Energy-Efficient Relay-Selection-Based Dynamic Routing Algorithm for IoT-Oriented Software-Defined WSNs

Ding, Zhaoming; Shen, Lianfeng; Chen, Hongyang; Yan, Feng; Ansari, Nirwan

doi:10.1109/jiot.2020.3002233

Cited by 50 publications

(16 citation statements)

References 55 publications

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“…Contributing to the research of magnetic sensing approaches, this article adopts several semiautomated learning techniques in order to design filters, features and hyperparameters and achieve the highest recognition accuracy. In [13], DRA-EERS, a dynamic routing algorithm for software-defined wireless sensor networks (SDWSNs) is proposed, based on energy-efficient relay selection. To find the best path according to energy-efficient criteria, first, the state-transition probability of each node is calculated and a link weight is attributed to the network links relevant to the link cost and reward values, while considering the location of the nodes.…”

Section: Related Workmentioning

confidence: 99%

Time Series Network Data Enabling Distributed Intelligence—A Holistic IoT Security Platform Solution

et al. 2022

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The Internet of Things (IoT) encompasses multiple fast-emerging technologies controlling and connecting millions of new devices every day in several application domains. The increased number of interconnected IoT devices, their limited computational power, and the evolving sophistication of cyber security threats, results in increased security challenges for the IoT ecosystem. The diversity of IoT devices, and the variety of QoS requirements among several domains of IoT application, impose considerable challenges in designing and implementing a robust IoT security solution. The aim of this paper is to present an efficient, robust, and easy-to-use system, for IoT cyber security operators. Following a by-design security approach, the proposed system is a platform comprising four distinct yet cooperating components; a distributed AI-enhanced detection of potential threats and anomalies mechanisms, an AI-based generation of effective mitigation strategies according to the severity of detected threats, a system for the verification of SDN routing decisions along with network- and resource-related policies, and a comprehensive and intuitive security status visualization and analysis. The distributed anomaly detection scheme implementing multiple AI-powered agents is deployed across the IoT network nodes aiming to efficiently monitor the entire network infrastructure. Network traffic data are fed to the AI agents, which process consecutive traffic samples from the network in a time series analysis manner, where consecutive time windows framing the traffic of the surrounding nodes are processed by a graph neural network algorithm. Any detected anomalies are handled by a mitigation engine employing a distributed neural network algorithm, which exploits the recorded anomalous events and deploys appropriate responses for optimal threat mitigation. The implemented platform also includes the hypothesis testing module, and a multi-objective optimization tool for the quick verification of routing decisions. The system incorporates visualization and analytics functionality and a customizable user interface.

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Section: Related Workmentioning

confidence: 99%

Time Series Network Data Enabling Distributed Intelligence—A Holistic IoT Security Platform Solution

et al. 2022

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“…Low energy consumption in IoT devices is a functional requirement. Proposals on caching and scheduling policies to reduce transmission delays and power consumption, such as [71] and a dynamic routing algorithm based on energy-efficient relay selection [72], confirm the need to keep computing operations in the IoT device lightweight.…”

Section: Diota: a Decentralised Ledger-based Framework For Data Authe...mentioning

confidence: 99%

Identity and Access Management Resilience against Intentional Risk for Blockchain-Based IOT Platforms

2021

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Some Internet of Things (IoT) platforms use blockchain to transport data. The value proposition of IoT is the connection to the Internet of a myriad of devices that provide and exchange data to improve people’s lives and add value to industries. The blockchain technology transfers data and value in an immutable and decentralised fashion. Security, composed of both non-intentional and intentional risk management, is a fundamental design requirement for both IoT and blockchain. We study how blockchain answers some of the IoT security requirements with a focus on intentional risk. The review of a sample of security incidents impacting public blockchains confirm that identity and access management (IAM) is a key security requirement to build resilience against intentional risk. This fact is also applicable to IoT solutions built on a blockchain. We compare the two IoT platforms based on public permissionless distributed ledgers with the highest market capitalisation: IOTA, run on an alternative to a blockchain, which is a directed acyclic graph (DAG); and IoTeX, its contender, built on a blockchain. Our objective is to discover how we can create IAM resilience against intentional risk in these IoT platforms. For that, we turn to complex network theory: a tool to describe and compare systems with many participants. We conclude that IoTeX and possibly IOTA transaction networks are scale-free. As both platforms are vulnerable to attacks, they require resilience against intentional risk. In the case of IoTeX, DIoTA provides a resilient IAM solution. Furthermore, we suggest that resilience against intentional risk requires an IAM concept that transcends a single blockchain. Only with the interplay of edge and global ledgers can we obtain data integrity in a multi-vendor and multi-purpose IoT network.

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“…This method is a beneficial improvement to the problem of static path selection. A dynamic routing algorithm based on energy-efficient relay selection (RS), referred to as DRA-EERS, is proposed in [10] to adapt to the higher dynamics in timevarying software-defined wireless sensor networks. In [11], a solution to the data advertising problem that is based upon random linear network coding was provided; the simulation results show that the proposed approach is both highly scalable and can significantly decrease the time for advertisement message delivery.…”

Section: The Outline Of Dtnmentioning

confidence: 99%

Data Transmission Evaluation and Allocation Mechanism of the Optimal Routing Path: An Asynchronous Advantage Actor‐Critic (A3C) Approach

Ding

Guo

et al. 2021

Wireless Communications and Mobile Computing

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The delay tolerant networks (DTN), which have special features, differ from the traditional networks and always encounter frequent disruptions in the process of transmission. In order to transmit data in DTN, lots of routing algorithms have been proposed, like “Minimum Expected Delay,” “Earliest Delivery,” and “Epidemic,” but all the above algorithms have not taken into account the buffer management and memory usage. With the development of intelligent algorithms, Deep Reinforcement Learning (DRL) algorithm can better adapt to the above network transmission. In this paper, we firstly build optimal models based on different scenarios so as to jointly consider the behaviors and the buffer of the communication nodes, aiming to ameliorate the process of the data transmission; then, we applied the Deep Q-learning Network (DQN) and Advantage Actor-Critic (A3C) approaches in different scenarios, intending to obtain end-to-end optimal paths of services and improve the transmission performance. In the end, we compared algorithms over different parameters and find that the models build in different scenarios can achieve 30% end-to-end delay decline and 80% throughput improvement, which show that our algorithms applied in are effective and the results are reliable.

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Energy-Efficient Relay-Selection-Based Dynamic Routing Algorithm for IoT-Oriented Software-Defined WSNs

Cited by 50 publications

References 55 publications

Time Series Network Data Enabling Distributed Intelligence—A Holistic IoT Security Platform Solution

Time Series Network Data Enabling Distributed Intelligence—A Holistic IoT Security Platform Solution

Identity and Access Management Resilience against Intentional Risk for Blockchain-Based IOT Platforms

Data Transmission Evaluation and Allocation Mechanism of the Optimal Routing Path: An Asynchronous Advantage Actor‐Critic (A3C) Approach

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