Summary: | With the advancement of wireless networking technologies and communication infrastructures, mobile cloud computing has emerged as a pervasive paradigm to execute computing tasks for capacity-limited mobile devices. More specifically, at the network edge, the resource-rich and trusted cloudlet system can provide in-proximity computing services by executing the workloads for nearby devices. Nevertheless, there are chances for malicious users to generate distributed denial-of-service (DDoS) flooding tasks to overwhelm cloudlet servers and block computing services from legitimate users. Load balancing is one of the most effective methods to solve DDoS attacks in distributed networks. However, existing solutions require overall load information to achieve load balancing in cloudlet networks, making it costly in both communication and computation. To achieve more efficient and low-cost load balancing, we propose CTOM, a novel collaborative task offloading scheme to avoid DDoS attacks for secure and sustainable mobile cloudlet networks. The proposed solution is based on the balls-and-bins theory and it can balance the task loads with extremely limited information. The CTOM reduces the number of overloaded cloudlets smoothly, thus handling the potential DDoS attacks in mobile cloudlet networks. Extensive simulations and evaluation demonstrate that, the proposed CTOM outperforms the conventional random and proportional allocation schemes in reducing the task gaps between maximum load and minimum load among mobile cloudlets by 65% and 55%, respectively.
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