Multi-party Mobile Virtual Reality (MMVR) enables multiple mobile users to share virtual scenes for an immersive multimedia experience in scenarios such as gaming, social interaction, and industrial mission collaboration. Dynamic 3D Point Cloud (DPCL) is an emerging representation form of MMVR that can be consumed as a free-viewpoint video with 6 degrees of freedom. With limited on-device resources, it is a challenge to achieve a satisfying frame rate for DPCL rendering, which makes edge-assisted rendering a practical solution. However, repeated loading of DPCL scenes with a substantial amount of metadata introduces a significant redundancy overhead that cannot be overlooked when enabling multiple edge servers to support the rendering requirements of user groups. In this paper, we design PoClVR, an edge-assisted DPCL rendering system for MMVR applications, which introduces an object-level splitting mode to alleviate performance bottlenecks caused by redundant loading. In addition, PoClVR dynamically selects the splitting mode and scheduling decisions to adapt to varying task requirements and available computational resources, thereby improving overall system efficiency. To evaluate the performance of PoClVR, we implement and deploy a realistic prototype system and also conduct large-scale trace-driven simulations. The experimental results show that PoClVR can reduce resource usage by up to approximately 49.3% under different task requirements and resource conditions, while decreasing bottleneck performance degradation by up to 77.3%.

Multi-party Mobile Virtual Reality (MMVR) enables multiple mobile users to share virtual scenes for immersive multimedia experience in scenarios such as gaming, social interaction, and industrial mission collaboration. Dynamic 3D Point Cloud (DPCL) is an emerging representation form of MMVR that can be consumed as a free-viewpoint video with 6 degrees of freedom. Given that it is challenging to render DPCL at a satisfying frame rate with limited on-device resources, offloading rendering tasks to edge servers is recognized as a practical solution. However, repeated loading of DPCL scenes with a substantial amount of metadata introduces a significant redundancy overhead that cannot be overlooked when enabling multiple edge servers to support the rendering requirements of user groups. In this paper, we design PoClVR, an edge-assisted DPCL rendering system for MMVR applications, which breaks down the rendering process of the complete dynamic scene into multiple rendering tasks of dynamic objects. PoClVR significantly reduces the repetitive loading overhead of DPCL scenes on edge servers and periodically adjusts the rendering task allocation during the application running to accommodate rendering requirements. We deploy PoClVR based on a real-world implementation and the experimental evaluation results show that PoClVR can reduce GPU utilization by up to 15.1% and increase rendering frame rate by up to 34.6% compared to other baselines while ensuring that the image quality viewed by the user is virtually unchanged.

Task cooperation emerges as a efficacious strategy for the execution of intricate tasks within the context of challenging wireless edge networks characterized by limited resources and intermittent infrastructure connections. Presently, TCP/IP-based solutions encounter issues related to suboptimal utilization of network resources and a substantial dependency on infrastructure connections. In light of this, Information-Centric Networking (ICN) has surfaced as a promising architectural paradigm aimed at mitigating these challenges. In ICN-based task cooperation, the data reuse characteristic of ICN enhances the efficiency of network resource utilization. However, this also introduces plausible security vulnerabilities to the reused data, encompassing eavesdropping attacks and unauthorized access attacks. In this paper, we propose an ICN-based secure task cooperation scheme to mitigate the above threats without compromising the efficiency of task execution. We present the task cooperation model that quantifies the cost of securing data reuse in task execution. We also introduce a specific naming convention to support the acquisition of collaborative task requests and keys related to the task cooperation. Besides, we introduce a novel design for an enhanced name-based access control scheme that ensure both data confidentiality and access control in collaborative tasks accessed by the same sub-policy, streamlining the encryption process for content keys. Security analysis and experimental results demonstrate that our scheme effectively safeguards the security of data reuse. Furthermore, compared to existing schemes, our scheme incurs lower cost associated with computation and security.

Adaptive forwarding is one unique architectural benefit of Named Data Networking (NDN). However, it suffers from high cost of realtime path performance measurement. We propose efficient measurement techniques in NDN’s adaptive forwarding. Specifically, we eliminate the longest prefix matching operation at each data retrieval by decoupling the measurement and the FIB, which is proved to achieve the same effectiveness of the measurement while saving operation costs when network conditions are stable.

Task cooperation is an effective way to execute a complex task in challenging wireless edge networks. Existing TCP/IP-based solutions encounter the problem of low network resource utilization and the heavy dependency of infrastructure connections. Information-centric networking(ICN) is a promising architecture to address these issues. In existing ICN-based task cooperation schemes, the data reuse feature of ICN improves the utilization of network resources, which also brings potential security threats to the reused data. To guarantee the security of data reuse in task cooperation without affecting the data reuse feature, we propose an ICN-based secure task cooperation scheme. In our scheme, the specific naming convention is designed to support task cooperation and the acquisition of keys. In addition, our scheme implements fine-grained access control for data reuse in task cooperation combined with attribute-based encryption. Experimental results show that our scheme enhances the security of task cooperation with low cost compared with existing schemes.

Large low Earth orbit (LEO) satellite constellations provide low-latency and high-bandwidth Internet connectivity at the global scale. One major challenge is to handle frequent satellite handovers. Named Data Networking (NDN) adopts a pull-based communication model, which allows users to retrieve data that fail to come back because of satellite handovers by retransmitting the corresponding requests, hence simplifying mobility management when retrieving data. However, we find that relying on such retransmissions alone can be highly inefficient in typical LEO satellite constellations. Specifically, typical inter-satellite topologies and satellite handover strategies may produce bad cases for retransmissions, generating a significant amount of additional traffic. Motivated by this observation, this paper attempts to consolidate NDN's advantage in mobility management with the Data Recovery Link Service (DRLS), a shim layer service operating between the network and link layer in the NDN protocol stack. DRLS hides recurring satellite handovers from forwarding by recovering data from the previously connected satellite via alternative paths, thus ensuring the bidirectional request-response exchange of NDN without retransmitting requests. A prototype of DRLS is implemented in the reference NDN software forwarder and evaluated through simulations. Results prove the efficacy of the proposed mechanism at reducing the overall traffic volume.

One unique architectural benefit of Named Data Networking (NDN) is adaptive forwarding, i.e., the forwarding plane is able to observe past data retrieval performance and use it to adjust forwarding decisions for future Interests. To be effective, adaptive forwarding assumes thatInterest Routing Localityis related to Interests’ common name prefix, meaning that Interests sharing the same prefix are likely to follow a similar forwarding path within a short period of time. Since Interests can have multiple common prefixes with different lengths, the real challenge is determining which prefix length should be used in adaptive forwarding to record path performance measurements - we refer to this as thePrefix Granularity Problem. The longer the common prefix is, the better the Interest Routing Locality, and the larger the forwarding table. Given the limited FIB size, route names are designed to be considerably shorter than Interest names. Existing adaptive forwarding designs use route names to record path performance measurements, which looses forwarding adaptability as it promises in the event of partial network failures. In this work, we propose to dynamically aggregate and de-aggregate name prefixes in the forwarding table in order to use the prefixes that are the most appropriate given current network situation. In addition, to reduce the overhead of adaptive forwarding, we propose mechanisms to minimize the use of the longest prefix matching in Data packet processing. Simulations demonstrate that the proposed techniques can result in better forwarding decisions in the event of partial network failures with significantly reduced overhead.