Charles Sanders Peirce [4] developed semiotics into its modern form, which embodies empirical and syntactical issues addressed by Shannon's communication ...
Meeting the Challenge of Ubiquitous Systems Semiotic Autonomics Tim Millea, Kecheng Liu and Rachel Harrison Applied Software Engineering Research Group, The University of Reading
“Human Society is becoming increasingly dependant on integrated computer systems. Development of technologies to cope requires a comprehensive, interdisciplinary development of a theoretical base framework. Considered as systems, the interacting processes in their domain must be recognised, analysed, and managed as multi-tool, multi-level, multi-agent feedback systems.” M.M. Lehman, SOCE 2000 workshop, Oxford.
1. Introduction This paper forms a contribution towards meeting the Grand Challenge for Computing Research of ubiquitous systems. The requirements of software systems cannot in general be completely or accurately expressed simply because 1) they are never completely or accurately known, and 2) we do not have the language to completely or accurately express them. The challenge of ubiquitous computing is now forcing fundamental issues upon the software engineering research community that, due to scale, volume and/or complexity, have become inescapable.
Many Lehman’s quote (above) captures the nature of this area of research. The emergent behaviour of continuously evolving ubiquitous systems will be guided not by engineering, but by multi-level feedback communicated between stakeholders of systems that assemble and maintain themselves. We propose novel research for underpinning formalisations and delivery mechanisms based on current work in semiotics and market-oriented autonomic computing.
2. Semiotics Semiotics is the discipline of signs (e.g. icons, indices, symbols, signals and tokens) that are processed and interpreted in all human systems [1]. In recent years, semiotics has provided a theoretical underpinning for information systems [2]. From the semiotic perspective, an organisation, whether a small collection of computers and people or an entire society, is an information system: information is created, stored and processed for communication, coordination and achieving organisational objectives. The expression and interpretation of objectives is the medium of feedback in human-computer systems. The field of semiotics is therefore fundamental to this research challenge.
Signs are completely different in properties, functions and measurements to physical objects. Information about each of us is constantly generated e.g. by our employers, financial, telephone and utility companies and Government agencies. Information does not always flow (otherwise it would be easy to turn the flow off); information is a field [3] like gravity from which we cannot escape.
Charles Sanders Peirce [4] developed semiotics into its modern form, which embodies empirical and syntactical issues addressed by Shannon’s communication theory and goes much beyond. Ronald Stamper with his own remarkable contribution to semiotics, summarises the six aspects of signs [5].
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Physics: signals, traces, physical distinctions, hardware, component density, speed, etc.
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Empirics: pattern, variety, noise, entropy, channel capacity, redundancy, efficiency, codes, etc.
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Syntactics: formal structure, language, logic, data, records, deduction, software, files, etc.
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Semantics: meanings, propositions, validity, truth, signification, denotations, etc.
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Pragmatics: intentions, communications, conversations, negotiations, etc.
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Social layer: beliefs, expectations, commitments, contracts, law, culture, etc.
Computer scientists have effective means to deal with the first three aspects of signs. The latter three aspects are yet to receive a sound theoretical treatment. Ubiquitous computing will depend upon fundamental theory in these areas. Emergent technologies are already demonstrating convincing evidence and future trends. An immediate task will be to concentrate on the effective and proper use of these technologies for ubiquitous systems.
3. Autonomic Computing Taking its meaning from the self-regulating behaviour of the human central nervous system, the field of autonomic computing seeks to automate the assembly, maintenance and management of software systems. The need for automation is clear: the number of computing devices is increasing exponentially and managing this volume and complexity is currently a human activity. However, the demand for skilled IT labour has already outstripped supply [6]. Without automation, the dream of ubiquitous computing systems is likely to become the “nightmare of pervasive computing” in which society gradually grinds to a support-bound halt [7]. Automation of the development and maintenance cycles brings the potential for stakeholder feedback-driven rapid systems evolution.
