Over the past few years, the integration of mobile edge computing (MEC) and serverless computing, known as serverless MEC (SMEC), has garnered considerable attention. Despite abundant existing works on SMEC exploration, there remains an unaddressed gap in guaranteeing dependable application outputs due to ignoring the threat of both soft and bit errors on SMEC infrastructures. Furthermore, existing works fall short of accommodating the personalized requirements and approximate computation of Internet of Things (IoT) applications, thereby resulting in holistic quality-of-service (QoS) degradation of SMEC systems typically provisioned by limited edge resources. In this article, we investigate the reliability-aware personalized deployment of approximate computation IoT applications for QoS maximization in SMEC environments. To this end, we propose a hybrid methodology composed of offline and online optimization phases. At the offline phase, a decomposition-based function placement method is devised to accomplish function-to-server mapping by integrating convex optimization, cross-entropy method, and incremental control techniques. At the online phase, a lightweight reinforcement learning scheme based on proximal policy optimization (PPO) is developed to handle the inherent dynamicity of IoT applications. We also build a simulation platform upon the real-world base station distribution in Shanghai Telecom and the practical cluster trace in the Alibaba open program. Evaluations demonstrate that our hybrid approach boosts the holistic QoS by 63.9% compared with the state-of-the-art peer algorithms.

According to the World Health Organization (WHO), the population of people over 80 years of age is projected to triple by 2050, due to advances in quality of life, as well as continued progress in medicine and technology. With this context in mind, this article focuses on conducting a comprehensive study on conventional walkers, which represent a fundamental tool to improve the mobility of elderly people. The main objective of this study is to establish the foundations for the design of walkers, with the purpose of identifying the functional and end user requirements under the WalkIES project funded by IEEE’s Industrial Electronics Society (IES). In this initial phase, we seek to define the ergonomic design of a conventional walker, evaluating its advantages and disadvantages, in addition to establishing the standards that these devices must meet. Based on the results obtained, the specific characteristics of the WalkIES walker will be determined. Additionally, international manufacturing standards for walkers are examined and detailed, taking into account the specific features necessary to ensure the effectiveness and safety of these devices for elderly people. Special attention is paid to the individual characteristics of each component that makes up the walkers, with the aim of optimizing their functionality and comfort for the user. In summary, the study of walkers and the establishment of standards are essential to address the mobility needs of the elderly population and those who require assistance to walk, guaranteeing their safety, comfort, and quality of life, as well as to define the requirements of design and manufacturing for robotic walker WalkIES.

Cyber-physical systems (CPSs) have attracted increasing attention in recent years due to their promise for substantial and long-term benefits to society, economy, environment, and citizens. In addition, the rapid advances in computing, communication, and storage technologies have resulted in a revolution in the information communication technology domain and domination in the industry context. The utilization of CPSs in industrial settings has led to industrial cyber-physical systems (ICPSs), which, in conjunction with the information-driven interactions, enables large-scale cooperation in industrial facilities and among all the stakeholders of the value chain. Hence, the research on ICPSs is essential, especially with respect to the engineering of such systems for industrial applications. This article presents an overview of recent developments in ICPSs. We first introduce the architecture of ICPSs. Then, we review the developments of ICPSs in relevant research domains. Finally, this article concludes by presenting some potential future research directions on ICPSs.

This paper presents a cross-disciplinary view of industrial electronics for building a sustainable society. After explaining efforts and challenges from human factors, professional education, electronic systems on chip, technology ethics and society, and standards, we suggest a methodology for cross-disciplinary technology integrating the above-mentioned fields, in which the technical committees in Cluster 4, Industrial Electronics Society, play an active part.

