Risk-sensitive task fetching and offloading for vehicular edge computing
Batewela, Sadeep; Liu, Chen-Feng; Bennis, Mehdi; Suraweera, Himal A.; Hong, Choong Seon (2019-12-19)
S. Batewela, C. Liu, M. Bennis, H. A. Suraweera and C. S. Hong, "Risk-Sensitive Task Fetching and Offloading for Vehicular Edge Computing," in IEEE Communications Letters, vol. 24, no. 3, pp. 617-621, March 2020.
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This letter studies an ultra-reliable low latency communication problem focusing on a vehicular edge computing network in which vehicles either fetch and synthesize images recorded by surveillance cameras or acquire the synthesized image from an edge computing server. The notion of risk-sensitive in financial mathematics is leveraged to define a reliability measure, and the studied problem is formulated as a risk minimization problem for each vehicle’s end-to-end (E2E) task fetching and offloading delays. Specifically, by resorting to a joint utility and policy estimation-based learning algorithm, a distributed risk-sensitive solution for task fetching and offloading is proposed. Simulation results show that our proposed solution achieves performance improvements up to 40% variance reduction and steeper distribution tail of the E2E delay over an averaged-based baseline.
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