Abstract: Slow tasks in Spark computing environments extend stage execution time. Spark uses speculative execution to solve the straggler problem by launching extra backup for the straggler to finish early. The Spark original and improved…
Abstract: Cloud computing and big data are used most to meet user functional requirements. Big data analysis, conversion, extraction, and refinement can prevent disease and predict group behavior. Big data includes users’ private data. Service…
Abstract: Modular inversion is a frequent and time-consuming operation in cryptography and algorithmic number theory. Since modular inversion requires many operations on large numbers, resource-constrained clients like mobile devices and IC cards cannot directly perform…
Abstract: First evaluated for multi-level cell memory applications were amorphous indium-gallium-zinc oxide (a-IGZO) thin-film transistor nonvolatile memory devices with an IGZO charge storage layer. The original state (OS) of the pristine device can be switched…
Abstract: Network Function Virtualization (NFV) is a promising networking technology for heterogeneous and complex network services. NFV separates network functions from hardware. Telecom providers place VNFs on software-based middleboxes in the NFV architecture. Traffic follows…
Abstract: Tail latency reduction improves service experience. User-facing latency-sensitive cloud applications typically have multiple interactive tiers (e.g., Web, App, Database) running in different VMs with complex interaction patterns. Previous VM consolidation methods neglected such VM-tier…
Abstract: Military and government agencies are becoming more interested in fog computing. The Internet-of-Things (IoT) and society’s interconnectivity contribute to this. Fog computing deployment requires privacy protection. This paper introduces fog-based access filter (FAF), a…
Abstract: Tenants want automatic MapReduce resource estimation tools to move cloud computing from pay-per-request to pay-per-use. These tools require accurate workload, resource, and completion time quantification. Prediction models exist. None of these models account for…
Abstract: Large-scale cloud infrastructure resource management requires improving data center energy efficiency while guaranteeing Quality of Service (QoS) and detecting server performance variability caused by hardware or software failures. Dynamic Virtual Machine (VM) consolidation works…
Abstract: MCC is promoted to improve mobile users’ service experience. MCC offloads computation-intensive applications from smart mobile devices (SMDs) to the cloud, but it also increases cloud center computing and storage overhead and wireless link…
Abstract: Healthcare Internet-of-Things (IoT) allows embedded devices to monitor patient vital signs and aggregate and outsource data to the cloud. The cloud lets authorized users store and share data for on-demand services. However, untrusted networks,…
Abstract: MapReduce frameworks will be used to analyze ever-growing data volumes as large-scale data analytics becomes standard in various industries. This encourages MapReduce migration to multi-tenant clouds. In a shared cluster, time-varying network bandwidth can…
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