In recent years, the investigations on cyber-physical systems (CPS) have become increasingly popular in both academia and industry. A primary obstruction against the booming deployment of CPS applications lies in how to process and manage large amounts of generated data for decision making. To tackle this predicament, researchers advocate the idea of coupling edge computing, or edge-cloud computing into the design of CPS. However, this coupling process raises a diversity of challenges to the quality-of-services (QoS) of CPS applications. In this article, we present a survey on edge computing or edge-cloud computing assisted CPS designs from the QoS optimization perspective. We first discuss critical challenges in service latency, energy consumption, security, privacy, and reliability during the integration of CPS with edge computing or edge-cloud computing. Afterwards, we give an overview on the state-of-the-art works tackling different challenges for QoS optimization, and present a systematic classification during outlining literature for highlighting their similarities and differences. We finally summarize the experiences learned from surveyed works and envision future research directions on edge computing or edge-cloud computing assisted CPS optimization.

This Special Section on ‘`Cloud-Edge Computing for Cyber-Physical Systems and Internet-of-Things’' is oriented to the dissemination of a few of those latest research and innovation results, covering many aspects of design, optimization, implementation, and evaluation of emerging cloud-edge solutions for CPS and IoT applications. The selected high-quality contributions cover a broad range of novel technologies and application scenarios in CPS and IoT. We hope that these accepted papers will produce long-lasting impacts, as well as stimulating and encouraging the international community to work on this exciting and impactful topic.

Global trends such as mass customization and lot size one, demand flexibility, autonomy and adaptability in production. Interoperability of devices is a key challenge as production systems evolve into Cyber-Physical Production Systems (CPPS). As part of the German strategic project Industrie 4.0 (I4.0), concepts and solutions for continuous digitization of production are being developed, in order to meet these numerous challenges. The concept of the Asset Administration Shell (AAS) was introduced in order to provide data and information in a standardized and semantically described manner, thus enabling interoperability and easy interaction. In this paper, we show how users can translate a semantic description of plants, machines or individual components that are based on a standardized Open Platform Communication Unified Architecture (OPC UA) information model, into the AAS information model.

A wide gap exists between the state of the art in developing Wireless Sensor Network (WSN) software and current practices concerning the design, execution, and maintenance of business processes. WSN software is most often developed based on low-level OS abstractions, whereas business process development leverages high-level languages and tools. This state of affairs places WSNs at the fringe of industry. The makeSense system addresses this problem by simplifying the integration of WSNs into business processes. Developers use BPMN models extended with WSN-specific constructs to specify the application behavior across both traditional business process execution environments and the WSN itself, which is to be equipped with application-specific software. We compile these models into a high-level intermediate language-also directly usable by WSN developers-and then into OS-specific deployment-ready binaries. Key to this process is the notion of meta-abstraction, which we define to capture fundamental patterns of interaction with and within the WSN. The concrete realization of meta-abstractions is application-specific; developers tailor the system configuration by selecting concrete abstractions out of the existing codebase or by providing their own. Our evaluation of makeSense shows that i) users perceive our approach as a significant advance over the state of the art, providing evidence of the increased developer productivity when using makeSense; ii) in large-scale simulations, our prototype exhibits an acceptable system overhead and good scaling properties, demonstrating the general applicability of makeSense; and, iii) our prototype-including the complete tool-chain and underlying system support-sustains a real-world deployment where estimates by domain specialists indicate the potential for drastic reductions in the total cost of ownership compared to wired and conventional WSN-based solutions.

The integration of industrial automation systems and software agents has been practiced for many years. However, such an integration is usually done by experts and there is no consistent way to assess these practices and to optimally select one for a specific system. Standards such as the ISO/IEC 25023 propose measures that could be used to obtain a quantification on the characteristics of such integration. In this work, the suitability of these characteristics and their proposed calculation for assessing the connection of industrial automation systems with software agents is discussed. Results show that although most of the measures are relevant for the integration of agents and industrial automation systems, some are not relevant in this context. Additionally, it was noticed that some measures, especially those of a more technical nature, were either very difficult to computed in the automation system integration, or did not provide sufficient guidance to identify a practice to be used.

Agent-based systems, an approach derived from distributed artificial intelligence, have been introduced for designing large complex systems. They are also suitable to solve challenging problems in industrial environments, being an appropriate technology for realizing cyber-physical systems. In such configuration, they need to interface with automation and control devices. However, until now there is no widely accepted practice nor pattern to interface the software agents with the automation functions. This work addresses this issue and introduces corresponding integration patterns in order to achieve full interoperability and reusability. This work, therefore, provides a methodology for mapping existing practices into a set of generic templates and also discusses the applicability of the proposed approach to different industrial application domains.

