Showing papers on "Communications protocol published in 2020"

The Use of MQTT in M2M and IoT Systems: A Survey

Abstract: Nowadays billions of smart devices or things are present in Internet of Things (IoT) environments, such as homes, hospitals, factories, and vehicles, all around the world. As a result, the number of interconnected devices is continuously and rapidly growing. These devices communicate with each other and with other services using various communication protocols for the transportation of sensor or event data. These protocols enable applications to collect, store, process, describe, and analyze data to solve a variety of problems. IoT also aims to provide secure, bi-directional communication between interconnected devices, such as sensors, actuators, microcontrollers or smart appliances, and corresponding cloud services. In this paper we analyze the growth of M2M protocol research (MQTT, AMQP, and CoAP) over the past 20 years, and show how the growth in MQTT research stands out from the rest. We also gather relevant application areas of MQTT, as the most widespread M2M/IoT protocol, by performing a detailed literature search in major digital research archives. Our quantitative evaluation presents some of the important MQTT-related studies published in the past five years, which we compare to discuss the main features, advantages, and limitations of the MQTT protocol. We also propose a taxonomy to compare the properties and features of various MQTT implementations, i.e. brokers and libraries currently available in the public domain to help researchers and end-users to efficiently choose a broker or client library based on their requirements. Finally, we discuss the relevant findings of our comparison and highlight open issues that need further research and attention.

A Survey of IoT Security Based on a Layered Architecture of Sensing and Data Analysis.

Abstract: The Internet of Things (IoT) is leading today’s digital transformation Relying on a combination of technologies, protocols, and devices such as wireless sensors and newly developed wearable and implanted sensors, IoT is changing every aspect of daily life, especially recent applications in digital healthcare IoT incorporates various kinds of hardware, communication protocols, and services This IoT diversity can be viewed as a double-edged sword that provides comfort to users but can lead also to a large number of security threats and attacks In this survey paper, a new compacted and optimized architecture for IoT is proposed based on five layers Likewise, we propose a new classification of security threats and attacks based on new IoT architecture The IoT architecture involves a physical perception layer, a network and protocol layer, a transport layer, an application layer, and a data and cloud services layer First, the physical sensing layer incorporates the basic hardware used by IoT Second, we highlight the various network and protocol technologies employed by IoT, and review the security threats and solutions Transport protocols are exhibited and the security threats against them are discussed while providing common solutions Then, the application layer involves application protocols and lightweight encryption algorithms for IoT Finally, in the data and cloud services layer, the main important security features of IoT cloud platforms are addressed, involving confidentiality, integrity, authorization, authentication, and encryption protocols The paper is concluded by presenting the open research issues and future directions towards securing IoT, including the lack of standardized lightweight encryption algorithms, the use of machine-learning algorithms to enhance security and the related challenges, the use of Blockchain to address security challenges in IoT, and the implications of IoT deployment in 5G and beyond

AFLNET: A Greybox Fuzzer for Network Protocols

Abstract: Server fuzzing is difficult. Unlike simple command-line tools, servers feature a massive state space that can be traversed effectively only with well-defined sequences of input messages. Valid sequences are specified in a protocol. In this paper, we present AFLNET, the first greybox fuzzer for protocol implementations. Unlike existing protocol fuzzers, AFLNET takes a mutational approach and uses state-feedback to guide the fuzzing process. AFLNET is seeded with a corpus of recorded message exchanges between the server and an actual client. No protocol specification or message grammars are required. AFLNET acts as a client and replays variations of the original sequence of messages sent to the server and retains those variations that were effective at increasing the coverage of the code or state space. To identify the server states that are exercised by a message sequence, AFLNET uses the server’s response codes. From this feedback, AFLNET identifies progressive regions in the state space, and systematically steers towards such regions. The case studies with AFLNET on two popular protocol implementations demonstrate a substantial performance boost over the state-of the-art. AFLNET discovered two new CVEs which are classified as critical (CVSS score CRITICAL 9.8).

Security in IoMT Communications: A Survey

Abstract: The Internet of Medical Things (IoMT) couples IoT technologies with healthcare services in order to support real-time, remote patient monitoring and treatment. However, the interconnectivity of critical medical devices with other systems in various network layers creates new opportunities for remote adversaries. Since most of the communication protocols have not been specifically designed for the needs of connected medical devices, there is a need to classify the available IoT communication technologies in terms of security. In this paper we classify IoT communication protocols, with respect to their application in IoMT. Then we describe the main characteristics of IoT communication protocols used at the perception, network and application layer of medical devices. We examine the inherent security characteristics and limitations of IoMT-specific communication protocols. Based on realistic attacks we identify available mitigation controls that may be applied to secure IoMT communications, as well as existing research and implementation gaps.

