• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.5
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• pp.1238-1259
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• 2024

Previous studies on joint optimization of computation offloading and service caching policies in Mobile Edge Computing (MEC) have often neglected the impact of dependency-aware subtasks, edge server resource constraints, and multiple users on policy formulation. To remedy this deficiency, this paper proposes a many-objective joint optimization dependency-aware task offloading and service caching model (MaJDTOSC). MaJDTOSC considers the impact of dependencies between subtasks on the joint optimization problem of task offloading and service caching in multi-user, resource-constrained MEC scenarios, and takes the task completion time, energy consumption, subtask hit rate, load variability, and storage resource utilization as optimization objectives. Meanwhile, in order to better solve MaJDTOSC, a many-objective evolutionary algorithm TSMSNSGAIII based on a three-stage mating selection strategy is proposed. Simulation results show that TSMSNSGAIII exhibits an excellent and stable performance in solving MaJDTOSC with different number of users setting and can converge faster. Therefore, it is believed that TSMSNSGAIII can provide appropriate sub-task offloading and service caching strategies in multi-user and resource-constrained MEC scenarios, which can greatly improve the system offloading efficiency and enhance the user experience.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.2
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• pp.514-535
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• 2019

Information-centric networks operate under the assumption that all network components have built-in caching capabilities. Integrating the caching strategies of information centric networking (ICN) with wireless virtualization improves the gain of virtual infrastructure content caching. In this paper, we propose a framework for software-defined information centric virtualized wireless device-to-device (D2D) networks. Enabling D2D communications in virtualized ICN increases the spectral efficiency due to reuse and proximity gains while the software-defined network (SDN) as a platform also simplifies the computational overhead. In this framework, we propose a joint virtual resource and cache allocation solution for latency-sensitive applications in the next-generation cellular networks. As the formulated problem is NP-hard, we design low-complexity heuristic algorithms which are intuitive and efficient. In our proposed framework, different services can share a pool of infrastructure items. We evaluate our proposed framework and algorithm through extensive simulations. The results demonstrate significant improvements in terms of visiting latency, end user QoE, InP resource utilization and MVNO utility gain.

• Journal of IKEEE
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• v.28 no.3
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• pp.458-464
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• 2024

This study proposes a fault-tolerant caching system to address the issue of caching content imbalance caused by the dynamic departure and participation of cache servers in a heterogeneous cache server network, and validates it in both real and virtual environments. With the increase of large-scale media content requiring various types and resolutions, the necessity of cache servers as key components to reduce response time to user requests and alleviate network load has been growing. In particular, research on heterogeneous cache server networks utilizing edge computing and low-power devices has been actively conducted recently. However, in such environments, the irregular departure and participation of cache servers can occur frequently, leading to content imbalance among the cache servers deployed in the network, which can degrade the performance of the cache server network. The fault-tolerant caching algorithm proposed in this study ensures stable service quality by maintaining balance among media contents even when cache servers depart. Experimental results confirmed that the proposed algorithm effectively maintains content distribution despite the departure of cache servers. Additionally, we built a network composed of seven heterogeneous cache servers to verify the practicality of the proposed caching system and demonstrated its performance and scalability through a large-scale cache server network in a virtual environment.