The increasing need for more adaptive production environments is a big motivator for the adoption of agentbased technologies in industrial systems, as they provide better mechanisms for handling dynamically and intelligently various kinds of production disturbances. Unlike with the utilization of most conventional automation languages, the use of agents enables, in an easy way, the setup of dynamic and autonomous adaptive processes to handle large and complex engineering system functions and interactions. Agent-technologies in cyberphysical systems contexts require at some point integration with automation controllers. However, most commonly available and used agent system implementations in the industry were not designed for hard real-time control use cases, and do not utilize real-time operating systems or dedicated hardware. Hence, they cannot match the hard-real-time performance of automation controllers. This work provides some insights on the performance that can be achieved with agent-based approaches that integrate with low-level automation system functions. It considers the performance of the agent-based practices in light of non-real-time dedicated hardware or operating systems. The results show that agents are well suited for the majority of soft-real-time control applications.

Employees are increasingly using electric vehicles (EVs) as their choice of company car. This means modern companies are becoming owners of EV fleets that need to charge on company premises. Without an effective charging strategy the cost of running an EV charging infrastructure for a large fleet of company EVs quickly becomes prohibitive. For this purpose, we investigate three different charging strategies: (i) a “naive” baseline strategy, (ii) intelligent charging (using an optimal schedule) and (iii) multi-location intelligent charging (i.e. allowing charging at home). Experimental results from simulations show how the selection of a charging strategy affects the number of adequately charged EVs as well as infrastructure utilization. Multi-location intelligent charging is the most effective strategy.

Agent-technologies have been used for higher-level decision making in addition to carrying out lower-level automation and control functions in industrial systems. Recent research has identified a number of architectural patterns for the use of agents in industrial automation systems but these practices vary in several ways, including how closely agents are coupled with physical systems and their control functions. Such practices may play a pivotal role in the Cyber-Physical System integration and interaction. Hence, there is a clear need for a common set of criteria for assessing available practices and identifying a bestfit practice for a given industrial use case. Unfortunately, no such common criteria exist currently. This work proposes an assessment criteria approach as well as a methodology to enable the use case based selection of a best practice for integrating agents and industrial systems. The software product quality model proposed by the ISO/IEC 25010 family of standards is used as starting point and is put in the industrial automation context. Subsequently, the proposed methodology is applied, and a survey of experts in the domain is carried out, in order to reveal some insights on the key characteristics of the subject matter.

The rapid advances in technology can be witnessed in the emergence of cyber-physical systems that pertain to several domains of our society. In transportation, we see the emergence of self-driving vehicles that utilize a multitude of sensors and intelligent learning techniques to navigate autonomously. Such vehicles are complex cyber-physical systems that are mobile and due to their sensor and intrinsic intelligence are able to collect, analyze, and capitalize upon an unprecedented amount of fine-grained data, as well as collaborate in real time with multiple stakeholders. Although such rich data can play a key role in data-driven economies of scale, this raises questions with respect to privacy- and integrity-dependent scenarios. In this work, the feasibility of ensuring integrity, and hence safety, while preserving privacy in the emerging hyperconnected vehicle scenarios is discussed. An exemplary case study on real-time vehicle interactions pertaining to map updates exemplifies the combination of privacy-enhancing technologies with integrity-protecting mechanisms.

At the dawn of the 4thindustrial revolution, the use of software agents, service-oriented architectures and related technologies as primary constructs of Cyber-Physical Industrial systems is of high relevance. Current developments in this area have been consistently supported by an active community of researchers and practitioners in the past decades. Most of the main actors in the area are members of the IEEE IES Technical Community on Industrial Agents (TCIA). This work analyzes the evolution of this research and development network. It does so by identifying and investigating specialized sub-communities within the larger umbrella of Industrial Agents, their research interests and directions. In total of 7430 documents from 8045 authors were collected from the Google Scholar profiles of the TCIA members. The analysis reveals different research trends, transitions over the years and the emergence of application and domain foci, that are critically discussed.

