2021 IEEE International Systems Conference (SysCon)最新文献

{"title":"Combating DDoS Attacks with Fair Rate Throttling","authors":"A. Nur","doi":"10.1109/SysCon48628.2021.9447054","DOIUrl":"https://doi.org/10.1109/SysCon48628.2021.9447054","url":null,"abstract":"Distributed Denial of Service (DDoS) attacks are among the most harmful cyberattack types in the Internet. The main goal of a DDoS defense mechanism is to reduce the attack’s effect as close as possible to their sources to prevent malicious traffic in the Internet. In this work, we examine the DDoS attacks as a rate management and congestion control problem and propose a collaborative fair rate throttling mechanism to combat DDoS attacks. Additionally, we propose anomaly detection mechanisms to detect attacks at the victim site, early attack detection mechanisms by intermediate Autonomous Systems (ASes), and feedback mechanisms between ASes to achieve distributed defense against DDoS attacks. To reduce additional vulnerabilities for the feedback mechanism, we use a secure, private, and authenticated communication channel between AS monitors to control the process. Our mathematical model presents proactive resource management, where the victim site sends rate adjustment requests to upstream routers. We conducted several experiments using a real-world dataset to demonstrate the efficiency of our approach under DDoS attacks. Our results show that the proposed method can significantly reduce the impact of DDoS attacks with minimal overhead to routers. Moreover, the proposed anomaly detection techniques can help ASes to detect possible attacks and early attack detection by intermediate ASes.","PeriodicalId":384949,"journal":{"name":"2021 IEEE International Systems Conference (SysCon)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125408925","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The roles of modeling and simulation in assessing spacecraft Integration Readiness Levels","authors":"Gabriel T. Jesus, M. F. C. Júnior","doi":"10.1109/SysCon48628.2021.9447057","DOIUrl":"https://doi.org/10.1109/SysCon48628.2021.9447057","url":null,"abstract":"Introducing new technologies in Complex Products and Systems (CoPS) requires in-depth knowledge of technology and the system integration process. Technology Readiness Assessment (TRA) is a systematic evidence-based process that assesses technology maturity based on Technology Readiness Levels (TRL). System Readiness Assessment (SRA) is the process of conducting integrated assessments of a developing system to assess technology maturation and provide a systemic understanding of the development life-cycle. The Integration Readiness Levels (IRL) scale complements TRL in representing integration between technological elements in a system, and both scales are used in SRA to calculate system readiness metrics. SRA is expected to be an emerging systems engineering best practice and has evolved over the last decade. However, SRA does not explicitly guide whether simulation could comply with IRL dedicated to interface verification and validation. Modeling and simulation (M&S) play many roles in systems engineering. Digital and M&S technologies advancement, as Model-Based System Engineering (MBSE) and digital twins, may contribute to reducing space missions´ costs and schedule, along with trends in systems and technology reuse. This research identified the possible roles of modeling and simulation in assessing spacecraft Integration Readiness Levels. Results showed M&S possible roles for each IRL and whether the roles were essential or support to achieve IRL. Also, a link between system life cycle processes and these results contributes to the SRA research stream. A case study with the China-Brazil Earth Resources Satellite (CBERS) program was used to validate part of the proposed theory, in line with other cases extracted from the literature. This paper contributes to the SRA research stream with these theoretical and practical results, by suggesting future studies that could improve SRA practice and consequently support the decision-making on technology introduction in CoPS.","PeriodicalId":384949,"journal":{"name":"2021 IEEE International Systems Conference (SysCon)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126420378","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multi-Agent Based Distributed Dynamic State Estimation Algorithm for Smart Grid Integrating Intermittent Electric Vehicles","authors":"M. Rana, A. Abdelhadi, M. Ali, Amer Daowud","doi":"10.1109/SysCon48628.2021.9478342","DOIUrl":"https://doi.org/10.1109/SysCon48628.2021.9478342","url":null,"abstract":"Large number of physical systems such as electric vehicles and energy storage elements are connected to the main grid. Monitoring and regulating of this interconnected cyberphysical power system state within a short period of time is a challenging task, and it can perform by the process of grid state estimation. This paper proposes a multi-agent based optimal distributed dynamic state estimation algorithm for smart grid incorporating intermittent electric vehicles and turbines. After mathematically representation of large-scale grid systems into a compact state-space framework, the smart sensors are installed to get real-time measurements which are manipulated by environmental noise. A distributed smart