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Register a new userConcurrent Cyber Physical Systems:Tensor State Space Representation
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Added by
Sumit Kumar
Publication date
2013
fields
Informatics Engineering
and research's language is
English
Authors
Garimella Rama Murthy
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No Arabic abstract
In this research paper, state space representation of concurrent, linearly coupled dynamical systems is discussed. It is reasoned that the Tensor State Space Representation (TSSR) proposed in [Rama1] is directly applicable in such a problem. Also some discussion on linearly coupled, concurrent systems evolving on multiple time scales is included. Briefly new ideas related to distributed signal processing in cyber physical systems are included.
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Technical advances in ubiquitous sensing, embedded computing, and wireless communication are leading to a new generation of engineered systems called cyber-physical systems (CPS). CPS promises to transform the way we interact with the physical world just as the Internet transformed how we interact with one another. Before this vision becomes a reality, however, a large number of challenges have to be addressed. Network quality of service (QoS) management in this new realm is among those issues that deserve extensive research efforts. It is envisioned that wireless sensor/actuator networks (WSANs) will play an essential role in CPS. This paper examines the main characteristics of WSANs and the requirements of QoS provisioning in the context of cyber-physical computing. Several research topics and challenges are identified. As a sample solution, a feedback scheduling framework is proposed to tackle some of the identified challenges. A simple example is also presented that illustrates the effectiveness of the proposed solution.
Cyber-physical control applications impose strict requirements on the reliability and latency of the underlying communication system. Hence, they have been mostly implemented using wired channels where the communication service is highly predictable. Nevertheless, fulfilling such stringent demands is envisioned with the fifth generation of mobile networks (5G). The requirements of such applications are often defined on the application layer. However, cyber-physical control applications can usually tolerate sparse packet loss, and therefore it is not at all obvious what configurations and settings these application level requirements impose on the underlying wireless network. In this paper, we apply the fundamental metrics from reliability literature to wireless communications and derive a mapping function between application level requirements and network level parameters for those metrics under deterministic arrivals. Our mapping function enables network designers to realize the end-to-end performance (as the target application observes it). It provides insights to the network controller to either enable more reliability enhancement features (e.g., repetition), if the metrics are below requirements, or to enable features increasing network utilization, otherwise. We evaluate our theoretical results by realistic and detailed simulations of a factory automation scenario. Our simulation results confirm the viability of the theoretical framework under various burst error tolerance and load conditions.
The popularity of concurrent transmissions (CT) has soared after recent studies have shown their feasibility on the four physical layers specified by BLE 5, hence providing an alternative to the use of IEEE 802.15.4 for the design of reliable and efficient low-power wireless protocols. However, to date, the extent to which physical layer properties affect the performance of CT has not yet been investigated in detail. This paper fills this gap and provides the first extensive study on the impact of the physical layer on CT-based solutions using IEEE 802.15.4 and BLE 5. We first highlight through simulation how the impact of errors induced by de-synchronization and beating on the performance of CT highly depends on the choice of the underlying physical layer. We then confirm these observations experimentally on real hardware through an analysis of the bit error distribution across received packets, unveiling possible techniques to effectively handle these errors. We further study the performance of CT-based flooding protocols in the presence of radio interference on a large-scale, and derive important insights on how the used physical layer affects their dependability.
There is a pressing need to interconnect physical systems such as power grid and vehicles for efficient management and safe operations. Owing to the diverse features of physical systems, there is hardly a one-size-fits-all networking solution for developing cyber-physical systems. Network slicing is a promising technology that allows network operators to create multiple virtual networks on top of a shared network infrastructure. These virtual networks can be tailored to meet the requirements of different cyber-physical systems. However, it is challenging to design secure network slicing solutions that can efficiently create end-to-end network slices for diverse cyber-physical systems. In this article, we discuss the challenges and security issues of network slicing, study learning-assisted network slicing solutions, and analyze their performance under the denial-of-service attack. We also present a design and implementation of a small-scale testbed for evaluating the network slicing solutions.
In cyber-physical systems such as automobiles, measurement data from sensor nodes should be delivered to other consumer nodes such as actuators in a regular fashion. But, in practical systems over unreliable media such as wireless, it is a significant challenge to guarantee small enough inter-delivery times for different clients with heterogeneous channel conditions and inter-delivery requirements. In this paper, we design scheduling policies aiming at satisfying the inter-delivery requirements of such clients. We formulate the problem as a risk-sensitive Markov Decision Process (MDP). Although the resulting problem involves an infinite state space, we first prove that there is an equivalent MDP involving only a finite number of states. Then we prove the existence of a stationary optimal policy and establish an algorithm to compute it in a finite number of steps. However, the bane of this and many similar problems is the resulting complexity, and, in an attempt to make fundamental progress, we further propose a new high reliability asymptotic approach. In essence, this approach considers the scenario when the channel failure probabilities for different clients are of the same order, and asymptotically approach zero. We thus proceed to determine the asymptotically optimal policy: in a two-client scenario, we show that the asymptotically optimal policy is a modified least time-to-go policy, which is intuitively appealing and easily implementable; in the general multi-client scenario, we are led to an SN policy, and we develop an algorithm of low computational complexity to obtain it. Simulation results show that the resulting policies perform well even in the pre-asymptotic regime with moderate failure probabilities.
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