Cyber Physical System: Architecture, Applications and ...

Cyber Physical System: Architecture, Applications and Research Challenges Syed Hassan Ahmed, Gwanghyeon Kim and Dongkyun Kim School of Computer Science & Engineering, Kyungpook National University, Daegu, Korea {hassan,khkim}@monet.knu.ac.kr, [email protected]

Abstract— Cyber world and physical world were considered as two different entities in the past decade. However, researchers have found that these two entities are closely correlated with each other after integration of sensor/actuators in the cyber systems. Cyber systems became responsive to the physical world by enabling real time control emanating from conventional embedded systems, thus emerging a new research paradigm named Cyber Physical System (CPS). In this article, we investigate major challenges in the integration of cyber world with physical world and its applications. In addition, we propose an architecture which contains several modules supporting the CPS. We found that every module in our proposed architecture has its own significance and can be applied to various applications. Keywords— Cyber Physical Systems (CPS), CPS Applications, Service Oriented Architecture (SOA), Research Challenges in CPS.

I. INTRODUCTION In the past decade, computer networks have been intensively explored by the research community around the world due to its wide applications. Enormous efforts have been made while improving wired technology to wireless including WSN, WMN, UWSN, and M2M. Thus, communication systems are aimed and described using variety of modeling tools and formulations. Recently, Cyber Physical Systems (CPS) has attracted much research attention from both academia and industry. CPS can be used in a wide range of application fields, including intelligent transportation, precision agriculture, Health CPS, water and mine monitoring, aerospace and so on, which undeniably demonstrates that in future many service providers will be focusing on implementing CPS technologies for their customers. In cyber physical systems, communication is needed for conveying sensor observations to controllers/actuators; thus, the design of the communication architecture is a critical requirement for system functionality. In this paper, we investigate some challenges for integration of physical world with the cyber world (i.e. CPS) and also propose our architecture for CPS. The rest of the paper is structured as follows: In Section II, possible CPS applications are summarized. In Section III, CPS architectures are discussed. In Section IV, our proposed architecture is explained. In Section V, future research challenges are introduced. Finally, some concluding remarks are given in Section VI.

II.

CPS APPLICATIONS

CPS can be used in a wide range of application fields, including intelligent transportation, precision agriculture, Health CPS, water and mine monitoring, aerospace and so on. A. Vehicular CPS With the increasing number of personal cars, many problems such as the traffic congestion, air pollution and safety issues are taking more attentions to be addressed. Advanced computing and sensing capabilities will be widely used in next-generation transportation systems, such as air traffic, railway, and car control, in order to improve safety and throughput. Vehicular Cyber Physical System (VCPS) is not a new concept. It refers to a wide range of integrated transportation management system which should be real-time, efficient and accurate. Based on modern technologies such as electronics, computers, sensors, and networks, the traditional modes of transport are becoming more intelligent. NAHSC is dedicated to the study and development of independent high-speed system "AHS" (Automated Highway systems), aiming to achieve a more secure and intelligent traffic. CarTel is one of the American NSF support projects, developed by MIT [14]. The CarTel project combines mobile computing and sensing, wireless networking, and data intensive algorithms running on servers in the cloud to address these challenges. CarTel helps applications to easily collect process, deliver, analyze, and visualize data from sensors located on mobile units. The contributions of CarTel include traffic mitigation, road surface monitoring and hazard detection, vehicular networking and so on. B. Agricultural CPS Accuracy in agriculture was expected in the early 1980s from traditional agriculture, which is supported by information technology, to implement a full range of modern systems of agricultural management strategies and technologies [7]. Design of precision agriculture includes data management of production experiments, fundamental geographic information of farmland, micro-climate information and other data. The project "underground wireless sensor network" was developed by University of Nebraska-Lincoln Cyber physical