Industrial agent technologies have been integrated in key elements coupling industrial systems and software logic, which is an important issue in the design of cyber-physical systems. Although several efforts have been tried out over the last decades to integrate software agents with physical hardware devices, and some commonalities can be observed among the existing practices, there is no uniform way overall. This work presents an empirical survey of existing practices in three application area, namely factory automation, power & energy systems and building automation. It identifies pertaining common issues and discusses how they integrate low level automation functions by utilizing industrial agents. The surveyed practices reveal high diversity, customized traditional integration focusing mostly on I/O functions, without security, and an overall approach that is mostly coupled rather than embedded.

New Internet of Things open source technologies, middlewares, and programming languages, make the quick integration of devices, systems and cloud services easier than never before. With their utilization, complex tasks such as object detection, tracking and tracing, can be easily realized, even by embedded devices in a fraction of time. The interplay of highly heterogeneous IoT devices and open source software, has been utilized in this work as a learning tool, in order to train developers and enhance their IoT skills. By designing, implementing, testing and deploying a rapid prototype, new knowledge is acquired, assessment of technologies and concepts is carried out, and the end-result, although developed in a constraint timeframe, is technologically promising, cost-effective and feature-rich. This work sheds some light on the prototype implemented and discusses the developer experiences and benefits of this IoT integration hands-on approach.

Multiple software agent-based solutions have been developed during the last decades, and applied with varying success to different domains offering control, reconfiguration, diagnosis, monitoring, etc. However, the promise that they once posed in terms of a new alternative decentralized approach offering modularity, flexibility and robustness, is only partially fulfilled. This paper investigates some key factors, i.e., design, technology, intelligence/algorithms, standardization, hardware, challenges, application and cost, which are hypothesized to be linked to the Industrial Agent acceptance. Empirical data was acquired via a conducted survey, and statistically analyzed to investigate the support of the posed hypotheses. The results indicate that all the factors are seen important issues that play a role toward deciding for or against an industrial agent solution.

The manufacturing industry is facing a technology paradigm change, as also captured in the Industrie 4.0 vision as the fourth industrial revolution. Future smart industries will require to optimize not only their own manufacturing processes but also the use of products and manufacturing resources, their maintenance and their recycling. In this context the strengths and weaknesses of two key concepts, namely Cyber-Physical Systems (CPS) and Intelligent Product (IP) are discussed, and it is suggested that an integration of these two approaches to meet the introduced emergent requirements is beneficial. The integration of CPS and IP is shown via two real-world industrial cases, covering different phases of the product life-cycle, namely the production, use and maintenance phases.

The articles in this special issue present the latest developments and achievements in industrial cyber-physical systems (ICPSs). The papers in this issue cover key areas on architecture, design,enabling technologies, and applications of ICPSs. Additionally, they present emerging trends and visions of ICPSs for future investigations.

Future industrial systems can be realized using the cyber-physical systems (CPSs) that advocate the coexistence of cyber and physical counterparts in a network structure to perform the system's functions in a collaborative manner. Multiagent systems share common ground with CPSs and can empower them with a multitude of capabilities in their efforts to achieve complexity management, decentralization, intelligence, modularity, flexibility, robustness, adaptation, and responsiveness. This work surveys and analyzes the current state of the industrial application of agent technology in CPSs, and provides a vision on the way agents can effectively enable emerging CPS challenges.

Industrial automation systems have been established in various domain over the past decades exploiting standards, dedicated to network protocols, resource models, interfaces, programming languages etc. While systems increasingly get networked, the potential of their interactions and collaboration, especially in large-scale and complex settings, may unveil new business opportunities. A series of challenges have been systematically tackled the last years and demonstrated the feasibility of key parts. Among them, the IMC-AESOP has paved the way from web-service enabled systems to cloud-based industrial cyber-physical systems, and demonstrated with real industrial use cases various aspects with respect to next generation supervision control and data acquisition (SCADA) that may empower collaborative industrial systems. In this paper, a selected set of innovative results achieved within the IMC-AESOP project are summarized - migration strategies to the application of service based communication, system-wide introduction of Complex Event Processing capabilities, integration concepts between different generations of technologies and provision of cloud capabilities across different levels of production systems as well as experimentation in real industrial applications.

