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Electric drives are used to control electric motors, which are pervasive in industrial applications. In this paper we propose enhancing the electric drives to fulfil the role of fog nodes within a Fog Computing Platform (FCP). Fog Computing is envisioned as a realization of future distributed architectures in Industry 4.0. We identify the system-level requirements of such an FCP, including requirements that are extracted from the current architecture of drives, which we consider as a baseline. These requirements are then used to design a system-level architecture, which we model using the Architecture Analysis & Design Language (AADL). We identify the "technology bricks" (components such as hardware, software, middleware, services, methods and tools) needed to implement the FCP. The proposed fog-based architecture is then used to implement a Conveyor Belt industrial use case. We evaluate the resulting use case on several aspects, demonstrating the usefulness of the proposed fog-based approach. By developing the electric drives as fog nodes, that we call fogification, new offerings like programmability, analytics and connectivity to customer Clouds are expected to increase the added value. Increased flexibility allows drives to assume a larger role in industrial and domestic control systems, instrumenting thus also legacy systems by using drives as the data source.

Time sensitive networking (TSN) is gaining attention in industrial automation networks since it brings essential real-time capabilities to the Ethernet layer. Safety-critical realtime applications based on TSN require both timeliness as well as fault-tolerance guarantees. The TSN standard 802.1CB introduces seamless redundancy mechanisms for time-sensitive data whereby each data frame is sequenced and duplicated across a redundant link to prevent single points of failure (most commonly, link failures). However, a major shortcoming of 802.1CB is the lack of fault detection mechanisms which can result in unnecessary replications even under good link conditions - clearly inefficient in terms of bandwidth use. This paper proposes a machine learning-based intelligent configuration synthesis mechanism that enhances bandwidth utilization by replicating frames only when a link has a higher propensity for failure.

Current industrial automation applications particularly within the smart manufacturing domain require mobility, flexibility of deployment, and scalability. In addition to these, it is important to mitigate the risk of safety hazards. In this paper we discuss a flexible, granular, and software-based system design that aims to improve both security and safety of an autonomous mobile robot (AMR) based industrial automation systems. The decentralised control architecture ensures that safety-critical functions are distributed throughout the network. To this end, we first define system-level safety requirements and identify procedures required to satisfy safety-critical functions such as emergency-stop (E-Stop). We then explain the benefits provided by the proposed system architecture vis-a-vis its resilience towards potential safety hazards.

Low latency and on demand resource availability enable fog computing to host industrial applications in a cloud like manner. One industrial domain which stands to benefit from the advantages of fog computing is robotics. However, the challenges in developing and implementing a fog-based robotic system are manifold. To illustrate this, in this paper we discuss a system involving robots and robot cells at a factory level, and then highlight the main building blocks necessary for achieving such functionality in a fog-based system. Further, we elaborate on the challenges in implementing such an architecture, with emphasis on resource virtualization, memory interference management, real-time communication and the system scalability, dependability and safety. We then discuss the challenges from a system perspective where all these aspects are interrelated.

The Fog computing paradigm employing multiple technologies is expected to play a key role in a multitude of industrial applications by fulfilling futuristic requirements such as flexible and enhanced computing, storage, and networking capability closer to the field devices. While performance aspects of the Fog paradigm has been the central focus of researchers, safety aspects have not received enough attention so far. In this paper, we identify various safety challenges related to the Fog paradigm and provide specific safety design aspects as a step towards enhancing safety in industrial automation scenarios. We contextualize these ideas by invoking a distributed mobile robots use-case that can benefit from the use of the Fog paradigm.

©2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. Due to the fast growing of data consumed in mobile devices through cellular networks, solutions that provide higher data rates are an important target for the mobile networking community. One such solution is the aggregation of mobile technologies (most commonly LTE) with wireless LAN solutions (most commonly Wi-Fi). Seeing its potential impact, 3GPP has devised the LTE/Wi-Fi Aggregation (LWA) specification, which defines a tight coupling between eNBs and Wi-Fi Access Points (APs). In this paper, we implement and evaluate an LWA solution, and compare its performance to the one for full offloading (only Wi-Fi) and no offloading (only LTE) through physical experimentation. The developed prototype LWA solution is based on open source and commodity hardware, which promises a low-cost and easily implementable LWA solution. Aggregation and offloading process are managed by the eNB, therefore, the core network remains intact without any modification. Physical experiments are done to detail the network performances for all these three policies for TCP and UDP traffic and both for uplink and downlink connections. In TCP transmissions with LWA policy, the different delays between Wi-Fi and LTE links causes the performance degradation because of the out-of-order arrivals of the segments. For this, we evaluate a solution where an artificial delay is added to reduce the number of out-of-order packets.

The proliferation of mobile devices and the pervasiveness of wireless technology have provided a major impetus to replicate the network-based service discovery technologies in wireless and mobile networks. However, existing service discovery protocols and delivery mechanisms designed for traditional infrastructure-based networks fall short of accommodating the complexities of the ad hoc environment. Konark is a service discovery and delivery protocol designed specifically for ad hoc, peer-to-peer networks, and targeted toward device-independent services in general and m-commerce oriented software services in particular. It has two major aspects-service discovery and service delivery. For discovery, Konark uses a novel decentralized, peer-to-peer mechanism that provides each device the ability to advertise and discover services in an efficient way. The approach toward service description is XML-based. It includes a description template that allows services to be described in a human and software understandable forms. A micro-HTTP server present on each device handles service delivery, which is based on SOAP. Konark provides a framework for connecting isolated services offered by proximal pervasive devices over a wireless medium.

The proliferation of mobile devices and the pervasiveness of wireless technology have provided a major impetus to replicate the network-based service discovery technologies in wireless and mobile networks. However, existing service discovery protocols and delivery mechanisms fall short of accommodating the complexities of the ad-hoc environment. They also place emphasis on device capabilities as services rather than device independent software services, making them unsuitable for m-commerce oriented scenarios. Konark is a service discovery and delivery protocol designed specifically for ad-hoc, peer-to-peer networks, and targeted towards device independent services in particular. It has two major aspects - service discovery and service delivery. For discovery, Konark uses a completely distributed, peer-to-peer mechanism that provides each device the ability to advertise and discover services in the network. The approach towards service description is XML based. It includes a description template that allows services to be described in a human and software understandable forms. A micro-HTTP server present on each device handles service delivery, which is based on SOAP. Konark provides a framework for connecting isolated services offered by proximal pervasive devices over a wireless medium.