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Home > Books > Systems-of-Systems Perspectives and Applications - Design, Modeling, Simulation and Analysis (MS&A), Gaming and Decision Support

Introductory Chapter: Recent Trends in Systems-of-Systems Design, Modeling, Simulation and Analysis for Complex Systems, Gaming and Decision Support Final

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DOI: 10.5772/intechopen.97754

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Systems-of-Systems Perspectives and Applications - Design, Modeling, Simulation and Analysis (MS&A), Gaming and Decision Support

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Tien m. nguyen *.

• Center for Computational and Applied Mathematics (CCAM), California State University, Fullerton (CSUF), USA
• The Aerospace Corporation, USA

Tung X. Bui

• Shidler College of Business, USA
• Information Technology Management, University of Hawaii at Manoa, USA
• Haas School of Business, University of California at Berkeley, USA

*Address all correspondence to: [email protected]

1. Introduction

SOS Type 1: A family of system-of-systems that provides similar core services, e.g., communication services. But each system provides different core service types, e.g., non-secure FDMA vs. secure TDMA 1 communication services;

SOS Type 2: An integration of many families of SoS. When combined, this type of system provides unique SOS capabilities at the enterprise level (i.e., integrated level). An example of this complex system is a combination of a family of communications SoS with a family of Global Position Satellite (GPS) SoS; and

SOS Type 3: An integration of many heterogenous, independent but interrelated types of systems with each system providing distinctive core services. For example, a production line consists of (i) electrical system, (ii) sensor system, and (iii) mechanical system with belt conveyor, etc.

Note that we use U.S. Department of Defense (DoD) SOS System engineering guide [ 1 ] to define SOS. While many existing papers, documents and System-of-Systems (SoS, which is not SOS) standards considered integration of (i) many systems of the same type of systems together which is identical to our Type 1, and (ii) many different types of systems as a system consisted of many systems and referred to as SoS, which is identical to our SOS Type 3. In this chapter, we focus our discussion on SOS Type 2, since existing SoS engineering standards can be directly applied to SOS Type 1 and Type 3 but not Type 2.

It would be safe to claim that the disciplines of current system thinking, decision science and computer and telecommunication engineering have played a critical role in the emergence of SoS 2 and SOS. Traditional system theory posits that the whole is greater than the sum of its isolated parts [ 2 , 3 , 4 ]. And to achieve this holistic added value, it seeks to identify, analyze and create processes through optimal arrangements or adaptations of individual and independent subsystems’ components and systems under system and SoS perspectives, respectively. This part-to-whole and whole-to-part thinking has been extended to SOS perspective for complex systems belong to SOS Type 2 and is prevalent in the selected chapters of this book.

Decision theory deals with the reasoning -- be it rational or not -- that drives a person’s choice. The three core concepts in decision theory are elicitation and interpretation of the decision maker’s preferences, the search of available options, and the management of uncertainty, risks and regrets [ 5 , 6 , 7 ]. In organizational or collective settings, decision making is extended to multiple stakeholders. Von Neumann, Morgenstern and Nash are universally credited for their pioneering work on game theory [ 8 , 9 , 10 ]. They proposed mathematical models of strategic interaction among rational decision-makers. The latter can be either cooperative or non-cooperative. The discussion on modern SOS in this volume constantly the basic foundations of game theory that uses Nash equilibrium as a prime operational goal.

The third underlying discipline that unifies the chapter of this book is the discipline of computer, information, communication and computer system (ICS) engineering. As ICS engineers continue to stay at the forefront of technological development, specific issues related to process flow design and conflict management of federated systems have emerged to be most challenging. The majority of chapters in this book, throughout their specific domain applications, such as space systems, attempt to address the challenges related to merging computing and communications due to the limitations of existing core protocols and at SOS design level, a deep understanding of how to conceptualize, design and manage coordinating parallelism [ 11 , 12 ]. These design issues appear virtually in all chapters of this book. And the authors have demonstrated several different approaches to address these challenges in their specific applications.

The lack of authority over the constituent systems because of their independent management, funding and objectives that may not align with those of the SOS as a whole.

The emergent behavior adds a large degree of unpredictability, as overall system behavior cannot be predicted by having individual knowledge of each of the constituents.

Recently in 2019, the International Council on Systems Engineering (INCOSE) [ 13 ] has released the latest version of the “Guidelines for the Utilization of ISO/IEC/IEEE 15288 in the Context of System of Systems (SoS) Engineering”, which is an extension of existing system engineering, to industry for review and comments. This document provides guidance for the utilization of ISO/IEC/IEEE 15288 in the context of SoS in many domains. This INCOSE guidebook perceives that SoS engineering demands a balance between linear procedural procedures for systematic activity and holistic nonlinear procedures due to additional complexity from SoS emergence. ISO/IEC/IEEE 15288 is considered by most system engineers as the foundation for SoS Engineering for many civilian and commercial applications, while U.S. DoD Systems Engineering Guide for SOS is considered as the foundation for SOS engineering design and implementation for defense applications.

The following sections address the objectives presented in the abstract section.

2. Current trends on SOS engineering

Using a requirement-based approach, existing System-of-Systems (SoS) engineering is a software engineering discipline that deals with the analysis, design, development, deployment and evaluation of heterogenous systems. A peculiar aspect of SoS engineering is to deal with a significant level of uncertainty in requirements engineering [ 13 ]. As such, while the goal of traditional system engineering is to build the system right, SoS engineering goal is to build the right system in the SoS context. Instead of optimizing individual systems, the primary objective of SoS engineering methodology is to maximize the overall performance of an integrated platform.

