Unreliable Environment Research Articles

Proactively Verifying Quantitative Network Policy Across Unsafe and Unreliable Environments

Proactively Verifying Quantitative Network Policy Across Unsafe and Unreliable Environments

Dynamic redeployment of UAV base stations in large-scale and unreliable environments

The deployment of Unmanned Aerial Vehicles (UAVs) as aerial base stations (UAV-BSs) has emerged as a promising solution to enhance communication services provided to ground users. However, deploying UAV-BSs faces challenges including the cooperation of multiple UAVs, dynamic user distribution, low-reliability issues of UAVs, and efficient redeployment in large environments. Existing literature addresses some of these challenges but lacks a comprehensive approach. In this paper, we investigate all these challenges and propose a novel deployment framework with the objective of maximizing the quality of communication service by dynamically deploying UAV-BSs. The proposed framework employs a decentralized approach, allowing UAV-BSs to locally adjust their locations and rapidly respond to changes, thus ensuring stable and efficient service supply to ground users. In addition, we implement multiple simulation experiments to evaluate the performance of the proposed framework in solving the UAV-BSs redeployment problem in large and dynamic environments. The results demonstrate its ability to effectively improve the quality of communication services.

Output Reachable Set Synthesis of Event-Triggered Control for Singular Markov Jump Systems Under Multiple Cyber-Attacks

This paper investigates the asynchronous event-triggered state-feedback control for discrete-time nonlinear singular Markov jump systems subject to reachable set bounding and stochastic cyber-attacks. An event-triggered mechanism is introduced to regulate data transmission and save network resources. While this mechanism brings advantages, it also causes that the mode information of the system and the controller are not synchronized. On the other hand, network communication has brought convenience to signal transmission, and it has also resulted in the network channel being in an open and unreliable environment, which is vulnerable to cyber-attacks. In order to solve these problems, the secure asynchronous controller is designed to effectively resist the influence of attacks. In addition, by using the reachable set analysis approach, the constructed controller ensures that the estimation error is within the boundary of the ellipsoid, and the existence conditions of the required controller are given by solving the linear matrix inequalities. Finally, a simulation example is given to illustrate the effectiveness of the theoretical results.

Resilient Consensus for Multi-Agent Systems Under Adversarial Spreading Processes

This paper addresses novel consensus problems for multi-agent systems operating in an unreliable environment where adversaries are spreading. The dynamics of the adversarial spreading processes follows the susceptible-infected-recovered (SIR) model, where the infection induces faulty behaviors in the agents and affects their state values. Such a problem setting serves as a model of opinion dynamics in social networks where consensus is to be formed at the time of pandemic and infected individuals may deviate from their true opinions. To ensure resilient consensus among the noninfectious agents, the difficulty is that the number of infectious agents changes over time. We assume that a local policy maker announces the local level of infection in real-time, which can be adopted by the agent for its preventative measures. It is demonstrated that this problem can be formulated as resilient consensus in the presence of the socalled mobile malicious models, where the mean subsequence reduced (MSR) algorithms are known to be effective. We characterize sufficient conditions on the network structures for different policies regarding the announced infection levels and the strength of the epidemic. Numerical simulations are carried out for random graphs to verify the effectiveness of our approach.

Time-Division ISAC Enabled Connected Automated Vehicles Cooperation Algorithm Design and Performance Evaluation

To overcome the bottleneck of unreliable environment sensing caused by sensor failure and obstacle blockage, the cooperation among connected automated vehicles (CAVs) is crucial for the reliable and efficient raw sensing data sharing in order to guarantee the driving safety. Empowered by the narrow beamwidth and high data rate abilities, the millimeter wave (mmWave) communication technology can substantially improve the environment sensing ability among multiple CAVs. In this paper, a mmWave enabled CAVs cooperation algorithm is designed based on the proposed time-division integrated sensing and communication (TD-ISAC) system for raw sensing data sharing among CAVs. Considering various computing abilities at vehicle and infrastructure, a closed-form solution to the V2V or V2V/V2I cooperative communication mode selection is theoretically achieved based on response delay analysis to guarantee the timeliness of raw sensing data sharing. And the age of information based system status update algorithm is proposed for the V2V/V2I collaborative communication mode. The feasibility of the proposed TD-ISAC system is verified by simulation and hardware testbed results. Based on simulation results, the proposed communication mode selection algorithm can effectively minimize the response time delay in different conditions. The mmWave enabled TD-ISAC hardware testbed is developed and the position error of target detection can be reduced by 18.5 % using the sensing data fusion from two vehicles, while the communication throughput remains over 2.2 Gbps.