A Review of IEC 62351 Security Mechanisms for IEC 61850 Message Exchanges

Abstract: Smart grid is the nexus of advanced information and communication technologies and legacy power systems. With increasing awareness on the vulnerabilities of smart grids to cyberattacks, cybersecurity is becoming a prime concern. Earlier, it was assumed that the power system communication protocols are very specialized and different, so the “security by obscurity” approach would be sufficient. However, with the standardization of communication protocols for power utilities and the emergence of the power market, this approach is no longer valid. IEC 62351 Standard has been published to provide security recommendations for different power system communication protocols including IEC 61850. IEC 61850 is emerging as the most promising and popular power system communication standard. Therefore, in this article, a detailed analysis of security threats, possible attacks, and security requirements for IEC 61850 communication is presented. Building on this, the security considerations presented in IEC 62351 for securing different IEC 61850 messages, such as generic object-oriented substation events (GOOSE), sampled values (SV), routable-GOOSE, routable-SV, and manufacturing message specification messages have been presented in great detail.

Evaluation of CAN Bus Security Challenges

Abstract: The automobile industry no longer relies on pure mechanical systems; instead, it benefits from many smart features based on advanced embedded electronics. Although the rise in electronics and connectivity has improved comfort, functionality, and safe driving, it has also created new attack surfaces to penetrate the in-vehicle communication network, which was initially designed as a close loop system. For such applications, the Controller Area Network (CAN) is the most-widely used communication protocol, which still suffers from various security issues because of the lack of encryption and authentication. As a result, any malicious/hijacked node can cause catastrophic accidents and financial loss. This paper analyses the CAN bus comprehensively to provide an outlook on security concerns. It also presents the security vulnerabilities of the CAN and a state-of-the-art attack surface with cases of implemented attack scenarios and goes through different solutions that assist in attack prevention, mainly based on an intrusion detection system (IDS).

An Intrusion Detection System Against DDoS Attacks in IoT Networks

Abstract: In this paper, we present an Intrusion Detection System (IDS) using the hybridization of the deep learning technique and the multi-objective optimization method for the detection of Distributed Denial of Service (DDoS) attacks in the Internet of Things (IoT) networks is proposed in this paper. IoT networks consist of different devices with unique hardware and software configurations communicating over different communication protocols, which produce huge multidimensional data that make IoT networks susceptible to cyber-attacks. In a network the IDS is a vital tool for securing it from cyber-attacks. Detection of new emerging cyber threats are becoming difficult for existing IDS, and therefore advanced IDS is required. A DDoS attack is a cyber-attack that has posed substantial devastating losses in IoT networks recently. In this paper, we propose an IDS founded on the fusion of a Jumping Gene adapted NSGA-II multi-objective optimization method for data dimension reduction and the Convolutional Neural Network (CNN) integrating Long Short-Term Memory (LSTM) deep learning techniques for classifying the attack. The experimentation is conducted using a High-Performance Computer (HPC) on the latest CISIDS2017 datasets on DDoS attacks and achieved an accuracy of 99.03% with a 5-fold reduction in training time. We evaluated our proposed method by comparing it with other state-of-the-art algorithms and machine learning algorithms, which confirms that the proposed method surpasses other approaches.

Emerging use of UAV’s: secure communication protocol issues and challenges

Abstract: In recent years, unmanned aerial vehicles (UAVs)/drones have gained popularity in many areas due to their widely used applications. They are used extensively in military and civil applications such as search and rescue, reconnaissance, monitoring of the environment and traffic, entertainment, and logistics. UAVs usually operate with the assistance of various communication protocols, such as MAVLink, UranusLink, UAVCan, from a remote control or a ground control station (GCS). These protocols of communication are used for messages exchange. These messages contain important UAV status information and control commands that are sent from GCS to the UAV and GCS to the UAV, although these protocols offer better communication. However, most of the messages are not subtle, and there is no delicate way to secure such messages and are vulnerable to several security threats, including man-in-the-middle attack, DoS attack, packet data injection attack, and eavesdropping. It can lead to severe consequences, for example, a UAV crash, stealing important military operation data, falsifying reports in a reconnaissance or search and rescue operation, and much more. A new secure communication protocol is therefore required to ensure that the necessary safety standards for the communication of UAVs are met. This chapter gives an overview of UAV, their working mechanism, types, different communication protocols which are used for communication among UAVs. It also discusses the issues related to these communication protocols and propose a new secure communication protocol for UAVs.

