Abstract
Mobile Cloud Computing or Fog computing refers to offloading computationally intensive algorithms from a mobile device to the cloud or an intermediate cloud in order to save resources e.g., time and energy in the mobile device. This paper proposes new solutions for situations when the cloud or fog is not available. First, the sensor network is modelled using a network of queues, then a linear programming technique is used to make scheduling decisions. Various centralized and distributed algorithms are then proposed, which improves overall system performance. Extensive simulations show slightly higher energy usage in comparison to the baseline non-offloading case, however, the job completion rate is significantly improved, the efficiency score metric shows the extra energy usage is justified. The algorithms have been simulated in various environments including high and low bandwidth, partial connectivity, and different rate of information exchanges to study the pros and cons of the proposed algorithms.
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