Benchmarking Eventually Consistent Distributed Storage Systems

Cloud storage services and NoSQL systems typically offer only "Eventual Consistency", a rather weak guarantee covering a broad range of potential data consistency behavior. The degree of actual (in-)consistency, however, is unknown. This work presents novel solutions for determining the degree of (in-)consistency via simulation and benchmarking, as well as the necessary means to resolve inconsistencies leveraging this information

Towards a Benchmark for Fog Data Processing

Fog data processing systems provide key abstractions to manage data and event processing in the geo-distributed and heterogeneous fog environment. The lack of standardized benchmarks for such systems, however, hinders their development and deployment, as different approaches cannot be compared quantitatively. Existing cloud data benchmarks are inadequate for fog computing, as their focus on workload specification ignores the tight integration of application and infrastructure inherent in fog computing. In this paper, we outline an approach to a fog-native data processing benchmark that combines workload specifications with infrastructure specifications. This holistic approach allows researchers and engineers to quantify how a software approach performs for a given workload on given infrastructure. Further, by basing our benchmark in a realistic IoT sensor network scenario, we can combine paradigms such as low-latency event processing, machine learning inference, and offline data analytics, and analyze the performance impact of their interplay in a fog data processing system

Can Orbital Servers Provide Mars-Wide Edge Computing?

Human landing, exploration and settlement on Mars will require local compute resources at the Mars edge. Landing such resources on Mars is an expensive endeavor. Instead, in this paper we lay out how concepts from low-Earth orbit edge computing may be applied to Mars edge computing. This could lower launching costs of compute resources for Mars while also providing Mars-wide networking and compute coverage. We propose a possible Mars compute constellation, discuss applications, analyze feasibility, and raise research questions for future work.Comment: 1st ACM MobiCom Workshop on Satellite Networking and Computing (SatCom '23

Edge Computing in Low-Earth Orbit -- What Could Possibly Go Wrong?

Large low-Earth orbit (LEO) satellite networks are being built to provide low-latency broadband Internet access to a global subscriber base. In addition to network transmissions, researchers have proposed embedding compute resources in satellites to support LEO edge computing. To make software systems ready for the LEO edge, they need to be adapted for its unique execution environment, e.g., to support handovers in face of satellite mobility. So far, research around LEO edge software systems has focused on the predictable behavior of satellite networks, such as orbital movements. Additionally, we must also consider failure patterns, e.g., effects of radiation on compute hardware in space. In this paper, we present a taxonomy of failures that may occur in LEO edge computing and how they could affect software systems. From there, we derive considerations for LEO edge software systems and lay out avenues for future work.Comment: 1st Workshop on Low Earth Orbit Networking and Communication (LEO-NET '23

Eventually Consistent Configuration Management in Fog Systems with CRDTs

Current fog systems rely on centralized and strongly consistent services for configuration management originally designed for cloud systems. In the geo-distributed fog, such systems can exhibit high communication latency or become unavailable in case of network partition. In this paper, we examine the drawbacks of strong consistency for fog configuration management and propose an alternative based on CRDTs. We prototypically implement our approach for the FReD fog data management platform. Early results show reductions of server response times of up to 50%

Efficient Exchange of Metadata Information in Geo-Distributed Fog Systems

Metadata information is crucial for efficient geo-distributed fog computing systems. Many existing solutions for metadata exchange overlook geo-awareness or lack adequate failure tolerance, which are vital in such systems. To address this, we propose HFCS, a novel hybrid communication system that combines hierarchical and peer-to-peer elements, along with edge pools. HFCS utilizes a gossip protocol for dynamic metadata exchange. In simulation, we investigate the impact of node density and edge pool size on HFCS performance. We observe a significant performance improvement for clustered node distributions, aligning well with real-world scenarios. Additionally, we compare HFCS with a hierarchical system and a peer-to-peer broadcast approach. HFCS outperforms both in task fulfillment at the cost of an average 16\% detected failures due to its peer-to-peer structures