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IoT interoperability is critical to the realization of the IoT on a global scale. This paper examines how seemingly obvious choices for perfect IoT interoperability are not so perfectly rational and offers the concept of "Rational Interoperability" as a means to frame and to scope the discussion. We identify why a new framing conceptualization adds value. We explore the gradations, progression and implications of Rational Interoperability: from good-enough interoperability in a pervasively connected world, to enriched interoperability for trusted groups of Things, to the aspirational goal to use interoperability requirements to guide the behavior of groups of Things toward the common good. To motivate Rational Interoperability, we describe architectural shifts underway in the IoT and present key building blocks, both of which play pivotal roles and impact its realization. We examine pragmatic near-term goals for IoT interoperability, as well as longer-term research directions. Throughout, we share lessons learned from IoT standards, highlighting pragmatic and philosophical viewpoints. Finally, we identify the gaps, challenges and opportunities in realizing IoT interoperability, including meta-data handling, enhanced discovery, data-driven insights, data-centric networks and the coordination of collective behaviors.

The Internet of Things (IoT) is producing a tidal wave of data, much of it originating at the network edge, from applications with requirements unmet by the traditional back-end Cloud architecture. To address the disruption caused by the overabundance of data, this paper offers a holistic data-centric architectural vision for the data-centric IoT. It advocates that we rethink our approach to the design and definition of key elements: that we shift our focus from Things to Smart Objects; grow Trust organically; and evolve back-end Clouds toward Edge and Fog clouds, which leverage data-centric networks and enable optimal handling of upstream data flows. Along the way, we wax poetic about several blue-sky topics, assess the status of these elements in the context of related work, and identify known gaps in meeting this vision.

This paper presents a solution that improves remote monitoring and real-time control of medical devices in eHealth, and provides better user experience and deployment simplicity. Our approach builds a unified, scalable, secure and real-time platform making use of IoT Gateways to remotely monitor patients and manage/control diverse types of sensors and IoT medical devices. WebRTC is used as a key architectural component to enable interactive communication between smart medical spaces (e.g., clinics, patients' homes) and remote users (e.g., health/wellness services, physicians, medical staff). We also demonstrate the need for an Edge Cloud to save on network bandwidth usage especially for video traffic for remote monitoring and to ensure real-time control of medical devices. We implemented a Proof of Concept (PoC) to test our solution. The performance results obtained measure the utility of the proposed approach and its effectiveness in real-time eHealth services.

With the ever increasing number of connected devices and the over abundance of data generated by these devices, data privacy has become a critical concern in the Internet of Things (IoT). One promising privacy-preservation approach is Attribute-Based Encryption (ABE), a public key encryption scheme that enables fine-grained access control, scalable key management and flexible data distribution. This paper presents an in-depth performance evaluation of ABE that focuses on execution time, data and network overhead, energy consumption, and CPU and memory usage. We evaluate two major types of ABE, Key-Policy Attribute-Based Encryption (KP-ABE) and Ciphertext-Policy Attribute-Based Encryption (CP-ABE), on different classes of mobile devices including a laptop and a smartphone. To the best of our knowledge, this is the first comprehensive study of ABE dedicated solely to its performance. Our results provide insights into important practical issues of ABE, including what computing resources ABE requires in heterogeneous environments, at what cost ABE offers benefits, and under what situations ABE is best suited for use in the IoT.

We design a content-centric privacy scheme for Information-Centric Networking (ICN). We enhance ICN's ability to support data confidentiality by introducing attribute-based encryption into ICN and making it specific to the data attributes. Our approach is unusual in that it preserves ICN's goal to decouple publishers and subscribers for greater data accessibility, scalable multiparty communication and efficient data distribution. Inspired by application-layer publish-subscribe, we enable fine-grained access control with more expressive policies. Moreover, we propose an attribute-based routing scheme that offers interest confidentiality. A prototype system is implemented based on CCNx, a popular open source version of ICN, to showcase privacy preservation in Smart Neighborhood and Smart City applications.

The Real-time Transport Control Protocol (RTCP) is a crucial mechanism used, amongst other things, for synchronisation and feedback control in multimedia sessions. However as groups grow to large numbers, it faces two serious challenges: the growing deployment of unidirectional and asymmetric broadcast architectures, such as Source-Specific Multicast and satellite networks, eliminate the shared control backchannel on which RTCP relies; the per-receiver RTCP reporting frequency diminishes prohibitively due to the bandwidth-sharing algorithm. We present new algorithmic techniques that enable RTCP to combat these issues, allowing it to function in a wider range of environments and to scale to larger groups.

This paper identifies some of the issues that need to be explored in systems that support content-based delivery. Distributed systems today are based on address-based delivery of messages. Each message carries the unique addresses of the intended recipients. The idea in content-based delivery is that information is delivered to those objects that have subscribed for that information. The ideas on content-based delivery reported are based partly on Roman Ginis' doctoral dissertation at Caltech. The ideas on directories reported are based partly on Eve Schooler's doctoral dissertation at Caltech.

We specify an abstract model for dynamic distributed control systems in which the component objects make local decisions based on system-wide constraints and approximate global state. We focus on the issue of distributed resource management, exploring a solution that is both compositional and scalable because it builds global events into the Java infrastructure by exploiting its multicast facilities. © 1998 John Wiley & Sons, Ltd.

Proposes a framework for the systematic design of directory-based distributed applications. We evaluate a space of directory designs using our framework. We present a case study consisting of design, implementation and analysis of directories for a multicast application. Our framework is based on a model that extends the formal concept of process knowledge in distributed systems. This concept is used informally in phrases such as "process p knows when it is in state s that process q is active". We show that this definition of knowledge is too strong for many distributed applications, including directory design. We propose a weaker concept: estimation. We describe the meaning of phrases of the form: "process p in state s estimates with probability 0.9 that process q is active". We specify directory design as an optimization problem with the objective function of maximizing estimation probabilities, and with constraints on the amount of bandwidth, computation and storage used. We show how this specification helps in a systematic analysts of alternative directory designs.

The design, implementation, and use of a distributed processing environment on a network of IBM PCs running DOS is described. Temporarily unused PCs can be accessed by other users on the network to perform distributed computations. An owner of a PC need not be aware that the machine is being used during idle times; the machine is immediately returned when the owner begins to work again. Some degree of computation resiliency is provided in this unreliable environment; if a PC is part of a distributed algorithm and is reclaimed by its owner, the system finds a replacement node (if possible), resends the affected code to the processor, and restarts it. Thus, a distributed computation is able to proceed despite a set of transient processors. System performance, distributed applications, and fault tolerance are discussed. Performance improvements are demonstrated by applications like parallel merge sort and a distributed search solution to the eight puzzle.>