On Maintaining Linear Convergence of Distributed Learning and Optimization Under Limited Communication

Abstract: In distributed optimization and machine learning, multiple nodes coordinate to solve large problems. To do this, the nodes need to compress important algorithm information to bits so that it can be communicated over a digital channel. The communication time of these algorithms follows a complex interplay between a) the algorithm's convergence properties, b) the compression scheme, and c) the transmission rate offered by the digital channel. We explore these relationships for a general class of linearly convergent distributed algorithms. In particular, we illustrate how to design quantizers for these algorithms that compress the communicated information to a few bits while still preserving the linear convergence. Moreover, we characterize the communication time of these algorithms as a function of the available transmission rate. We illustrate our results on learning algorithms using different communication structures, such as decentralized algorithms where a single master coordinates information from many workers and fully distributed algorithms where only neighbours in a communication graph can communicate. We conclude that a co-design of machine learning and communication protocols are mandatory to flourish machine learning over networks.

A Novel Artificial Intelligence Based Timing Synchronization Scheme for Smart Grid Applications

Abstract: The smart grid control applications necessitate real-time communication systems with time efficiency for real-time monitoring, measurement, and control. Time-efficient communication systems should have the ability to function in severe propagation conditions in smart grid applications. The data/packet communications need to be maintained by synchronized timing and reliability through equally considering the signal deterioration occurrences, which are propagation delay, phase errors and channel conditions. Phase synchronization plays a vital part in the digital smart grid to get precise and real-time control measurement information. IEEE C37.118 and IEC 61850 had implemented for the synchronization communication to measure as well as control the smart grid applications. Both IEEE C37.118 and IEC 61850 experienced a huge propagation and packet delays due to synchronization precision issues. Because of these delays and errors, measurement and monitoring of the smart grid application in real-time is not accurate. Therefore, it has been investigated that the time synchronization in real-time is a critical challenge in smart grid applications, and for this issue, other errors raised consequently. The existing communication systems are designed with the phasor measurement unit (PMU) along with communication protocol IEEE C37.118 and uses the GPS timestamps as the reference clock stamps. The absence of GPS increases the clock offsets, which surely can hamper the synchronization process and the full control measurement system that can be imprecise. Therefore, to reduce this clock offsets, a new algorithm is needed which may consider any alternative reference timestamps rather than GPS. The revolutionary Artificial Intelligence (AI) enables the industrial revolution to provide a significant performance to engineering solutions. Therefore, this article proposed the AI-based Synchronization scheme to mitigate smart grid timing issues. The backpropagation neural network is applied as the AI method that employs the timing estimations and error corrections for the precise performances. The novel AIFS scheme is considered the radio communication functionalities in order to connect the external timing server. The performance of the proposed AIFS scheme is evaluated using a MATLAB-based simulation approach. Simulation results show that the proposed scheme performs better than the existing system.

Denial of service attack detection through machine learning for the IoT

Abstract: Sustained Internet of Things (IoT) deployment and functioning are heavily reliant on the use of effective data communication protocols. In the IoT landscape, the publish/subscribe-based Message Que...

Neural Network-Based Relay Selection in Two-Way SWIPT-Enabled Cognitive Radio Networks

Abstract: In this paper, we investigate the relay selection problem for two-way simultaneous wireless information and power transfer (SWIPT) enabled cognitive radio networks. The system we consider includes a pair of primary users and multiple secondary user transceivers, where the secondary transmitters are energy-constrained and employ the decode-and-forward scheme to assist the transmission between the primary users. Specifically, in order to improve the spectrum efficiency of the considered system, we design a novel two-way communication protocol for SWIPT-enabled cognitive radio networks. Furthermore, different from the traditional relay selection scheme, under this protocol, we propose two data-driven relay selection methods based on the neural network for the fixed number of relays and the variable number of relays, respectively. The simulation results demonstrate that the proposed methods can achieve better performance than the traditional relay selection as well as the traditional machine learning methods, and approach to the theoretical optimal value in most cases.