IBM Research produced a manifesto of autonomic computing suggesting eight defining system properties: self-aware, self configuring, self-optimising, self-repairing, self-protecting, self-adapting, able to operate in a heterogeneous world and hiding internal complexity [8]. Kephart and Chess state the
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essence of autonomic computing is system self-management, freeing administrators of low-level task management whilst delivering an optimized system [7]. The research challenges they identify include:
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Managing the life cycles of autonomic elements
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Managing element interactions from negotiation to provision of service
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Providing means of security, privacy and trust
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Understanding emergent autonomic element types
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Mapping from local to global behaviour
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Goal specification
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Theories of robustness, negotiation, and learning
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Statistical models for testing autonomic systems
The UK e-Science programme placed autonomic computing high in its research agenda as a means of reducing the cost of managing the e-Science infrastructure and identified the following research challenges [9].
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New theories and techniques to analyse, describe and reason about adaptive systems that are self-organising, self-managing and self-decommissioning.
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New models to allow semiautonomous systems to be managed through a combination of specified policies, negotiated agreements, services, software agents and regulatory structures.
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Techniques to allow interoperability across and between different autonomous domains and to reason about the combination of different domains.
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Techniques to model and measure performance and ensure quality of services when they depend on autonomic computational structures.
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Techniques to capture context relating to location, device capabilities, history of the computation, user activity, ambient environment and to build applications which can automatically adapt to their context.
Autonomic computing faces many challenges before its grand vision becomes reality. The plethora of crosscutting, multifaceted problems still being identified appear at first overwhelming. This should be no surprise: researchers are faced with simultaneously solving all the problems associated with developing and maintaining software, in the general case, and for all time. However, we believe that autonomic systems should drive the problem-solving process, and cause quality in software to be both more attainable and a naturally emergent property.
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4. The Work at Reading The recently established Informatics Research Centre at Reading builds on the success of the Applied Software Engineering Research Group in working with researchers from other disciplines, such as environment, biology, bio-diversity, and business studies. Work has been carried out in e-science, GRID computing, and computer supported collaborative work [2, 10, 11]. Much our work addresses the semantic, pragmatic and social issues in the design of computer systems.
In Semantics, our work in requirements engineering and software quality focuses on capturing and representing views of stakeholders who may be geographically and time-distributed with multiple requirements. The semantic clarity and conflicts in systems models has been addressed with the semiotic method of Semantic Analysis.
In Pragmatics, we recognise that we must understand the
Rights
requirements of all stakeholders in terms of responsibility,
Powers
obligation, right and privilege. We draw input from legal studies to understand the fundamental concepts relevant to the control of access to information sources (see right). Norm Analysis and Deontic logic
Right No right Power Disability
Duty Privilege Liability Immunity
Legal notions relevant to the use of information service (from Allen and Saxon 1986, quoted in [7])
are used to facilitate the design of the control algorithm by employing deontic operators, as below.
→ where: describes events and the external environment; → denotes the consequent (normally an action by some agent, see below). is one of the following deontic operators: O (for obligatory or “must”), P (for permission or “may”), and F (for forbidden or “must not”), which qualifies the responsibility relationship to the intended action. can be a human individual or group, or a software application can be from a human actor or, by delegation, from a software agent
In Social Aspects, we investigate the social, organisational and cultural impact of the use of information systems. The organisational rules and common practice in a user community may have a profound impact on the user of information systems through distributed workflow and processes. Perceived benefits and drawbacks may influence an organisation or a community in the use of ubiquitous systems.
In Autonomic Computing, we are investigating whether 1) the concerns and requirements of a system’s stakeholders may be being expressed in a form amenable to the machine inference of their optimal compromise, and 2) this may be used to guide the dynamic optimisation of a system within the space of possibilities determined by a virtual market of available system components. This project (GR/S19066/01) is the first funded by EPSRC in the area of autonomic computing.
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5. Looking Ahead – Benefits and Dangers Computers now pervade every aspect of daily life and society. The dawn of ubiquitous computing promises the personalisation of every citizen’s interaction with e-society, a term spanning education, labour, the trade in goods and services, financial and legal systems, defence, political representation and government. All are areas already currently being transformed by computerisation. Ubiquitous systems will be able to negotiate with their human principals and each other about all interactions with, and within, the digital domain.