In the Smart Grid era fine-grained energy information pertaining real world processes can be collected and may reveal new insights if these can be analyzed in real-time. Energy “Big Data” analytics can lead to a plethora of new innovative applications and enhance decision making processes. However, to do so, we need new enterprise tools and approaches that can take into consideration the specifics of the energy domain and offer high performance analytics on its raw data. In this work, experiments are conducted to measure the performance of the different levels of energy data aggregation. Thousands of smart meters are aggregated, by usage of the collected energy readings from a real-world trial. Using a selected dataset, the traditional database system (row-based) performance is compared to the emerging column-based approach in order to assess the suitability for real-time analytics in such scenarios.

The emergence of the Smart Grid promises a new generation of innovative applications and services that are based on the fine-grained information acquired almost in “real-time” from the underlying infrastructure. To realize this vision, (open) platforms providing access to the smart meter data as well as potential management and value-added functionalities are needed. These will offer basic energy services that can be commonly used by application developers. We depict here our assessment from implementing and operating such a platform in a pilot that took place in Spain in 2012, and draw some lessons learned that affect their design and performance.

Significant effort is invested towards creating innovative applications for the emerging Smart Grid. However, many of these efforts use the old modus operandi of the energy domain providers i.e. offer of a monolithic application residing on proprietary or provider-only data, with little thought about cross-application collaboration and information exchange. However, the future of Smart Grid applications resides on sophisticated multi-channel applications that can rely on multi-source data and Internet provided basic services that can be easily customized for the specific end-user groups. Such a web application for monitoring and managing a Smart Grid neighborhood, where real-time energy monitoring, prediction and management of energy trading takes place, has been realized and piloted. We present here some of the key functionalities, as well as an assessment of the application and its design decisions.

The electric power grid is undergoing fundamental changes in light of the current focus on distributed generation, and in particular renewable generation (e.g., solar and wind). As a result, new methodologies and technologies are needed to effectively coordinate and make optimal use of the these resources. A distribution-system level energy market offers the potential to address this issue by providing an efficient mechanism for the pricing and allocation of resources. Market participants (e.g., households, ESCos, asset managers etc.) can apply economically driven strategies to trade energy while reacting to current and local levels of production and consumption. We evaluate here such a local neighborhood market and investigate its scalability under different numbers of participants and different penetrations photo-voltaic (PV) generation. The evaluation is carried out by simulating market operations under realistic production and consumption conditions. Results showed that the proposed market model scales well against both parameters.

The industrial adoption of wireless sensor networks (WSNs) is hampered by two main factors. First, there is a lack of integration of WSNs with business process modeling languages and back-ends. Second, programming WSNs is still challenging as it is mainly performed at the operating system level. To this end, we provide makeSense: a unified programming framework and a compilation chain that, from high-level business process specifications, generates code ready for deployment on WSN nodes.

The fusion of mechatronics, communication, control and information technologies has allowed the introduction of new automation paradigms into the production environment. The virtualization of the production environment facilitated by the application of the service-oriented architecture paradigm is one of major outcomes of that fusion. On one side, service-oriented automation works based on exposition, subscription and use of automation functions represented by e.g. web services. On the other side, the evolution of traditional industrial systems, particularly in the production area, as a response to architectural and behavioural (functional) viewpoints of the ISA95 enterprise architecture, where a close inter-relation between SCADA, DCS and MES systems facilitate the management and control of the production environment. Automation functions are increasingly performed by the composition and orchestration of services. Among other methods, the application of formal Petri net based orchestration approaches is being industrially established. This paper presents the major characteristics that such a Petri net based orchestration presents when it is developed, implemented and deployed in an industrial environment.