Networking Lab, where Agnelo R. Silva and Mehmet C. Vuran developed a novel cyber-physical system through the integration of center pivot systems with wireless underground sensor networks, i.e. CPS^2 for precision agriculture [8]. The Wireless Underground Sensor Networks (WUSNs) consist of wirelessly connected underground sensor nodes that communicate untethered through soil. The experiment results showed that the concept of CPS^2 is feasible and can be made highly reliable using commodity wireless sensor motes. This combination of CPS and precision agriculture is one of the typical applications of CPS, with good prospects. C. Health CPS Health CPS (HCPS) will replace traditional Health devices working individually which we will face in the future. With sensors and networks, various Health devices work together to detect the patients’ physical condition in real time, especially for critical patients, such as the patients with heart disease. The portable terminal devices carried by the patient can detect the patient’s condition at any time and send timely warning or prediction in advance. In addition, the collaboration between Health equipment and real-time data delivery would be much more convenient for patients. Insup Lee and Oleg Sokolsky [9] introduced the development and issues of the highly trustworthy Health CPS system, including the dependence on software from the new function development, demand for network connections and request for continuous monitoring of patients, and analyze the future development of Health CPS. For Health device interoperability issues, Cheolgi Kim et al. [10] introduced a generic framework: the NASS (NetworkAware Supervisory Systems) to integrate Health devices into such a clinical interoperability system that uses real networks. It provides a development environment, in which Healthdevice supervisory logic can be developed based on the assumptions of an ideal, robust network. Concerning the particularity of the Health applications, more features such as the higher requirement of security, real-time, network delay, will be considered in the design of Health CPS. Some of the requirements for applications supporting CPS are summarized in Table 1. Applications Vehicular CPS Environmental CPS

Air CPS

Critical

CPS Requirements CPSs for the automotive industry require high computing power, due to complex traffic control algorithms that calculate for example the best route according to traffic situation. CPSs for environment monitoring, distributed in a wide and varied geographical area (forests, rivers, mountains) must operate without human intervention for long time periods with minimal energy consumption. In such an environment, the accurate and in-time data collection provided by the ad-hoc network with low power consumption, represent a real research challenge. CPSs for aviation and defense require a precise control and high security and not least high power computing. In this scope, the development of the security protocols is a main research challenge. CPSs for energy control, water resources

Infrastructure

Health CPS

management, etc. require a precise and reliable control, leading to application software methodologies to ensure the quality of the software. CPSs for healthcare and Health equipment require a new generation of analysis, synthesis and integration technologies, leading to the development and the application of the interoperability algorithms. Table.1 CPS Application Requirements

III.

CPS ARCHITECTURES

In the past decade, architectural evolution has been shifted into systems integration, ensuring that SOA (Service Oriented Architecture) will have a major role to play in many branches of technology. SOA basically enables a rapid, low cost composition of interoperable and scalable systems based on reusable services exposed by these systems. In [1], authors proposed a simplified middleware CPS architecture integrating with web services named “WebMed”, through which an interaction with physical devices becomes as easy as invoking a computation service. Emphasizing the basics of service-oriented guidelines, authors built a loosely coupled infrastructure that exposes the functionality of physical devices to the Web for application development. However, Sanislav et al. [3] addressed the architecture of a CPS to precisely provide a uniform treatment of cyber and physical elements. The software architecture provides a good starting point but the concept should be extended to CPS by using a new vocabulary for physical and cyber-physical elements necessary to analyze the system behavior. Tan et al. [4] presented representative prototype architecture of the CPS concept. They highlighted the cyber world represented by events/information as an abstraction of the real physical world governed by semantic laws, evolving the typical architecture of the embedded systems and aligned it to current technological requirements. In [6], authors analyzed the features of M2M, WSNs, CPS and IoT, and illuminated the correlations among them. Then, home M2M networks were reviewed. Authors gave a CPS scenario (HCPS) to demonstrate how M2M systems with the capabilities of decision-making and autonomous control can be upgraded to CPS and sketched the important research proposals and challenges related to CPS designs. IV.