Many researchers, scientists and system engineers in the field have recognized the following challenges related to existing requirement based SoS approach when extended to complex SOS Type 2 defined above: (i) Requirements are usually derived from the assumptions of certain selected technology enablers that are usually a few years behind the current technologies, and (ii) When the requirements are changing at a fast pace, the current (As-Is) system architecture design using this SoS requirement-based approach becomes a “bottleneck” when interfacing with newer (To-Be) systems that are not within the same family. The current SOS engineering approach is to focus on the use of capability-based SOS engineering approach to address the “requirements” challenges for monolithic and complex systems (SOS Type 2 or complex SOS) with changing requirements due to technology changes and dynamic environments.

3. Current trends on SOS architecture design and MS&A

Known as complex SOS, these new deployments represent a step further in integrating task-driven dedicated systems that pool and share resources (i.e., data) and capabilities (i.e., modeling and intelligence) together to expand more functionalities and improved SOS performance (i.e., effectiveness and efficiency) to deliver unique capabilities than simply the sum of the individual constituent systems. Many of these SOS appear invisible to most users, but their presence is omnipresent in our daily lives: smart power grids, integrated traffic networks for air, land and sea connectivity, health information systems, global supply chain networks, and many others.

As mentioned above, requirements are usually derived based on the assumptions of selected technology enablers that are usually a few years behind the current technologies (e.g., at least 3 to 5 years for space systems),

When the requirements of one type of FoS are changing at a fast pace, the As-Is system architecture design using SOS requirement-based approach becomes a “bottleneck” when interfacing with newer systems that are not within the same family,

The family of SoS that requires frequent upgrade/refresh due to technology changes can cause a loss of interoperability with family of SoS that have stable requirements,

Practically, SOS management at the enterprise level can pose a real challenge, when a family of SoS systems with stable requirements are not able to synchronize with the other families of SoS systems to be deployed at a later date; Managing this mis-alignment of systems and requirements synchronization is unmanageable task.

SOS architecture design is based on the top-down approach by associating each system with its high-level capabilities not subsystem’s components’ requirements. This approach leaves the flow-down of capability-to-requirement to the selected contractors for the design and build of each FoS,

Managing the capabilities at the SOS enterprise level, i.e., SOS capability alignment, synchronization and integration will be managed using capability-based engineering approach.

Develop MS&A models to simulate, analyze and characterize SOS capabilities with well-defined SOS architecture performance metrics focusing on capabilities, and not detail requirements’ metrics.

4. Existing SOS Modeling, simulation and analysis (MS&A)

The current trends for the development of SOS MS&A models requires to classify and decompose complex SOS according to their presumed capability’s attributes and relationships. In the context of this chapter, the classification and decomposition will be performed using SOS capability-based engineering perspective, which is also referred to as SOS perspective that encapsulate the three SOS types as defined earlier. Using [ 15 ], the book chapters have presented SOS taxonomy for space and airborne systems.

Optimizing the synergy between independent and heterogeneous systems or FoS’ systems is a particular challenge in SOS architecture analysis. In order to analyze the SOS architecture effectiveness and to specify SOS characteristics, behaviors and features, engineers develop SOS MS&A frameworks and models and associated SOS performance metrics. The book chapters successfully demonstrated the use of SOS perspective for the development of MS&A models to characterize the performance of a notional space systems-of-systems with different FoS types.

5. A SOS perspective and current trends on the MS&A of decision support systems (DSS)

Decision-making is being profoundly challenged by the digitization of the business world and the rise of environmental uncertainty and risks. Augmented by digital technologies, decision makers have in their hands massive amount of open source data, and often, they are forced to make swift decisions while trying to mitigate increasing level of risks. Given the diversification of massive information sources that go beyond the organization boundaries, decision makers are facing with a triple level of uncertainty – increased difficulty in identifying the possible courses of actions given a complex decision; increased difficulty in estimating the likelihood of decision outcomes of a chosen action, and unexpected emergence of new actors – be it allies or foes – along the decision-making process.

DSS are commonly known as computer-based systems that are designed for aiding decision-makers to transform an ill-defined and unstructured problem into a well-defined and structured problem. In that process, the problem can be iteratively analyzed, and possible decision outcomes can be visualized. The role and function of a DSS is to guide the user throughout the decision-making process that eventually lead to a final decision – either optimal or satisfactory. In this DSS perspective, MS&A is seen as a set of tools that help decision makers to (i) express their preferences and needs, (ii) explore all possible solutions, (iii) perform evaluation analyses, and (iv) select the best possible preferred outcomes. In complex decision-making situations, a DSS is a computer-based system that supports its user(s) to make effective decisions in ill-structured problems.

A Data Component: that allows the decision maker to retrieve relevant data from all possible relevant sources to generate new alternatives and new perspectives in decision making;

A Model Component: that enables selection, creation, and manipulation of models to help decision makers best capture the dimensions of the decision problems;

An Interface Component: that provides context-sensitive and personalized interaction with the users; and

A Communication Component: that facilitates structured and free-format information exchanges between users.

SOS Dynamic Program Solver: Given a specific complex problem at hand, the DSS facilitates the generating of problem-solving solutions. It can simply be the execution of an existing ready-to-be-applied decision model, or it can set up a sequence of trial-and-error algorithms in search for an optimal problem formulation.

SOS Daemon: In a highly distributed system, the role of this kernel of the multi-tasking DSS is to manage, coordinate and control in the background, without the direct control of the user, the overall execution of the SoS. Upon request, the daemon activates the processing of data, model and analysis, interpretation and visualization.

SOS Scheduler: In a large-scale, loosely coupled distributed architectures, the SoS scheduler task is to generate a feasible scheduling scheme to execute decision making problems. It is providing process-driven policies to help the SOS Deamon to sequence DSS execution – either in a concurrent or sequential manner – and to allocate computational resources to each of the DSS tasks.

SOS Planner and Controller: In highly vulnerable operations, the Planner and Controller performs the function of a hardware/software watchdog to ensure that the SoS can be promptly reset if it is disrupted by malfunctions or failures. In normal operations, the DSS should allow for the coordination of modeling and simulation processes.

