Inside Job: Diagnosing Bluetooth Lower Layers Using Off-the-Shelf Devices

Bluetooth is among the dominant standards for wireless short-range communication with multi-billion Bluetooth devices shipped each year. Basic Bluetooth analysis inside consumer hardware such as smartphones can be accomplished observing the Host Controller Interface (HCI) between the operating system's driver and the Bluetooth chip. However, the HCI does not provide insights to tasks running inside a Bluetooth chip or Link Layer (LL) packets exchanged over the air. As of today, consumer hardware internal behavior can only be observed with external, and often expensive tools, that need to be present during initial device pairing. In this paper, we leverage standard smartphones for on-device Bluetooth analysis and reverse engineer a diagnostic protocol that resides inside Broadcom chips. Diagnostic features include sniffing lower layers such as LL for Classic Bluetooth and Bluetooth Low Energy (BLE), transmission and reception statistics, test mode, and memory peek and poke

Enabling collaboration in virtual reality navigators

In this paper we characterize a feature superset for Collaborative Virtual Reality Environments (CVRE), and derive a component framework to transform stand-alone VR navigators into full-fledged multithreaded collaborative environments. The contributions of our approach rely on a cost-effective and extensible technique for loading software components into separate POSIX threads for rendering, user interaction and network communications, and adding a top layer for managing session collaboration. The framework recasts a VR navigator under a distributed peer-to-peer topology for scene and object sharing, using callback hooks for broadcasting remote events and multicamera perspective sharing with avatar interaction. We validate the framework by applying it to our own ALICE VR Navigator. Experimental results show that our approach has good performance in the collaborative inspection of complex models.Postprint (published version

Throughput analysis of TCP congestion control algorithms in a cloud based collaborative virtual environment

Collaborative Virtual Environment (CVE) has become popular in the last few years, this is because CVE is designed to allow geographically distributed users to work together over the network. In CVE the state of the virtual objects is witnessing unprecedentant change. When a user performs an action in CVE, the information of the action needs to be transmitted to other users to maintain consistency in the cooperative work. TCP is the most widely used protocol in the design of CVE, and its throughput deteriorates in the network with large delay. Gital et al, 2014 proposes a cloud based architectural model for improving scalability and consistency in CVE. Therefore, this paper aim at evaluating and comparing the performance of different TCP variant (Tahoe, Reno, New Reno, Vegas, SACK, Fack and Linux) with the cloud based CVE architecture to determine the suitability of each TCP variant for CVE. A comparative analysis between the different TCP variants is presented in terms of throughput verses elapse time, with increasing number of users in the system. TCP with the cloud based model was found to be effective, promising and robust for achieving consistency requirement in CVE system

Performance analysis of cloud-based cve communication architecture in comparison with the traditional client server, p2p and hybrid models

Gital et al. (2014) proposed a cloud based communication architecture for improving efficiency of collaborative virtual environment (CVE) systems in terms of Scalability and Consistency requirements. This paper evaluates the performance of the proposed CVE architecture. The metrics use for the evaluation is response time. We compare the cloud-based architecture to the traditional client server and peer-2–peer (P2P) architecture. The comparison was implemented in the CVE systems. The comparative simulation analysis of the results suggested that the CVE architecture based on cloud computing can significantly improve the performance of the CVE system