A Comprehensive Zero-Copy Architecture for High Performance Distributed Data Acquisition Over Advanced Network Technologies for the CMS Experiment

Embarrassingly parallel Grid applications require no inter-worker interaction. Thus, the underlying communication infrastructure is based on the simple but well understood client/server execution model. This is no longer sufficient if more demanding parallel applications that require true Peer-to-Peer interaction are to be deployed on Grids. In this paper, we propose the industrial-strength eXtensible Messaging and Presence Protocol (XMPP) as a network substrate for these non-trivial Peer-to-Peer Grid Computing applications.

One way to achieve reliability with low-latency is through multi-path routing and transport protocols that build redundant delivery channels (or data paths) to reduce end-to-end packet losses and retransmissions. However, the applicability and effectiveness of such protocols are limited by the topological constraints of the underlying communication infrastructure. Multiple data delivery paths can only be constructed over networks that are capable of supporting multiple paths. In mission-critical wireless networks, the underlying network topology is directly affected by the terrain, location and environmental interferences, however the settings of the wireless radios at each node can be properly configured to compensate for these effects for multi-path support. In this work we investigate optimization models for topology designs that enable end-to-end dual-path support on a distributed wireless sensor network. We consider the case of a fixed sensor network with isotropic antennas, where the control variable for topology management is the transmission power on network nodes. For optimization modeling, the network metrics of relevance are coverage, robustness and power utilization. The optimization models proposed in this work eliminate some of the typical assumptions made in the pertinent network design literature that are too strong in this application context.

Recent developments in virtualization and communication technologies have transformed the way data centers are designed and operated by providing new tools for better sharing and control of data center resources. In particular, Virtual Machine (VM) migration is a powerful management technique that gives data center operators the ability to adapt the placement of VMs in order to better satisfy performance objectives, improve resource utilization and communication locality, mitigate performance hotspots, achieve fault tolerance, reduce energy consumption, and facilitate system maintenance activities. Despite these potential benefits, VM migration also poses new requirements on the design of the underlying communication infrastructure, such as addressing and bandwidth requirements to support VM mobility. Furthermore, devising efficient VM migration schemes is also a challenging problem, as it not only requires weighing the benefits of VM migration, but also considering migration costs, including communication cost, service disruption, and management overhead. This chapter provides an overview of VM migration benefits and techniques and discusses its related research challenges in data center environments. Specifically, the authors first provide an overview of VM migration technologies used in production environments as well as the necessary virtualization and communication technologies designed to support VM migration. Second, they describe usage scenarios of VM migration, highlighting its benefits as well as incurred costs. Next, the authors provide a literature survey of representative migration-based resource management schemes. Finally, they outline some of the key research directions pertaining to VM migration and draw conclusions.

Nowadays, the increasing penetration of renewable energies often leads to system frequency variation due to the intermittent outputs, which limits the utilization of renewable electricity and brings higher requirements to frequency regulation. Aggregated electric vehicles (EVs) are suggested to be used as good regulation resources because of the vehicle-to-grid (V2G) capability and quick response characteristic. However, the participation of EVs inevitably leads to cyber delays due to their underlying communication infrastructure and scheduling, which may cause instability. To guarantee the system stability, this paper investigates the stability of a grid frequency regulation system with electric vehicle (EV) aggregators embedded by cyber delays in the cyber system. A comprehensive stability assessment method is proposed in this paper based on the discrete spectrum iteration. A stability assessment method flow is designed with only five stages: 1) system initialization and modeling; 2) spectrum transformation; 3) Chebyshev discretization; 4) Krylov subspace projection dimension reduction; 5) Newton correction. Comprehensive case studies are performed on the cyber regulation systems with single, double, and three EV aggregators to extract the stability region and to validate the proposed approach. It is revealed that the controller gain, the ratio between the participation ratios of each aggregator, and that between EV and grid are important factors for determining the stability of the regulation system at a given controller gain. Besides, the criterion of the stability region changing with the three factors is proposed. It is found that the mass utilization of electric vehicles in the frequency control disrupts system stability due to the aggregation delay and thus the stability region can be divided into several intervals and presents periodicity. It is expected that the proposed criteria can help to guide the determination of delay requirements for EV aggregators participating in frequency regulation service.

The emerging area of (smart) Cyber Physical Systems (sCPS) triggers demand for new methods of design, development, and deployment of architecturally dynamic distributed systems. Current approaches (e.g. Component-Based Software Engineering and Agent-Based Development) become insufficient since they fail in addressing challenges specific to sCPS such as mobility, heterogeneous and unreliable deployment infrastructure, and architectural dynamicity. The strong dependence on the underlying communication infrastructure, often combining ad-hoc established links typical for wireless connectivity with more reliable connections of infrastructural networks, requires a novel method to optimize system deployment. In this paper we propose such a method based on the domain knowledge elicited from design level specification. As a proof of concept, we have provided an extension to the DEECo (Dependable Emergent Ensembles of Components) model and validated it on a scenario from the domain of Vehicular Area Networks.

