Self-Organizing Interaction Spaces: A Framework for Engineering Pervasive Applications in Mobile and Distributed Environments

TL;DR

SOIS addresses the limitations of cloud-centric pervasive applications by enabling adaptive, device-to-device interactions at the network edge. It introduces an organizational programming model and mechanisms for self-grouping and decentralized role allocation, supported by an XML-based specification of groups and roles. Through simulated mobile crowd-sensing and bus-monitoring scenarios, SOIS demonstrates reduced cloud dependency, lower latency, and improved collaboration in dynamic, heterogeneous environments. The work suggests that 5G‑D2D features can amplify benefits and positions SOIS as a foundation for scalable, resilient mobile/distributed applications.

Abstract

The rapid adoption of pervasive and mobile computing has led to an unprecedented rate of data production and consumption by mobile applications at the network edge. These applications often require interactions such as data exchange, behavior coordination, and collaboration, which are typically mediated by cloud servers. While cloud computing has been effective for distributed systems, challenges like latency, cost, and intermittent connectivity persist. With the advent of 5G technology, features like location-awareness and device-to-device (D2D) communication enable a more distributed and adaptive architecture. This paper introduces Self-Organizing Interaction Spaces (SOIS), a novel framework for engineering pervasive applications. SOIS leverages the dynamic and heterogeneous nature of mobile nodes, allowing them to form adaptive organizational structures based on their individual and social contexts. The framework provides two key abstractions for modeling and programming pervasive applications using an organizational mindset and mechanisms for adapting dynamic organizational structures. Case examples and performance evaluations of a simulated mobile crowd-sensing application demonstrate the feasibility and benefits of SOIS. Results highlight its potential to enhance efficiency and reduce reliance on traditional cloud models, paving the way for innovative solutions in mobile and distributed environments.