PROPOSED ARCHITECTURE

4.1 Proposed Architecture: As shown in Figure 1, we have five main modules for our proposed architecture. In this sub-section, each module is described in more detail: A. Sensing Module: For data collection from physical world through sensors, the main function of this module works for environment awareness which is achieved by preliminary data preprocessing. The data is provided to the Data Management Module (DMM). The Sensing module supports multiple networks1. It depends on nature of networks that is deployed. For example, in a WSN, each sensor node is equipped with a sensing module for real time sensing. Other network nodes can also operate with a part of this module in different scenarios. In case of VCPS, VANETS nodes (i.e. cars) can be equipped with sensing module to sense data from physical world. In case of HCPS, using BAN, sensors attached with patients are equipped with sensing modules nodes to enable real time control. B. Data Management Module(DMM): DMM consists of the computational devices and storage media. This provides the heterogeneous data processing such as normalization, noise reduction, data storage and other similar functions. DMM is considered as the bridge between dynamic environment and services as it is collecting the sensed data from sensors and forwards the data to service aware modules using Next Generation Internet. C. Next Generation Internet: A common feature of emerging Next Generation Internet is the ability for applications to select the path, or paths that their packets take between the source and destination. This dynamic nature of internet service is required for designing Cyber Physical System. Unlike the current Internet architecture where routing protocols find a single (the best) path between a source and destination, future Internet routing protocols will need to present applications with a choice of paths. For achieving this, research is still pending to find QoS routing. While QoS routing provides applications with a path that better meets the application’s needs, it does not scale to the size of the current Internet, let alone the Next Generation Internet. IPv6 and exploiting 802.16n and 802.16p are ongoing projects and expected to be included in Next Generation Internet services trial. D. Service Aware Modules (SAM): Service Aware Module (SAM) provides the typical functions of the whole system, including the decision-making, task analysis, task schedule and so on. After receiving sensed data, this module recognizes and sends data to the services available. E. Application Module (AM): In Application Module, a number of services are deployed and interact with NGI. Simultaneously, information is getting saved on secured database for QoS support. Database is maintained at local storage and on cloud platforms at the same time in order to keep data safe. We can use a concept of

1

However other network nodes like WMN, MANETs and M2M are also part of Cyber Physical Systems [2] and can be placed in sensing module.

NoSQL for saving data [13]. Although the NoSQL systems have a variety of different features, there are some common ones. First, many NoSQL systems manage data that is distributed across multiple sites. This saved data over cloud system can be accessed from anywhere followed by authenticated access. F. Sensors and Actuators: Actuators and the Sensing Modules are two different electronic devices which interact with the physical environment [5]; the actuator may be a physical device, a car, a lamp or watering pump. It receives the commands from the Application Module, and executes. The security assurance part is inherently important in a whole system, from the access security, data security to device security. We divide CPS security into different requirements in different scenarios. For example, as for military applications, the confidentiality feature is more important, but in the smart home system or HCPS, the real-time requirements are more emphasized. Security of CPS can be divided into the following three phases: awareness security, which is to ensure the security and accuracy of the information collected from physical environment; transport security, which is to prevent the data from being destroyed during the transmission processes; physical security, such as safety procedures in servers or workstations. Feedback Awareness is one of the advanced level services to minimize the data processing by communication between sensor and actuator for executing required actions directly. 4.2 Communication Topology in Proposed Architecture:

Fig.2 Dynamic Communications

In this subsection, we describe the interactions between modules in the proposed CPS architecture. First of all, the sensing module sends an association request to Data Management Module (DMM) and it replies with an acknowledgement packet. Once association between DMM and Sensing module is completed, nodes start sending the sensed data to DMM. Here, noise reduction and data normalization provide the bridge between the cyber world and physical world. Through QoS routing [section 4.1.C], data is transferred to Service Aware Modules using services of Next Generation Internet. Available services are assigned to different applications in Application Module. To ensure the security and integrity of data, during each network operation, data is sent to a cloud platform and also to a local database.

