Decentralized Publish/Subscribe (P/S) systems deployed at the edge must cope with two major challenges: frequent membership churn and storage hot-spots caused by skewed topic popularity. In this work, we address these challenges in topic-based P/S systems built over Distributed Hash Tables (DHTs). We introduce PARSLEY, a group-based DHT based on a hybrid architecture that supports dynamic group management. Groups are flexibly maintained through splits, merges, and proactive peer relocation driven by soft size limits, ensuring balanced membership while minimizing expensive global operations. Additionally, we propose a lightweight sharding mechanism for popular topics, which partitions metadata and subscriptions across multiple DHT groups to alleviate overload by directing only subsequent data to new shards. Both mechanisms are coordinated by an edge server while preserving decentralized execution within the overlay. An implementation in the THYME framework demonstrates that proactive peer relocation reduces merge operations substantially lowers bandwidth consumption for state transfers, stabilizing group sizes under churn, while sharding alleviates storage pressure on popular topics, reducing maximum group load by up to 65% with moderate overhead. Together, they improve scalability, resilience, and responsiveness of edge-enabled P/S systems.

The implementation of collaborative applications in highly volatile environments, such as the ones composed of mobile devices, requires low coordination mechanisms. The replication without coordination semantics of Conflict-Free Replicated Data Types (CRDTs) makes them a natural solution for these execution contexts. However, the current CRDT models require each replica to know all other replicas beforehand or to discover them on-the-fly. Such solutions are not compatible with the dynamic ingress and egress of nodes in volatile environments. To cope with this limitation, we propose the Publish/Subscribe Conflict-Free Replicated Data Type (PS-CRDT) model that combines CRDTs with the publish/subscribe interaction model, and, with that, enable the spatial and temporal decoupling of update propagation. We implemented PS-CRDTs in Thyme, a reactive storage system for mobile edge computing. Our experimental results show that PS-CRDTs require less communication than other CRDT-based solutions in volatile environments.

Nowadays, smart mobile devices generate huge amounts of data in all sorts of gatherings. Much of that data has localized and ephemeral interest, but can be of great use if shared among co-located devices. However, mobile devices often experience poor connectivity, leading to availability issues if application storage and logic are fully delegated to a remote cloud infrastructure. In turn, the edge computing paradigm pushes computations and storage beyond the data center, closer to end-user devices where data is generated and consumed, enabling the execution of certain components of edge-enabled systems directly and cooperatively on edge devices. In this article, we address the challenge of supporting reliable and efficient data storage and dissemination among co-located wireless mobile devices without resorting to centralized services or network infrastructures. We propose Thyme, a novel time-aware reactive data storage system for pervasive edge computing environments, that exploits synergies between the storage substrate and the publish/subscribe paradigm. We present the design of Thyme and elaborate a three-fold evaluation, through an analytical study, and both simulation and real world experimentations, characterizing the scenarios best suited for its use. The evaluation shows that Thyme allows the notification and retrieval of relevant data with low overhead and latency, and also with low energy consumption, proving to be a practical solution in a variety of situations.

The edge computing paradigm has been recently introduced with the aim of bringing cloud services closer to endusers. It provides an intermediate layer between devices and the actual cloud infrastructure, resulting in faster response times. In this paper, we propose a framework that leverages stationary nodes within the edge infrastructure to provide a persistent publish/subscribe system to a set of mobile devices, distributed across multiple network regions. We combine device-to-device and device-to-edge interactions with the goal of optimizing access to relevant data and allowing such data to be available to all users, hence creating a persistent, local-area data storage and dissemination network. Our experimental results show adequate response times for interactive usage and low energy consumption. We also evaluate our system against a cloud solution and verify that our proposal yields considerable latency speedups.

Nowadays, smart mobile devices generate huge amounts of data in all sorts of gatherings. Much of that data has localized and ephemeral interest, but can be of great use if shared among co-located devices. However, these devices often experience poor connectivity, leading to availability issues if applications' storage and logic are fully delegated to a remote cloud infrastructure. In turn, the edge computing paradigm pushes computations and storage beyond the data center, closer to end-user devices where data is generated and consumed. Thus, enabling the execution of certain components of edge-enabled systems directly and cooperatively on edge devices. In this paper, we address the challenge of supporting reliable and efficient data storage and dissemination among co-located wireless mobile devices without resorting to centralized services or network infrastructures. We propose Thyme, a novel time-aware reactive data storage system for wireless edge networks, that exploits synergies between the storage substrate and the publish/subscribe paradigm. We present the design of Thyme and evaluate it through simulation, characterizing the scenarios best suited for its use. The evaluation shows that Thyme allows for reliable notification and retrieval of relevant data with low overhead and latency.

This article presents Pot, a system that leverages the concept of preordered transactions to achieve deterministic multithreaded execution of programs that use Transactional Memory. Preordered transactions eliminate the root cause of nondeterminism in transactional execution: they provide the illusion of executing in a deterministic serial order, unlike traditional transactions that appear to execute in a nondeterministic order that can change from execution to execution. Pot uses a new concurrency control protocol that exploits the serialization order to distinguish between fast and speculative transaction execution modes in order to mitigate the overhead of imposing a deterministic order. We build two Pot prototypes: one using STM and another using off-the-shelf HTM. To the best of our knowledge, Pot enables deterministic execution of programs using off-the-shelf HTM for the first time. An experimental evaluation shows that Pot achieves deterministic execution of TM programs with low overhead, sometimes even outperforming nondeterministic executions, and clearly outperforming the state of the art.

In this paper we propose a fully distributed storage system for everyday hand-held mobile devices, e.g., smartphones and tablets, that follows a best effort approach to ensure data persistence and availability even in the presence of churn (i.e., the unpredictable arrival and departure of nodes).