原標題：邊緣計算 | SCI期刊JoCCASA誠邀專刊稿件

期刊基本信息

期刊名稱

Journal of Cloud Computing: Advances, Systems and Applications

影響因子

2.14

期刊難度

★ ★

領域

計算機體系結構,并行與分布式計算

JCR分區

大類 : 工程技術 - 3區

小類 : 計算機：信息系統 - 3區

專刊名稱

Call for papers: Edge-cloud computing cooperation for task offloading in internet-of-things

專刊簡介

With the fast development trend of Internet of Things (IoTs), the demand for User Terminals (UTs) such as smartphones, unmanned aerial vehicles, and wearable devices is increasing dramatically. However, UTs are constrained by limited resources, such as CPU computing power, storage space, energy capacities, environmental awareness and complex computing tasks. To solve the above contradictions, one effective way is to offload complex computing tasks from UTs either to remote cloud servers or nearby edge servers. Compared to cloud servers, edge servers are closer to UTs and thus achieve lower latency; however, edge servers have low computing capacity while cloud servers have relatively sufficient computing power. Therefore, edge computing and cloud computing can cooperate and complement with each other in terms of computing, storage, and communication facilities. The combination of edge and cloud computing will make task execution faster, cheaper, and more stable.

This thematic series is devoted to state-of-the-art research covering concepts of task offloading technologies for IoT applications. It is of great significance to the rapid promotion of collaboration between Mobile Cloud Computing (MCC) and Mobile Edge Computing (MEC). With the continuous development of theory and methods of decision-making and thorough perception of the hybrid task offloading, and further meets the application requirements on UTs, compensates for the lack of computing capacity and limited battery power for IoT systems.

關鍵日期

Submission Deadline

2020-09-01

征稿主題

Topics of interest include but are not limited to:返回搜狐，查看更多

Computing paradigm frontiers: edge, fog, mist and cloud computing cooperation

Optimization algorithms for edge-cloud computing cooperation

Delay and energy minimization for edge-cloud computing cooperation

Novel techniques and future perspectives for edge-cloud computing cooperation

Energy-efficient task offloading in edge-cloud computing environments

5G-enabled services for task offloading in edge-cloud computing environments

Security and privacy issues for task offloading with hybrid clouds in IoTs

Model and architecture design for computation offloading, resource management and task scheduling in IoTs

Computation and communication integration for task offloading in IoTs

High-performance low-cost communication task offloading in IoTs

Sustainable and green computing for task offloading in IoTs

Deep learning-driven algorithms for task offloading in IoTs

責任編輯：

與50位技術專家面對面20年技術見證，附贈技術全景圖

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