Order Preserving Stream Processing in Fog Computing Architectures

A Fog Computing architecture consists of edge nodes that generate and possibly pre-process (sensor) data, fog nodes that do some processing quickly and do any actuations that may be needed, and cloud nodes that may perform further detailed analysis for long-term and archival purposes. Processing of a batch of input data is distributed into sub-computations which are executed at the different nodes of the architecture. In many applications, the computations are expected to preserve the order in which the batches arrive at the sources. In this paper, we discuss mechanisms for performing the computations at a node in correct order, by storing some batches temporarily and/or dropping some batches. The former option causes a delay in processing and the latter option affects Quality of Service (QoS). We bring out the trade-offs between processing delay and storage capabilities of the nodes, and also between QoS and the storage capabilities.

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Vehicular Fog Computing: The Need for a New Paradigm and its Issues

International Journal of Engineering & Technology ◽

10.14419/ijet.v7i2.7.10890 ◽

2018 ◽

Vol 7 (2.7) ◽

pp. 606

Author(s):

G Sri Gnana Deepika ◽

P Sai Kiran

Keyword(s):

Cloud Computing ◽

Quality Of Service ◽

Fog Computing ◽

Cloud Services ◽

New Paradigm ◽

Smart Vehicles ◽

Vehicular Cloud Computing ◽

Security Challenges ◽

And Storage

Smart vehicles participating in VANET have high computing capabilities which lead the demand to support more applications that give safety and effective measures to people. The vehicles in VANET are taking the help of cloud services for communication, computation and storage which benefits in economical way and we call that as vehicular cloud computing (VCC). Due to certain limitations in VCC and also demand for more quality of service applications in smart vehicles a new paradigm called vehicular fog computing (VFC) is proposed which helps to overcome limitations in VCC and provide more quality services to users participating in VANET. Some of the security challenges and possible attacks in VFC are also stated.

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THE EFFECT OF CUSTOMER ENGAGEMEMTN EXPERIENCE ON REPURCHASE INTENTION BASED ON THE CAPAABILITY OF TECHNICAL SUPPORT OF SALESPERSON IN CUSTOMER PERCEIVED QUALITY OF SERVICE: FOCUSED ON THE ENERGY INDUSTRY IN NEED OF LONG-TERM SERVICE

Global Fashion Management Conference ◽

10.15444/gmc2020.05.03.03 ◽

2020 ◽

Vol 2020 ◽

pp. 598-598

Keyword(s):

Quality Of Service ◽

Perceived Quality ◽

Technical Support ◽

Energy Industry ◽

Repurchase Intention

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Simulation and Emulation Tools for Fog Computing

Recent Advances in Computer Science and Communications ◽

10.2174/2666255813999201002152003 ◽

2020 ◽

Vol 13 ◽

Author(s):

Simar Preet Singh ◽

Rajesh Kumar ◽

Anju Sharma ◽

S. Raji Reddy ◽

Priyanka Vashisht

Keyword(s):

Quality Of Service ◽

Programming Languages ◽

Traffic Management ◽

Fog Computing ◽

Research Work ◽

Research Experience ◽

Computing Paradigm ◽

Quality Of Service Parameters ◽

User Friendly

Background: Fog computing paradigm has recently emerged and gained higher attention in present era of Internet of Things. The growth of large number of devices all around, leads to the situation of flow of packets everywhere on the Internet. To overcome this situation and to provide computations at network edge, fog computing is the need of present time that enhances traffic management and avoids critical situations of jam, congestion etc. Methods: For research purposes, there are many methods to implement the scenarios of fog computing i.e. real-time implementation, implementation using emulators, implementation using simulators etc. The present study aims to describe the various simulation and emulation tools for implementing fog computing scenarios. Results: Review shows that iFogSim is the simulator that most of the researchers use in their research work. Among emulators, EmuFog is being used at higher pace than other available emulators. This might be due to ease of implementation and user-friendly nature of these tools and language these tools are based upon. The use of such tools enhance better research experience and leads to improved quality of service parameters (like bandwidth, network, security etc.). Conclusion: There are many fog computing simulators/emulators based on many different platforms that uses different programming languages. The paper concludes that the two main simulation and emulation tools in the area of fog computing are iFogSim and EmuFog. Accessibility of these simulation/emulation tools enhance better research experience and leads to improved quality of service parameters along with the ease of their usage.