A Distributed Real-time Scheduling System for Industrial Wireless Networks

The concept of Industry 4.0 introduces the unification of industrial Internet-of-Things (IoT), cyber physical systems, and data-driven business modeling to improve production efficiency of the factories. To ensure high production efficiency, Industry 4.0 requires industrial IoT to be adaptable, scalable, real-time, and reliable. Recent successful industrial wireless standards such as WirelessHART appeared as a feasible approach for such industrial IoT. For reliable and real-time communication in highly unreliable environments, they adopt a high degree of redundancy. While a high degree of redundancy is crucial to real-time control, it causes a huge waste of energy, bandwidth, and time under a centralized approach and are therefore less suitable for scalability and handling network dynamics. To address these challenges, we propose DistributedHART—a distributed real-time scheduling system for WirelessHART networks. The essence of our approach is to adopt local (node-level) scheduling through a time window allocation among the nodes that allows each node to schedule its transmissions using a real-time scheduling policy locally and online. DistributedHART obviates the need of creating and disseminating a central global schedule in our approach, thereby significantly reducing resource usage and enhancing the scalability. To our knowledge, it is the first distributed real-time multi-channel scheduler for WirelessHART. We have implemented DistributedHART and experimented on a 130-node testbed. Our testbed experiments as well as simulations show at least 85% less energy consumption in DistributedHART compared to existing centralized approach while ensuring similar schedulability.

TZMon: Improving mobile game security with ARM trustzone

As the game industry is moving from PC to smartphone platforms, security problems related to mobile games are becoming critical. Considering the characteristics of mobile games such as having short life-cycles and high communication costs, the server/network-side security technologies designed for PC games are not appropriate for mobile games. In this study, we propose TZMon, a client-side game protection mechanism based on the ARM TrustZone, which protects the confidentiality and integrity of mobile games. TZMon is composed of application integrity protocol, secure update protocol, data hiding protocol, and timer synchronization protocol. To adequately safeguard game codes and data, TZMon is designed considering an environment of frequent communications with the game server, a stand-alone operation environment, and an unreliable environment using a rooted OS. Furthermore, flexibility is provided to game application developers who apply security policies by using the Java Native Interface (JNI). In this study, we use Android and the Open Portable Trusted Execution Environment (OPTEE) as the OS platforms for Normal World and Secure World, respectively. After implementing a full-featured prototype of TZMon, we apply it to several open-source mobile games. We prove through the experiments that the application of the proposed TZMon does not cause any noticeable performance degradation and can detect major cheating techniques of mobile games.

A novel blockchain protocol for selecting microservices providers and auditing contracts

Software architectures based on containers and microservices are often used to develop and manage large-scale distributed applications. Still, large vertical deployments spanning over multiple cloud and edge infrastructures are cumbersome to negotiate for, as each infrastructure provider is usually unique concerning prices, management strategies and Quality-of-Service (QoS) levels. In this scenario, Service Level Agreement (SLA) contracts are primarily crafted through pre-established templates and clients must trust providers to manage provisioned resources. The present paper proposes Dawn, a novel blockchain protocol for selecting microservice providers and auditing contracts. The protocol exploits the distributed and verifiable storage of a blockchain, as well as its decentralized consensus to enable contracts establishments in unreliable environments. Besides providing a formal definition of the protocol, this work discusses the possible threats to the correct operation of the network, originated by tenants and providers. We show that Dawn is secure under the evaluated terms, that it can efficiently help the contract establishment process as well as it guarantees a functional systematic way of auditing through monitoring. Finally, we studied both best and worst case scenarios regarding the number of issued messages, stored data volume and network traffic to execute Dawn with different numbers of clients and providers.

Fuzzy-based reliable and secure cooperative spectrum sensing for the smart grid

Cognitive radio is a promising technology to solve the spectrum scarcity problem caused by inefficient utilization of radio spectrum bands. It allows secondary users to opportunistically access the underutilized spectrum bands assigned to licensed primary users. The local individual spectrum detection is inefficient, and cooperative spectrum sensing is employed to enhance spectrum detection accuracy. However, cooperative spectrum sensing opens up opportunities for new types of security attacks related to the cognitive cycle. One of these attacks is the spectrum sensing data falsification attack, where malicious secondary users send falsified sensing reports about spectrum availability to mislead the fusion center. This internal attack cannot be prevented using traditional cryptography mechanisms. To the best of our knowledge, none of the previous work has considered both unreliable communication environments and the spectrum sensing data falsification attack for cognitive radio based smart grid applications. This paper proposes a fuzzy inference system based on four conflicting descriptors. An attack model is formulated to determine the probability of detection for both honest and malicious secondary users. It considers four independent malicious secondary users’ attacking strategies of always yes, always no, random, and opposite attacks. The performance of the proposed fuzzy fusion system is simulated and compared with the conventional fusion rules of AND, OR, Majority, and the reliable fuzzy fusion that does not consider the secondary user’s sensing reputation. The results indicate that incorporating sensing reputation in the fusion center has enhanced the accuracy of spectrum detection and have prevented malicious secondary users from participating in the spectrum detection fusion

