Memory-intensive applications, such as in-memory databases, caching systems, and key-value stores, are increasingly demanding larger main memory to fit their working sets. Conventional swapping can enlarge the memory capacity by paging out inactive pages to backend stores. However, existing swapping solutions suffer several performance and compatibility issues, making them unsuitable for high-concurrency and memory-intensive applications. In this article, we redesign the swapping system and propose Lightswap, a high-performance user-space swapping solution that supports paging with both local SSDs and remote memories. First, to avoid kernel involvement, we propose to leverage the extended Berkeley packet filter (eBPF) for handling page faults (PFs) in user space and further eliminate the heavy I/O stack with the help of user-space I/O drivers. Then, we co-design the PF handling with lightweight thread (LWT) scheduling to improve system throughput and reduce the end-to-end PF latency. Finally, we propose a try-catch framework in Lightswap to deal with swap-in errors which have been exacerbated by the scaling in process technology. We implement Lightswap in our production-level system and evaluate it with various benchmarks. Results show that Lightswap achieves scalable PF notification latency ($4 \mu \text{s}$under 128 LWTs), reduces the PF handling latency by 3–5 times, and improves the throughput of memcached by more than 40% compared with the state-of-art swapping systems.

In this paper a novel (t, n) threshold image secret sharing scheme is proposed. Based on the idea that there is close connection between secret sharing and coding theory, coding method on GF(2m) is applied in our scheme instead of the classical Lagrange's interpolation method in order to deal with the fidelity loss problem in the recovery. All the generated share images are meaningful and the size of each share image is the same as the secret image. The analysis proves our scheme is perfect and ideal and also has high security. The experiment results demonstrate that all the shares have high quality and the secret image can be recovered exactly.

Image sharing is an attractive research subject in computer image techniques and in the information security field. This article presents a novel scheme of image sharing with a ( t , n ) high-security threshold structure. The scheme can encode secret images into n shadow images in such a way that all the shadow images are in a perfect and ideal ( t , n ) threshold structure, while each shadow image has its own visual content assigned at random. The most common method to implement image sharing is based on interpolation polynomial over the field F p ={0, 1, 2,…, p -1} [Shamir 1979]. In this article, the authors present a new approach to image sharing and its computation based on algebraic-geometry code over the pixel value field GF(2 m ).

Grid has been widely used in the field of evolutionary multi-objective optimization (EMO) due to its property combining convergence and diversity naturally. Most EMO algorithms of grid-based fitness perform well on problems with two or three objectives, but encounter difficulties in their scalability to many-objective optimization. This paper develops the potential of using grid technique to balance convergence and diversity in fitness for many-objective optimization problems. To strengthen selection pressure and refine comparison level, three hierarchical grid-based criterions are incorporated into fitness to establish a completer order among individuals. Moreover, an adaptive fitness penalty mechanism in environmental selection is employed to guarantee the diversity of archive memory. Based on an extensive comparative study with three other EMO algorithms, the proposed algorithm is found to be remarkably successful in finding well-converged and well-distributed solution set.