grid state estimation process is developed and verified. Each agent learns and runs an innovation and consensus type distributed scheme based on local measurements, previous and neighbouring estimated grid states. In this way, each local agent estimated grid state converges to the global consensus estimation over time. The proposed algorithm can effectively reconstruct the original grid states.","PeriodicalId":384949,"journal":{"name":"2021 IEEE International Systems Conference (SysCon)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122611218","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Towards Context-Awareness in Model-Based Requirements Engineering","authors":"Yaniv Mordecai, E. Crawley","doi":"10.1109/SysCon48628.2021.9763443","DOIUrl":"https://doi.org/10.1109/SysCon48628.2021.9763443","url":null,"abstract":"Evolutionary system development and capability deployment are becoming common even in aerospace and defense. As systems evolve, the need to reach significant understanding of the existing architecture is critical for good requirements specification, due to the growing dependency of the requirements on assets in the current architecture. At present, requirement specifications typically do not clearly separate the baseline, or context, from the necessary delta, or prospect. The context informs the prospect and grounds it in the given architecture. The prospect specifies what the requirement owner needs, requires, or expects the system to be or do that is not already in the baseline. We propose a Context-Aware Model-Based Requirements Engineering (CAMBRE) method in which the context of a requirement is modularly composed with its prospect, such that the requirement text is specified in a context-aware manner. We distill those parts of a requirement that are designated for development from those that constitute the background. This approach is acute for complex, evolving, interdependent, or adaptive systems, in which system properties mostly extend or enhance the existing architecture. We implement CAMBRE with Object-Process Methodology (OPM), and demonstrate our approach on the evolutionary extension of a missile defense system with drone interception capabilities to support border protection efforts.","PeriodicalId":384949,"journal":{"name":"2021 IEEE International Systems Conference (SysCon)","volume":"217 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122185602","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Model Based Systems Engineering Approach for Behavioral Responses to Advanced Quantitative Precipitation Information","authors":"W. Brooks, V. Chandrasekar, G. Pratt, R. Cifelli","doi":"10.1109/SysCon48628.2021.9447116","DOIUrl":"https://doi.org/10.1109/SysCon48628.2021.9447116","url":null,"abstract":"Atmospheric rivers (AR) contribute a significant portion of the precipitation for the United States’ west coast. Flooding events caused by ARs can create millions of dollars in damages. Identifying probable ARs and early warning of potential flooding events can provide state and local agencies the time to prepare for such events. The Bay Area Advanced Quantitative Precipitation Information (AQPI) system links users with varied meteorological data ranging from weather radar observations, short term forecasts (Nowcast), 12-hour forecasts, and coastal inundation modeling data. The range of data types presents an opportunity for proactive responses by the users; however, it also presents the challenge of ensuring the correct data is available to the appropriate user. Through Model Based Systems Engineering (MBSE) Behavioral Analysis, the AQPI team analyzes the appropriate requirements for each of the different types of AQPI users. MBSE behavioral analysis leads to the development of a system that services the broad user community’s needs while giving each user group a specific interface tailored for them. This engineering approach also allows for the separation of the processing and weather model execution from the user interface. This separation allows for development and advancements in processing without being tied to the user interfaces.","PeriodicalId":384949,"journal":{"name":"2021 IEEE International Systems Conference (SysCon)","volume":"203 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123308328","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Energy Consumption Evaluation of LPWAN: A Stochastic Modeling Approach for IoT Systems","authors":"Diogo Lages, Eric Borba, J. Araujo, E. Tavares, E. Sousa","doi":"10.1109/SysCon48628.2021.9447103","DOIUrl":"https://doi.org/10.1109/SysCon48628.2021.9447103","url":null,"abstract":"Energy consumption has been a well-known concern on computing systems, and due to the emergence of IoT applications, particular attention has been devoted to network technologies. The energy for a communication transceiver component to send one single bit can be 1500 to 2000 times higher than the energy required to execute a single instruction, and many IoT applications adopt energy-constrained networks, such as low-power wide-area networks (LPWANs). Thus, mechanisms for assessing energy consumption of the network physical layer for IoT applications are prominent for system design. Despite the importance of assessing the communication transceiver’s energy consumption, to the best of our knowledge, just