromise data while transferring from one source to another until reaching the destination during data routing. Existing Routing Protocols for Low Power and Lossy Networks (RPL) are considered lightweight and secure routing protocols for IoT devices, which offer a slight safeguard against innumerable forms of RPL routing attacks. Based on the nature of the IoT network, being resource constraints, the conventional routing techniques do not suit them at all. The IoT routing security is therefore, a challenging task. This review aims to elaborate on the current research literature, opportunities and research gaps of secure RPL routing protocols. Where mainly considering the Rank and Version number attacks types for IoT applications. Further, the review extravagant the need for a new secure RPL protocol to address the security issues of IoT applications for smart cities particularly based on available literature.

SDN-MCHO: Software Define network based Multi-criterion Hysteresis Optimization based for reliable device routing in Internet of Things for the smart surveillance application

Internet of Things (IoT) is a sophisticated communication paradigm that is capable of integrating diverse elements from humans to interactive machines. This kind of integration provides seamless and ubiquitous communication support for mobile users. The infrastructure of IoT environment endorses multiple technologies and networks where, selecting a precise neighbor/ device becomes mandatory for the extreme surveillance application. It determines the reliability is service discovery and resource access. The process of request processing through reliable neighbor discovery is leveraged using multi-criterion hysteresis optimization (MCHO) based on SDN aided routing that is discussed in this article. The introduced routing optimization method is capable of identifying reliable IoT neighbors for request handling and delivery. This routing process depends on the activation function that classifies neighbors on the basis of three metrics namely Received Signal Strength (RSS), Rank, and Expected Transmission Count (ETX)for differentiating the neighbors on the basis of their consistency. Through differentiated hysteresis analysis, the neighbors are segregated and hence optimal devices are integrated to form a request friendly route to the access layer. The introduced routing optimization method is evaluated through appropriate experiments and the results are verified using the metrics: throughput, request delivery ratio, delay, response time, request loss and average ETX.

Lecr: Less Energy Consumption Routing in Internet of Things

Internet of Things (IoT) constitutes a network of various devices has an equipment with the mandatory facility of communication and optional facilities of sensing, information collecting, storage and processing. IoT network has been used for research and development purpose in many application areas such as military environment, traffic management, and e-healthcare system. IoT network was enormous in scale and complexity, mainly in terms of energy efficiency because battery lifetime is limited. The previous routing protocols for IoT are difficult and require a huge memory use and high energy consumption which are insufficient for IoT network processing. For that reason, an efficient routing algorithm needed to decrease energy consumption while communication. To tackle this problem, this paper proposes Less Energy Consumption Routing (LECR) algorithm. This algorithm reduces energy consumption using 4 ways in IoT, (1) Sleep and Wake up Scheduling, (2) Route Discovery in IoT Base Station (3) Less Power Consumption Route for Communication (4) Reduce Overhead while Routing. The experimental result proves the LECR algorithm reduces IoT devices battery drain and increases lifetime of the IoT network efficiently.

Multi-feature fusion energy-saving routing in internet of things based on hybrid ant colony algorithm

Multi-feature fusion energy-saving routing in internet of things based on hybrid ant colony algorithm

Multi-feature fusion energy-saving routing in internet of things based on hybrid ant colony algorithm

This paper analyses the research status of sensor networks and several improved LEACH protocols. It is known that there are some shortcomings in current low-energy clustering protocols: the problem of uneven network cluster and unequal energy consumption of each node in the cluster group leads to excessive energy consumption of some nodes, the whole network life cycle is also greatly shortened. This paper proposes a multi-feature fusion energy-saving routing algorithm based on hybrid ant colony algorithm to optimise and upgrade LEACH energy-saving routing model for the internet of things on the basis of LEACH (NPCHS-Leach) to improve the problems of short lifetime and low energy utilisation caused by existing clustering routing protocols, it improves and pro-longs the network life cycle. Finally, the effectiveness of the proposed algorithm is verified by simulation experiments.

When Crowdsourcing Meets Social IoT: An Efficient Privacy-Preserving Incentive Mechanism

Crowdsourcing is an effective paradigm in human centric computing for addressing problems by utilizing human computation power, especially in booming social Internet of Things (IoT). By leveraging mutual friendship between computing entities (i.e., workers), collaborative tasks can thus be routed and finally fulfilled by multihop friends with high expertise. However, crowdsourcing in social IoT may reveal the privacy of task requesters which results in a large dilemma. In this paper, we focus on designing a multihop routing incentive mechanism which can also preserve task requester’s privacy. Specifically, a utility maximization problem under privacy and budget feasibility constraints is formulated. Defining the conditions for privacy insurance, we give guidelines on how many subtasks should an entire task be divided into, and analyze the tradeoff between privacy and task accuracy. To enable efficient crowdsourcing task routing in social IoT, we first consider 1-hop myopic routing case and propose a near-optimal task assignment algorithm with 1/2 approximation ratio for an arbitrary prior knowledge. We further design multihop payment policy to establish an equilibrium where workers are motivated to forward subtasks to their friends with the best expertise. The extensive simulations validate that our mechanism achieves a high level of average information gain with modest privacy guarantee.

