Due to the successful application of the Internet of Things (IoT) and the Internet of Services (IoS) in association with other emerging technologies, fourth industrial revolution is finally achieved through various advancements of Cyber-Physical Systems (CPS). In manufacturing, CPS, in association with the existing enabling technologies, gives birth to the smart factory that is significantly changing the global market, societal life, and economic growth. This transformation will go far beyond today's conventional industry in terms of adaptability, energy and resource efficiency, accuracy, reliability, safety, user-friendliness, scalability, and intelligence while thoughtfully dealing with the technical challenges allied with the development of CPSs, wireless networking, reliability, complexity, security, and data protection to achieve the desired level of performance. This paper provides a detailed analysis of CPS in the industrial domain, its required technologies, architectures, and expected features. This paper also highlights a few case studies and discusses their related challenges along with their possible solutions.

Software Defined Radio (SDR) or Software Radio is one of the most important technologies for the modern wireless communication system. SDR is a radio which can tune to any frequency band, implement different modulation and demodulation schemes and different standards in the same device by using reconfigurable hardware and powerful software. SDR provides flexible, upgradeable, multi-standard and longer lifetime radio equipment for both the military and for civilian wireless communications infrastructure. This paper provides a detailed analysis of SDR hardware and its operation focusing on analog front end and digital front end. The paper also highlights the benefits of SDR. However, it was expected to implement SDR since the third generation of wireless communication but many practical challenges that SDR faces, causing SDR evolution slower. This paper also discusses some of the current issues impacting the SDR technology and investigates how they are being resolved.

“Age of Information” has emerged as an interesting metric in real-time wireless networks that captures the freshness of information in the underlying applications. This topic is motivated by the problem in which users of a network care about timely information defined as the “age” of the most recent status update a user has received. In the proposed work we have studied this concept in the context of an industrial wireless sensor-actuator network for cyber-physical production systems. Such a network with ever-changing dynamics requires continuous updates of the system states and ongoing tasks by exchanging the time critical, event-driven and/or time-driven information to maintain the stability of the system failing which may lead to shut down of the plant and other fatal consequences. Different real-time transmission scheduling algorithms manage how the channel resources are allocated each time, depending on the packet arrivals, to minimize the age of the information. However, unlike other real-time networks like broadcasting, sensor networks, etc. in cyber-physical systems, cyber and physical devices have different requirements to improve their quality of performance. Balancing between the performance criteria of both cyber and physical units seems to be a great challenge. In this work, minimization of staleness of the real-time updates by minimizing the age of information and their effect on network performance have been studied extensively for this purpose. Two greedy scheduling policies have been proposed. One for total age minimization and another one for stale age and jitter minimization. Their performances and complexity are compared with other existing algorithms. Moreover, the optimality of each of our proposed algorithms are proved analytically and claims are validated via simulation results too. Eventually, these results come to a conclusion that minimum age does not always guarantee the maximum freshness of information and satisfactory system performance at the same time.

“Age of Information” is an interesting metric that captures the freshness of information in the underlying applications. It is a combination of both packets inter-arrival time and packet transmission delay. In recent times, advanced real-time systems rely on this metric for delivering status updates as timely as possible. This paper aims to accomplish optimal transmission scheduling policy to maintain the information freshness of real-time updates in the industrial cyber-physical systems. Here, the coexistence of both cyber and physical units and their individual requirements to provide the quality of service is one of the critical challenges to handle. A greedy scheduling policy called Deadline-aware highest latency first has been proposed for this purpose. This paper also gives the analytical proof of its optimality, and finally, the claim is validated by comparing the performance of our algorithm with other scheduling policies by extensive simulations.

(2006). A case of recurrent lymphocytic hypophysitis in pregnancy. Journal of Obstetrics and Gynaecology: Vol. 26, No. 3, pp. 255-256.

Software Defined Radio (SDR) or Software Radio is one of the most important technologies for the modern wireless communication system. The vision of SDR is implementing a single radio that can emulate any radio signal of evolving or already existing wireless standards. It can be done simply by updating software without replacing the underlying hardware platform. Again, different air interface requires different sample rate for baseband processing. So, Sample Rate Conversion (SRC) is an important functionality of SDR. SRC includes both sample rate reduction or decimation and sample rate increase or interpolation. But in both the cases Comb Integrator Comb (CIC) filter plays an important role as anti-aliasing filter (in case of decimation) or anti-imaging filter (in case of interpolation). This paper describes the basic structure of CIC filter and illustrates important parameters to characterize this filter. Consequently it focuses on implementation of CIC filter in decimator and interpolator. This paper also tries to find a technique to improve the characteristics of this filter and point out some problems associated with it.