a few works propose models for evaluating LPWAN and WSN transceivers independently of technology with probabilistic packet loss behavior. This paper presents a modeling approach based on Stochastic Petri nets (SPN) formalism family capable to evaluate the energy consumption for LPWAN and WSN networks, focusing on the communication transceivers and channel with packet loss probabilistic behavior. The proposed models have been validated using Lora physical layer chip with an error of 1.6% to transmit data and 1.3% to receive data. The experimental results show the feasibility of the proposed models to estimate a node and network energy consumption.","PeriodicalId":384949,"journal":{"name":"2021 IEEE International Systems Conference (SysCon)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130363064","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enabling the Digital Transformation of the Workforce: A Digital Engineering Competency Framework","authors":"A. Baker, Kara Pepe, Nicole Hutchison, H. Y. Tao, R. Peak, M. Blackburn, Rabia Khan, C. Whitcomb","doi":"10.1109/SysCon48628.2021.9447063","DOIUrl":"https://doi.org/10.1109/SysCon48628.2021.9447063","url":null,"abstract":"This paper describes the goals, approaches, initial results, and preliminary implementation of WRT-1006, a multiphase research task within the Systems Engineering Research Center (SERC). Evidence across the Services and industry has affirmed digital engineering is a critical practice necessary to support acquisition in an environment of increasing global challenges, dynamic threats, rapidly evolving technologies, and increasing life expectancy of our systems currently in operation. Digital engineering updates the systems engineering practices to take full advantage of computational technology, modeling, data analytics, and data sciences. The Department of Defense's vision for digital engineering is to modernize how the Department designs, develops, delivers, operates, and sustains systems, while continuing to practice systems engineering efficiently and effectively. Digital transformation is fundamentally changing the way acquisition and engineering are performed across a wide range of government agencies, industries, and academia. As the Department of Defense (DoD) transitions to digital engineering, there is a need to develop and maintain an acquisition workforce and culture that is literate in model-based engineering, competent in digital engineering models, methods, processes, tools, and understands digital artifacts across the acquisition lifecycle. One of the critical steps that was identified to enable this digital transformation is the development of a competency model that can be used to modernize the workforce. This paper outlines the results after completion of Phase 1 of WRT-1006, which concluded in the initial release of the Digital Engineering Competency Framework (DECF) by SERC, and the initial Phase 2 efforts of implementing the framework as a benchmark for the content of a digital engineering training curriculum. The purpose of the DECF is to provide clear guidance for the DoD acquisition workforce, in particular the engineering acquisition workforce, through clearly defined competencies that illuminate the knowledge, skills, abilities, and behaviors required for digital engineering professionals. The approach taken to develop the DECF drew from existing competency models in fields neighboring digital engineering and from the feedback of experienced practicing digital engineering community. The initial version of the DECF v.1.0 was released as a key WRT1006 Phase 1 result with confidence in the maturity of the structure and general content. The overarching structure of the DECF v.1.0 consists of competency areas, proficiency levels within the competency, and constituting knowledge, skills, abilities, and behaviors (KSABs). Now that this benchmark is established, the second phase of our project involves the comparison of the DECF to the existing Defense Acquisition University (DAU) curriculum to determine what elements of such existing curriculum already support the competencies in the model. This is a bidirectional analysis that ","PeriodicalId":384949,"journal":{"name":"2021 IEEE International Systems Conference (SysCon)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116611585","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"System Level Knowledge Representation for Complexity","authors":"Paola Di Maio","doi":"10.1109/SysCon48628.2021.9447091","DOIUrl":"https://doi.org/10.1109/SysCon48628.2021.9447091","url":null,"abstract":"To develop systems capable of high level cognitive functions such as intelligence, it is necessary to formally capture different types of knowledge, so that they can be used to support complex processes, such as inference and reasoning. The design and engineering of Intelligent Systems to support large distributed socio technical processes increasingly leverages converging techniques from Artificial Intelligence, Knowledge Representation (KR) and Cognitive Architectures. This is resulting in multi layered architectures and AI technologies which one the one hand offer unprecedented capabilities, on the other hand present innumerable, often inconceivable risks. Sophisticated conceptual structures are necessary not only to support the