An efficient and optimised approach for secured file sharing in cloud computing

Cloud computing has brought a new revolution to IT industry. In this era, information sharing is more convenient and fast, but applying security mechanism on information while outsourcing it on cloud is challenging. In this paper, we proposed hybrid approach comprising of symmetric and asymmetric algorithm. For encrypting file, we generated optimal and efficient symmetric key using genetic algorithm (GA), further an efficient and secure re-encryption concept has been proposed for ensuring the security of data in unreliable cloud environment. Our results have proved that our proposed approach is more efficient and secured while sharing file with authorised users using cloud in comparison to existing approaches.

Survey of Mission Planning and Management Architectures for Underwater Cooperative Robotics Operations

Almost every research project that focuses on the cooperation of autonomous robots for underwater operations designs their own architectures. As a result, most of these architectures are tightly coupled with the available robots/vehicles for their respective developments, and therefore the mission plan and management is done using an ad-hoc solution. Typically, this solution is tightly coupled to just one underwater autonomous vehicle (AUV), or a restricted set of them selected for the specific project. However, as the use of AUVs for underwater operations increases, there is the need to identify some commonalities and weaknesses of these architectures, specifically in relation to mission planning and management. In this paper, we review a selected number of architectures and frameworks that in one way or another make use of different approaches to mission planning and management. Most of the selected works were developed for underwater operations. Still, we have included some other architectures and frameworks from other domains that can be of interest for the survey. The explored works have been assessed using selected features related to mission planning and management, considering that underwater operations are performed in an uncertain and unreliable environment, and where unexpected events are not strange. Furthermore, we have identified and highlighted some potential challenges for the design and implementation of mission managers. This provides a reference point for the development of a mission manager component to be integrated in architectures for cooperative robotics in underwater operations, and it can serve for the same purposes in other domains of application.

The impact factors on the competence of big data processing

A major challenge of using volunteer computing (VC) for big data problems is the opportunistic environment. In such a dynamic, unreliable, and heterogeneous environment, there exist many uncertain factors that may impair the competence of big data processing. This paper explores these factors and their impact, aiming at exposing the original impaired performance that the undedicated environment of VC can achieve under the impact. Our investigation on this issue is four-fold. First, we define a number of impact factors to represent the opportunistic features of VC environment. Second, we model a distributed hash table-based MapReduce approach to process big data. Third, we proposes an ideal computing environment and then inject impact factors into the running MapReduce to quantitatively evaluate how the performance is impaired. Finally, we analyze the evaluation results to figure out the cause of impact and predict optimization potentials. The developers, who plan to construct MapReduce frameworks by using commodity computers or voluntary cycles on the public internet, will benefit from the evaluation results when considering performance requirements.

The good, the bad and the ugly: social media prospects and perils for records management

Records and information professionals have in recent years, seen themselves grappling with new technologies in order to ensure that records generated in the process are captured and preserved for business requirements. It has been evident that the availability of information and communication technologies (ICTs) and their associated benefits have resulted in an increased number of organisations adopting and using social media to reach out to customers and clients. With social media issues like security, privacy, service agreements and standards are continually added and can change instantly. These frequent changes and unreliable environments call for organisations adopting social media initiatives to be aware of the risks and opportunities involved, thereby ensuring that resultant records are controlled, monitored and preserved accordingly or stand the risk of losing their digital information. This conceptual study used documentary reviews to collect data in the analysis of opportunities and risks brought by social media in the records management field and explore alternatives for records management. This study found that social media presents a volatile environment with both the good and the bad. Therefore, this study recommends that organisations that adopt and use social media platforms should put measures in place for the management of social media records to meet legal and business requirements.

Skycore

Deploying LTE networks on modern UAVs requires a redesign of the key components of the LTE architecture. In this article, we propose a radical, edge-EPC design, called SkyCore, that pushes one of its central functionalities, namely its evolved packet core (EPC) to the extreme edge of the LTE network - collapses the EPC into a single, lightweight, selfcontained entity that is co-located with each of the UAV base-stations. SkyCore incorporates elements that are designed to address the unique challenges facing such a distributed design in the UAV environment, namely the resource-constrained nature of UAV platforms, and the distributed management of UAV and user mobility. We build and deploy a fully functional SkyCore system on a multi-UAV LTE network and showcase its (i) ability to interoperate with commercial LTE basestations as well as smartphones, (ii) support for both hotspot and standalone multi-UAV deployments, and (iii) robust control and data plane performance compared to other EPC variants in this inherently dynamic, unreliable environment.