Over the last thirty years, with the emergence of Decision Support Technology, decision makers have benefited from dedicated DSS applications, from engineering to business and healthcare to engineering. Elevating the role and function of DSS to support complex SoS presents both opportunities and challenges to the discipline. As exemplified in the book chapters, the concept of DSS can offer group decision for risk management and collective generation of social urban policies. Furthermore, game theories can be used to engage antagonists in finding a solution that would be acceptable to all.

6. A SOS perspective and current trends on MS&A of game theoretical models (GTM)

Game theory, i.e., what type of game that the analyst should be selected for the problem being investigated and how-to set-up the game to achieve desire outcomes,

Advanced mathematics 3 in several fields, including modeling and simulation, algebra, probability, statistics and calculus, and

The problems being investigated with profound subject matter expertise in a particular scientific area. As an example, the analyst may require having a thorough understanding of the behavior of the cellular system being investigated or understanding of several medical fields, including tumor cells, thoracic surgery, neocortical epilepsy and kidney donation.

Complete information games: Players know all information about the other players, e.g., their “types”, strategies, payoffs and preferences.

Incomplete information games: Players may or may not know some information about the other players, e.g., their “types”, strategies, payoffs or their preferences.

Perfect information games: Players are aware of the actions chosen by other players. They know who the other players are, what their possible strategies/actions are, and the preferences/payoffs of these other players. Information about the other players in perfect information game is also complete.

Imperfect information games: Players simply do not know of the actions chosen by other players. However, they know who the other players are, what their possible strategies/actions are, and the preferences/payoffs of these other players. Hence, information about the other players in imperfect information game is incomplete.

Game theoretical Modeling Taxonomy from SOS perspective.

Figure 1 assumes all games are Bayesian games. Basically, there are seven game models associated with static and dynamic game types. Each of these game models can be considered as a model of a “system” with a specified set of inputs and outputs and when these systems are set-up properly, together they will provide desired outcomes. Recently, References [ 16 , 17 ] have used this SOS MS&A approach for developing complex computer simulation models to evaluate and develop acquisition strategy for acquiring complex space systems for U.S. DoD. Reference [ 18 ] discusses the use of decision support system to complement the game models when decisions on a selecting of a particular architecture solution does not converge. Therefore, it is probably safe to claim that the current trends for the development of complex MS&A models for game theoretical modeling applications are to use (i) SOS perspective, and (ii) Decision support system when the game model of a complex system or process does not converge.

7. Conclusion

The chapters presented in this technical book share a common thread of using Systems-of-Systems (SOS) perspectives and existing INCOSE System-of-Systems (SoS) engineering to address complex practical test-and-evaluation processes and systems, ranging from melt spinning process and space systems enterprise to medical problems. While dealing with a great level of details illustrating their thematic methodologies, the authors do take the effort in providing the readers with a thorough background discussion, making their chapters comprehensive and reachable to all. We hope that the readers will find the chapters selected for this book a source of ideas for their own work -- ideas that are anchored in a set of interdisciplinary and, moreover, ideas are being explored or experimented in promising systems-of-systems applications.

By its very nature, an SOS evolves overtime with changing systems requirements. Looking forward, the coordination of simultaneous and real-time processes in large-scale programmable networks remains to us a major challenge in the design of SOS for complex problem solving. In spite of the recent advances in Artificial Intelligent (AI) and automated systems, the burden of managing the interfaces between distributed data repositories, disparate and incompatible model bases, and context-dependent visualization and presentation techniques, the coordination of parallel operations still depends in a large part on the SOS designers. It is a time-consuming and tedious process to conceptualize and implementing parallelism. We hope the readers find in this book concepts and ideas that would help them achieve their requirements analysis and SOS design task.

Last but not least, and although not explicitly discussed, most of the chapters in this book have judiciously pointed out the necessity of establishing a coherent set of principles for systems-of-systems engineering, including synergism, symbiosis, modularity and self-governance, conservation and reconfiguration, emergence and re-architecting, efficiency and effectiveness. If these principles are clearly defined and adopted by the community of SOS developers and users, we expect that SOS would be the next and ultimate generation of digital applications.

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• 17. Tien M. Nguyen, Hien T. Tran, Andy T. Guillen, Tung X. Bui, and Sumner S. Matsunaga, “Acquisition War-Gaming Technique for Acquiring Future Complex Systems: Modeling and Simulation Results for Cost Plus Incentive Fee Contract,” Journal of Mathematics, 2018. Available at: https://doi.org/10.3390/math6030043
• 18. Tien M. Nguyen, Tom Freeze, Tung Bui, Andy Guillen, “Multi-Criteria Decision Theory for Enterprise Architecture Risk assessment: Theory, Modeling and Results,” 2020 SPIE Conference Proceedings, Conference: Sensors and Systems for Space Applications XIII; DOI:10.1117/12.2559317
• FDMA = Frequency Division Multiple Access vs. TDMA = Time Division Multiple Access.
• Note that in this Chapter SoS can be considered as SOS Type 1 and Type 2 but not Type 3. Existing standard SoS engineering approach needs to be modified or extended to address SOS Type 2 enterprise challenges.
• Note that mathematical game theory can also be considered as a brand of mathematics that required mathematical background in modeling and simulation, algebra, probability, statistics and calculus.

