Julie A. McCann

A survey of autonomic computing—degrees, models, and applications

Autonomic Computing is a concept that brings together many fields of computing with the purpose of creating computing systems that self-manage. In its early days it was criticised as being a “hype topic” or a rebadging of some Multi Agent Systems work. In this survey, we hope to show that this was not indeed ‘hype’ and that, though it draws on much work already carried out by the Computer Science and Control communities, its innovation is strong and lies in its robust application to the specific self-management of computing systems. To this end, we first provide an introduction to the motivation and concepts of autonomic computing and describe some research that has been seen as seminal in influencing a large proportion of early work. Taking the components of an established reference model in turn, we discuss the works that have provided significant contributions to that area. We then look at larger scaled systems that compose autonomic systems illustrating the hierarchical nature of their architectures. Autonomicity is not a well defined subject and as such different systems adhere to different degrees of Autonomicity, therefore we cross-slice the body of work in terms of these degrees. From this we list the key applications of autonomic computing and discuss the research work that is missing and what we believe the community should be considering.

A survey on the ietf protocol suite for the internet of things: standards, challenges, and opportunities

Technologies to support the Internet of Things are becoming more important as the need to better understand our environments and make them smart increases. As a result it is predicted that intelligent devices and networks, such as WSNs, will not be isolated, but connected and integrated, composing computer networks. So far, the IP-based Internet is the largest network in the world; therefore, there are great strides to connect WSNs with the Internet. To this end, the IETF has developed a suite of protocols and open standards for accessing applications and services for wireless resource constrained networks. However, many open challenges remain, mostly due to the complex deployment characteristics of such systems and the stringent requirements imposed by various services wishing to make use of such complex systems. Thus, it becomes critically important to study how the current approaches to standardization in this area can be improved, and at the same time better understand the opportunities for the research community to contribute to the IoT field. To this end, this article presents an overview of current standards and research activities in both industry and academia.

Evaluation Issues in Autonomic Computing

Autonomic computing is a concept that brings togethermany fields of computing with the purpose of creating computing systems that are reflective and self-adaptive. In this paper we draw upon our experience of this field to discuss how we can attempt to evaluate autonomic systems. By looking at the diverse systems that describe themselves as autonomic, we provide an introduction to the concepts of autonomic computing and describe some achievements that have already been made. We then discuss this work in terms of what is necessary to evaluate and compare such systems. We conclude with a set of metrics, which we believe are useful to evaluate autonomicity.

Towards the design of an energy-efficient, location-aware routing protocol for mobile, ad-hoc sensor networks

Developments in wireless, mobile communications combined with advancements in electronics have contributed to the emergence of a new class of networks: wireless ad-hoc sensor networks. Tiny, smart, network-enabled sensing nodes can be deployed to construct sensor fields that form the infrastructure for various self-adaptive and autonomic applications. We identify the requirements and properties that still need to be addressed and discuss possible approaches that could be adopted in the design of efficient routing protocols for such networks.

Selfish Mules: Social Profit Maximization in Sparse Sensornets using Rationally-Selfish Human Relays

Future smart cities will require sensing on a scale hitherto unseen. Fixed infrastructures have limitations regarding sensor maintenance, placement and connectivity. Employing the ubiquity of mobile phones is one approach to overcoming some of these problems. Here, mobility and social patterns of phone owners can be exploited to optimize data forwarding efficiency. The question remains, how can we stimulate phone owners to serve as data relays? In this paper, we combine network science principles and Lyapunov optimization techniques, to maximize global social profit across this hybrid sensor and mobile phone network. Sensor data packets are produced and traded (transmitted) over a virtual economic network using a lightweight social-economic-aware backpressure algorithm, combining rate control, routing, and resource pricing. Phone owners can get benefits through relaying sensor data. Our algorithm is fully distributed and makes no probabilistic/stochastic assumptions regarding mobility, topology, and channel conditions, nor does it require prediction. The global social profit achieved by our algorithm can perform close to (or better than) an ideal algorithm with perfect prediction- proven by rigorous theoretical analysis. Simulation results further demonstrate that the proposed algorithm outperforms pure backpressure and social-aware schemes; highlighting the advantage of building systems combining communication with other types of networks.

UbiFlow: Mobility management in urban-scale software defined IoT

The growing of Internet of Things (IoT) devices has resulted in a number of urban-scale deployments of IoT multinetworks, where heterogeneous wireless communication solutions coexist. Managing the multinetworks for mobile IoT access is a key challenge. Software-defined networking (SDN) is emerging as a promising paradigm for quick configuration of network devices, but its application in multinetworks with frequent IoT access is not well studied. In this paper we present UbiFlow, the first software-defined IoT system for ubiquitous flow control and mobility management in multinetworks. UbiFlow adopts distributed controllers to divide urban-scale SDN into different geographic partitions. A distributed hashing based overlay structure is proposed to maintain network scalability and consistency. Based on this UbiFlow overlay structure, relevant issues pertaining to mobility management such as scalable control, fault tolerance, and load balancing have been carefully examined and studied. The UbiFlow controller differentiates flow scheduling based on the per-device requirement and whole-partition capability. Therefore, it can present a network status view and optimized selection of access points in multinetworks to satisfy IoT flow requests, while guaranteeing network performance in each partition. Simulation and realistic testbed experiments confirm that UbiFlow can successfully achieve scalable mobility management and robust flow scheduling in IoT multinetworks.

