Showing papers by "Hans P. Reiser published in 2019"

Resilient Wide-Area Byzantine Consensus Using Adaptive Weighted Replication

Abstract: In geo-replicated systems, the heterogeneous latencies of connections between replicas limit the system's ability to achieve consensus fast. State machine replication (SMR) protocols can be refined for their deployment in wide-area networks by using a weighting scheme for active replication that employs additional replicas and assigns higher voting power to faster replicas. Utilizing more variability in quorum formation allows replicas to swiftly proceed to subsequent protocol stages, thus decreasing consensus latency. However, if network conditions vary during the system's lifespan or faults occur, the system needs a solution to autonomously adjust to new conditions. We incorporate the idea of self-optimization into geographically distributed, weighted replication by introducing AWARE, an automated and dynamic voting weight tuning and leader positioning scheme. AWARE measures replica-to-replica latencies and uses a prediction model, thriving to minimize the system's consensus latency. In experiments using different Amazon EC2 regions, AWARE dynamically optimizes consensus latency by self-reliantly finding a fast weight configuration yielding latency gains observed by clients located across the globe.

SORRIR: A Resilient Self-organizing Middleware for IoT Applications [Position Paper]

Abstract: The increasing societal pervasion and importance of the Internet-of-Things (IoT) raises questions regarding the fault tolerance and robustness of IoT applications as these increasingly become part of critical infrastructures. In this position paper, we outline novel ideas that focus on the design of a resilient and self-organizing execution platform for IoT applications called SORRIR. Its main ambition is to simplify, alleviate and accelerate the development, configuration and operation of resilient IoT systems. We follow a holistic approach which is based on a novel design process, a library containing resilience mechanisms and a robust execution platform that is equipped with monitoring and self-organizing capabilities. The goal is that developers only need to specify the desired resilience degree without having to worry about the technical, implementation-level details of employed resilience mechanisms.

VMIGuard: Detecting and Preventing Service Integrity Violations by Malicious Insiders Using Virtual Machine Introspection

Abstract: Organizations often focus their IT security strategy on protecting the perimeter from outside attacks, but internal attacks can often cause the greatest damage. Version control systems are frequently used in software development, including processes for automated build and deployment. Malicious insider manipulations in a version control system can, for example, lead to a clandestine distribution of software with implanted vulnerabilities, backdoors, or other malicious functionality.

TwinPorter - An Architecture For Enabling the Live Migration of VMI-Based Monitored Virtual Machines

Abstract: Virtual machine introspection has evolved into a valuable tool for several purposes such as incident analysis and intrusion detection. In addition to that, there has been a lot of work that aims at enabling cloud tenants to do VMI on their virtual machines in IaaS-based clouds. Migration can be a required operation in cloud environments, for example, to keep service level agreements or to minimize power consumption. Common tools for migration of virtual machines do not provide support for coordinating VMI-based monitoring with migration. TwinPorter introduces a mechanism that migrates in parallel both the analyzing system and the analyzed system to the same target host. It ensures that the analyzed virtual machine never runs without being actively monitored and keeps the downtime of the analyzed system minimal by extending the live pre-copy based migration protocol of Xen. In our TwinPorter prototype, we measured an additional downtime of about 2 s of the monitored system during migration.