© 2021 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution 3.0 License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Introduction to systems analysis and design: A structured approach

1987, Information and Software Technology

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ACM Transactions on Information Systems ( …

Keld Bødker

Systems analysis is the dissection of a system into its component pieces for purposes of studying how those component pieces interact and work [Edwa89]. Structured analysis was one the first formal strategies developed for systems analysis of information systems and computer applications [Whit98]. Modern structured analysis is a process-centered technique that is used to model requirements for a system. The models are structured pictures that illustrate the processes, inputs, outputs, and files required to respond to events. Structured analysis introduced an overall strategy that has been adopted by many of the other techniques – model-driven development. A model is a representation of reality. Just as 'a picture is worth a thousand words,' most models use pictures to represent reality. Model-driven development techniques emphasize the drawing of models to define requirements and system designs. The model becomes the design blueprint for constructing the final system. Before developing this model, however, it is essential to identify the components that will make up the system to be designed. In order to best aid the machine designer and reduce the design time, the following key elements were identified: an implicit solver to solve

Subhrajit Hazra

Systems analysis Is sorely in need of a conceptual framework that establishes principles and guidelines for the task of trarslating the qualitative and unstructured p e r c e o t i o n of organizational information requirements into the technical and rigid solutions available with computerized hardware and s o f t w a r e . This paper outlines the major characteristics of a model for erecting a bridge between the diverse organization and computer systems that must be joined by an Information s y s t e m . Structured programming has provided the programmer with such a rrodel. Surely* the systems analyst can benefit from new and old perspectives on his even mors conolsx tisk.

varun raghuwanshi

Nwakanma Cosmas , akuta Cletus Ikechukwu

Systems Analysis and Design is an exciting endeavour as well as an active field in which analysts continually learn new techniques and approaches to develop systems more effectively and efficiently. Any organization that wants to have a long-lasting impact on its target market, must be ready to invest its resources in planning and research, to ascertain whether a new project is viable, partially viable or impracticable. This will either show the survival tendencies of the organization as it relates to the project or its weaknesses in handling the project. Every system development inadvertently follows four phases, which are: planning, analysis, design, and implementation. All complex systems can be decomposed into a nested hierarchy of subsystems because the different facets of every individual organization are either a system, part of a system or a subsystem. For an embodiment of various singular interconnected parts to be considered a system, it must have followed through with a methodology or an approach. This paper utilizes expository methodology and drives towards giving a concise overview of the various approaches to be adopted while developing a system. It begs to give more insight to the current methodologies in systems development, the emerging approaches and the pros and cons. The authors investigate from inception to the current methodologies, knowing full well that many occurrences in life happens in correspondence to dispensations, times and seasons; just like winter and summer, the authors understudy the various dispensations to pin the prevalent methodologies in certain time spaces, the advances or improvement as well as the advantages and disadvantages they have over others as time progresses. In the process, old systems methodologies are improved to serve a larger target and the amount of work needed per time reduces as new system methodology are developed over time.

Dr. VISHAL VARIA

PREFACE Saurshtra University has designed versatile courses like BCA and PGDCA. This courses focus on the development of student in the field of information technology. This field is every expanding and developing. To keep pace with the global requirements and challenges we must develop ourselves uptodate in this field. To take the students to the international platform and prepare them to face the challanges of information technology (the next generation) Saurashtra University has not only introduced but also developed such courses in the favour of students. By being in BCA for three years the student almost passes through all the areas of information technology viz. programming, web-designing, software analysis, web-programming, embedded programming, etc. Networking is also one such important area where students can focus on and develop themselves. To cope up with the industry and bring good results with the University Exams one must have good tools/weapons to fight competition. With this book, we are trying to give such tool/weapon to students so that they can prepare themselves to face the challenges of the future competition. The book is desinged in the way that is most understanding and comprehensive to students and their grasping power. The language used by the author is simple and easy to understand. The topics are divided into subtopics and points that are easy to grasp and remember. The book focuses on the minute details of the chapters and their topics as per the syllabus weightage. Important questions are also summerized at the end of each chapter that will enable the students on the exact topics that are important from the chapter and for scoring marks. The book also contains appropriate graphics and examples for better understanding. This book will also be useful as the last minute revision guide to the exam as the topics are represented in pointwise fashion for easy rememberance. In short, through this book we are trying to fill the requirement of students for the subject material for SYSTEM ANALYSIS AND DESIGN AND SOFTWARE ENGINEERING subject. This is our maiden project and is bound to contain some errors non-technical in nature. We regret such errors if any and would like to have your feedback on this book. The feedback form is included in this book after this page. We, wish you all the very best to for the subject for University Exams.

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New Directions for Systems Analysis and Design

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• Ronald Stamper 2  

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Information systems analysis and design is stagnant. It exists largely as an adjunct to software engineering to facilitate the application of computers. Its fundamental ideas, which have scarcely advanced since the 1950s, are based a paradigm that makes us think with a technical bias. This paper proposes a new perspective that can make ISAD more productive, both practically and intellectually.

We are used to treating an information system as the flow and manipulation of data to produce more data, which we re-label “information”. This old “flow” paradigm fails to acknowledge that computers and data are not ends in themselves but only the means to achieve ends that are essentially social. Data have no value until they change how people think and how they are disposed to act. Starting from this different point, we arrive at an “information field” paradigm.

An information field is established by a group of people who share a set of norms. Norms are the units of knowledge that enable us to co-operate in an organised way. They regulate our behaviour, beliefs, values and perceptions, and they all have the form IF condition THEN subject HAS attitude TO proposition Information then serves the norm subject who needs to know when the condition is met. When this happens, for example, in the case of a behavioral norm, to be obliged, permitted or forbidden to act as the proposition specifies. For example: IF the goods are faulty THEN the vendor HAS an obligation TO replace them As a result of the norm being activated in this example, the vendor will tend to replace the goods or offer to do so. Either output produces more information that enters the social system. The information needed by the group in the information field is defined by the set of norms they share. The requirements for any computer-based system to serve these people are simply a logical consequence of the formally defined field.

This field paradigm leads to a theory of information systems as social systems in which IT can play its limited role. It transforms our discipline from an aid to computer application into a formal and precise study of organised social behaviour with wide intellectual and practical implications. Our discipline will be able to underpin all kind of organisational re-engineering, with or without the use of IT. It has the potential to change the present broad-brush study of organisation into a precise science. In practice, with computer applications, we have shown that the field paradigm can lead to massive reductions in development, support and maintenance costs, increased system stability, greater reusability of design elements and far less documentation that is also easier to understand.