Many application scenarios envisioned as part of the ‘Smarter’ Grid depend on an effective underlying communication infrastructure for power distribution. To this end, a linear chain wireless communication architecture is proposed in this work to meet communication requirements at the distribution level of the power grid. A theoretical study is done to understand the capacity limitations of using such linear chain wireless technologies at the distribution level. The application of advanced metering infrastructure (AMI) that encourages customer participation in energy delivery is used as a case study to understand the implications of any limitations imposed by the proposed communication architecture.

Systems deployed in mobile environments are typically characterized by intermittent connectivity and asynchronous sending/reception of data. To create effective mobile systems for such environments, it is essential to guarantee acceptable levels of timeliness between sending and receiving mobile users. In order to provide QoS guarantees in different application scenarios and contexts, it is necessary to model the system performance by incorporating the intermittent connectivity. Queueing Network Models (QNMs) offer a simple modeling environment, which can be used to represent various application scenarios, and provide accurate analytical solutions for performance metrics, such as system response time. In this paper, we provide an analytical solution regarding the end-to-end response time between users sending and receiving data by modeling the intermittent connectivity of mobile users with QNMs. We utilize the publish/subscribe (pub/sub) middleware as the underlying communication infrastructure for mobile users. To represent the user's connections/disconnections, we model and solve analytically an ON/OFF queueing system by applying a mean value approach. Finally, we validate our model using simulations with real-world workload traces. The deviations between the performance results foreseen by the analytical model and the ones provided by the simulator are shown to be less than 5% for a variety of scenarios.

Virtualization and energy management optimization of high speed computer network data centers based on optical switching and network technology

Building large resilient and computer systems can be challenging, especially when temporal predictability is also required. Large resilient systems are typically composed of different networking technologies, for example, using different wired and wireless communication technologies. Building such systems with safety-relevant services demands appropriate system interfaces and algorithmic concepts. In this talk we present some design patterns that are useful to build such large resilient and predictable systems. Often, the underlying communication medium does not provide the reliability and real-time properties that are needed for a concrete application. In such a case the presented design patterns can be implemented as a communication layer on top of the underlying communication system. We discuss design patterns for interaction autonomy, system communication and reliability.

Recent advancements in hardware and networking technologies have resulted in a large growth in the number of Internet of Things (IoT) devices connected to the Internet, which is likely to continue growing in the coming years. Traditional security solutions are insufficiently suited to the IoT context due to the restrictions and diversity of the resources available to objects. Security techniques such as intrusion detection and authentication are considered to be effective. Additionally, the decentralised and distributed nature of Blockchain technology makes it an excellent solution for overcoming the security issue. This paper proposes a chaotic bird swarm algorithm (CBSA)-based clustering technique based on an optimum deep belief network (ODBN) and Blockchain technology for secure authentication in an IoT setting. The CBSA-ODBN technique creates a clustering algorithm that utilises CBSA to pick cluster heads (CHs). The ODBN model is then utilised to identify the network, and the learning rate of the Deep Belief Network (DBN) model is optimally adjusted using the flower pollination technique (FPA). The suggested concept creates a layered security network paradigm for the Internet of Things using blockchain technology. Numerous simulations are run, with the outcomes analysed using a variety of measures, including detection rate, packet delivery ratio, energy usage, end-to-end latency, and processing cost. A careful comparison of the suggested model's performance to recently developed methodologies demonstrated the proposed model's superior performance.

E-organisations are expected to be one of the promising organisational forms in this Internet cultural era (ICE). E-organisations are different from traditional organisations; and most traditional organisations are evolving towards becoming e-organisations. These are organisations established and operated, based on the Internet and other related technologies in an environment referred to as Internet culture—whereby organisations will be placing the Internet at the centre of their business and encouraging ubiquitous use of networked technologies. This paper incorporates several perspectives to examine how small- and medium-sized enterprises (SMEs) use the network technologies and information and communication technology (ICT) in their current business environment. Through a literature review and interviews, we analyse the various options for managing the transformation, and its effects, to ascertain the appropriate strategies within a range of SMEs. The results of this study reveal that the SMEs’ journey towards becoming e-organisations can be classified into three stages: 1/2-fusion, fusion and the ultimate e-organisation stage. Based on this work, strategic solutions are proposed for future SMEs intending to adopt Internet and other network technologies.