Distributed Real-Time Anomaly Detection in Networked Industrial Sensing Systems

Reliable real-time sensing plays a vital role in ensuring the reliability and safety of industrial cyber-physical systems (CPSs) such as wireless sensor and actuator networks. For many reasons, such as harsh industrial environments, fault-prone sensors, or malicious attacks, sensor readings may be abnormal or faulty. This could lead to serious system performance degradation or even catastrophic failure. Current anomaly detection approaches are either centralized and complicated or restricted due to strict assumptions, which are not suitable for practical large-scale networked industrial sensing systems (NISSs), where sensing devices are connected via digital communications, such as wireless sensor networks or smart grid systems. In this paper, we introduce a fully distributed general anomaly detection (GAD) scheme, which uses graph theory and exploits spatiotemporal correlations of physical processes to carry out real-time anomaly detection for general large-scale NISSs. We formally prove the scalability of our GAD approach and evaluate the performance of GAD for two industrial applications: building structure monitoring and smart grids. Extensive trace-driven simulations validate our theoretical analysis and demonstrate that our approach can significantly outperform state-of-the-art approaches in terms of detection accuracy and efficiency.

AutoHome: An Autonomic Management Framework for Pervasive Home Applications

This article introduces the design of the AutoHome service-oriented framework to simplify the development and runtime adaptive support of autonomic pervasive applications. To this end, we describe our novel open infrastructure for building and executing home applications. This includes the amalgamation of the two computing areas of autonomics and service orientation, to produce a component-based platform providing facilities including monitoring, touchpoints, and other common autonomic services. This infrastructure uniquely blends the advantages of distributed autonomic control with global conflict management in a management hierarchy. We discuss this platform in terms of pervasive home systems and show how one would develop such a system for two examples of automated home applications: intruder detection and medical support, respectively. Both applications were built within our framework and evaluated showing that the use of the framework introduces minimal overheads but provides many benefits. We then conclude by highlighting the contributions of AutoHome and a discussion about the lessons learned, limitations, and future research directions.

Distributed Networking in Autonomic Solar Powered Wireless Sensor Networks

Recent advances in solar harvesting technologies pave the way for sustainable environmental-monitoring applications in the emerging solar powered wireless sensor networks (SP-WSNs). The complexities associated with the low-resourced, highly-dynamic, and vulnerable sensor nodes operating in potentially unattended or hostile environments require a high degree of self-management and automation. Guided by autonomic communication principles, this paper presents AutoSP-WSN, a novel distributed framework to achieve sustainable data collection while also optimizing end-to-end network performance for SP-WSNs. Initially, we present the energy-aware support component that provides reliable energy monitoring and prediction. This drives the power management component, which is adaptive to time-varying solar power, avoiding battery exhaustion as well as maximizing the per-node utility. Finally, to demonstrate the key design issues of the network protocol component, we propose two self-adaptive network protocols, a routing protocol SP-BCP and a rate control scheme PEA-DLEX. We show that the individual components seamlessly highly integrate as a whole, and the AutoSP-WSN framework exhibits the properties of context-awareness, distributed operation, self-configuration, self-optimization, self-protection and self-healing. Through extensive experiments on a real SP-WSN platform, and hardware-driven simulations, we show that the proposed schemes achieve substantial improvements over previous work, in terms of reliability, sustainable operation, and network utility.

WaterBox: A Testbed for Monitoring and Controlling Smart Water Networks

Smart water distribution networks are a good example of a large scale Cyber-Physical System that requires monitoring for precise data analysis and network control. Due to the critical nature of water distribution, an extensive simulation of decision making and control algorithms are required before their deployment. Although some aspects of water network behaviour can be simulated in software such as hydraulic responses in valve changes, software simulators are unable to include dynamic events such as leakages or bursts in physical models. Furthermore, due to safety concerns, contemporary large-scale testbeds are limited to the monitoring processes or control methods with well established safety guarantees. Sophisticated algorithms for dynamic and optimal water network reconfiguration are not yet widespread. This paper presents a small-scale testbed, WaterBox, which allows the simulation of emerging/advanced monitoring and control algorithms in a fail-safe environment. The flexible hydraulic, hardware, and software infrastructure enables a substantial number of experiments. On-going experiments are related to in-node data processing and decision making, energy optimization, event-driven communication, and automatic control.