Online Auction of Cloud Resources in Support of the Internet of Things

Abstract

Internet of Things (IoT) applications can benefit greatly from cloud-hosted message broker services that utilize publish–subscribe communications. The operators of IoT cloud-hosted services are often interested in delivering services that maximize their revenue given quality of service guarantees. In this paper, we formulate the problem of maximizing the profit of the service provider given the prior knowledge of the request sequence as an integer linear program and prove that it is strongly NP-complete, and thus there is no fully polynomial-time approximation scheme for the problem, unless ${P=} \text {NP}$ . Due to the above-mentioned problem and the difficulty of obtaining the request sequence in advance in real-world scenarios, we propose an auction-based online algorithm that does not require the prior knowledge of the request sequence. We prove that the competitive ratio of the online algorithm is ${\mathcal {O}(\log (N))}$ , where ${N}$ is the number of cloud zones that host the publish–subscribe services. Moreover, we show that no online algorithm can achieve a competitive ratio better than ${\Omega (\log (N))}$ . Therefore, our online algorithm achieves the optimal competitive ratio in the asymptotic sense. Our simulations, based on real data traces, show that our algorithm achieves up to 83% more profit compared to a heuristic approach, while consuming 60% less resources.