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

Autonomic Wireless Sensor Networks: A Systematic Literature Review

Autonomic computing (AC) is a promising approach to meet basic requirements in the design of wireless sensor networks (WSNs), and its principles can be applied to efficiently manage nodes operation and optimize network resources. Middleware for WSNs supports the implementation and basic operation of such networks. In this systematic literature review (SLR) we aim to provide an overview of existing WSN middleware systems that address autonomic properties. The main goal is to identify which development approaches of AC are used for designing WSN middleware system, which allow the self-management of WSN. Another goal is finding out which interactions and behavior can be automated in WSN components. We drew the following main conclusions from the SLR results: (i) the selected studies address WSN concerns according to the self-* properties of AC, namely, self-configuration, self-healing, self-optimization, and self-protection; (ii) the selected studies use different approaches for managing the dynamic behavior of middleware systems for WSN, such as policy-based reasoning, context-based reasoning, feedback control loops, mobile agents, model transformations, and code generation. Finally, we identified a lack of comprehensive system architecture designs that support the autonomy of sensor networking

GRIDKIT: Pluggable overlay networks for Grid computing

A `second generation' approach to the provision of Grid middleware is now emerging which is built on service-oriented architecture and web services standards and technologies. However, advanced Grid applications have significant demands that are not addressed by present-day web services platforms. As one prime example, current platforms do not support the rich diversity of communication `interaction types' that are demanded by advanced applications (e.g. publish-subscribe, media streaming, peer-to-peer interaction). In the paper we describe the Gridkit middleware which augments the basic service-oriented architecture to address this particular deficiency. We particularly focus on the communications infrastructure support required to support multiple interaction types in a unified, principled and extensible manner-which we present in terms of the novel concept of pluggable overlay networks

Towards epistemic autonomy in adaptive biomimetic middleware for cooperative sensornets

University of Technology, Sydney. Faculty of Engineering and Information Technology.The importance of studying biomimetic models of software infrastructure for sensornet systems lies in the fact that they are not entirely formal models and thus have to cover a range of issues of epistemic autonomy as well as linguistic and mental adaptation. This adaptation considers the context of software ability to reflect upon the verifiability and validity of its actions and measurements. This research elucidates and explores epistemological consequences of embodying biological autonomic patterns in software architectural models. Autonomy in software systems is a complex issue that raises many fundamental inquiries. The proposal is to initially concentrate on transformations of biological paradigms into epistemological queries and then adapt suitable biomimetic mechanisms into the development of software structure and ethology. Such methodology has proven to be very successful in the design of many engineering systems. The approach leads to a better understanding of the ontology of biomimetic patterns in software as well as a confirmation of requirements validity and design verifiability of autonomous software systems. In a dynamic, cooperative but often hostile environment, a software system infrastructure requires autonomic abilities to execute its normal operations, detect faults and perform necessary recovery actions without the need for external intervention. We approach this problem from the point of view of cognitive and mimetic systems research. The simplest way to make an autonomous and adaptive sensornet system is to include a hierarchy of layers in its middleware, not only to monitor activities of its components but to learn and adapt new behavioural patterns of these components in a changing environment. There are situations, however, where the components will not be able to adapt, learn new behaviour and evolve by themselves. For instance, these may not have yet encountered the new situation while others already have. A solution to this problem is to distribute the new behaviour to neighbouring elements via direct and indirect stigmergy mechanisms so that collaborating components can mutually improve their individual and team performance. The main objective is to disallow distribution of multiple versions of the software components and rather allow each software component to acquire and share with others, new “skills”. The components have to compare/verify these new behavioural patterns against their own set of beliefs, desires and intentions. In this thesis we intend to present simulations to test the learning capability of biomimetic algorithms, build a proof-of-concept middleware solution and demonstrate that such systems can not only adapt and evolve but they are robust and highly interoperable (co-operative). The thesis also assesses the suitability of various biomimetic design patterns and algorithms for building autonomic software infrastructure systems for cooperative networked agents

Policy-based management for body-sensor networks

Accepted versio