Abstract
The emergence of fog computing in existing cloud-based infrastructure has facilitated quality of service (QoS) delivery to end users. The real-time communication is a significant concern in fog networks for delay-sensitive applications. The number of research works has been conducted in the past to improve the content retrieval delay during content delivery with major focus toward content placement. However, node placement is another critical aspect for efficient communication. The timely delivery can be achieved through content caching on network nodes while considering content parameters as well. To address the real-time application requirements, this paper proposes caching of popular contents on the nodes based on caching filtration mechanism. The caching filtration allows only fog nodes with enough computation resources to cache the content replicas. The performance evaluation of the proposed scheme exhibits significant improvement in achieving reduced content retrieval delay in comparison to existing benchmark caching strategies.
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References
Datta P, Sharma B (2017) A survey on IoT architectures, protocols, security and smart city based applications. In: 2017 8th international conference on computing, communication and networking technologies (ICCCNT). IEEE, pp 1–5
Abdulqadir HR, Zeebaree SR, Shukur HM, Sadeeq MM, Salim BW, Salih AA, Kak SF (2021) A study of moving from cloud computing to fog computing. Qubahan Acad J 1(2):60–70
Yang Y, Zhao S, Zhang W, Chen Y, Luo X, Wang J (2018) Debts: delay energy balanced task scheduling in homogeneous fog networks. IEEE Internet Things J 5(3):2094–2106
Singh J, Singh P, Gill SS (2021) Fog computing: a taxonomy, systematic review, current trends and research challenges. J Parallel Distrib Comput
Wan J, Chen B, Wang S, Xia M, Li D, Liu C (2018) Fog computing for energy-aware load balancing and scheduling in smart factory. IEEE Trans Ind Inform 14(10):4548–4556
Pooranian Z, Shojafar M, Naranjo PGV, Chiaraviglio L, Conti M (2017) A novel distributed fog-based networked architecture to preserve energy in fog data centers. In: 2017 IEEE 14th international conference on mobile ad hoc and sensor systems (MASS). IEEE, pp 604–609
Kaur K, Dhand T, Kumar N, Zeadally S (2017) Container-as-a-service at the edge: trade-off between energy efficiency and service availability at fog nano data centers. IEEE Wirel Commun 24(3):48–56
Iberl R, Schillinger R (2018) Cloud technologies—may ‘fog computing’ help out the traditional cloud and pave the way to 5G networks. In: Digital marketplaces unleashed. Springer, pp 763–774
Nan Y, Li W, Bao W, Delicato FC, Pires PF, Dou Y, Zomaya AY (2017) Adaptive energy-aware computation offloading for cloud of things systems. IEEE Access 5:23947–23957
Althamary I, Huang CW, Lin P, Yang SR, Cheng CW (2018) Popularity-based cache placement for fog networks. In: 2018 14th international wireless communications and mobile computing conference (IWCMC). IEEE, pp 800–804
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Gupta, D., Wadhwa, S., Rani, S., Sharma, P. (2023). Delay Efficient Caching in Fog Computing. In: Goyal, D., Kumar, A., Piuri, V., Paprzycki, M. (eds) Proceedings of the Third International Conference on Information Management and Machine Intelligence. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-19-2065-3_33
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DOI: https://doi.org/10.1007/978-981-19-2065-3_33
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