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- W4382995759 abstract "The deployment of multiple edge servers has a significant difference in the performance of mobile edge computing (MEC) due to the more diverse options for computation. It is important to distribute the imposed workload evenly among the MEC servers by considering the existing load and resourses. The task like offloading the data is redirected to other servers to balance the load in the network. An ant colony multi-edge load balancing offloading (ACMLO) strategy is used to optimize the load on a MEC sever. Authors use ACMLO to balance and optimize the load between cells, which are connected to the server. The proposed algorithm $$LB_MECs$$ calculates average load of edge network (ALN), and it is used to balance the load between the MEC servers. That is the congested MEC selects the one, which is having lesser load than the ALN to offload the data. Further data from MEC servers is transferred to cloud through core network. The offloading mobile edge-cloud computing (OMECC) is designed to offload the data to cloud. However, offloading data to cloud is vulnerable to security aspects, due to malicious mobile devices (MDs). To address this security concern, the blockchain-based Internet of things (IoT) networks for MEC are presented in this work. It can protect cloud-based services against unlawful offload and allow only authorized MDs to access the services. The ACMLO, $$LB_MECs$$ , and OMECC are analyzed using NS3. The results show that all three algorithms improve throughput and delay parameters." @default.
- W4382995759 created "2023-07-04" @default.
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- W4382995759 date "2023-01-01" @default.
- W4382995759 modified "2023-09-25" @default.
- W4382995759 title "Load Balancing for MEC in 5G-Enabled IoT Networks and Malicious Data Validation Using Blockchain" @default.
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- W4382995759 doi "https://doi.org/10.1007/978-981-99-1373-2_11" @default.
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