Aggregation protocols allow for distributed lightweight computations deployed on ad-hoc networks in a peer-to-peer fashion. Due to reliance on wireless technology, the communication medium is often hostile which makes such protocols susceptible to correctness and performance issues. In this paper, we study the behavior of aggregation protocols when subject to communication failures: message loss, duplication, and network partitions. We show that resolving communication failures at the communication layer, through a simple reliable communication layer, reduces the overhead of using alternative fault tolerance techniques at upper layers, and also preserves the original accuracy and simplicity of protocols. The empirical study we drive shows that tradeoffs exist across various aggregation protocols, and there is no one-size-fits-all protocol.

TCP is typically the default transport protocol of choice for its supposed reliability, even for message-oriented middleware (e.g., ZeroMQ) or inter-actor communication (e.g., distributed Erlang). However, under network issues, TCP connections can fail, which requires ensuring both at-least-once and at-most-one delivery at the upper middleware layer. Moreover, the use of TCP at scale, in highly concurrent systems, can lead to drastic performance loss due to the need for TCP connection multiplexing and the resulting head-of-line blocking. This paper introduces Exon, an oblivious exactly-once messaging protocol, and a corresponding lightweight library implementation. Exon uses a novel strategy of a per-message four-way protocol to ensure oblivious exactly-once messaging, with on-demand protocol-level "soft half-connections" that are established when needed and safely discarded. This achieves correctness, obliviousness, and performance, through merging and pipelining basic protocol messages. The empirical evaluation of Exon demonstrates significant improvements in throughput and latency under packet loss, while maintaining a negligible overhead over TCP in healthy networks.

Edge/Fog Computing is an extension to the Cloud Computing model, primarily proposed to pull some of the load on cloud data center towards the edge of the network, i.e., closer to the clients. Despite being a promising model, the foundations to adopt and fully exploit the edge model are yet to be clear, and thus new ideas are continuously advocated. In his paper on "Life beyond Distributed Transactions: an Apostate's Opinion", Pat Helland proposed his vision to build "almost infinite" scale future applications, demonstrating why Distributed Transactions are not very practical under scale. His approach models the applications data state as independent "entities" with separate serialization scopes, thus allowing efficient local transactions within an entity, but precluding transactions involving different entities. Accessing remote data (which is assumed rare) can be done through separate channels in a more message-oriented manner. In this paper, we recall Helland's vision in the aforementioned paper, explaining how his model fits the Edge Computing Model either regarding scalability, applications, or assumptions, and discussing the potential challenges leveraged.