Online Cost-effective Edge Service Renting for Content Providers in Cloud and Edge Environments

Abstract

For solving the problem of high bandwidth costs and service delays faced by content service providers (CSPs), edge computing services can be used as a supplement to existing cloud data centers for building more efficient Content Delivery Networks (CDNs). When there are a large number of requests for a content in one certain area, the content service provider can choose to rent an edge computing service near this area to lower the bandwidth cost for content delivery. But if the requests then drop after that, additional costs will be incurred instead due to the edge service renting. Therefore, it is necessary to dynamically decide whether to rent an edge service according to the request arrival situations in the future, but the future is often difficult to predict. For dealing with this problem, we propose an online edge service renting approach, as well as a corresponding request redirection algorithm, which can help content service providers save bandwidth cost significantly, while without requiring any knowledge about the future. Through theoretical analysis, we prove that the cost achieved by our online algorithm won't exceed 2 - α times compared to the optimal offline algorithm, where α is the bandwidth discount between edge and cloud services. Finally, by conducting extensive simulations with both real-world and synthetic data, we verify that our online edge service renting approach can effectively save costs for CSPs.