In a SOA-based system the applications are organized in a manner such that interoperable services can be used from different domains. In a process industry context, different domains can refer to, for example, process instrumentation and monitoring, execution of process control, data acquisition, etc. Large process industry systems are a complex and potentially very large sets of multi-disciplinary, heterogeneous, networked distributed systems. Current industrial process control systems are typically vendor specific; in addition the different domains are associated with different layers, different standards and different technologies. In the paper the authors report about the investigations and assessments performed to find answers for four major critical questions that arise as key when technologies have to be selected and used in a true Service Oriented Architecture (SOA) based distributed large scale Process Monitoring and Control system: (1) Real-time SOA (what are the limits of bringing SOA into high performance control loops?); (2) Management of large scale industrial distributed control systems (is it feasible to manage up to tens of thousands of service-oriented devices?); (3) Distributed event-based systems are asynchronous (what are the limits compared to traditional periodic scanning systems?) and (4) Service specification (which semantics are the most suitable for specifying process control and monitoring services?).

The last years we are witnessing of rapid advances in the industrial automation domain, mainly driven by business needs towards agility and supported by new disruptive technologies. Future factories will rely on multi-system interactions and collaborative cross-layer management and automation approaches. Such a factory, configured and managed from architectural and behavioural viewpoints, under the service-oriented architecture (SOA) paradigm is virtualized by services exposed by its key components (both HW and SW). One of the main results of this virtualization is that the factory is transformed into a “cloud of services”, where dynamic resource allocation and interactions take place. This paper presents a view on such architecture, its specification, the main motivation and considerations, as well as the preliminary services it may need to support.

The electricity network is undergoing a significant change towards a more adaptive, intelligent, self-managing, collaborative and information-driven grid. According to the smart grid vision, any electronic device connected to it will be able to communicate its consumed or produced energy almost in real time. Based on the analysis of this newly acquired information, a new generation of services and decision support systems can be realized, enabling more intelligent decisions, and ultimately a more efficient energy system. Therefore, high-performance acquisition of smart metering information from large scale distributed infrastructures is of key importance for the upcoming Internet-based enterprise services and mash-up applications. We have used open source software to build a web service-based advanced metering infrastructure of simulated smart meters, concentrators, and a smart metering platform, all interconnected via web services. We measure in a methodological fashion the performance of the various components of the architecture and evaluate their limitations. Finally we identify key performance indicators that need to be considered when deploying large-scale smart metering systems, and discuss on challenges and directions that arise.

The increasing usage of smart embedded devices in business blurs the line between the virtual and real worlds. This creates new opportunities to build applications that better integrate real-time state of the physical world, and hence, provides enterprise services that are highly dynamic, more diverse, and efficient. Service-Oriented Architecture (SOA) approaches traditionally used to couple functionality of heavyweight corporate IT systems, are becoming applicable to embedded real-world devices, i.e., objects of the physical world that feature embedded processing and communication. In such infrastructures, composed of large numbers of networked, resource-limited devices, the discovery of services and on-demand provisioning of missing functionality is a significant challenge. We propose a process and a suitable system architecture that enables developers and business process designers to dynamically query, select, and use running instances of real-world services (i.e., services running on physical devices) or even deploy new ones on-demand, all in the context of composite, real-world business applications.

The increasing usage of smart embedded devices is blurring the line between the virtual and real worlds. This creates new opportunities for applications to better integrate the real-world, providing services that are more diverse, highly dynamic and efficient. Service Oriented Architecture is on the verge of extending its applicability from the standard, corporate IT domain to the real-world devices. In such infrastructures, composed of a large number of resource-limited devices, the discovery of services and on demand provisioning of missing functionality is a challenge. This work proposes a process, its architecture and an implementation that enables developers and process designers to dynamically discover, use, and create running instances of real-world services in composite applications.