Mind the gap- open communication protocols for vehicle grid integration

Abstract: Mass adoption of battery electric vehicles (BEVs) and their associated charging requirements introduce new electricity demand, which needs to be managed to minimise electricity grid upgrades. Management of BEV charging requires coordination and communication between various mobility and energy entities. Communication protocols provide a set of rules and guidelines to facilitate the communication and data exchange between two or more entities to ensure successful charging demand management and electricity grid integration of BEVs. A key challenge is that companies are currently developing and implementing several proprietary protocols to manage BEV charging, which could risk losing or vastly under-utilising BEV charging demand flexibility, and consequently hindering proper grid integration. This work presents the status quo on communication protocols and standards for vehicle grid integration and it is targeted for industries and governments. The objectives of the work are to review current protocols, present some of the advantages of open protocols, identify challenges and additional efforts required to develop, implement, and standardise these protocols to ensure that charging infrastructure for electric vehicles is synergistic with the operation of the electricity system.

Cyberattacks and Countermeasures For In-Vehicle Networks

Abstract: As connectivity between and within vehicles increases, so does concern about safety and security. Various automotive serial protocols are used inside vehicles such as Controller Area Network (CAN), Local Interconnect Network (LIN) and FlexRay. CAN bus is the most used in-vehicle network protocol to support exchange of vehicle parameters between Electronic Control Units (ECUs). This protocol lacks security mechanisms by design and is therefore vulnerable to various attacks. Furthermore, connectivity of vehicles has made the CAN bus not only vulnerable from within the vehicle but also from outside. With the rise of connected cars, more entry points and interfaces have been introduced on board vehicles, thereby also leading to a wider potential attack surface. Existing security mechanisms focus on the use of encryption, authentication and vehicle Intrusion Detection Systems (IDS), which operate under various constrains such as low bandwidth, small frame size (e.g. in the CAN protocol), limited availability of computational resources and real-time sensitivity. We survey In-Vehicle Network (IVN) attacks which have been grouped under: direct interfaces-initiated attacks, telematics and infotainment-initiated attacks, and sensor-initiated attacks. We survey and classify current cryptographic and IDS approaches and compare these approaches based on criteria such as real time constrains, types of hardware used, changes in CAN bus behaviour, types of attack mitigation and software/ hardware used to validate these approaches. We conclude with potential mitigation strategies and research challenges for the future.

Analysis of Network Coverage Optimization Based on Feedback K-Means Clustering and Artificial Fish Swarm Algorithm

Abstract: There is a certain energy loss in the process of wireless sensor network information collection. Moreover, the current network protocols and network coverage methods are not sufficient to effectively reduce system energy consumption. In order to improve the operating efficiency and service life of wireless sensor networks, this study analyzes the classic LEACH protocol, summarizes the advantages and disadvantages, and proposes a targeted clustering method based on the K-means algorithm. At the same time, in order to maximize the network coverage and minimize the energy consumption on the basis of ensuring the quality of service, a wireless sensor network coverage optimization method based on an improved artificial fish swarm algorithm was proposed. In addition, a controlled experiment is designed to analyze the effectiveness and practical effects of the proposed algorithm. The experimental results show that the method proposed in this paper has certain advantages over traditional methods and can provide theoretical references for subsequent related research.

Synchronous Transmissions in Low-Power Wireless: A Survey of Communication Protocols and Network Services

Abstract: Low-power wireless communication is a central building block of Cyber-physical Systems and the Internet of Things. Conventional low-power wireless protocols make avoiding packet collisions a cornerstone design choice. The concept of synchronous transmissions challenges this view. As collisions are not necessarily destructive, under specific circumstances, commodity low-power wireless radios are often able to receive useful information even in the presence of superimposed signals from different transmitters. We survey the growing number of protocols that exploit synchronous transmissions for higher robustness and efficiency as well as unprecedented functionality and versatility compared to conventional designs. The illustration of protocols based on synchronous transmissions is cast in a conceptional framework we establish, with the goal of highlighting differences and similarities among the proposed solutions. We conclude the paper with a discussion on open research questions in this field.

RISA: routing scheme for Internet of Things using shuffled frog leaping optimization algorithm

Abstract: Internet of Things (IoT) has emerged with the recent developments in different technologies such as smart sensors, radio frequency identifier (RFID), wireless networks and communication protocols with various applications. However, gathering large amounts of multimedia data from IoT applications cause traffic congestion. Congestion can affect network quality of service (QoS) parameters such as latency and packet delivery rate (PDR). On the other hand, providing appropriate packet routing scheme in IoT is an important issue. Hence, in this paper, we propose a routing scheme for IoT using shuffled frog leaping algorithm (SFLA). RISA uses SFLA to find a content-based path between the source and destination nodes. RISA can reduce energy consumption and improve the network lifetime using an appropriate data aggregation scheme. The simulation results of the proposed method in Matlab software show that the proposed method is able to optimize the power consumption, network lifetime, throughput, and PDR.

