基於霧運算之物聯網服務的復原力軟體架構設計

隨著物聯網時代的來臨，大量的終端裝置進入了網際網路中並產生大量的資料，使得情境感知計算的服務模式變得更廣泛，進而提升智慧城市與工業4.0的應用。終端裝置收集的資料被集中傳送到擁有豐富計算與儲存資源的雲端系統進行巨量資料的分析。然而，將這些從網路邊際端收集到的資料集中移送到遠端的資料中心作分析不但增加延遲性，也消耗網路的頻寬。霧運算被用來延伸雲端運算的計算智慧到應用情境的網路邊際端來提升即時性應用的反應速度即減少因資料訊息傳遞所產生的延遲。霧運算在很多物聯網應用上扮演重要的角色，例如：交通流量控制及空氣汙染監控。恢復力是指當環境狀態改變時維持系統可信度的能力。恢復力已經成為未來可信度計算研究的重要研究方向。霧運算系統架構是一個具有高異質軟體與硬體系統，因而使得其計算環境有較差的可信度。因此，在霧運算服務成為高效能運算的模式之一時，提升霧運算系統的恢復力是必要的事務，進而使其運作的環境在其狀態動態改變時依然保持其可信度。既然為物聯網應用而發展的霧運算系統將越來越受重視，相關的服務跟應用也應該被逐步的發展。因此，霧運算服務系統成為智慧城市與工業4.0的關鍵在於其具恢復力與否，並決定是否霧運算未來將被發展為新興的商業模式。在本論文將探討設計具恢復力霧運算服務系統的研究挑戰及提出解決方式。首先，本論文中提出一個基於霧運算的事件導向服務機制以在霧運算環境上建立事件導向服務。除此之外，為了評估提出服務機制的正確性，設計了一個服務案例作說明，並提出一個評估系統來評估事件導向服務設計的正確性。另外，在本論文中亦提出一個程式框架輔助應用開發者去開發容錯機制在物聯網裝置上。應用開發者可以有效的在物聯網裝置上使得恢復力在物聯網裝置上可以提升。

關鍵字

霧運算；物聯網服務；複雜事件處理；事件導向服務；程式抽象化；恢復力；錯誤容忍

並列摘要

With the advent of the Internet of Things (IoT) era, a variety of terminal devices have entered the Internet and generated a lot of information, making the context-aware computing service model more widespread, which promotes the applications of smart city and Industry 4.0. The collected big data is sent to a central cloud system with sufficient computing and storage resources for big data analytics. However, moving this big volume of data from the network edge to the central data center for analytics not only adds latency but also consumes network bandwidth. Fog computing is employed to extend the intelligence of cloud computing to the edge of the application context to increase the responsiveness of real-time applications and reduce the latency in message delivery. Fog computing plays a vital role in various IoT application solutions, such as traffic flow control and air pollution monitoring. Resilience means the ability to maintain the dependability of a system while the state of the context changes. It has become the main future research direction in the area of dependable computing. Fog computing is a system architecture that integrates highly heterogeneous software and hardware systems, which makes its computing environment highly undependable. Therefore, if the fog computing service to be one of the high-performance computing models, it is necessary to enhance the resilience of the fog computing system so that the operating environment still maintains its dependability even in the state under the dynamic changes. Since developing fog computing systems for IoT applications will be more and more prevalent, related services and applications should also be gradually developed. Therefore, high resilient fog service systems will be the key in the area of smart city and industry 4.0 to determine whether the fog computing will further be developed into an emerging business model. The research challenges in designing resilient fog computing service system was be investigated and propose solutions in this thesis. First, a fog-based event-driven service mechanism to build event-driven service on fog computing is proposed in this thesis. Furthermore, to evaluate correctness of propose service mechanism, a case study was devised to be examined, and proposed a evaluation system to evaluate correctness of event-driven service design. Second, a programming framework to assist application developers to program fault-tolerant mechanism on IoT device is proposed in this thesis. Application developers can realize fault-tolerant programming efficiently on IoT device, and the resilience of IoT applications executed on IoT device can be improved.

並列關鍵字

Fog Computing ； IoT Services ； Complex Event Processing ； Event-Driven Services ； Programming Abstraction ； Resilience ； Fault Tolerance

參考文獻

[1] Varshney, P. and Simmhan, Y.: Demystifying Fog Computing: Characterizing Architectures, Applications, and Abstractions. In: 1st IEEE international Conference on Fog and Edge Computing (ICFEC), pp. 115-124. IEEE Press (2017).

[4] Wen, Z., Yang, R., Garraghan, P., Lin, T., Xu, J., and Rovatsos, M.: Fog Orchestration for Internet of Things Services. IEEE Internet Computing 21(2), 16-24 (2017).

[6] Gerla, M., Lee, E. K., Pau, G., and Lee, U: Internet of Vehicles: From Intelligent Grid to Autonomous Cars and Vehicular Clouds. In: IEEE World Forum on Internet of Things (WF-IoT), pp. 241–246. IEEE Press (2014).

[7] Luckham, D. C.: The Power of Events: An Introduction to Complex Event Processing in Distributed Enterprise Systems. Addison-Wesley (2001).

[8] Terroso-Saenz, F., Valdes-Vela, M., Sotomayor-Martinez, C., Toledo-Moreo, R., and Gomez-Skarmeta, A. F.: A Cooperative Approach to Traffic Congestion Detection with Complex Event Processing and VANET. IEEE Transactions on Intelligent Transportation Systems 13(2), 914–929 (2012).

國際替代計量

基於霧運算之物聯網服務的復原力軟體架構設計

全文下載

主題瀏覽