With the advances in networking technologies, robots can use the almost unlimited resources of large data centers, overcoming the severe limitations imposed by onboard resources: this is the vision of Cloud Robotics. In this context, we present DewROS, a framework based on the Robot Operating System (ROS) which embodies the three-layer, Dew-Robotics architecture, where computation and storage can be distributed among the robot, the network devices close to it, and the Cloud. After presenting the design and implementation of DewROS, we show its application in a real use-case called SHERPA, which foresees a mixed ground and aerial robotic platform for search and rescue in an alpine environment. We used DewROS to analyze the video acquired by the drones in the Cloud and quickly spot signs of human beings in danger. We perform a wide experimental evaluation using different network technologies and Cloud services from Google and Amazon. We evaluated the impact of several variables on the performance of the system. Our results show that, for example, the video length has a minimal impact on the response time with respect to the video size. In addition, we show that the response time depends on the Round Trip Time (RTT) of the network connection when the video is already loaded into the Cloud provider side. Finally, we present a model of the annotation time that considers the RTT of the connection used to reach the Cloud, discussing results and insights into how to improve current Cloud Robotics applications.

The vision of Industry 4.0, otherwise known as the fourth industrial revolution, is the integration of massively deployed smart computing and network technologies in industrial production and manufacturing settings for the purposes of automation, reliability, and control, implicating the development of an Industrial Internet of Things (I-IoT). Specifically, I-IoT is devoted to adopting the Internet of Things (IoT) to enable the interconnection of anything, anywhere, and at anytime in the manufacturing system context to improve the productivity, efficiency, safety and intelligence. As an emerging technology, I-IoT has distinct properties and requirements that distinguish it from consumer IoT, including the unique types of smart devices incorporated, network technologies and quality of service requirements, and strict needs of command and control. To more clearly understand the complexities of I-IoT and its distinct needs, and to present a unified assessment of the technology from a systems perspective, in this paper we comprehensively survey the body of existing research on I-IoT. Particularly, we first present the I-IoT architecture, I-IoT applications (i.e., factory automation (FA) and process automation (PA)) and their characteristics. We then consider existing research efforts from the three key systems aspects of control, networking and computing. Regarding control, we first categorize industrial control systems and then present recent and relevant research efforts. Next, considering networking, we propose a three-dimensional framework to explore the existing research space, and investigate the adoption of some representative networking technologies, including 5G, machine-to-machine (M2M) communication, and software defined networking (SDN). Similarly, concerning computing, we again propose a second three-dimensional framework that explores the problem space of computing in I-IoT, and investigate the cloud, edge, and hybrid cloud and edge computing platforms. Finally, we outline particular challenges and future research needs in control, networking, and computing systems, as well as for the adoption of machine learning, in an I-IoT context.

Many advances have been done to allow groups of people to work together and collaborate in the Internet. Collaborative systems are characterized by the way participants interact. In many cases, equal standing members should cooperate in a non-authoritative environment, where no entity or authority is or should be in charge of regulating the group. Therefore, decentralized communication infrastructures have been hailed as promising alternatives. Recently, decentralized infrastructures based on P2P approaches have drawn the attention of the research community because of their benefits in terms of scalability, robustness, availability and potentials for leveraging computational resources distributed across the Internet. In this paper, a scalable peer-to-peer (P2P) communication Infrastructure for groupware applications is presented. It enables a large number of people to join and cooperate in a robust, decentralized and easy deployable way, without requiring high capacity servers or any other special network infrastructure. The communication infrastructure is based on a binary tree as overlay structure, which implements all groupware communication functionality, including membership management and packet forwarding, at application level, making it an inexpensive and fast deployable solution for equal standing members, such as home users with a domestic connection to the Internet. Two applications, one for synchronous groupware and the other for asynchronous collaboration, have been developed to validate the approach. Comparisons with other communication infrastructures in aspects such as end-to-end propagation delay, group latency, throughput, protocol overhead, failure recovery and link stress, show that our approach is a scalable and robust alternative.

Future computer environments will include mobile computers which will either be disconnected, weakly interconnected by low-speed wireless networks such as GSM (global system for mobile communications), or fully interconnected by high-speed networks ranging from Ethernet to ATM (asynchronous transfer mode). While the transition between networks is currently a heavyweight operation, we believe that developments in network interface technology will soon enable mobile computers to dynamically select their network service based on cost and performance requirements. Such flexibility, coupled with the inherent unreliability of mobile communications, means that system services and applications will be subject to rapid and massive fluctuations in the quality-of-service provided by their underlying communications infrastructure. In this paper, we discuss the design of a distributed systems platform to support the development of services which are able to tolerate this environment by dynamically adapting to changes in the available communications quality-of-service.