Energy-Efficient Clustering Routing Protocol for Wireless Sensor Networks Based on Yellow Saddle Goatfish Algorithm

Abstract: The usage of wireless sensor devices in many applications, such as in the Internet of Things and monitoring in dangerous geographical spaces, has increased in recent years. However, sensor nodes have limited power, and battery replacement is not viable in most cases. Thus, energy savings in Wireless Sensor Networks (WSNs) is the primary concern in the design of efficient communication protocols. Therefore, a novel energy-efficient clustering routing protocol for WSNs based on Yellow Saddle Goatfish Algorithm (YSGA) is proposed. The protocol is intended to intensify the network lifetime by reducing energy consumption. The network considers a base station and a set of cluster heads in its cluster structure. The number of cluster heads and the selection of optimal cluster heads is determined by the YSGA algorithm, while sensor nodes are assigned to its nearest cluster head. The cluster structure of the network is reconfigured by YSGA to ensure an optimal distribution of cluster heads and reduce the transmission distance. Experiments show competitive results and demonstrate that the proposed routing protocol minimizes the energy consumption, improves the lifetime, and prolongs the stability period of the network in comparison with the stated of the art clustering routing protocols.

Synchronous Transmissions in Low-Power Wireless: A Survey of Communication Protocols and Network Services

Abstract: Low-power wireless communication is a central building block of cyber-physical systems and the Internet of Things. Conventional low-power wireless protocols make avoiding packet collisions a cornerstone design choice. The concept of synchronous transmissions challenges this view. As collisions are not necessarily destructive, under specific circumstances, commodity low-power wireless radios are often able to receive useful information even in the presence of superimposed signals from different transmitters. We survey the growing number of protocols that exploit synchronous transmissions for higher robustness and efficiency as well as unprecedented functionality and versatility compared to conventional designs. The illustration of protocols based on synchronous transmissions is cast in a conceptional framework we establish, with the goal of highlighting differences and similarities among the proposed solutions. We conclude this article with a discussion on open questions and challenges in this research field.

A Lightweight Privacy-Preserving Communication Protocol for Heterogeneous IoT Environment

Abstract: While Internet-of-Things (IoT) significantly facilitates the convenience of people's daily life, the lack of security practice raises the risk of privacy-sensitive user data leakage. Securing data transmission among IoT devices is therefore a critical capability of IoT environments such as Intelligent Connected Vehicles, Smart Home, Intelligent City and so forth. However, cryptographic communication scheme is challenged by the limited resource of low-cost IoT devices, even negligible extra CPU usage of battery-powered sensors would result in dramatical decrease of the battery life. In this paper, to minimize the resource consumption, we propose a communication protocol involving only the symmetric key-based scheme, which provides ultra-lightweight yet effective encryptions to protect the data transmissions. Symmetric keys generated in this protocol are delegated based on a chaotic system, i.e., Logistic Map, to resist against the key reset and device capture attacks. We semantically model such protocol and analyze the security properties. Moreover, the resource consumption is also evaluated to guarantee runtime efficacy.

UAV’s Applications, Architecture, Security Issues and Attack Scenarios: A Survey

Abstract: Unmanned aerial vehicles (UAVs)/drones have become very popular in recent years as they are widely used in several domains. They are widely used in both military and civilian applications such as aerial photography, entertainment, search and rescue missions, reconnaissance, traffic monitoring, and logistics. Typically, UAVs are operated from a controller or a ground control station (GCS) with the help of different communication protocols such as MAVLink, UranusLink, UAVCAN. These communication protocols are used to exchange messages. The messages contain considerable information about the UAV and certain control commands sent from GCS to UAV or UAV to GCS. Though these protocols provide better communication along with secure aspects, however, mostly there is no subtle mechanism for securing these messages and are prone to many security attacks such as man-in-the-middle (MITM) attack, denial-of-services (DoS) attack, packet data injection attack, and eavesdropping. This can result in serious consequences, for instance, crash land of a military or civilian UAV, steal important data of a military operation, false injection of reports in a reconnaissance or search and rescue operation, and many more. So, there is a need for a secure communication protocol which can ensure the required security standard sets for communication of UAVs. This survey presents the applications, general architecture, attacks on UAVs, and an insight into the security issues of UAV’s communication protocols and proposes a new secure communication protocol for the stated issues of UAVs.

