Dispersed Computing

Description | People | Projects and Sponsors | Links | Publications


We are witnessing a rapid growth in the number of connected devices, which is only going to grow further with the Internet of Things (IoT). Most of the these devices are constrained by their batteries and have limited processing capabilities, and thus cannot locally run computationally intensive tasks. These connected devices can, however, share resources with each other and collaborate to create a platform with large computational resources for the execution of the complex applications. This is in contrast to the traditional cloud services that provide high performance and reliable servers. With long RTTs of a wide area network and possibly long setup times, the remote servers might incur a high delay. The connected devices, we consider, are not as powerful as cloud servers, but can be accessed by faster device-to-device (D2D) communication.

Computational Task Mapping
In above figure, we illustrate the basic idea of dispersed computing. Given an application consisting of multiple tasks, we wish to assign them to the networked devices with the goal of minimizing the total expected cost. The cost can depend on performance metrics like the energy consumption and the overall application latency. We analyze different D2D transmission models and the computational models, design algorithms to minimize the execution cost and prove performance guarantees for them.

Note that these collaborating devices are connected with wireless links which have time-varying gains. The collaborating wireless devices are mobile and can get disconnected arbitrarily and come back later. The link qualities are, therefore, highly dynamic and variable. The quantity of the resources shared by a device is dependent on its own local processes. Hence, the performance of each device may vary with time.


Principal Investigator and Director: Bhaskar Krishnamachari

Ph.D. Students: Jared Coleman, Diyi Hu, Pradipta Ghosh, Quynh Nguyen, Jason Tran, Yi-Hsuan Kao, Pranav Sakulkar, Kwame Lante Wright

Postdoctoral Scholars: Eugenio Grippo, Aleksandra Knezevic

Collaborators: Murali Annavaram (USC), Salman Avastimehr (USC), Alexander Poylisher, Latha Kant (Perspecta Labs), Fan Bai (GM), Gunjan Verma (Devcom Army Research Lab)

Projects and Sponsors


  • Jupiter: a Containerized Dispersed Computing Orchestrator. Open Source Code (Python) at https://github.com/ANRGUSC/Jupiter
  • Short Video Talk by ANRG member Jared Coleman on Network Synthesis for Dispersed Computing:





  1. Jared Coleman, Eugenio Grippo, Bhaskar Krishnamachari, Gunjan Verma, “Multi-objective network synthesis for dispersed computing in tactical environments” SPIE Conference on Signal Processing, Sensor/Information Fusion, and Target Recognition XXXI
    4 – 6 April 2022.
  2. Mehrdad Kiamari and Bhaskar Krishnamachari, “GCNSCheduler: Scheduling Distributed Computing Applications using Graph Convolutional Networks,” Online Preprint arXiv:2110.11552, 2021.
  3. Pradipta Ghosh, Quynh Nguyen, Pranav K. Sakulkar, Jason A. Tran, Aleksandra Knezevic, Jiatong Wang, Zhifeng Lin, Bhaskar Krishnamachari, Murali Annavaram, Salman Avestimehr, “Jupiter: a networked computing architecture,” 14th IEEE/ACM International Conference on Utility and Cloud Computing Companion, 2021.
  4. Alexander Poylisher, Andrzej Cichocki, K. Guo, J. Hunziker, Latha A. Kant, Bhaskar Krishnamachari, Salman Avestimehr, Murali Annavaram, “Tactical Jupiter: Dynamic Scheduling of Dispersed Computations in Tactical MANETs,” IEEE MILCOM 2021.
  5. Yi-Hsuan Kao, Kwame Wright, Po-Han Huang, Bhaskar Krishnamachari and Fan Bai, “MABSTA: Collaborative Computing over Heterogeneous Devices in Dynamic Environments“, IEEE International Conference on Computer Communications (INFOCOM), 2020.
  6. Diyi Hu, Bhaskar Krishnamachari, “Fast and accurate streaming CNN inference via communication compression on the edge,” 5th ACM/IEEE conference on internet of things design and implementation (IoTDI), April, 2020.
  7. Pradipta Ghosh, Quynh Nguyen, and Bhaskar Krishnamachari, “Container Orchestration for Dispersed Computing,” In 5th International Workshop on Container Technologies and Container Clouds (WOC ’19), December 2019.
  8. Diyi Hu, Bhaskar Krishnamachari, “Throughput Optimized Scheduler for Dispersed Computing Systems,” In 7th IEEE International Conference on Mobile Cloud Computing, Services, and Engineering (Mobile-Cloud), San Francisco, USA, 2019.
  9. Quynh Nguyen, Pradipta Ghosh, and Bhaskar Krishnamachari, “End-to-End Network Performance Monitoring for Dispersed Computing,” International Conference on Computing, Networking and Communications, March 2018.
  10. Yi-Hsuan Kao, Bhaskar Krishnamachari, “Optimizing Mobile Computational Offloading with Delay Constraints“, IEEE Global Communications Conference (GLOBECOM), 2014.
  11. Yi-Hsuan Kao, Bhaskar Krishnamachari, Moo-Ryong Ra and Fan Bai, “Hermes: Latency Optimal Task Assignment for Resource-constrained Mobile Computing“, International Conference on Computer Communication (INFOCOM), 2015.
  12. Yi-Hsuan Kao, “Optimizing Task Aassignment for Ccollaborative Computing over Heterogeneous Network Devices“, PhD Thesis, USC, 2016.