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A Decentralized Latency-Aware Task Allocation and Group Formation Approach with Fault Tolerance for IoT Applications

Muhammad Mudassar, Yanlong Zhai, Lejian Liao, Jun Shen
2020 IEEE Access  
Our experiment results show that our approach is effective as well as providing desired goals of achieving deadline for latency-aware IoT applications, with staggering decrease in overall network traffic  ...  Our experiment results show that our approach is effective as well as providing desired goals of achieving deadline for latency-aware IoT applications, with staggering decrease in overall network traffic  ...  in lower latency, and also a staggering cut down in overall network traffic can be achieved, as data will be restricted in local network rather than routing towards cloud in default mobile edge computing  ... 
doi:10.1109/access.2020.2979939 fatcat:hfvngqfo7vdmzkeuy43y454toy

Edge Computing and Networking: A Survey on Infrastructures and Applications

Yongli Zhao, Wei Wang, Yajie Li, Carlos Colman Meixner, Massimo Tornatore, Jie Zhang
2019 IEEE Access  
Taking advantage of the close distance to end user and access networks, edge datacenters can provide low-latency and context-aware services and further improve users' quality of experience.  ...  As a concept to enhance and extend cloud-computing capabilities, edge computing aims to provide Internet-based services in the close proximity to users by placing IT infrastructures at the network edge  ...  However, cloud DCs are far away from users and assigning workloads to them will incur higher network latency.  ... 
doi:10.1109/access.2019.2927538 fatcat:klaxwhwtdfgifcx45xfioahray

Towards Computation Offloading in Edge Computing: A Survey

Congfeng Jiang, Xiaolan Cheng, Honghao Gao, Xin Zhou, Jian Wan
2019 IEEE Access  
Computation offloading plays a crucial role in edge computing in terms of network packets transmission and system responsiveness through dynamic task partitioning between cloud data centers and edge servers  ...  The explosive growth of massive data generation from Internet of Things in industrial, agricultural and scientific communities has led to a rapid increase for data analytics in cloud data centers.  ...  data to centralized cloud data centers, which in turn provides lower latency, increase reliability and improves overall network efficiency.  ... 
doi:10.1109/access.2019.2938660 fatcat:qcpqojzxsnbsnmuez3x2ew4sqa

Leveraging Fog Computing for Scalable IoT Datacenter Using Spine-Leaf Network Topology

K. C. Okafor, Ifeyinwa E. Achumba, Gloria A. Chukwudebe, Gordon C. Ononiwu
2017 Journal of Electrical and Computer Engineering  
With the Internet of Everything (IoE) paradigm that gathers almost every object online, huge traffic workload, bandwidth, security, and latency issues remain a concern for IoT users in today's world.  ...  Consequently, a spine-leaf Fog computing network (SL-FCN) is presented for reducing latency and network congestion issues in a highly distributed and multilayer virtualized IoT datacenter environment.  ...  Acknowledgments This research was carried out as an extended work on Distributed Cloud Computing Network for SGEMS/EETACP project commissioned by the Department of Electronic Engineering, University of  ... 
doi:10.1155/2017/2363240 fatcat:7x7xvrmuf5dm7ixlu4m33ryxta

Modeling and Analyzing Offloading Strategies of IoT Applications over Edge Computing and Joint Clouds

Jaber Almutairi, Mohammad Aldossary
2021 Symmetry  
For enhancing customer experience and accelerating job execution, IoT task offloading enables mobile end devices to release heavy computation and storage to the resource-rich nodes in collaborative Edges  ...  This paper exploits potential network performance that manifests within the edge-cloud environment, then investigates and compares the impacts of two types of architectures: Loosely-Coupled (LC) and Orchestrator-Enabled  ...  Acknowledgments: The authors would like to acknowledge the Deanship of Scientific Research, Taibah University, Al-Madinah, Saudi Arabia, for providing research resources and equipment.  ... 
doi:10.3390/sym13030402 doaj:d9cd7389fe11406e8ee32482d67bfabe fatcat:zd5jbf73wffnbb7sm6cng5sdpy

Resource Management Techniques for Cloud/Fog and Edge Computing: An Evaluation Framework and Classification

Adriana Mijuskovic, Alessandro Chiumento, Rob Bemthuis, Adina Aldea, Paul Havinga
2021 Sensors  
In this paper, we review resource management techniques that can be applied for cloud, fog, and edge computing.  ...  One of the considerations of cloud-based IoT environments is resource management, which typically revolves around resource allocation, workload balance, resource provisioning, task scheduling, and QoS  ...  Acknowledgments: We would like to thank Yanqui Huang and Henk Soppe for their discussions and effective comments on different sections of the review.  ... 
doi:10.3390/s21051832 pmid:33808037 fatcat:sh4dwl2wmba2jhcmcuss5nahsq

2019 Index IEEE Transactions on Network and Service Management Vol. 16

2019 IEEE Transactions on Network and Service Management  
Dong, C., +, T-NSM June 2019 729-742 Latency and Reliability-Aware Workload Assignment in IoT Networks With Mobile Edge Clouds.  ...  Vallero, G., +, T-NSM Sept. 2019 896-908 Latency and Reliability-Aware Workload Assignment in IoT Networks With Mobile Edge Clouds.  ...  Stochastic programming Tiered Cloud Storage via Two-Stage, Latency-Aware Bidding. Zhang  ... 
doi:10.1109/tnsm.2019.2960621 fatcat:zdo7i4plobaqxp54v7624wkrxi