modeling, validation and explanation of complex engineered systems, but primarily to support cognition and conceptualization of the complexities involved, for designers, developers, end users and any stakeholder. Depending on the cognitive makeup of observers, and on the knowledge available, complexity can be conceptualized and traversed following a diversity of methods and patterns. Sometimes complexity can be broken down into cognitively accessible chunks, in other cases however, it cannot be broken down without losing essential information about the system as a whole. Addressing the need to develop cognitive artifacts, methods and techniques that can capture and represent complexity, this paper proposes the outline of conceptual structure that bridges existing approaches which tend to distinguish between cognitive engineering and Knowledge Representation, with the aim to integrate technical and socio technical systems dimensions. The paper presents considerations about cognitive aspects of complex systems theory and practice. It anticipates a convergence between cognitive architectures and KR, introduces the notion of System Level Knowledge Representation and applies it to navigate socio technical complexity in systems engineering. A summary of related work where the System Level Knowledge Representation is being developed and evaluated is also provided.","PeriodicalId":384949,"journal":{"name":"2021 IEEE International Systems Conference (SysCon)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129904631","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"System execution path profiling using hardware performance counters","authors":"Francis Giraldeau, Naser Ezzati-Jivan, M. Dagenais","doi":"10.1109/SysCon48628.2021.9447121","DOIUrl":"https://doi.org/10.1109/SysCon48628.2021.9447121","url":null,"abstract":"The task critical execution path, obtained from a kernel trace, reports the time spent waiting for each task involved in a heterogeneous and distributed application. However, additional profiling is needed to understand and identify the problematic code associated with long-lasting path edges. Hardware counter sampling provides insight on software performance at the microarchitecture level, for instance extracting the call stack every 100K execution cycles to understand where the execution time is spent. Similarly, extracting the call stack at the end of a long waiting system call is often useful. This technique is readily available for either statically or JIT compiled code. However, interpreted code is indirectly executed on the processor and the link between the statements and the executed assembly is missing. We propose an architecture to efficiently record call stacks along the execution path, including interpreted programs, in a low intrusive way that maintains the abstraction boundary between the kernel, the interpreter, and the user code. The method consists in sending a signal from within the performance counter interrupt handler. The user-space code receiving the signal can inspect and record the state of the program. We implemented a profiler for the CPython interpreter using this technique. We studied the benefit, the accuracy, and the cost of the proposed technique compared to an all-kernel monitoring solution.","PeriodicalId":384949,"journal":{"name":"2021 IEEE International Systems Conference (SysCon)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134382897","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Equivalent Circuit Modeling of All-Solid-State Battery by using DC-IR Data","authors":"Burak Celen, A. C. Aras, Markus Dohr, Thyagesh Sivaraman","doi":"10.1109/SysCon48628.2021.9447086","DOIUrl":"https://doi.org/10.1109/SysCon48628.2021.9447086","url":null,"abstract":"In modern Battery Management Systems (BMSs), it is significant to obtain an accurate battery model to estimate the states of the battery such as State of Charge (SoC), State of Health (SoH), State of Power (SoP), State of Safety (SoS) etc. Traditional lithium-ion batteries (LIBs) have some drawbacks in terms of safety and energy density. To overcome these drawbacks, all-solid-state batteries (ASSBs) are being developed as an alternative solution for conventional lithium-ion batteries. The focus of this study is on all-solid-state batteries and their modeling based on the equivalent circuit model. On the other hand, the modeling of a cell needs an immense amount of data and long test duration time. Instead of cell characterization test data, the all-solid-state cell is modeled by using DC internal resistance (DC-IR) information. During this study, two different equivalent circuit models containing series-connected RC pairs with and without ohmic resistance are investigated. In addition, the equivalent circuit model parameters are derived via Genetic Algorithm. Moreover, measured and simulated resistance values are compared with Mean Absolute Error (MAE) criteria for two different equivalent circuit models. Finally, the plausibility of the obtained models are analyzed and compared with experimental Hybrid Pulse Power Characterization (HPPC) test results.","PeriodicalId":384949,"journal":{"name":"2021 IEEE International Systems Conference (SysCon)","volume":"158 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114926400","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}