4.3 Application Scenarios: Consider a deployment scenario of our proposed architecture where various sensors are utilized to collect data while various actuators can make changes to the environment. Suppose that the sensed data S1 is to be sent by the sensing module to DMM as shown in Figure 2. Besides storing data in its local storage, DMM forwards the data to the service aware module. The service awareness module is used to identify and assign an exact application A1 in response to the data S1. Now, A1 in the application module communicates with relevant actuators. At the same time, the application module sends association information between S1 and A1 (S1A1) to the service aware module and most importantly to DMM. DMM keeps track of the data and its associated application in local storage. In the future, when a similar data is received by DMM, instead of sending the data to the service awareness module, it directly sends the data to the application module. The application module sends a required action request to actuators. 4.4 Vehicular Scenario: For vehicular CPS, we suppose vehicles are connected to Road Side Unit (RSU), where RSU has access to Next Generation Internet infra-structure providing different services through wired networks. In near future, almost every car will be having different actuators like speed controlling, lights, brakes etc. Our proposed architecture is applicable for real time control of those actuators. Service aware modules make communication and control efficient by providing the best application in different services to a single car. For example, in case of folk, lights should be on automatically. In case of road damage ahead, breaks should be applied and in case of congestion, the best and shortest path is updated on GPS automatically. 4.5 Agriculture Scenario: For agriculture CPS, here we consider a greenhouse scenario. In greenhouse technology, more parameters should be controlled due to a large variety of the crops. They are growing day by day because of the development in agriculture technology [11]. In this situation, the wireless sensor network with additional hardware and software is an efficient solution for greenhouse control. Real time control can be applied using our architecture in the future. After receiving a configuration of greenhouse by consumer, here our feedback awareness makes network efficient to control different services like watering, humidity, plant health monitoring etc. with real time control. 4.6 Health Scenario: For now, our concern is Patient safety and Hospital liability. We consider several services to be expected from Health CPS, for example Meds/Patient care administration, real time Laboratory specimen tracking, patients putting themselves at risk (e.g. wandering patients), inability to alert staff of patient location for urgent needs and monitoring equipment exposure that may put patients at risk (e.g. infectious disease) [12]. We suppose that sensors and actuators are installed using BANs with patient and WSN within hospital building. Real time monitoring and control can be achieved by Data Management Module and Service awareness module which also plays an important role in order to provide QoS monitoring. While designing a system for hospital, sensitive applications are queued on the top priority.

V. OPEN RESEARCH CHALLENGES CPS researchers are focusing on following areas: the definition of a standard architecture, the classification of the CPSs design principles in their application domains, the modeling of the CPSs, the ensuring of the CPSs dependability, and the CPSs implementation (for critical infrastructure control and beyond). The software architecture provides a good starting point but the concept should be extended to CPS by using a new vocabulary for physical and cyber-physical elements necessary to analyze the system behavior. In the past, significant efforts were made to ensure end-to-end QoS support using algorithms and different mechanisms at varying network protocol layers. Distinguishing characteristics of CPS however enlightened further challenges in order to provide QoS support. In this section, some open research topics of interest are identified precisely. QoS-Aware Communication Protocols: Efficiency is always considered as back-bone of any network topology. In CPS, due to heterogeneity between sensing modules and the need of applications to ensure real time data control, real time QoSaware MAC, routing and transport protocols are required to be developed. It was formerly indicated that CPS bridges the cyber world to the physical world through lots of sensors and actuators for varied applications [2] which have different QoS support requirements. Network protocols for CPS should be capable of identifying application requirement of each type of traffic so that QoS can be guaranteed at certain level. Resource Management: In CPS, we are not lacking in resources but data from such applications is also expected to generate streaming data with a very large volume, storing, processing, and interpreting these data in a real-time manner is essential. While dealing with more dynamic environmental changes, more complex computing, communication resources are inherently restricted. To overcome these limitations, automanagement techniques are required to ensure that a system will address resource management issues in an autonomous mode. Some feedback scheduling techniques seem promising for WSN proposed in the last decade. We can use these technologies but they need to be more flexible to provide guaranteed QoS support. However, how to map resource management to control problems is still a subject of future research. QoS-Aware Power Management: Energy consumption is a vital challenge from a very beginning of WSN, WMN, and UWSN, etc. Network lifetime and performance is always dependent on the residual energy of sensor nodes and actuators in most applications. In CPS, dynamic computing with real time control demands much CPU energy consumption, which should be minimized by exploiting dynamic voltage technology. VI.

CONCLUSION

This paper summarizes a concept of CPS with its applications and current research progress in this area. Characteristics of CPS such as real time, scalability and reliability, were

introduced, presenting a number of challenges in CPS design and implementation. After discussing several proposed architectures for CPS, an explicit standard CPS Architecture has been described. We explored different applications of future with our architecture. We found that due to the capability of dynamic control, every module can be implemented individually or combined to achieve the QoS real time control. ACKNOWLEDGMENT This research was supported by the MSIP (Ministry of Science, ICT & Future Planning), Korea, under the C-ITRC (Convergence Information Technology Research Center) support program (NIPA-2013-H040113-1005) supervised by the NIPA (National IT Industry Promotion Agency). This work was supported by the IT R&D program of MSIP/KEIT. [10041145, Self-Organizing Software platform (SoSp) for Welfare Devices]. REFERENCES [1]

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