The lesson will illustrate the basic ideas of this theory and the methods of analysis (MEASUR) that it has generated.

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Stamper, R. (2000). New Directions for Systems Analysis and Design. In: Filipe, J. (eds) Enterprise Information Systems. Springer, Dordrecht. https://doi.org/10.1007/978-94-015-9518-6_2

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In the areas of science, information technology, and knowledge, the difficulty of systems is of much importance. As systems became more complicated, the traditional method of problem-solving became inefficient. System analysis is to examine a business problem, identify its objectives and requirements, and then design the most optimal solution to fulfill those needs.

Important Topics for System Analysis

System Analysis

• System Design

What is a System?

Constraints of a system, properties of a system, elements of a system, types of systems, system models, categories of information.

It is the very first step in any system development and the critical phase where developers come together to understand the problem, needs, and objectives of the project.

Some of the key aspects of system analysis are:

• Problem Identification: It involves identifying the issues that the system is aiming to address. Whether it is automating a business process, improving data management, or improving the user experience, understanding the problem is the first and most important step.
• Requirements Gathering: Once the problem is identified, the next step is to gather and write down the requirements. This involves communicating with the customer and developer to gather information about how the system is to be designed.
• Feasibility study: Before going into development, it is important to check the feasibility of the project. This includes the evaluation of technical, operational, and financial aspects to determine the feasibility of the proposed solution.
• Analysis and modeling: To get a deep insight into the system, analysts develop various models, such as Data Flow Diagrams(DFD), Use Cases, and Entity-Relationship(ER) diagrams. These models help the customer to visualize the system and its interactions.
• Scope Definition: Defining the scope of the system is important to prevent adding excessive features to the system and ensure that the project stays within its limits. It identifies what is part of the system and what is not.

Fraud Detection Systems: Studying transaction patterns and inconsistencies in financial data to develop algorithms for detecting and preventing fraudulent activities.

System design is where the project’s blueprint is created. It involves transforming the requirements identified in the analysis phase into a visual solution. The main components of system design are as follows:

• Architecture design: This phase describes the high level structure of the system. This includes deciding software and hardware components, their connectivity with each other and the overall design of the system. Architects make critical designs ensuring scalability, performance, and security.
• Database configuration : The design phase includes defining the database schema, data storage, and access methods. A database programmer ensures that data is organized correctly, and that the system can retrieve and process data efficiently.
• Communication system: Communication controls are important components of most systems. In this phase, designers create the system’s visual elements and interactions.
• Algorithm Design: Complex algorithms are designed in this phase. Algorithms are the logic or program that makes systems work, and their efficiency and accuracy are critical.
• Security: Data security is a major concern in today’s digital world. Developers must plan for security measures to protect the system and its data, such as encryption, access control, and threat measures.
• Test and Maintenance: System plans should also include plans for testing and validation. The designer must specify how the system will be tested to ensure that it meets specified requirements and performs as planned.
• Documentation : Suitable documentation is necessary to maintain the system and enable future use. During the design phase, documentation should be created or updated to ensure that the development team and end users can access the necessary information.

Educational Management System:

• Components: Student database, course details, management module, grading system.
• Modules: Enrollment, attendance tracking, assignment submission, grades.
• Interfaces: Student portals, teacher interfaces, parents portal.

A system is a set of things that work together as an interconnecting network to achieve a particular goal. The set of things can be hardware, software, employees and much more. Systems are everywhere around us such as computer systems which have both hardware and software to execute certain functions.

Example: Biological system, Educational system, Physical system, etc.

Every system works within certain boundaries called constraints. These constraints define the limits within which the system can operate. Typical constraints include financial constraints, technical constraints, and time constraints, which are important in guiding program development and operation.

Systems exhibit several key homes:

• Interconnectedness: Components inside a device are interconnected, change in one system might cause change in the another system.
• Environment: Systems exist within an surroundings, interacting with it and being influenced through it.
• Boundary: Systems have a described boundary that separates them from the external environment. This is essential for studying how the system interact with external environment.
• Purpose: Systems are designed with clear purpose and specific objectives. The components of a system are organized in such a way to perform intended tasks.
• Input and Output: Systems need input which leads to give the desired output.
• Feedback: Feedbacks are most important part of the system as it helps the developers to upgrade it with the user requirements.
• Input: The data that the device gets from external source.
• Process : The activities that occur within the system.
• Output : The result after processing the input.
• Feedback : It is given by the customers end to improve the system.

• Open Systems: An open system is the one that interacts freely with the external factors. These systems are capable of adapting the changes made within the system. Example: business organizations.
• Closed Systems : A closed system is one which is contained within itself. It does not have any interaction with the environment. Example: A computer system.
• Adaptive Systems : Adaptive systems are those that change their behavior with the changing environment. Example: constantly changing market.
• Dynamic Systems : Dynamic systems are those that change and evolve over a period of time. Example: ecological system change with factors like climate change.

System models are simplified representations of real-world systems that help us to understand, analyze, and design complex systems. These models are important tools used in various fields such as engineering, computer science, economics, and biology to study and predict behavior of the system. System models can be visual, mathematical or conceptual. They provide insights into program design, communication, and development. Here are a few types of system models commonly used: Mathematical, Simulation, Graphical, Physical, Conceptual.

In the context of system, records may be categorized as follows:

• Operational Information : Information used to perform each day operations.
• Management Information : Information utilized by managers for decision-making.
• Strategic Information : Information related to long-term making plans and approach formula.

In conclusion, system analysis and design form the cornerstone of successful software development and problem-solving in different domains. System analysis and design are fundamental processes that help us navigate the complexities of modern systems and to make innovation in a rapidly changing world.

