For Deaf and Hard of Hearing (DHH) individuals, limited access to sound cues in outdoor environments can reduce situational awareness, making it challenging to notice events and respond to potential dangers. To address this, we investigated the needs for sound awareness and preferences of DHH individuals for visualizing environmental sounds using AR glasses. We conducted four participatory design workshops with DHH participants, social workers, and designers to explore sound awareness needs and co-design ideal visual representations. Based on our insights, we conducted interviews with 15 DHH participants to select their preferred visualizations. The most voted designs were implemented in prototype, which eight DHH participants evaluated in outdoor environment. Results demonstrate that visualizing sound cues through AR can enhance situational awareness and increase sense of safety and confidence among DHH individuals while walking outdoors. Our findings provide design suggestions for translating auditory information into accessible visual representations for DHH users.

Finger wearable haptic devices enrich virtual reality experiences by offering haptic feedback corresponding to the virtual environment. However, despite the effectiveness of current finger wearable haptic devices in delivering haptic feedback, many are often constrained in their ability to provide force feedback across a diverse range of directions or to sustain it. Therefore, we present AirPush, a finger wearable haptic device capable of generating continuously adjustable force feedback in multiple directions using compressed air. To evaluate its usability, we conducted a technical evaluation and four user studies: (1) we obtained the user’s perceptual thresholds of angles under different directions on horizontal and vertical planes, (2) in perception studies, we found that users can identify five different magnitudes of force and eight different motion when using AirPush, and (3) using it in VR applications, we confirmed that users felt more realistic and immersed when using AirPush than the HTC VIVE Controller or AirPush with a fixed nozzle.

When we enter Virtual Reality (VR) in the first person, the avatar replaces our real body. Within a certain range of mismatches, we tend to identify with our avatar and perceive it as our own body. Previous research has shown that we can even believe that a deformed forearm is our own through haptic and visual feedback. However, the haptic devices used in earlier research were only explored using skin-stretching and weight-shifting. Vibrotactile feedback is the most common technique used to create a haptic VR experience in academia and industry because of its light weight and ease of application. Taking these advantages, we introduce VibroArm, a lightweight wearable haptic system with the vibrotactile funneling illusion that enhances the virtual forearm’s ownership in the forearm deformation illusion. In a perceptual study, we determined that users can make correct direction judgments about vibration on the forearm in different directions. The result shows that all vibration patterns can be sufficiently recognized, with an average recognition rate of $87.17 \%$. Based on our results, we designed 18 vibration patterns and compared their impact on the forearm deformation illusion. Finally, our study shows that using VibroArm in VR applications can significantly improve user realism and enjoyment compared to relying on visual feedback alone.

Edge computing is an indispensable technology that overcomes delay limitations of cloud computing. In edge computing, computational resources are deployed at the network edge, and computational tasks and data of end terminals can be efficiently processed by edge nodes. Considering the computational resource limitations of edge nodes, collaborative edge computing integrates computational resources of edge nodes and provides more efficient computing services for end terminals. This article considers a computation offloading problem in collaborative edge computing networks, where computation offloading and resource allocation are optimized by means of a collaborative load shedding approach: a terminal can offload a computing task to an edge node, which either can process the task with its computing resource or further offload the task to other edge nodes. Long-term objectives and long-term constraints are considered, and Lyapunov optimization is applied to convert the original nonconvex computation offloading problem into a second problem that approximate the original problem and it is still nonconvex but has a special structure, which gives rise to a new distributed algorithm that optimally solves the second problem. Finally, the performance and provable bound of the distributed algorithm is theoretically analyzed. Numerical results demonstrate that the distributed algorithm can achieve a guaranteed long-term performance, and also demonstrate the improvement in performance achieved over the case of computation offloading without collaborating edge nodes.