Introducing the new paradigm of Social Dispersed Computing: Applications, Technologies and Challenges

Marisol Garc\'\ia-Valls, Abhishek Dubey, Vicent J. Botti

Journal of Systems Architecture - Embedded Systems Design 2018

PDF DOI

Why This Matters

Traditional cloud computing introduces latency and bandwidth challenges for community-scale applications requiring real-time response, such as transportation and emergency services. Social dispersed computing addresses this by pushing computation to the network edge where it can leverage local resources. This work is innovative because it synthesizes distributed computing paradigms into a unified social dispersed computing vision, providing architects with conceptual frameworks for designing low-latency community applications.

What We Did

This paper introduces the Social Dispersed Computing paradigm that distributes computation across edge devices and networks to enable low-latency services for smart and connected communities. The work analyzes key computing paradigms including cloud computing, mobile cloud computing, cloudlets, fog computing, and edge computing, identifying their characteristics and tradeoffs. The paper discusses technological enablers and research challenges for implementing practical social dispersed computing applications.

Key Results

The analysis identified key characteristics distinguishing social dispersed computing from traditional cloud paradigms, including reduced latency, improved bandwidth efficiency, and enhanced local autonomy. Case studies demonstrated practical applications where edge computing provided significantly better performance than cloud-only approaches. The framework enables system designers to systematically evaluate tradeoffs when distributing computation across edge and cloud resources.

Full Abstract

Cite This Paper

@article{GarciaValls2018,
  author = {Garc{\'{\i}}a{-}Valls, Marisol and Dubey, Abhishek and Botti, Vicent J.},
  journal = {Journal of Systems Architecture - Embedded Systems Design},
  title = {Introducing the new paradigm of Social Dispersed Computing: Applications, Technologies and Challenges},
  year = {2018},
  pages = {83--102},
  volume = {91},
  abstract = {If last decade viewed computational services as a utilitythen surely this decade has transformed computation into a commodity. Computation is now progressively integrated into the physical networks in a seamless way that enables cyber-physical systems (CPS) and the Internet of Things (IoT) meet their latency requirements. Similar to the concept of {\textquotedblleft}platform as a service{\textquotedblright} or {\textquotedblleft}software as a service{\textquotedblright}, both cloudlets and fog computing have found their own use cases. Edge devices (that we call end or user devices for disambiguation) play the role of personal computers, dedicated to a user and to a set of correlated applications. In this new scenario, the boundaries between the network node, the sensor, and the actuator are blurring, driven primarily by the computation power of IoT nodes like single board computers and the smartphones. The bigger data generated in this type of networks needs clever, scalable, and possibly decentralized computing solutions that can scale independently as required. Any node can be seen as part of a graph, with the capacity to serve as a computing or network router node, or both. Complex applications can possibly be distributed over this graph or network of nodes to improve the overall performance like the amount of data processed over time. In this paper, we identify this new computing paradigm that we call Social Dispersed Computing, analyzing key themes in it that includes a new outlook on its relation to agent based applications. We architect this new paradigm by providing supportive application examples that include next generation electrical energy distribution networks, next generation mobility services for transportation, and applications for distributed analysis and identification of non-recurring traffic congestion in cities. The paper analyzes the existing computing paradigms (e.g., cloud, fog, edge, mobile edge, social, etc.), solving the ambiguity of their definitions; and analyzes and discusses the relevant foundational software technologies, the remaining challenges, and research opportunities.},
  bibsource = {dblp computer science bibliography, https://dblp.org},
  biburl = {https://dblp.org/rec/bib/journals/jsa/Garcia-VallsDB18},
  contribution = {colab},
  doi = {10.1016/j.sysarc.2018.05.007},
  file = {:Garcia-Valls2018-Introducing_the_new_paradigm_of_Social_Dispersed_Computing_Applications_Technologies_and_Challenges.pdf:PDF},
  keywords = {edge computing, social dispersed computing, IoT, latency reduction, distributed computing},
  project = {cps-middleware},
  tag = {platform,decentralization},
  timestamp = {Mon, 16 Sep 2019 01:00:00 +0200},
  url = {https://doi.org/10.1016/j.sysarc.2018.05.007}
}
Quick Info
Year 2018
DOI 10.1016/j.sysarc.2018.05.007
Keywords
edge computing social dispersed computing IoT latency reduction distributed computing
Research Areas
CPS middleware
Search Tags

Introducing, paradigm, Social, Dispersed, Computing, Applications, Technologies, Challenges, edge computing, social dispersed computing, IoT, latency reduction, distributed computing, CPS, middleware, 2018, Garc\'\ia-Valls, Dubey, Botti