Editorial: Advances in Mobile, Edge and Cloud Computing
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Editorial: Advances in Mobile, Edge and Cloud Computing Xiaowen Chu 1 & Hongbo Jiang 2 & Bo Li 3 & Dan Wang 4 & Wei Wang 3
# Springer Science+Business Media, LLC, part of Springer Nature 2020
Editorial: Emerging mobile applications exhibit heterogeneous requirements on the computing power, communication bandwidth, security and privacy. Given the restriction on the computing capability on battery-operated mobile devices, a variety of offloading techniques have been designed to leverage the abundant computing resources available on cloud servers. Mobile Cloud Computing provides enormous computing and storage resources for mobile applications that can tolerate a certain level of network delay, while Mobile Edge Computing offers an intelligent platform to enhance mobile devices’ capabilities and improve the Quality of Service of mobile applications. Both Mobile Cloud Computing and Mobile Edge Computing are key enabling paradigms for emerging mobile applications in Internet of Things (IoT), smart grids, robotics, crowd sensing, etc. New research challenges arise due to the heterogeneity of computing and network resources across the mobile devices, edge servers, and remote data centers. Aiming to address the challenges in resource planning and management, scheduling, networking, security and privacy in mobile edge and cloud computing, this special issue features nine selected articles with high quality. The first article, “Batch Auction Design for Cloud Container Services”, proposes efficient market mechanisms for container based cloud service. To simultaneously achieve incentive compatibility, computational efficiency, and economic efficiency, the
* Xiaowen Chu [email protected] 1
Hong Kong Baptist University, 224 Waterloo Rd, Kowloon Tong, Hong Kong
2
Hunan University, 2 Lushan S Rd, Yuelu District, Changsha, Hunan, China
3
The Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong
4
The Hong Kong Polytechnic University, 11 Yuk Choi Rd, Hung Hom, Hong Kong
authors leveraged compact exponential integer linear program, posted price auction, and primal-dual algorithms. Theoretical analysis and trace-driven empirical evaluation verify the efficacy of the proposed container auction algorithms. The second article entitled “Computing Cost Optimization for Multi-BS in MEC by Offloading” presents two novel task offloading strategies to optimally assign IoT tasks to multiple edge servers deployed at base stations. The offloading strategies, which are based on Genetic Algorithm, offload as many tasks as possible while taking into account both the computation overhead and energy consumption. Extensive numerical experiments are presented to demonstrate the effectiveness of the proposed offloading strategies. In the next article with the title “Effective Mobile Target Searching Using Robots”, the authors studied a robotics application in which a swarm of Unmanned Aerial Vehicles (UAVs) collaboratively search for a set of targets. They proposed a divide-and-conquer approach with two searching strate
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