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Exciting System Design Project Ideas and Topics

Home Blog Programming Exciting System Design Project Ideas and Topics

System design projects involve creating a plan for a complex system that will meet specific requirements or solve a particular problem. These projects may involve designing software applications, network infrastructures, manufacturing processes, or other complex systems.

System design projects require careful planning, analysis, and collaboration between various stakeholders, including business analysts, developers, and project managers. The design process involves identifying the goals and constraints of the system, defining its components and how they will interact, and determining how data and information will flow through the system.

What is System Design?

System design is the process of creating a plan for a complex system that meets a set of requirements. This can include software applications, network infrastructures, manufacturing processes, or any other complex system. The design process involves identifying the goals of the system and the constraints it must operate within, such as time, budget, and technical limitations.

The system design process includes several phases, such as requirements gathering, analysis, design, implementation, and testing. During each phase, various tools and techniques are used, such as flowcharts, data flow diagrams, and UML diagrams, to identify the system's components and how they will interact with each other.

It should be efficient, reliable, and easy to maintain and upgrade. Collaboration between different stakeholders, including business analysts, developers, system architects, and project managers, is essential to ensure the system meets their needs and expectations. Programming certification course online will help you to grow with mentorship programs, doubt clearing sessions, and coding challenges.

System Design Fundamentals

1. horizontal & vertical scaling.

Horizontal scaling and vertical scaling are two methods of increasing a system's capacity to handle more workload and traffic. Horizontal scaling, also known as scaling out, involves adding more machines or servers to a system's architecture. This means distributing the workload across multiple machines, each of which can handle a portion of the overall workload. Horizontal scaling is typically used to handle an increase in traffic or to improve fault tolerance.

Vertical scaling, also known as scaling up, involves adding more resources, such as CPU, memory, or storage, to a single machine or server. This approach aims to improve the performance and capacity of a system by adding more resources to an existing machine, rather than adding more machines. Vertical scaling is typically used to improve the system's overall performance and reduce the risk of hardware failure.

2. Microservices

Loosely connected services are used to structure applications utilising microservices, also known as microservice architecture. It separates a big application into a bunch of independent, modular services. These modules can be created, used, and maintained separately.

Compared to conventional monolithic programmes, microservices operate at a speed that is both faster and more dependable. Each independent service in the programme has its own logic and codebase since the application is divided into separate services. Application Programming Interfaces (APIs) allow these services to talk to one another.

3. Proxy Servers

An intermediary between a user and the internet is a proxy server, sometimes known as a forward proxy. The user is cut off from the website they are visiting. In addition to forwarding user requests, proxy servers offer a number of advantages, including:

• Enhanced security
• Enhanced privacy
• Unblocking of resources
• Limiting how much time kids and employees spend online
• Cache information to expedite inquiries

The traffic goes through a proxy server en route to the address whenever a user sends a request for it from the end server. The same proxy server again handles the request when it returns to the user, who is then forwarded it.

4. CAP Theorem

A foundational theorem in the discipline of system design is the CAP theorem. According to this, a distributed system can only provide consistency, availability, and partition tolerance in pairs. The theorem formalizes the compromise between availability and consistency in the presence of a partition.

What does System Design Teach?

System design is the process of defining the architecture, components, modules, interfaces, and data for a system to satisfy specified requirements. It is an important discipline in software engineering that helps to ensure that the resulting system is reliable, efficient, and maintainable.

One of the primary goals of system design is to ensure that the system meets the needs of the stakeholders. This requires a thorough understanding of the requirements, constraints, and objectives of the system. The design process involves breaking down the system into smaller, more manageable components, defining the interactions between these components, and optimizing the system to meet the desired performance criteria.

OG’s of Design Systems 

Material design and human interface standards make up OG's design systems. When digital mobile OSes first appeared on cell phones, these were in many respects the beginning of what design systems earlier looked like. The gold standard of design systems, designers studied these and discovered numerous useful design techniques.

Apple’s Human Interface

Learn all you need to know and get UI tools for creating fantastic apps that work well with Apple platforms. You can learn about key app structural elements including app architecture, system capabilities, visual design, iconography, and more with the help of human interface guidelines.

Google’s Material Design

Material Design is to create a consistent and intuitive user experience across different devices and platforms. It is based on the principles of real-world materials and their behavior, such as how objects move, react to touch, and cast shadows. Material Design uses these principles to create a set of guidelines for designing digital products that are both visually appealing and functional.

Atlassian’s Design Language  

With the help of Atlassian's end-to-end design language and thoughtfully chosen components, create outstanding enterprise experiences. The inclusion of a code sample in each part so that developers can study and evaluate it is its best feature.

Mozilla Firefox’s Photon Design System 

With Firefox's Photon design language, you can develop cutting-edge, uncomplicated, and captivating user interfaces for products across all mediums, from mobile to desktop to TV to the next big thing.

GitLab’s Pajamas Design System

Over 3000 people have contributed to the community-driven open-source project GitLab. According to GitLab, when everyone participates, customers become participants and the pace of human growth quickens significantly.

HubSpot’s Canvas Design System 

The elements of Hubspot's design system are illustrated in this collection, which ranges from React-based functionality and data visualization tools to colors and typography.

Whether you are a beginner or looking to enhance your skills, our software engineering course will provide you with the knowledge and expertise to succeed in the fast-paced and ever-evolving field of software engineering. Additionally, Software Engineering course training will level up your career and gear up to land a tech job in your dream company.

System Design Project Ideas

Here we will be talking about 10 interesting Software Development project ideas that are excellent for honing your programming and development skills:

Sentiment Analysis for Product Rating 

The goal of this project is to create a system for ranking products using sentiment analysis. It is an online storefront application. This sentiment analysis system's primary objective is to comprehend the customers' hidden sentiments in feedback and comments and examine their product rating patterns.