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Measuring patient engagement among cancer patients in eHealth and mHealth interventions on symptom management: an integrated review (Preprint)

10.2196/preprints.17966 ◽

2020 ◽

Author(s):

Juqing Zhao ◽

Pei Chen ◽

Guangming Wan

Keyword(s):

Cancer Patients ◽

Patient Engagement ◽

Symptom Management ◽

Subjective Experience ◽

Participation Rate ◽

Sensor Data ◽

Quality Of Data ◽

Mhealth Intervention

BACKGROUND There has been an increase number of eHealth and mHealth interventions aimed to support symptoms among cancer survivors. However, patient engagement has not been guaranteed and standardized in these interventions. OBJECTIVE The objective of this review was to address how patient engagement has been defined and measured in eHealth and mHealth interventions designed to improve symptoms and quality of life for cancer patients. METHODS Searches were performed in MEDLINE, PsychINFO, Web of Science, and Google Scholar to identify eHealth and mHealth interventions designed specifically to improve symptom management for cancer patients. Definition and measurement of engagement and engagement related outcomes of each intervention were synthesized. This integrated review was conducted using Critical Interpretive Synthesis to ensure the quality of data synthesis. RESULTS A total of 792 intervention studies were identified through the searches; 10 research papers met the inclusion criteria. Most of them (6/10) were randomized trial, 2 were one group trail, 1 was qualitative design, and 1 paper used mixed method. Majority of identified papers defined patient engagement as the usage of an eHealth and mHealth intervention by using different variables (e.g., usage time, log in times, participation rate). Engagement has also been described as subjective experience about the interaction with the intervention. The measurement of engagement is in accordance with the definition of engagement and can be categorized as objective and subjective measures. Among identified papers, 5 used system usage data, 2 used self-reported questionnaire, 1 used sensor data and 3 used qualitative method. Almost all studies reported engagement at a moment to moment level, but there is a lack of measurement of engagement for the long term. CONCLUSIONS There have been calls to develop standard definition and measurement of patient engagement in eHealth and mHealth interventions. Besides, it is important to provide cancer patients with more tailored and engaging eHealth and mHealth interventions for long term engagement.

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A Fog Computing Framework for Quality of Service Optimisation in the Internet of Things (IoT) Ecosystem

2020 2nd International Multidisciplinary Information Technology and Engineering Conference (IMITEC) ◽

10.1109/imitec50163.2020.9334083 ◽

2020 ◽

Author(s):

William Tichaona Vambe ◽

Khulumani Sibanda

Keyword(s):

Quality Of Service ◽

Internet Of Things ◽

Fog Computing ◽

The Internet ◽

Computing Framework ◽

The Internet Of Things

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Performance metrics in wireless sensor networks :a survey and outlook

International Journal of Engineering & Technology ◽

10.14419/ijet.v7i2.26.12527 ◽

2018 ◽

Vol 7 (2.26) ◽

pp. 25

Author(s):

E Ramya ◽

R Gobinath

Keyword(s):

Wireless Sensor Networks ◽

Quality Of Service ◽

Wireless Sensor Network ◽

Sensor Networks ◽

Sensor Network ◽

Performance Metrics ◽

Resource Constraints ◽

Sensor Data ◽

Wireless Sensor

Data mining plays an important role in analysis of data in modern sensor networks. A sensor network is greatly constrained by the various challenges facing a modern Wireless Sensor Network. This survey paper focuses on basic idea about the algorithms and measurements taken by the Researchers in the area of Wireless Sensor Network with Health Care. This survey also catego-ries various constraints in Wireless Body Area Sensor Networks data and finds the best suitable techniques for analysing the Sensor Data. Due to resource constraints and dynamic topology, the quality of service is facing a challenging issue in Wireless Sensor Networks. In this paper, we review the quality of service parameters with respect to protocols, algorithms and Simulations.

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