A frequency permutation array (FPA) of length n = mλ and distance d is a set of permutations on a multiset over m symbols, where each symbol appears exactly λ times and the distance between any two elements in the array is at least d. FPA generalizes the notion of permutation array. In this paper, under the Chebyshev distance, we first prove lower and upper bounds on the size of FPA. Then we give several constructions of FPAs, and some of them come with efficient encoding and decoding capabilities. Moreover, we show one of our designs is locally decodable, i.e., we can decode a message bit by reading at most λ+1 symbols, which has an interesting application to private information retrieval.

Internet of Things (IoT) allows interactive learning of students by inspiring their innovation everywhere on the campus. This paper proposes CampusTalk that provides convenient access to cyber and physical devices through the web technology. In this way, the campus applications can be accessed anywhere in the world through any computing device with a display and a browser without installing any mobile app. CampusTalk unifies the concepts of automatic creation of “mirror device features”(simulated counterpart) and talkPal device features, which are nicely demonstrated through several applications on campus. The core application of CampusTalk is SmartPhoneTalk that allows other applications to be accessed by students through their smartphones without installing any mobile apps. We describe three CampusTalk applications, including MusicTalk, PingPongTalk, and SkeletonTalk, to demonstrate cyber and physical interaction with SmartPhoneTalk. After the IoT devices of these applications have been developed and are accommodated in CampusTalk, the students can use the CampusTalk GUI to connect them with various combinations for innovative applications without extra programming effort.

Graphical IoT device management platforms, such as IoTtalk, make it easy to describe interactions between IoT devices. Applications are defined by dragging-and-dropping devices and specifying how they are connected, e.g. a door sensor controlling a light. While this allows simple and rapid development, it remains possible to specify unwanted device configurations – such as using the same device to drive a motor up and down simultaneously, risking damaging the motor. We propose , a verification framework for IoTtalk that utilizes formal techniques, based on bigraphs, to statically guarantee that unwanted configurations do not arise. In particular, we check for invalid connections between devices, as well as type errors, e.g. passing a float to a boolean switch. To the best of our knowledge, is the first platform to support the graphical specification of correct-by-design IoT applications. provides fully automated verification and feedback without end-users ever needing to specify a bigraph. This means any application, specifiable in IoTtalk, is guaranteed, so long as verification succeeds, not to violate the given configuration constraints when deployed; with no extra cost to the user.

An Internet of Things (IoT) application typically involves implementations in both the device domain and the network domain. In this two-domain environment, it is possible that application developers implement the wrong network functions and/or connect some IoT devices that should never be linked, which result in the execution of wrong operations on network functions. To resolve these issues, we propose the VerificationTalk mechanism to prevent inappropriate IoT application deployment. VerificationTalk consists of two subsystems: the BigraphTalk subsystem which verifies IoT device configuration; and AFLtalk which validates the network functions. VerificationTalk provides mechanisms to conduct online anomaly detection by using a runtime monitor and offline by using American Fuzzy Lop (AFL). The runtime monitor is capable of intercepting potentially harmful data targeting IoT devices. When VerificationTalk detects errors, it provides feedback for debugging. VerificationTalk also assists in building secure IoT applications by identifying security loopholes in network applications. By the appropriate design of the IoTtalk execution engine, the testing capacity of AFLtalk is three times that of traditional AFL approaches.

This article proposes EduTalk, an out-of-the-box Internet of Things (IoT)-based smart learning environment for programming education. In particular, EduTalk enables the students to write VPython programs that render 3-D animations in the browser without installing extra software or using any specific (and typically expensive) hardware. EduTalk takes the user’s smartphone as a controller for cyber–physical interaction, which nicely integrates with learning of other core courses such as physics and mathematics. EduTalk allows building science exhibition projects by writing VPython programs to show 3-D animation, where the cost for EduTalk’s cyber–physical interaction is low and is almost maintenance free. The major contribution of this article is the IoT-based EduTalk proposal that subtly utilizes an IoT platform IoTtalk to conveniently generate cyber–physical interaction for learning how to program as well as learning core courses such as physics. The programming exercises can be easily extended to science exhibition projects and then the development of digital twin applications. A mechanism is provided to easily integrate GlowScript animation demos with EduTalk, which significantly simplifies the effort for teachers to prepare the lecturers. Finally, we show how data collected from EduTalk can be analyzed to improve learning design for cyber–physical interactive animation.