Self-Adaptive and Self-Organizing Systems 

About: Self-Adaptive and Self-Organizing Systems is an academic conference. The conference publishes majorly in the area(s): Multi-agent system & Wireless sensor network. Over the lifetime, 695 publications have been published by the conference receiving 7623 citations.

A Survey of Self-Awareness and Its Application in Computing Systems

Abstract: Novel computing systems are increasingly being composed of large numbers of heterogeneous components, each with potentially different goals or local perspectives, and connected in networks which change over time. Management of such systems quickly becomes infeasible for humans. As such, future computing systems should be able to achieve advanced levels of autonomous behaviour. In this context, the system's ability to be self-aware and be able to self-express becomes important. This paper surveys definitions and current understanding of self-awareness and self-expression in biology and cognitive science. Subsequently, previous efforts to apply these concepts to computing systems are described. This has enabled the development of novel working definitions for self-awareness and self-expression within the context of computing systems.

JA-BE-JA: A Distributed Algorithm for Balanced Graph Partitioning

Abstract: Balanced graph partitioning is a well known NP-complete problem with a wide range of applications. These applications include many large-scale distributed problems including the optimal storage of large sets of graph-structured data over several hosts-a key problem in today's Cloud infrastructure. However, in very large-scale distributed scenarios, state-of-the-art algorithms are not directly applicable, because they typically involve frequent global operations over the entire graph. In this paper, we propose a fully distributed algorithm, called JA-BE-JA, that uses local search and simulated annealing techniques for graph partitioning. The algorithm is massively parallel: there is no central coordination, each node is processed independently, and only the direct neighbors of the node, and a small subset of random nodes in the graph need to be known locally. Strict synchronization is not required. These features allow JA-BE-JA to be easily adapted to any distributed graph-processing system from data centers to fully distributed networks. We perform a thorough experimental analysis, which shows that the minimal edge-cut value achieved by JA-BE-JA is comparable to state-of-the-art centralized algorithms such as METIS. In particular, on large social networks JA-BEJA outperforms METIS, which makes JA-BE-JA-a bottom-up, self-organizing algorithm-a highly competitive practical solution for graph partitioning.

CoCoRo -- The Self-Aware Underwater Swarm

Abstract: The EU-funded CoCoRo project studies heterogeneous swarms of AUVs used for the purposes of under water monitoring and search. The CoCoRo underwater swarm system will combine bio-inspired motion principles with biologically-derived collective cognition mechanisms to provide a novel robotic system that is scalable, reliable and flexible with respect its behavioural potential. We will investigate and develop swarm-level emergent self-awareness, taking biological inspiration from fish, honeybees, the immune system and neurons. Low-level, local information processing will give rise to collective-level memory and cognition. CoCoRo will develop a novel bio-inspired operating system whose default behaviour will be to provide AUV shoaling functionality and the maintenance of swarm coherence. Collective discrimination of environmental properties will be processed on an individual-or on a collective-level given the cognitive capabilities of the AUVs. We will investigate collective self-recognition through experiments inspired by ethology and psychology, allowing for the quantification of collective cognition.

Dissecting Self-* Properties

Abstract: The scale and complexity of distributed systems have steadily grown in the recent years. Management of this complexity has drawn attention towards systems that can automatically maintain themselves throughout different scenarios. These systems have been described with many terms, such as self-healing, self-stabilizing, self-organizing, self-adaptive, self-optimizing, self-protecting, and self-managing. These attributes are collectively referred to as self-* properties. Even with the increased focus on self-* research, there exists much ambiguity in the perceptions of the different self-* properties. In this paper, we propose to resolve the ambiguity by introducing a template for defining self-* properties, and use it to offer formal definitions of existing self-* terms. We then present some observations about the relationships among the different self-* properties. Finally, we propose two new self-* properties that are meaningful in this space.

On Self-Adaptation, Self-Expression, and Self-Awareness in Autonomic Service Component Ensembles

Abstract: Software systems operating in open-ended and unpredictable environments have to become autonomic, i.e., capable of dynamically adapting their behavior in response to changing situations. To this end, key research issues include: (i) framing the schemes that can facilitate components (or ensembles of) to exhibit self-adaptive behaviors, (ii) identifying mechanisms to enable components or ensembles to self-express the most suitable adaptation scheme, and (iii) acquiring the proper degree of self-awareness to enable putting in action self-adaptation and self-expression schemes. In this position paper, with the help of a representative case study, we frame and discuss the above issues, survey the state of the art in the area, and sketch the main research challenges that will be faced in the ASCENS project towards the definition of a fully-fledged framework for autonomic services.