Abstract: Large-scale IoT services such as healthcare, smart cities and marine monitoring are pervasive in Cyber-physical environments strongly supported by Internet technologies and Fog computing. Complex IoT services are increasingly composed of sensors, devices, and compute resources within Fog computing infrastructures. The orchestration of such applications can be leveraged to alleviate the difficulties of maintenance and enhance data security and system reliability. However, how to efficiently deal with dynamic variations and transient operational behavior is a crucial challenge within the context of choreographing complex services. Furthermore, with the rapid increase of the scale of IoT deployments, the heterogeneity, dynamicity, and uncertainty within Fog environments and increased computational complexity further dramatically aggravate this challenge. This article provides an overview of the core issues, challenges and future research directions in Fog-enabled orchestration for IoT services. Additionally, we present early experiences of an orchestration scenario, demonstrating the feasibility and initial results of using a distributed genetic algorithm in this context.

Citation: Z. Wen, R. Yang, P. Garraghan, T. Lin, J. Xu, and M. Rovatsos. Fog Orchestration for IoT Services: Issues, Challenges and Directions. IEEE Internet Computing, 2017. In press

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Abstract: Collaborative localization is the computation of improved spatial coordinates in mobile agents based on their physical meetings in a pedestrian dead reckoning (PDR) system. Upon meeting the agents can exchange information about their subjective position and update it based on a simple algorithm. We show in a simulation model that the localization error diverges unless this algorithm is introduced in which case it remains bounded. We consider collaborative localization as an example of broader incremental knowledge fusion and discuss its various implications such as the importance of well-informed agents.

Citation: Kampis, G. and Lukowicz, P. (2014): Collaborative Localization as a Paradigm for Incremental Knowledge Fusion, 5th IEEE CogInfoCom 2014 Conference

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Abstract: Digital societies increasingly rely on secure communication between parties. Certificate enrollment protocols are used by certificate authorities to issue public key certificates to clients. Key agreement protocols, such as Diffie-Hellman, are used to compute secret keys, using public keys as input, for establishing secure communication channels. Whenever the keys are generated by clients, the bootstrap process requires either (a) an out-of-band verification for certification of keys when those are generated by the clients themselves, or (b) a trusted server to generate both the public and secret parameters. This paper presents a novel constrained key agreement protocol, built upon a constrained Diffie-Hellman, which is used to generate a secure public-private key pair, and to set up a certification environment without disclosing the private keys. In this way, the servers can guarantee that the generated key parameters are safe, and the clients do not disclose any secret information to the servers.

Citation: F{\’a}bio Borges and Leonardo A. Martucci and Filipe Beato and and Max M{\”u}hlh{\”a}user (2014). Secure and Privacy-Friendly Public Key Generation and Certification. In Proceedings of the 13th IEEE International Conference on Trust, Security and Privacy in Computing and Communications, 24–26 September, Beijing, China, TrustCom 2014.

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Abstract: Privacy-enhancing technologies for the Smart Grid usually address either the consolidation of users’ energy consumption or the verification of billing information. The goal of this paper is to introduce iKUP, a protocol that addresses both problems simultaneously. iKUP is an efficient privacy-enhancing protocol based on DC-Nets and Elliptic Curve Cryptography as Commitment. It covers the entire cycle of power provisioning, consumption, billing, and verification. iKUP allows: (i) utility providers to obtain a consolidated energy consumption value that relates to the consumption of a user set, (ii) utility providers to verify the correctness of this consolidated value, and (iii) the verification of the correctness of the billing information by both utility providers and users. iKUP prevents utility providers from identifying individual contributions to the consolidated value and, therefore, protects the users’ privacy. The analytical performance evaluation of iKUP is validated through simulation using as input a real-world data set with over 157 million measurements collected from 6,345 smart meters. Our results show that iKUP has a worse performance than other protocols in aggregation and decryption, which are operations that happen only once per round of measurements and, thus, have a low impact in the total protocol performance. iKUP heavily outperforms other protocols in encryption, which is the most demanded cryptographic function, has the highest impact on the overall protocol performance, and it is executed in the smart meters.

Citation: F{\’a}bio Borges and Leonardo A. Martucci (2014). {iKUP} Keeps Users’ Privacy in the Smart Grid. In Proceedings of the IEEE Conference on Communications and Network Security (CNS 2014), 29–31 Oct, San Francisco, CA, USA.

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Abstract: Crowdsourcing is generally used for tasks with minimal coordination, providing limited support for dynamic reconfiguration. Modern systems, exemplified by social machines, are subject to continual flux in both the client and development communities and their needs. To support crowd sourcing of open-ended development, systems must dynamically integrate human creativity with machine support. While workflows can be used to handle structured, predictable processes, they are less suitable for social machine development and its attendant uncertainty. We present models and techniques for coordination of human workers in crowd sourced software development environments. We combine the Social Compute Unit—a model of ad-hoc human worker teams—with versatile coordination protocols expressed in the Lightweight Social Calculus. This allows us to combine coordination and quality constraints with dynamic assessments of end-user desires, dynamically discovering and applying development protocols.

Citation: Dave Murray-Rust, Ognjen Scekic, Hong-Linh Truong, Dave Robertson and Schahram Dustdar. A Collaboration Model for Community-Based Software Development with Social Machines. 10th IEEE International Conference on Collaborative Computing: Networking, Applications and Worksharing, 22-25 Oct, Miami, FL, USA, 2014.

