Ada Diaconescu

Holonic Institutions for Multi-scale Polycentric Self-governance

Effective institutions are key to the success of self-governing systems, yet specifying and maintaining them can be challenging, especially in large-scale, highly dynamic and competitive contexts. Political economist Elinor Ostrom has studied the conventional arrangements for sustainable natural resource management and derived from these eight design principles for self-governing institutions. One principle, nested enterprises, is straightforwardly expressed, but is arguably structural rather than functional, and so is more resistant to declarative specification; yet it also appears to be critical to the effectiveness of complex compositional systems. In this paper, we converge the ideas of holonic systems with electronic institutions, to propose a formalisation of this principle based on holonic institutions. We show how holonic institutions provide a structural framework for nested enterprises, which can be designed as composite systems of systems. This, we believe, is compatible with Ostroms ideas for polycentric governance of complex systems. We use a case study in energy distribution to illustrate these ideas.

A Generic Holonic Control Architecture for Heterogeneous Multiscale and Multiobjective Smart Microgrids

Designing the control infrastructure of future “smart” power grids is a challenging task. Future grids will integrate a wide variety of heterogeneous producers and consumers that are unpredictable and operate at various scales. Information and Communication Technology (ICT) solutions will have to control these in order to attain global objectives at the macrolevel, while also considering private interests at the microlevel. This article proposes a generic holonic architecture to help the development of ICT control systems that meet these requirements. We show how this architecture can integrate heterogeneous control designs, including state-of-the-art smart grid solutions. To illustrate the applicability and utility of this generic architecture, we exemplify its use via a concrete proof-of-concept implementation for a holonic controller, which integrates two types of control solutions and manages a multiscale, multiobjective grid simulator in several scenarios. We believe that the proposed contribution is essential for helping to understand, to reason about, and to develop the “smart” side of future power grids.

Towards a Service-Oriented Component Model for Autonomic Management

Modern applications are increasingly dynamic and heterogeneous and their lifecycle is more and more governed by autonomic managers that are also getting more and more complex. The purpose of this paper is to present a service-oriented framework that facilitates the development and management of dynamically extensible autonomic managers. More precisely, we propose an architecture based on the opportunistic collaboration of very specialized and coherent modules called administration tasks. The current framework prototype has been implemented as a specialized Service-Oriented Component Model. It allows the dynamic integration of autonomic tasks and their management based on contextual evolutions.

The Notion of Self-aware Computing

We define the notion of “self-aware computing” and the relationship of this term to related terms such as autonomic computing, self-management, and similar. The need for a new definition, driven by trends that are only partially addressed by existing areas of research, is motivated. The semantics of the provided definition are discussed in detail examining the selected wording and explaining its meaning to avoid misleading interpretations. This chapter also provides an overview of the existing usage of the term self-aware computing, respectively self-awareness, in related past projects and initiatives.

Structure and Governance of Communities for the Digital Society

It has been argued that the value of communities is that they can solve certain types of collective action problems which are resistant to purely market-based or policy-based solutions. Such problems increasingly arise in a data-driven information economy, the (so-called) sharing economy, and in economies of scarcity, where the added-value of information, reciprocity or other pro-social behaviour is indeterminate, and/or the qualitative nature of traded services is subjective and cannot simply be measured by kilowatts, tons, etc. It is therefore predicted that self-organised community systems will be of increasing importance as a mechanism for solving collective action problems in the digital society. Using community energy systems as an exemplar, this paper investigates the inter-weaving of (holonic) structure and (algorithmic) governance which are required to deliver air, sustainable and successful community-based solutions.

Autonomic management via dynamic combinations of reusable strategies

Autonomic Management capabilities become increasingly important for attaining functional and quality goals in software systems. Nonetheless, successful Autonomic Management solutions must feature complex, adaptive behaviors, which remain difficult to conceive and control. This paper proposes a generic approach and a reusable framework for the construction of Autonomic Manager applications. The presented solution advocates creating Autonomic Management behaviors via the dynamic and opportunistic integration of individual management strategies. The provided framework proposes a general architecture and a common infrastructure for supporting the presented approach. A sample Autonomic Manager was built using the framework with several management strategies and was successfully tested in an experimental scenario.