Advances in the areas of embedded systems, computing, and networking are leading to an infrastructure composed of millions of heterogeneous devices. These devices will not simply convey information but process it in transit, connect peer to peer, and form advanced collaborations. This ``Internet of Things'' infrastructure will be strongly integrated with the environment, and its integration with the enterprise systems will not only further blur the line between business IT systems and the real world, but will change the way we design, deploy, and use services. New opportunities can emerge for businesses, which can now closely collaborate with the real world. The work presented here proposes an architecture for an effective integration of the Internet of Things in enterprise services.

Up to now, most factories and their processes were designed and constructed with the cost as the most important economic factor. However due to the increased changes in energy sector, the energy optimization should be another key indicator for cross layer optimization. In order to achieve this optimization, energy has to be measured locally and almost in real time, while manufacturing control activities should also be aware of the energy consumed. Furthermore higher-residing decision support systems and enterprise services, will take also into consideration the overall energy consumption, for each process and optimize globally and locally. These goals are assisted with the increasing automation within the factories that can provide better visibility and efficiency of the shop floor.

A revolution in utilities domain is underway, namely the Internet of Energy. Networked Embedded Devices (NEDs) are making the electricity grid itself, the homes and the factories smarter, increasing the possibilities of collaboration among them. It is expected that NEDs will offer their functionality as one or more services, one of which will be a real-time measurement of the energy they consume or produce. In such highly distributed heterogeneous infrastructures it is clear that the metering goes beyond the classical understanding; it is becoming ubiquitous, distributed and will be the core for future value added services. Modeling such dynamic event-based systems is a challenging approach. We focus our work on simulating large scale infrastructures where multiple web-service enabled devices offer metering data on an event based mode and provide some metrics for evaluating them.

Modern enterprises operate on a global scale and depend on complex business processes. Business continuity needs to be guaranteed, while changes at the shop floor should happen on-the-fly without stopping the production process. Unfortunately, the existing business processes found in most enterprises are not modular enough, nor they have dynamic support from the device level. However, as the number of sophisticated networked embedded devices in the shop-floor increases, SOA concepts can now be pushed down and provide a better collaboration between the business systems and the production line. This leads to highly dynamic systems that can adapt and optimize their behavior to achieve their goals. The work presented here shows directions to achieve this dynamism by means of simulation, state identification and close coupling of real world and business systems.

It is expected that future shop-floors will be populated by thousands of networked embedded devices. Those will not only communicate using IP (as in TCP/IP), but also feature some autonomy, allowing them to collaborate among themselves and with enterprise systems. As they can offer both their mechatronic and higher-level functions as a service and support dynamic deployment of new code, they can execute business logic locally, allowing for new classes of business processes that are executed collaboratively by back-end and embedded systems. While some parts of a process will still be executed in the data centre, the rest will execute directly on embedded devices on the shop-floor. Business Process execution will therefore be more dynamic and context-based.We introduce an approach to manage efficient business process execution over such highly dynamic infrastructures.

A common practice in enterprise environments is the usage of Service Oriented Architectures (SOA) which implies heavy usage of web services. Lately the trend is to extend these approaches down to the embedded device layer i.e. have devices running web services natively and offer their functionality as a service. The Internet of Things (IoT) envisions millions of such heterogeneous, usually mobile, devices communicating with each other creating a very dynamic infrastructure. In this paper we concentrate on our efforts to use a multi-agent system to simulate this emerging dynamic infrastructure populated with large number of web-service enabled devices.

Responding to the dynamic requirements of the changing market and optimising costs are two challenges faced by corporate manufacturing plants globally. In order to be agile, modern manufacturing plants employ optimized supply chain mechanisms to reduce the response time of the market needs. However bringing changes to the shop floor after a production is planned is costly. In this paper we demonstrate how Service Oriented Architecture (SOA) driven approaches offer the flexibility to adapt manufacturing plants based on a dynamic production plan in close cooperation with a backend system. The methods discussed were deployed on a prototype test rig and integrated with SAP ERP. The results introduce dynamic behaviour of the production plan by adapting to the changing nature of the shop floor, and at the same time, providing the real time status of the machines to the enterprise services which optimize further the production plan dynamically.