A Secure Encryption Scheme for Data Sharing in Unreliable Cloud Environment

A Secure Encryption Scheme for Data Sharing in Unreliable Cloud Environment

Hybrid heterogeneous routing scheme for improved network performance in WSNs for animal tracking

Wireless Sensor Networks (WSNs) experiences several technical challenges such as limited energy, short transmission range, limited storage capacities, and limited computational capabilities. Moreover, the sensor nodes are deployed randomly and massively over an inaccessible or hostile region. Hence, WSNs are vulnerable to adversaries and are usually operated in a dynamic and unreliable environment. Animal tracking using wireless sensors is one such application of WSN where power management plays a vital role. In this paper, an energy-efficient hybrid routing method is proposed that divides the whole network into smaller regions based on sensor location and chooses the routing scheme accordingly. The sensor network consists of a base station (BS) located at a distant place outside the network, and a relay node is placed inside the network for direct communications from nodes nearer to it. The nodes are further divided into two categories based on the supplied energy; such that the ones located far away from BS and relay have higher energy than the nodes nearer to them. The network performance of the proposed method is compared with protocols like LEACH, SEP, and SNRP, considering parameters like stability period, throughput and energy consumption. Simulation result shows that the proposed method outperforms other methods with better network performance.

Reinforcement learning-based real time search algorithm for routing optimisation in wireless sensor networks using fuzzy link cost estimation

Internet of things is a technological advancement of wireless sensor networks (WSNs) which are characterised by highly complex, large scale, heterogeneous, dynamically changing and asymmetric networks. Such constraints make routing in WSNs a difficult task. This paper introduces fuzzy link cost estimation-based real time search routing algorithm (fuzzy RTS) in which link cost estimation is obtained from physical and MAC layer parameters like residual energy, packet drop rate and RSSI. Its performance has been evaluated with traditional reinforcement learning-based algorithms like real time search, adaptive tree, ant routing and constrained flooding algorithms on the basis of metrics like throughput, loss rate, success rate, energy consumption, energy efficiency and node battery life. The simulation results reveal that fuzzy RTS algorithm is most appropriate reinforcement learning-based routing algorithm among given algorithms for ensuring energy efficient and QoS aware routing in dynamically changing, asymmetric and unreliable environment of WSNs.

Reinforcement learning-based real time search algorithm for routing optimisation in wireless sensor networks using fuzzy link cost estimation

Internet of things is a technological advancement of wireless sensor networks (WSNs) which are characterised by highly complex, large scale, heterogeneous, dynamically changing and asymmetric networks. Such constraints make routing in WSNs a difficult task. This paper introduces fuzzy link cost estimation-based real time search routing algorithm (fuzzy RTS) in which link cost estimation is obtained from physical and MAC layer parameters like residual energy, packet drop rate and RSSI. Its performance has been evaluated with traditional reinforcement learning-based algorithms like real time search, adaptive tree, ant routing and constrained flooding algorithms on the basis of metrics like throughput, loss rate, success rate, energy consumption, energy efficiency and node battery life. The simulation results reveal that fuzzy RTS algorithm is most appropriate reinforcement learning-based routing algorithm among given algorithms for ensuring energy efficient and QoS aware routing in dynamically changing, asymmetric and unreliable environment of WSNs.

Quantitative and qualitative safety analysis of a hemodialysis machine with S#

AbstractThis paper reports on our experiences of applying S# (“safety sharp”) to model and analyze the case study “hemodialysis machine.” The S# safety analysis approach focuses on the question, what happens if we place a controller with correct software into an unreliable environment. To answer that question, the S# toolchain natively supports the Deductive Cause Consequence Analysis, a fully automatic model checking‐based safety analysis technique that determines all sets of component faults with the potential of causing a system hazard. Furthermore, S# can give an approximate estimate of the hazard's probability. To demonstrate our approach, we created a model with a simplified controller of the hemodialysis machine and relevant parts of its environment and performed a safety analysis using Deductive Cause Consequence Analysis.

Comparison of Encryption Algorithms in Wireless Sensor Networks

In general, Wireless Sensor Networks occur when sensor nodes are randomly left in an unreliable environment. Sensor node has limited processor, limited memory, limited radio capacity and low cost. In sensor network applications, security mechanisms must be used, because of unsafe environments, excessive number of sensor nodes, and wireless communication environments. Ensuring confidentiality, the primary goal of security, is one of the most important problems to be solved in order to realize time and vital objectives. While ensuring security, it is also necessary to consider other important criteria such as memory usage, energy and latency of Sensor Networks. In this study, encryption is described in Wireless Sensor Networks and Skipjack, XXTEA and AES encryption algorithms are compared using TOSSIM simulation program in TinyOS operating system considering memory usage, energy and delay criteria. The study is considered to be useful academicians who study security in Wireless Sensor Networks.