• The product may win the support of the clientele.
• It assists brands in locating resources for products that are more popular and identifying those products.
• Improve the company's local search engine rating. 

Image Encryption Using AES Algorithm 

By utilizing the AES (Advanced Encryption Standard) algorithm, this research aims to develop a comprehensive image encryption system that will guard against infiltration assaults on imaging equipment and improper usage of digital photos. Only the sender and receiver may access the photographs because the system uses the AES technique to encrypt them. Compared to DES and triple DES systems, this encryption method is more secure.

• Only the user with access can view the encrypted images.
• It is safer to use encryption and decryption.
• Stop unapproved access.

AI Shopping System 

The AI multi-agent shopping system is more of a recommendation engine than a shopping assistant. The system is initially loaded with information about a variety of products. When a user signs up for the system and does a search for a certain product, the system returns the results of the most pertinent products that match the user's search terms.

• Customisable search features
• Enhanced user interface
• User friendly
• Easy to use

e-Learning Platform 

You will use cloud computing infrastructure to construct a sharing e-learning platform for this project. The separate Learning Management Systems (LMS) incorporated in different e-Learning standards might share their learning objects, modules, and content thanks to this e-learning platform powered by cloud computing. In essence, cloud computing will promote the sharing of a variety of educational resources, making it simple for students to access them online.

Importance 

• Attract to potential users
• Increase user base
• User-friendly
• Cost effective

Voice Recognition 

The voice is recognised by the machine. While users are speaking, the system studies the tone and pattern of their voice and then recognises the voice based on that.

To perform machine translation, the device uses neural machine translation. The method also includes speech classification and recognition. 

Importance  

• Increasing productivity
• Real-time text recognition

Software Piracy Protection System 

This project's development aims to reduce software piracy and enhance software protection and security measures. One of the major dangers to the sector is piracy. Hackers compromise a company's whole security architecture by using malware and harmful code to access software goods and systems. Therefore, it is crucial to include the required safeguards and protection methods to guarantee both the data integrity and the copyright rights of software products. 

• Prevents data to get Pirated
• Copyright ownership
• Prevents unauthorized access

Data Leakage Detection System 

Data leakage detection systems' main job is to identify the sources of data leaking and detect it. Sensitive data from an organization may end up on unauthorized devices if it ever leaks. This is why it's so important to identify the source of data leaking so you can stop it in its tracks. Data leakage from the source can be stopped with an advanced data leakage detection system. 

• Preventive measures
• Always maintaining brand image

Opinion Mining for Social Networking Platforms 

This web application employs opinion mining techniques to facilitate better decision-making and improve user experience. The application gathers and examines user reviews and comments on social media sites (such as Facebook, Instagram, Twitter, etc.) and divides them into good and negative categories.

Android Local Train Ticketing System 

You will create a local train ticketing application for this project. The software allows users to purchase tickets for local trains and download receipts for their purchases. They can print out these online booking confirmations to use as physical verification while taking local trains. 

• Time efficient
• Remote access
• Easy to use, and scalable

Effectiveness of System Design Project

Enhances research skills.

System design can also help in developing research skills. Research involves investigating a particular topic or problem to gather information and develop insights. System design can be used as a research tool to investigate the feasibility, usability, and effectiveness of different solutions to a problem.

Builds Problem-solving Skills 

It can help in developing problem-solving skills. System design involves defining the architecture, components, modules, interfaces, and data for a system to satisfy specified requirements. This requires making technical decisions and trade-offs to solve specific problems related to the system's functionality, performance, scalability, security, and reliability.

Project Management Skills 

A successful system design project should meet the stated goals and objectives of the project. This includes meeting functional requirements, technical specifications, and user needs.

Helps in Technical Skill 

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Today, system design is an essential process in developing any complex system, whether it be a software application, hardware system, or a combination of both. It involves defining the architecture, components, modules, interfaces, and data for a system to satisfy specified requirements. 

Effective system design can lead to a system that meets user needs, is efficient and scalable, and is cost-effective. System design can also help in developing technical skills, research skills, and problem-solving skills. With the increasing complexity of systems, the importance of system design in ensuring their success cannot be overstated.

Frequently Asked Questions (FAQs)

It is the process of defining the architecture, components, modules, interfaces, and data for a system to satisfy specified requirements. These projects can range from the design of a software application, hardware system, or a combination of both.

There are various types of system design, including high-level design, detailed design, logical design, physical design, and database design.

To come up with a system design, you need to gather and analyze the system requirements, define the system architecture, and develop the detailed design of each component.

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UCF Student’s Primitive Asteroids Work Provides Context for Further Research, Future NASA Missions

Brittany Harvison studied the composition of families of ancient asteroids to better understand the history of our solar system and if they may have carried water to Earth.

By Eddy Duryea ’13 | May 9, 2024

The primitive asteroids that UCF physics doctoral student Brittany Harvison studies carry with them traces of their origins and billions of years of our solar system’s history.

Harvison recently pored through a library of infrared telescope data to analyze the spectral composition of 25 members of the Erigone family of primitive asteroids and help fill in the gaps in our understanding of the creation of our solar system.

The data on the Erigone asteroids, which are located in the main asteroid belt found between the orbits of Mars and Jupiter, was collected as part of the PRIMitive Asteroid Spectroscopic Survey (PRIMASS) project co-led by UCF planetary scientist Noemí Pinilla-Alonso.

Harvison’s work, which was published recently in the journal Icarus , lays the foundation for future research, and may get scientists closer to concluding if asteroids brought water to Earth and if so, how much.

“There are theories that the Earth could have received a fraction of its water from primitive asteroids in the early Solar System,” says Harvison, who is also a researcher at the Florida Space Institute (FSI) . “A big portion of these theories is understanding how these primitive asteroids were transported into Earth’s path. So, exploring primitive asteroids in the Solar System today could help paint a picture of what was going on all those years ago.”