Goal-Oriented Holonics for Complex System (Self-)Integration: Concepts and Case Studies

System integration from sub-systems has always been a major engineering problem, which is progressively exacerbated by (1) sub-systems becoming more diverse, self-* and autonomous (2) systems operating in open environments, with third-party sub-systems joining and leaving unpredictably, (3) system (self-)integration being an ongoing process, increasingly needed at runtime. The fact that this problem occurs more and more often, as systems are built increasingly by composing existing sub-systems, requires rigorous, reusable integration solutions to replace ad-hoc approaches. In a complex world of uncertainty and change the new system integration paradigm must feature two main characteristics: support for a system-of-systems approach to manage complexity, and support for a high-level relation between sub-systems to manage diversity, uncertainty and dynamics. We propose a conceptual modelling solution combining holonic principles with goal-based relations. We highlight the key properties of holonic designs that support a systems-of-systems approach. We then specify the high-level relations between holonic sub-systems as goal-oriented requests and replies. Argumentation is grounded via concrete examples from existing complex systems. The proposed paradigm paves the way for future methodologies and tools for designing the next generation of socio-technical and cyber-physical systems.

Foraging-Inspired Self-Organisation for Terrain Exploration with Failure-Prone Agents

Mobile ad-hoc sensor systems are employed increasingly for distributed tasks in unreliable conditions, such as terrain exploration and measuring. Here, self-organising solutions can help ensure reliability, availability and scalability, while making use of unreliable components (or agents) with limited resources. These enable agents to act independently, and to exchange and combine their partial solutions into a (more) complete result, which can be transmitted to users before all agents fail. In previous work, we have studied how foraging-inspired self-organisation can help mobile agents achieve a collaborative task -- terrain exploration and information gathering. Obtained results revealed two key aspects impacting success rates: the strategy for exploring as much uncharted terrain as fast as possible, and the strategy for encountering the highest number of agents that hold complementary information. In this paper, we explore further techniques for these aspects and introduce passive pheromone evaporation. Our results show that a hybrid approach improving exploration efficiency features higher success rates than basic stigmergy models, random exploration and Lévy walks.

Creating Complex, Adaptable Management Strategies via the Opportunistic Integration of Decentralised Management Resources

The ambitious goals of autonomic management require complex, adaptable processing capabilities that prove extremely difficult to conceive and implement. This paper proposes a solution for the opportunistic integration of specialised autonomic management resources, so as to obtain complex, adaptable management strategies. The paper introduces an architecture that follows the proposed solution and provides a reusable framework that implements this architecture. The solutions validity is indicated by experimental results obtained by testing the framework prototype on a sample home security application.

Exploring Complex Networks with Failure-Prone Agents

Distributed data-collection and synchronization is essential in sensor networks and the Internet of Things (IoT), as well as for data-replication in server farms, clusters and clouds. Generally, such systems consist of a set of interconnected components, which cooperate and coordinate to achieve a collective task, while acting locally and being failure-prone. An important challenge is hence to define efficient and robust algorithms for data collection and synchronisation in large-scale, distributed and failure-prone platforms. This paper studies the performance and robustness of different multi-agent algorithms in complex networks with different topologies (Lattice, Small-world, Community and Scale-free) and different agent failure rates. Agents proceed from random locations and explore the network to collect local data hosted in each node. Their exploration algorithm determines how fast they cover unexplored nodes to collect new data, and how often they meet other agents to exchange complementary data and speed-up the process. Two exploration algorithms are studied: one random and one using a stigmergy model (that we propose). Experimental results show how network topologies and agent failure-rates impact data-collection and synchronization, and how a stigmergy-based approach can improve performance and success rates across most scenarios. We believe these results offer key insights into the suitability of various decentralised algorithms in different networked environments, which are increasingly at the core of modern information and communication technology (ICT) systems.