A New Small-World IoT Routing Mechanism Based on Cayley Graphs

An increasing number of low-power Internet of Things (IoT) devices will be widely deployed in the near future. Considering the short-range communication of low-power devices, multihop transmissions will become an important transmission mechanism in IoT networks. It is a crucial for low-power devices to transmit data over long distances via multihop in a low-delay and reliable way. The small-world characteristics of networks indicate that the network has an advantage of a small average shortest-path length (ASL) and a high average clustering coefficient (ACC). In this article, a new IoT routing mechanism considering small-world characteristics is proposed to reduce the delay and improve the reliability. The ASL and ACC are derived for the performance analysis of small-world characteristics in IoT networks based on Cayley graphs. Besides, the reliability and delay models are proposed for small-world IoT based on Cayley graphs (SWITCH). The simulation results demonstrate that SWITCH has lower delay and better reliability than that of conventional nearest neighboring routing (NNR). Moreover, the maximum delay of SWITCH is reduced by 50.6% compared with that by NNR.

A Review on Routing in Internet of Things

Recently, internet of things has drawn attention among the academicians, governments and engineers from various sectors. There are many critical issues in IoT such as security, scalability, big data analytics. Availability, interoperability, performance, mobility. This paper focus on providing optimal routing among the various networking environment such as wired wireless and sensors in the IoT. In this paper the major research issues involved in the existing routing protocols to meet the requirements of internet of things are reviewed the major issues involved in the design of a routing protocol and the different classification of routing protocols are studied. The major challenges of the internet of things, must address the problem of dynamic topology, scalability, mobility of nodes and limited bandwidth. The review covers different kinds of routing protocols such as reactive, proactive, hybrid, location aware, hybrid, multicast, multipath, Geocast, power aware and hierarchical existing geometric routing protocols have been sensibly studied which involves discussion on routing techniques, the advantages and disadvantages of the existing work area analysed in order to help the future researchers. The analysis of existing routing protocols is carried out based on shortest path, least transmission time. Finally, a research open challenge in routing which needs to be addressed by the research and academic community are discussed.

Towards a Light Weight Routing Security in IoT Using Non-cooperative Game Models and Dempster–Shaffer Theory

The internet of things (IoT) has become an emerging technology owing to the rapidly increasing number of devices and their connectivity to the internet. Routing protocol for low-power and lossy networks (RPL) is a predominant routing protocol for the IoT. The RPL routing embraces the distance to the gateway node as a rank for parent selection and builds the destination oriented directed acyclic graph (DODAG). The malicious nodes utilize the advantage of low rank based parent selection to involve in data forwarding. However, the malicious node behavior and the harsh channel conditions due to the collision are equally considered as malicious in the existing detection mechanisms. In addition, most of the routing solutions exploit the traditional schemes for IoT security, but not considering the adaptability to IoT routing specifications. Thus, this work attempts to integrate the DODAG-specific contextual trust model, and RPL-specific rank variance factor, named as Secure RPL using non-cooperative game MOdels and DEmpster Shaffer Theory in IoT (S-MODEST), such that it can detect the attackers accurately and significantly reduces the resource consumption. The non-cooperative game model consists of two interrelated formulations in the proposed solution. Firstly, non-zero sum game constructs the trust model and extracts the contextual information from DODAG structure to strengthen the trustworthiness. Secondly, the evolutionary game is utilized for trusted router selection. The non-zero sum game theory formulates the interaction of nodes and assists the trust measurement by applying direct and restricted Dempster–Shaffer theory. The DODAG-specific contextual trust evaluation differentiates the collision dropping from the undesirable scenarios and supports the nodes in building a highly trusted DODAG structure to the gateway using multiplicative trust factor. To enforce the routing cooperation of selfish nodes and differentiate malicious nodes, the evolutionary game model embraces the node trust, which is measured using non-zero sum game model. As a result, the non-cooperative game models enable the S-MODEST to precisely select a secure route as well as to maintain the routing performance effectively. The simulation results demonstrate that the detection accuracy and throughput of the proposed context-aware noncooperative game theory based trust model are substantially higher and outperform the existing SecTrust.