Enterprise applications support business activities in companies, so that they can manage complexity and be more effective. The service oriented architecture (SOA) concepts empower modern enterprises and provide them with flexibility and agility. These concepts nowadays expand towards the shop-floor activities, down to the device level. By implementing web services on the devices natively, we are able to push down at item level SOA concepts. In this work we focus on implementing web services on the SunSPOT wireless sensor nodes and coupling it with enterprise level services. The presented methods could be used as experimental platform to evaluate new SOA-based paradigm for factory automation and enterprise computing. The goal is to seamlessly integrate heterogeneous hardware on the shop floor and the business intelligence via the SOA approach.

Today manufacturers require efficient reaction to critical events occurring at the shop floor. Therefore, device-level data needs to be integrated into business processes in a standardized and flexible way to avoid time-consuming media breaks. Current approaches are characterized by a late indication of changes in the production environment and a delayed implementation of changed production plans. As a solution, we propose a web service-based integration of enterprise systems with shop-floor activities, using SOA-ready networked embedded devices. We examine the requirements for the integration and derive an appropriate architecture that tries to close the integration gap. The timely provision of data, the impact of device-level information on business processes, as well as the direct bidirectional communication with device-level services promotes the vision of adaptive manufacturing and leads to reduced production costs.

It has been more than a decade since the introduction of programmability in the network elements as the basis for providing rapid deployment and customization of new services across heterogeneous networks. Different fields, research initiatives and fora at different or same points in time have attempted in their own way to give their definition of programmability and how it should be realized to facilitate service deployment. Although these efforts seem, from the outset, as antagonistic to each other, and most of the time heavily dependent on the underlying networking technology, strong evidence points toward common features, that when put together, as pieces of a puzzle, give rise to a common picture which, we believe, is representative of the term "programmable networks." In this paper, we are going to bring out and elaborate on a number of such features, arguing are they are the ingredients that serve as building materials and principles to the next generation network element architecture enabled to realize the yet elusive rapid service deployment. Our analysis will draw from the state of the art and our experiences in working in the future active IP network (FAIN) project. As a result, we will take advantage of these observations and propose a new protocol that allows a programmable network to be configured in such a way that new functionality may be requested and installed, thus, extending the capabilities and the services offered by the network.

A variety of detailed technologies, concepts, and models aim at the realization of intelligent integrated networks and services. Active and programmable networking enable the introduction of new network services by adding dynamic programmability to network devices and making aspects of the programmability accessible to third-party vendors and users via open interfaces. Open and programmable network elements help redefine network software architectures and move control and management systems away from traditional closed and rigid solutions, bringing us one step closer to an environment where all devices and services seamlessly interoperate and cooperate with each other. Computational intelligence (CI) has emerged through a vivid and diversified synergy of technologies of granular computing, neural networks, and evolutionary computing. Each of the contributing technologies there plays an important and unique role. In essence, we can state that CI is a manifestation and implementation of a general design methodology applied to complex systems. The article reviews this special issue.

In recent years, we have witnessed a rapidly growing role of the Internet that has already formed a conceptual backbone of the society in the information era. What becomes apparent and highly visible is a broad range of services and their enormous diversity being seamlessly available to those surfing cyberspace. The ongoing developments not only have enabled a different way of doing business but also pushed toward ambient intelligence where the user fully interacts with his or her surrounding information environment. The three special issues bring together the ideas of CI to the network area in a systematic, coherent, and comprehensive fashion that will help us move one step closer to the realization of the vision of ambient intelligence.

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Denial of service (DoS) attacks is a well-known problem with victims even among prestigious commercial sites. Such attacks in traditional networking are difficult to recognize and to handle. An active infrastructure that can dynamically respond to event-triggered requests can deal better with recognition and handling of DoS attacks. We present a DoS attack response system architecture and we demonstrate via an application scenario its dynamicity and flexibility in dealing with this kind of attack. The approach is based on agent-enabled active programmable infrastructures and makes heavy use of mobile agent technology in order to asynchronously respond to critical situations. Finally, we comment on the pros and cons of our approach and discuss future directions that could be followed.