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Abstract: We report work in progress on the role of models in the formation and maintenance of collectives in Hybrid Diversity-Aware Collective Adaptive Systems (HDA-CASs). HDA-CASs utilize hybrid computations involving machines and humans operating in collectives in a way that manages and leverages the diversity of collectives and machine-based computation. Here we explore the role of models in helping to constitute particular collectives and how models help shape the response of the collective. It appears that models are a potentially critical resource in collecting, sharing and acting on data gathered from the operation of CASs. This points to the potential role for models in the design of HDA-CASs. In particular we are interested in how models provide a sense of identity for a collective and can provide resources that shape the potential for collective action.

Citation: Stuart Anderson, Mark Hartswood and Marina Jirotka (2014). Reflection, collectives and adaptation: the role of models in the design of Collective Adaptive Systems. In the 2014 IEEE Eighth International Conference on Self-Adaptive and Self-Organizing Systems Workshops (SASOW 2014).

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Abstract: With the advance of research in human computation, applications and software systems are increasingly being designed to include the human aspect of computation. We work with Social Compute Units (SCUs) that are computational constructs with people as their core resources. They are collaborative units, and have a cloud-like behavior in the sense that they may be elastically adapted at runtime. Systems that utilize the concept of SCUs bring challenges that are associated with the highly dynamic and unpredictable human-centric behavior. Thus, trust in the human based services that execute tasks is of paramount importance. While there is related work on social trust in the social networking and crowdsourcing areas, trust in highly coordinated team-based systems such as SCUs remains as a significant challenge. Thus, in this paper we provide a trust model that considers merging social trust with performance based trust of human based services into an integrated trust model. We illustrate the models’ application in concrete strategies, such as for elastic management of SCUs and incentives for SCU members.

Citation: Mirela Riveni, Hong-Linh Truong, Schahram Dustdar, “Trust-aware Elastic Social Compute Units”, The 14th IEEE International Conference on Trust, Security and Privacy in Computing and Communications (IEEE TrustCom-15), Helsinki, Finland, 20-22 August 2015.

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Abstract: Hybrid Diversity-aware Collective Adaptive Systems (HDA-CAS) is a new generation of socio-technical systems where both humans and machine peers complement each other and operate collectively to achieve their goals. These systems are characterized by the fundamental properties of hybridity and collectiveness, hiding from users the complexities associated with managing the collaboration and coordination of hybrid human/machine teams. In this paper we present the key programming elements of the SmartSociety HDA-CAS platform. We first describe the overall platform’s architecture and functionality and then present concrete programming model elements – Collective-based Tasks (CBTs) and Collectives, describe their properties and show how they meet the hybridity and collectiveness requirements. We also describe the associated Java language constructs, and show how concrete use-cases can be encoded with the introduced constructs.

Citation: O. Scekic, T. Schiavinotto, D. I. Diochnos, M. Rovatsos, H.-L. Truong, I. Carreras, S. Dustdar, Programming Model Elements for Hybrid Collaborative Adaptive Systems, 1st IEEE International Conference on Collaboration and Internet Computing (CIC’15), 27-30 October 2015, Hangzhou, China.

Citation: http://bit.ly/1p8SJOP

Abstract: Society is moving towards a socio-technical ecosystem in which physical and virtual dimensions of life are intertwined and where people interactions ever more take place with or are mediated by machines. Hybrid Diversity-aware Collective Adaptive Systems (HDA-CAS) is a new generation of sociotechnical systems where humans and machines synergetically complement each other and operate collectively to achieve their goals. HDA-CAS introduce the fundamental properties of hybridity and collectiveness, hiding from the users the complexities associated with managing the collaboration and coordination of machine and human computing elements. In this paper we present an HDA-CAS system called SmartSociety, supporting computations with hybrid human/machine collectives. We describe the platform’s architecture and functionality, validate it on two real-world scenarios involving human and machine elements and present a performance evaluation.

Citation: O. Scekic, D. Miorandi, T. Schiavinotto, D. I. Diochnos, A. Hume, R. Chenu-Abente, H.-L. Truong, M. Rovatsos, I. Carreras, S. Dustdar, F. Giunchiglia, SmartSociety — A Platform for Collaborative People-Machine Computation, The 8th IEEE International Conference on Service Oriented Computing & Applications (SOCA’15), 19-21 October 2015, Rome, Italy.

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Introduction: Worldwide, societies are seeing rapid change in modes of social interaction and organization. These new interaction modes are predicated on emerging forms of information infrastructure together with rapidly evolving devices, systems, and applications that are ever more deeply interwoven with our social fabric. Computers and humans complement each other, as there are activities that are difficult or impossible for one and easy for the other. We argue that the key to activating the potential for the new generation of high-impact technologies and services aimed at enhancing human problem-solving capabilities lies in realizing a tight symbiosis between human and computers. In this symbiosis, information and communications technology (ICT) becomes an unobtrusive, pervasive extension of individuals and groups, empowering and enabling them to achieve ambitious objectives. We believe that a new form of intelligence can be devised to tackle complex and challenging problems, by exploiting,in a coordinated and holistic fashion, the complementary strengths of human and machines through the integration of computers, the Internet, individuals, and society. We term this integration “social collective intelligence” (SCI).

Citation: “Programming” Social Collective Intelligence. Daniele Miorandi and Lorenzo Maggi. In IEEE Technology and Society, special issue on Technology for Collective Action (2014).

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