Some of these cosmic travelers, including the asteroids within the Erigone family, have hydrated silicates. The existing hydrated bodies that continue to move throughout our solar system could tell us more about those that collided with Earth.

It is one of the many outstanding questions that Harvison’s work is hoping to address.

“We mainly wanted to see if there were primitive asteroid families similar to the Erigone and Polana asteroid families,” Harvison says. “We used spectroscopy to study what kinds of minerals were on the surface to understand their composition.”

From the study, Harvison and her co-authors saw that the Erigone and Polana families are different from one another in the near infrared but that the other primitive families have their own levels of red color in their spectral distribution along with their own unique levels of hydration.

In other words, the primitive families in the inner solar system show a variety of redness and hydration . The analysis and comparison show evidence that these families are not linked to the proposed Erigone-like or Polana-like groups, challenging the previously held theories as to where they fit in. Also, one particular asteroid, (52246) Donaldjohanson, seems to belong to the Erigone family based on its spectrum.

Piecing Together History

Due to the importance of understanding the nature of primitive objects, numerous spacecraft have targeted primitive asteroids, such as JAXA’s Hayabusa2 and NASA’s OSIRIS-REx, which visited, studied, and returned samples from Ryugu and Bennu , respectively.

Bennu and Ryugu prompted researchers to further study primitive asteroids and figure out where they came from, Harvison says.

Erigone was one of the final pieces of the large library of PRIMASS data that existed, but had yet to be studied, Harvison says. PRIMASS aims to understand the diversity of surface properties amongst primitive collisional families in the asteroid belt and map their composition.

A collisional family of asteroids refers to a group of asteroids that are believed to have originated from the breakup of a larger parent body due to a collision. The members of a collisional family provide information about the interior of the intact body they were part of before the impact.

The PRIMASS project is characterizing the collisional families of primitive asteroids in the main belt, and particularly those that could be the origin of the primitive near-Earth asteroids such as Bennu and Ryugu.

The conclusions drawn by studying collisional families like Erigone are critical puzzle pieces in the greater endeavor of understanding the creation of our solar system.

“The larger scope was to look at primitive families in the inner part of the main asteroid belt, where Ryugu and Bennu are thought to have likely originated,” she says. “The Erigone family was the last piece of the puzzle to be placed into the PRIMASS library to provide full context on primitive asteroids in this region and allow other scientists to analyze the data.”

Harvison’s research provides supplemental context for the upcoming NASA Lucy mission, which will have the eponymous spacecraft visiting (52246) Donaldjohanson in Spring 2025 before it moves on to examine eight Trojan objects (space rocks trapped in Jupiter’s orbit) in 2027 through 2033.

Looking to the Future

Study co-author Mário De Prá, an assistant scientist at FSI, served as a research assistant and Harvison’s co-supervisor. Co-author Pinilla-Alonso is Harvison’s research advisor and assisted Harvison in her research.

Pinilla-Alonso says she’s delighted to assist Harvison and see her growth.

“For me, it was a pleasure to see the process and the end result,” she says. “She contacted me early during the pandemic when we were all working at home to express her interest in pursuing a Ph.D. degree here at UCF. Here we are about three years later: she has done an awesome job and there is more to come.”

Pinilla-Alonso and Harvison say they were surprised that no one had studied the spectroscopy of the Erigone family.

“When Brittany landed on this project, we saw there was one piece of information we were missing,” Pinilla-Alonso says. “PRIMASS had completed the analysis of the visible and near-infrared of all the primitive families in the inner belt but there was one missing family: Erigone. That was very important because it was the family that could give closure to learning about the inner [asteroid] belt families. Until you ask the right question or have the tools, sometimes you don’t seek that answer. But, in this case, we had the observations done and it was clear that we needed to analyze it.”

The knowledge gained from studying Bennu, Ryugu, and the Erigone and Polana primitive asteroid families will serve as a springboard for future James Webb Space Telescope observations and NASA missions.

“It is very exciting times going through all of this new data with more to come with the James Webb Space Telescope,” Pinilla-Alonso says. “I really think the biggest discovery is yet to come. The data we can collect from Earth is limited. Now, we have the best tool in space to keep learning more.”

Pinilla-Alonso, Harvison and other researchers at FSI are slated to begin using the JWST as early as this summer to observe Erigone and other primitive asteroids, and, over a span of about two years, evaluate the collected spectra.

Harvison maintains her enthusiasm as she looks forward to building upon her analyses and further unraveling the origins of these primitive asteroids.

“There’s this fascination when I’m looking at this data and I’m examining something that’s millions of miles away,” Harvison says. “We can look back billions of years and learn the initial structure and composition of the early solar system by studying the surface of these asteroids. That’s always been something that excites me.”

In addition to Harvison, Pinillia-Alonso and De Prá, FSI colleague and head of the Planetary and Space Science Group Humberto Campins provided research support. Vania Lorenzi of Fundación Galileo Galilei and Instituto de Astrofísica de Canarias, David Morate of El Centro de Estudios de Física del Cosmos de Aragon, Julia de León and Javier Licandro of Instituto de Astrofísica de Canarias and Universidad de La Laguna, Anicia Arredondo of the Southwest Research Institute also contributed to the research.

Researchers’ Credentials

Harvison joined UCF in 2021 and is a graduate student working toward her doctoral degree in physics. She graduated from Northern Arizona University in 2020 with a degree in astronomy, planetary astronomy, and science.

Pinilla-Alonso is a professor at FSI and joined UCF in 2015. She received her doctorate in astrophysics and planetary sciences from the Universidad de La Laguna in Spain. Pinilla-Alonso also holds a joint appointment as a professor in UCF’s  Department of Physics  and has led numerous international observational campaigns in support of NASA missions such as New Horizons, OSIRISREx and Lucy.

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