Of course there are dangers. The fault lines currently inherent within existing systems could be systematically exploited by the unscrupulous, the selfish, and the dangerous with the efficiency, potency and speed that only computers could affect. We argue that the only logical sure defence to these dangers is at the level of the atomic unit of e-society, the individual e-citizen. Human rights and common ethics, including issues of privacy and security need to be enshrined at the very core of human-computer interaction. There is the potential to mitigate the precursors of malicious acts because, and not despite, human rights are the basic precondition of all e-society interaction.
Ubiquitous computing has the potential to enable the contributions and rewards of each individual to be optimally balanced within specified policies of trust, rights, privacy and security to enable the efficient exchange of the full gamut of human productivity via the digital domain. However, there is a need to remove existing weaknesses from socio-computer systems to prevent their malicious exploitation.
6. Proposal Continuously evolving ubiquitous systems may be realised through minimalist autonomic agents, each serving one human, organisation, or other logical entity and initially requiring only the ability to trade in highly efficient, globally distributed virtual markets. However these are markets not just of software services but of all resources, e.g. language models to better communicate the goals of their human principals, partial solutions in the form of knowledge, goods, services and labour to achieve them, and the computing resources upon which to execute. Thus minimalist autonomic agents bootstrap themselves into systems ever more capable of understanding and serving their human principals, creating liquidity in human productivity and allocating resources for further work as efficiently as may be determined at the time. The key research areas are:
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Semiotic interpretation for requirements and resource description and comparison
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Highly efficient market mechanisms for ubiquitous autonomic agents
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Human-computer communication for evolutionary requirements discovery
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Formalisation of human rights, trust, ethics, privacy and security
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Fundamental semiotic research in semantics, pragmatics and social aspects support the requirements for global heterogeneity across all four areas, i.e. the need for a theoretical basis of information independent of protocol, language and paradigm. Autonomic computing provides the delivery model and ubiquitous computing follows as a consequence. We propose a substantial package of inter-disciplinary research in semiotic autonomics to meet the grand challenge of ubiquitous computing.
References [1] Locke, John (1690/1959) Essay concerning human understanding, Dover, New York. [2] Liu, K. (2000) Semiotics in Information Systems Engineering. Cambridge University Press, Cambridge. [3] Stamper, R.K. (1996) Signs, Information, Norms and Systems, in Holmqvist, P., Andersen, P.B., Klein, H. and Posner, R. (Eds.), Signs of Work, Walter de Gruyter. [4] Peirce, C. S., 1931/1935, Collected Papers of C. S. Peirce, Hartshorne, C. and Weiss, P. (eds.), Harvard University Press Cambridge,Mass. [5] Stamper, R. K., 1973, Information in Business and Administrative Systems. John Wiley and Sons, New York. [6] Trends in technology, survey, Berkeley University of California, USA, March 2002 [7] J. Kephart and D. Chess, The Vision of Autonomic Computing, IEEE Computer Magazine, January ‘03 [8] Autonomic Manifesto, IBM Research http://www.research.ibm.com/autonomic/ [9] Atkinson M., Crowcroft J., Goble C., Gurd J., Rodden T., Shadbolt N., Sloman N., and Sommerville I., Computer Challenges to emerge from eScience, http://umbriel.dcs.gla.ac.uk/Nesc/general/news/Vision.PDF, [10] Liu, K. and R. Harrison (2002) Embedding “Softer” Aspects into the Grid (Poster), Proceedings of EUROWEB 2002 - The Web and The GRID: from e-science to e-business, Eds: Brian Matthews, Bob Hopgood, Michael Wilson, The British Computer Society, ISBN 1-902505-50-6, pp179-182 [11] Blower, J., K. Haines, C. Liu, A. Woolf, K. Liu, A. Sandtokhee, Y. Zhao (2003) GADS: Using Web Services to Access Large Data Sets, Environment Science eScience Centre, The University of Reading
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