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In sprite the state-of-the-art, significantly reducing carbon footprint (CF)in communications systems remains urgent. We address this challenge in thecontext of edge computing. The carbon intensity of electricity supply largelyvaries spatially as well as temporally. This, together with energy sharing viaa battery management system (BMS), justifies the potential of CF-oriented taskoffloading, by redistributing the computational tasks in time and space. Inthis paper, we consider optimal task scheduling and offloading, as well asbattery charging to minimize the total CF. We formulate this CF minimizationproblem as an integer linear programming model. However, we demonstrate that,via a graph-based reformulation, the problem can be cast as a minimum-cost flowproblem. This finding reveals that global optimum can be admitted in polynomialtime. Numerical results using real-world data show that optimization can reduceup to 83.3% of the total CF.

Less Carbon Footprint in Edge Computing by Joint Task Offloading and Energy Sharing