Software Defined Networks based Smart Grid Communication: A Comprehensive Survey

The current power grid is no longer a feasible solution due to ever-increasing user demand of electricity, old infrastructure, and reliability issues and thus require transformation to a better grid a.k.a., smart grid (SG). The key features that distinguish SG from the conventional electrical power grid are its capability to perform two-way communication, demand side management, and real time pricing. Despite all these advantages that SG will bring, there are certain issues which are specific to SG communication system. For instance, network management of current SG systems is complex, time consuming, and done manually. Moreover, SG communication (SGC) system is built on different vendor specific devices and protocols. Therefore, the current SG systems are not protocol independent, thus leading to interoperability issue. Software defined network (SDN) has been proposed to monitor and manage the communication networks globally. This article serves as a comprehensive survey on SDN-based SGC. In this article, we first discuss taxonomy of advantages of SDNbased SGC.We then discuss SDN-based SGC architectures, along with case studies. Our article provides an in-depth discussion on routing schemes for SDN-based SGC. We also provide detailed survey of security and privacy schemes applied to SDN-based SGC. We furthermore present challenges, open issues, and future research directions related to SDN-based SGC.Comment: Accepte

Communication and Cyber Security issues in Smart Grid

Smart Grid is an Information and Communication Technology (ICT) enabled Power grid. It is efficient, secure, reliable and self-healing power grid. Integration of micro grids, electric vehicles and other utilities make it more interesting. The deregulation of electricity sector has necessitated the use of many advanced software and embedded technologies to handle the size and complexity of power network. Smart grid needs to be supported by efficient and secure communication architecture design and implementation. At the same time it is necessary to ensure the security and privacy of data and information moving or stored in the smart grid system to have near 100% uptime of the power grid. This paper presents a comprehensive analysis of the various communication and cyber security issues involved with the successful operation of Smart Grid

Self-healing and SDN: bridging the gap

Achieving high programmability has become an essential aim of network research due to the ever-increasing internet traffic. Software-Defined Network (SDN) is an emerging architecture aimed to address this need. However, maintaining accurate knowledge of the network after a failure is one of the largest challenges in the SDN. Motivated by this reality, this paper focuses on the use of self-healing properties to boost the SDN robustness. This approach, unlike traditional schemes, is not based on proactively configuring multiple (and memory-intensive) backup paths in each switch or performing a reactive and time-consuming routing computation at the controller level. Instead, the control paths are quickly recovered by local switch actions and subsequently optimized by global controller knowledge. Obtained results show that the proposed approach recovers the control topology effectively in terms of time and message load over a wide range of generated networks. Consequently, scalability issues of traditional fault recovery strategies are avoided.Postprint (published version

An Embryonics Inspired Architecture for Resilient Decentralised Cloud Service Delivery

Data-driven artificial intelligence applications arising from Internet of Things technologies can have profound wide-reaching societal benefits at the cross-section of the cyber and physical domains. Usecases are expanding rapidly. For example, smart-homes and smart-buildings provide intelligent monitoring, resource optimisation, safety, and security for their inhabitants. Smart cities can manage transport, waste, energy, and crime on large scales. Whilst smart-manufacturing can autonomously produce goods through the self-management of factories and logistics. As these use-cases expand further, the requirement to ensure data is processed accurately and timely is ever crucial, as many of these applications are safety critical. Where loss off life and economic damage is a likely possibility in the event of system failure. While the typical service delivery paradigm, cloud computing, is strong due to operating upon economies of scale, their physical proximity to these applications creates network latency which is incompatible with these safety critical applications. To complicate matters further, the environments they operate in are becoming increasingly hostile. With resource-constrained and mobile wireless networking, commonplace. These issues drive the need for new service delivery architectures which operate closer to, or even upon, the network devices, sensors and actuators which compose these IoT applications at the network edge. These hostile and resource constrained environments require adaptation of traditional cloud service delivery models to these decentralised mobile and wireless environments. Such architectures need to provide persistent service delivery within the face of a variety of internal and external changes or: resilient decentralised cloud service delivery. While the current state of the art proposes numerous techniques to enhance the resilience of services in this manner, none provide an architecture which is capable of providing data processing services in a cloud manner which is inherently resilient. Adopting techniques from autonomic computing, whose characteristics are resilient by nature, this thesis presents a biologically-inspired platform modelled on embryonics. Embryonic systems have an ability to self-heal and self-organise whilst showing capacity to support decentralised data processing. An initial model for embryonics-inspired resilient decentralised cloud service delivery is derived according to both the decentralised cloud, and resilience requirements given for this work. Next, this model is simulated using cellular automata, which illustrate the embryonic concept’s ability to provide self-healing service delivery under varying system component loss. This highlights optimisation techniques, including: application complexity bounds, differentiation optimisation, self-healing aggression, and varying system starting conditions. All attributes of which can be adjusted to vary the resilience performance of the system depending upon different resource capabilities and environmental hostilities. Next, a proof-of-concept implementation is developed and validated which illustrates the efficacy of the solution. This proof-of-concept is evaluated on a larger scale where batches of tests highlighted the different performance criteria and constraints of the system. One key finding was the considerable quantity of redundant messages produced under successful scenarios which were helpful in terms of enabling resilience yet could increase network contention. Therefore balancing these attributes are important according to use-case. Finally, graph-based resilience algorithms were executed across all tests to understand the structural resilience of the system and whether this enabled suitable measurements or prediction of the application’s resilience. Interestingly this study highlighted that although the system was not considered to be structurally resilient, the applications were still being executed in the face of many continued component failures. This highlighted that the autonomic embryonic functionality developed was succeeding in executing applications resiliently. Illustrating that structural and application resilience do not necessarily coincide. Additionally, one graph metric, assortativity, was highlighted as being predictive of application resilience, although not structural resilience

Toward Biologically-Inspired Self-Healing, Resilient Architectures for Digital Instrumentation and Control Systems and Embedded Devices

Digital Instrumentation and Control (I&C) systems in safety-related applications of next generation industrial automation systems require high levels of resilience against different fault classes. One of the more essential concepts for achieving this goal is the notion of resilient and survivable digital I&C systems. In recent years, self-healing concepts based on biological physiology have received attention for the design of robust digital systems. However, many of these approaches have not been architected from the outset with safety in mind, nor have they been targeted for the automation community where a significant need exists. This dissertation presents a new self-healing digital I&C architecture called BioSymPLe, inspired from the way nature responds, defends and heals: the stem cells in the immune system of living organisms, the life cycle of the living cell, and the pathway from Deoxyribonucleic acid (DNA) to protein. The BioSymPLe architecture is integrating biological concepts, fault tolerance techniques, and operational schematics for the international standard IEC 61131-3 to facilitate adoption in the automation industry. BioSymPLe is organized into three hierarchical levels: the local function migration layer from the top side, the critical service layer in the middle, and the global function migration layer from the bottom side. The local layer is used to monitor the correct execution of functions at the cellular level and to activate healing mechanisms at the critical service level. The critical layer is allocating a group of functional B cells which represent the building block that executes the intended functionality of critical application based on the expression for DNA genetic codes stored inside each cell. The global layer uses a concept of embryonic stem cells by differentiating these type of cells to repair the faulty T cells and supervising all repair mechanisms. Finally, two industrial applications have been mapped on the proposed architecture, which are capable of tolerating a significant number of faults (transient, permanent, and hardware common cause failures CCFs) that can stem from environmental disturbances and we believe the nexus of its concepts can positively impact the next generation of critical systems in the automation industry