A Lightweight Location-Aware Fog Framework (LAFF) for QoS in Internet of Things Paradigm

Qaisar Shaheen, Muhammad Shiraz, Muhammad Usman Hashmi, Danish Mahmood, Zhu zhiyu, Rizwan Akhtar
2020 Mobile Information Systems  
The comparison results depicts that the LAFF reduces latency, network use, and service time by 11.01%, 7.51%, and 14.8%, respectively, in contrast to the state-of-the-art frameworks.  ...  A comparative analysis is also presented to analyse network usage, service time, latency, and RAM and CPU utilization.  ...  WiCloud [31] is developed as mobile-edge computing platform with OpenStack to improve location awareness and to manage inter-mobile-edge communication and data acquisition for an innovative service.  ... 
doi:10.1155/2020/8871976 doaj:b458c4f643f542f5b43c59336f6a6c41 fatcat:bew73n2ihjcwxmqze6tfbta5be

Edge Computing: Vision and Challenges

Weisong Shi, Jie Cao, Quan Zhang, Youhuizi Li, Lanyu Xu
2016 IEEE Internet of Things Journal  
In this paper, we introduce the definition of Edge computing, followed by several case studies, ranging from cloud offloading to smart home and city, as well as collaborative Edge to materialize the concept  ...  network.  ...  ACKNOWLEDGMENT We are grateful to the early discussion with Tao Zhang from Cisco, Wensong Zhang from Alibaba about the idea of edge computing and fog computing.  ... 
doi:10.1109/jiot.2016.2579198 fatcat:35234wq4gbgcneblp5zg63pi3a

Edge Computing and Its Convergence with Blockchain in 5G and Beyond: Security, Challenges, and Opportunities

Showkat Ahmad Bhat, Ishfaq Bashir Sofi, Chong-Yung Chi
2020 IEEE Access  
Some key features that distinguish cloud, fog, and edge computing are mentioned in Table I . 2) MOBILE EDGE COMPUTING The objectives of mobile edge computing (MEC) is to reduce system latency and improve  ...  In addition to this, latency can be significantly enhanced by handling the workload at the edge rather than computation done on the cloud.  ... 
doi:10.1109/access.2020.3037108 fatcat:iksoyfx7nbhfrefnzgf6uxuw4q

All One Needs to Know about Fog Computing and Related Edge Computing Paradigms

Ashkan Yousefpour, Caleb Fung, Tam Nguyen, Krishna Kadiyala, Fatemeh Jalali, Amirreza Niakanlahiji, Jian Kong, Jason P. Jue
2019 Journal of systems architecture  
With the Internet of Things (IoT) becoming part of our daily life and our environment, we expect rapid growth in the number of connected devices.  ...  With this growth, fog computing, along with its related edge computing paradigms, such as multi-access edge computing (MEC) and cloudlet, are seen as promising solutions for handling the large volume of  ...  In [310] , the authors proposed a locality-aware workload sharing scheme for mobile edge computing environments.  ... 
doi:10.1016/j.sysarc.2019.02.009 fatcat:udonbl6rerfwdap2psex7ryloa

2020 Index IEEE Transactions on Services Computing Vol. 13

2021 IEEE Transactions on Services Computing  
-Dec. 2020 1128-1141 Minimizing Data Access Latencies for Virtual Machine Assignment in Cloud Systems. Malekimajd, M., +, TSC Sept.  ...  Yu, B., +, TSC May-June 2020 395-409 Minimizing Data Access Latencies for Virtual Machine Assignment in Cloud Systems. Malekimajd, M., +, TSC Sept.  ... 
doi:10.1109/tsc.2021.3055723 fatcat:eumbihmezvehxdfbmlp6ufzkwe

Mobility-Aware IoT Applications Placement in the Cloud Edge Continuum

Dragi Kimovski, Narges Mehran, Christopher Emanuel Kerth, Radu Prodan
2021 IEEE Transactions on Services Computing  
To address this gap, we propose a novel mobility-aware multi-objective IoT application placement (mMAPO) method in the Cloud -Edge Continuum that optimizes completion time, energy consumption, and economic  ...  The Edge computing extension of the Cloud services towards the network boundaries raises important placement challenges for IoT applications running in a heterogeneous environment with limited computing  ...  The IoT devices are close to the MEs in terms of network hops with an average latency of 1 ms.  ... 
doi:10.1109/tsc.2021.3094322 fatcat:elrfeep6ovfivbau7vuyemltzy

Resource Management in Fog/Edge Computing

Cheol-Ho Hong, Blesson Varghese
2019 ACM Computing Surveys  
Heterogeneity-aware: Edge devices in a mobile cloud are heterogeneous at all levels.  ...  It brings computing resources close to mobile and IoT devices to reduce communication latency and enable efficient use of the network bandwidth.  ...  ACKNOWLEDGMENTS The authors are grateful to the anonymous reviewers for their valuable comments and suggestions.  ... 
doi:10.1145/3326066 fatcat:4hkvzb2djfaezipbhqwoncg5wu

Resource Management in Fog/Edge Computing: A Survey [article]

Cheol-Ho Hong, Blesson Varghese
2018 arXiv   pre-print
in fog/edge computing.  ...  Contrary to using distant and centralized cloud data center resources, employing decentralized resources at the edge of a network for processing data closer to user devices, such as smartphones and tablets  ...  Heterogeneity-aware: Edge devices in a mobile cloud are heterogeneous at all levels.  ... 
arXiv:1810.00305v1 fatcat:erskczbjtjh5jigiu2dy4jgmdu
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