Browsing by Author "Li, Yong"
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- Evidence-aware Mobile Computational Offloading
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä(2018-08) Flores, Huber; Hui, Pan; Nurmi, Petteri; Lagerspetz, Eemil; Tarkoma, Sasu; Manner, Jukka; Kostakos, Vassilis; Li, Yong; Su, XiangComputational offloading can improve user experience of mobile apps through improved responsiveness and reduced energy footprint. Currently, offloading decisions are predominantly based on profiling performed on individual devices. While significant gains have been shown in benchmarks, these gains rarely translate to real-world use due to the complexity of contexts and parameters that affect offloading. We contribute by proposing crowdsensed evidence traces as a novel mechanism for improving the performance of offloading systems. Instead of limiting to profiling individual devices, crowdsensing enables characterising execution contexts across a community of users, providing better generalisation and coverage of contexts. We demonstrate the feasibility of using crowdsensing to characterize offloading contexts through an analysis of two crowdsensing datasets. Motivated by our results, we present the design and development of EMCO toolkit and platform as a novel solution for computational offloading. Experiments carried out on a testbed deployment in Amazon EC2 Ireland demonstrate that EMCO can consistently accelerate app execution while at the same time reduce energy footprint. We demonstrate that EMCO provides better scalability than current cloud platforms, being able to serve a larger number of clients without variations in performance. Our framework, use cases, and tools are available as open source from github. - Fog following me: Latency and quality balanced task allocation in vehicular fog computing
A4 Artikkeli konferenssijulkaisussa(2018-06) Zhu, Chao; Pastor Figueroa, Giancarlo; Xiao, Yu; Li, Yong; Ylä-Jääski, AnttiEmerging vehicular applications, such as real-time situational awareness and cooperative lane change, demand for sufficient computing resources at the edge to conduct time-critical and data-intensive tasks. This paper proposes Fog Following Me (Folo), a novel solution for latency and quality balanced task allocation in vehicular fog computing. Folo is designed to support the mobility of vehicles, including ones generating tasks and the others serving as fog nodes. We formulate the process of task allocation across stationary and mobile fog nodes into a joint optimization problem, with constraints on service latency, quality loss, and fog capacity. As it is a NP-hard problem, we linearize it and solve it using Mixed Integer Linear Programming. To evaluate the effectiveness of Folo, we simulate the mobility of fog nodes at different times of day based on real-world taxi traces, and implement two representative tasks, including video streaming and real-time object recognition. Compared with naive and random fog node selection, the latency and quality balanced task allocation provided by Folo achieves higher performance. More specifically, Folo shortens the average service latency by up to 41% while reducing the quality loss by up to 60%. - Folo: Latency and Quality Optimized Task Allocation in Vehicular Fog Computing
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä(2019-06) Zhu, Chao; Tao, Jin; Pastor Figueroa, Giancarlo; Xiao, Yu; Ji, Yusheng; Zhou, Quan; Li, Yong; Ylä-Jääski, AnttiWith the emerging vehicular applications such as real-time situational awareness and cooperative lane change, there exist huge demands for sufficient computing resources at the edge to conduct time-critical and data-intensive tasks. This paper proposes Folo, a novel solution for latency and quality optimized task allocation in Vehicular Fog Computing (VFC). Folo is designed to support the mobility of vehicles, including vehicles that generate tasks and the others that serve as fog nodes. Considering constraints on service latency, quality loss, and fog capacity, the process of task allocation across stationary and mobile fog nodes is formulated into a joint optimization problem. This task allocation in VFC is known as a non-deterministic polynomial-time hard (NP-hard) problem. In this paper, we present the task allocation to fog nodes as a bi-objective minimization problem, where a trade-off is maintained between the service latency and quality loss. Specifically, we propose an event-triggered dynamic task allocation (DTA) framework using Linear Programming based Optimization (LBO) and Binary Particle Swarm Optimization (BPSO). To assess the effectiveness of Folo, we simulated the mobility of fog nodes at different times of a day based on real-world taxi traces and implemented two representative tasks, including video streaming and real-time object recognition. Simulation results show that the task allocation provided by Folo can be adjusted according to actual requirements of the service latency and quality, and achieves higher performance compared with naive and random fog node selection. To be more specific, Folo shortens the average service latency by up to 27% while reducing the quality loss by up to 56%. - Microstructural evolution and properties of electromagnetic cast-rolled novel Al–Li alloy under different heat treatment procedures
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä(2022-01-01) Li, Yong; Li, Shiju; Wei, Bowen; Xu, Jiujian; Lian, Junhe; Xu, Guangming; Wang, ZhaodongA large number of dislocations and dislocation tangles are induced in the Al–Li alloy after 5% pre-stretching deformation before aging treatment, which increases the density of the defects in α(Al) matrix and affects the competitive precipitation relationship and precipitation behavior of δ′ (Al3Li), S′ (Al2CuMg) and T1 (Al2CuLi) precipitates during the aging process. The increase of crystal defects such as dislocations provides superior nucleation sites for the heterogeneous nucleation and promotes the precipitation of T1 phase, greatly improving the mechanical properties of the alloy. The uniform and dense precipitation of T1 phase in the grain reduces the potential difference between the grains and the grain boundaries. Therefore, not only does it reduce the driving force of intergranular corrosion (IGC), but also decreases the difference of the corrosion rate between the grain boundary and intragranular. These are beneficial to slow down the corrosion process and promote uniform corrosion. The intermittently distributed grain boundary precipitates (GBPs) in the T8 treated alloy cut off the continuous corrosion channel at grain boundaries and hinder the IGC process. Furthermore, the width of the precipitation free zones (PFZs) in the T8 treated alloy is narrow. Hence, the alloy exhibits excellent IGC resistance and superior corrosion protection performance under T8 single aging treatment. The pre-aging process in low temperature before T8 single aging treatment greatly enhances the precipitation driving force of T1 phase and effectively promotes the precipitation of T1 phase in the subsequent high-temperature aging process, which further increases the strength and improves the IGC resistance of the alloy. - Secure deduplication of encrypted data: Refined model and new constructions
A4 Artikkeli konferenssijulkaisussa(2018-01-01) Liu, Jian; Duan, Li; Li, Yong; Asokan, N.Cloud providers tend to save storage via cross-user deduplication, while users who care about privacy tend to encrypt their files on client-side. Secure deduplication of encrypted data (SDoE) which aims to reconcile this apparent contradiction is an active research topic. In this paper, we propose a formal security model for SDoE. We also propose two single-server SDoE protocols and prove their security in our model. We evaluate their deduplication effectiveness via simulations with realistic datasets.