Securing smart vehicles from relay attacks using machine learning

Abstract: Due to the rapid developments in intelligent transportation systems, modern vehicles have turned into intelligent transportation means which are able to exchange data through various communication protocols. Today’s vehicles portray best example of a cyber-physical system because of their integration of computational components and physical systems. As the IoT and data remain intrinsically linked together, the evolving nature of the transportation network comes with a risk of virtual vehicle hijacking. In this paper, we propose a combination of machine learning techniques to mitigate the relay attacks on Passive Keyless Entry and Start (PKES) systems. The proposed algorithm uses a set of key fob features that accurately profiles the PKES system and a set of driving features to identify the driver. First relay attack detection is performed, and if a relay attack is not detected, the vehicle is unlocked and algorithm proceeds to gain the driving features and use neural networks to identify whether the current driver is whom he/she claims to be. To assess the machine learning model, we compared the decision tree, SVM, and KNN method using a three-month log of a PKES system. Our test results confirm the effectiveness of the proposed method in recognizing relayed messages. The proposed methods achieve 99.8% accuracy rate. We used a Long Short-Term Memory recurrent neural network for driver identification based on the real-world driving data, which are collected from a driver who drives the vehicles on several routes in real-world traffic conditions.

A Lightweight Authentication Scheme for V2G Communications: A PUF-Based Approach Ensuring Cyber/Physical Security and Identity/Location Privacy

Abstract: Vehicle-to-grid (V2G) technology has become a promising concept for the near future smart grid eco-system. V2G improves smart grid resiliency by enabling two-way communication and electricity flows while reducing the greenhouse gases emission. V2G practicality and stability is strongly based on the exchanged data between electrical vehicles (EVs) and the grid server (GS). However, using communication protocols to exchange vital information leads grid to being vulnerable against various types of attack. To prevent the well-known attacks in V2G network, this paper proposes a privacy-aware authentication scheme that ensures data integrity, confidentiality, users’ identity and location privacy, mutual authentication, and physical security based on physical unclonable function (PUF). Furthermore, the performance analysis shows that the proposed scheme outperforms the state-of-the-art, since EVs only use lightweight cryptographic primitives for every protocol execution.

Architecture for Digital Twin implementation focusing on Industry 4.0

Abstract: Industry 4.0 is a new technological wave that dramatically transformed the industrial environment. It consists in taking to the shop floor solutions and concepts from Internet of Things, such as high connectivity, integration and cooperation between distinct elements. The development of smart devices, the continuous evolution of software tools and the implementation of new communication protocols make it possible to implement sophisticated techniques for control, supervision and optimization of industrial processes. Digital Twins are an approach for integrating physical systems to virtual counterparts that replicate in the virtual space the operation of real instruments and machines. Its main objective is to improve the real system performance by using information generated by the virtual counterpart, for example, by executing performance analysis, bottleneck identification, failure prediction, detection of deviations and others. Some of the biggest challenges on this context are creating trustworthy models with acceptable computational costs, assuring real-time communication and developing deep analysis methods. This paper presents the development of a modular architecture for implementing Digital Twins. The architecture is based on an open-source tool for process control, lightweight protocols and flexible tools for modeling and 3D visualization. Tools were chosen in order to allow diverse machines and productive systems to be modeled and represented on the Digital Twin architecture.

SeQUeNCe: A Customizable Discrete-Event Simulator of Quantum Networks

Abstract: Recent advances in quantum information science enabled the development of quantum communication network prototypes and created an opportunity to study full-stack quantum network architectures. This work develops SeQUeNCe, a comprehensive, customizable quantum network simulator. Our simulator consists of five modules: Hardware models, Entanglement Management protocols, Resource Management, Network Management, and Application. This framework is suitable for simulation of quantum network prototypes that capture the breadth of current and future hardware technologies and protocols. We implement a comprehensive suite of network protocols and demonstrate the use of SeQUeNCe by simulating a photonic quantum network with nine routers equipped with quantum memories. The simulation capabilities are illustrated in three use cases. We show the dependence of quantum network throughput on several key hardware parameters and study the impact of classical control message latency. We also investigate quantum memory usage efficiency in routers and demonstrate that redistributing memory according to anticipated load increases network capacity by 69.1% and throughput by 6.8%. We design SeQUeNCe to enable comparisons of alternative quantum network technologies, experiment planning, and validation and to aid with new protocol design. We are releasing SeQUeNCe as an open source tool and aim to generate community interest in extending it.