Collaborative Edge Computing (CEC) is a new edge computing paradigm that enables neighboring edge servers to share computational resources with each other. Although CEC can enhance the utilization of computational resources, it still suffers from resource waste. The primary reason is that end-users from the same area are likely to offload similar tasks to edge servers, thereby leading to duplicate computations. To improve system efficiency, the computation results of previously executed tasks can be cached and then reused by subsequent tasks. However, most existing computation reuse algorithms only consider one edge server, which significantly limits the effectiveness of computation reuse. To address this issue, this paper applies computation reuse in CEC networks to exploit the collaboration among edge servers. We formulate an optimization problem that aims to minimize the overall task response time and decompose it into a caching subproblem and a scheduling subproblem. By analyzing the properties of optimal solutions, we show that the optimal caching decisions can be efficiently searched using the bisection method. For the scheduling subproblem, we utilize projected gradient descent and backtracking to find a local minimum. Numerical results show that our algorithm significantly reduces the response time in various situations.

翻译：协同边缘计算（CEC）是一种新的边缘计算范式，允许相邻边缘服务器之间共享计算资源。尽管CEC可以提高计算资源的利用率，但仍存在资源浪费的问题。其主要原因是来自同一区域的终端用户可能向边缘服务器卸载相似的任务，从而导致重复计算。为了提升系统效率，可以将先前执行任务的计算结果缓存起来，供后续任务复用。然而，现有大多数计算复用算法仅考虑单个边缘服务器，这显著限制了计算复用的效果。为解决这一问题，本文在CEC网络中应用计算复用，以利用边缘服务器之间的协作。我们建立了一个优化问题，旨在最小化整体任务响应时间，并将其分解为缓存子问题和调度子问题。通过分析最优解的性质，我们展示了最优缓存决策可以通过二分法高效搜索。对于调度子问题，我们利用投影梯度下降法和回溯法寻找局部最优解。数值结果表明，我们的算法在不同场景下均能显著降低响应时间。