Edge computing gained popularity for its promises of low latency and high-quality computing services to users. However, it has also introduced the challenge of mutual untrust between user and edge devices for service level agreement (SLA) compliance. This obstacle hampers wide adoption of edge computing, especially in...
Xiaojian Wang, Ruozhou Yu, Dejun Yang et al.· IEEE Transactions on Mobile...· 0 citations
The flexible architecture of the open radio access network (O-RAN) provides effective support for the deployment of federated learning (FL). However, existing FL schemes in wireless networks often suffer from packet errors, which lead to reduced model test accuracy and increased training delay. In this paper, we propos...
Kai Qiao, Hongchao Wang, Zi-Hao Zhang et al.· IEEE Transactions on Mobile...· 0 citations
Split Learning (SL) enables collaborative model training by distributing computation between resource-constrained mobile edge devices and a central server. In this distributed framework, mobile edge devices compute the early layers of the model and transmit feature maps to the server. However, due to practical mobile w...
Wen-Xuan Zhou, Zhi-Hao Qu, Baoliu Ye et al.· IEEE Transactions on Mobile...· 0 citations
The integration of homomorphic encryption (HE) into split federated learning (SFL) offers significant security advantages by maintaining end-to-end encryption of intermediate computations. Existing SFL approaches often overlook encryption, adopting fixed machine learning (ML) model partitioning strategies without consi...
Penghui Chen, Wenhao Fan, Guan Wang et al.· IEEE Transactions on Mobile...· 0 citations
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In 6G multiple uncrewed aerial vehicles (UAVs) cooperative edge computing networks, strongly coupled system states and limited single-UAV observability lead to inefficient resource management and difficulty in guaranteeing Quality of Service (QoS). To address these issues, we propose a QoS-aware resource allocation met...
Ya-Qing Wang, Lun Tang, Wei-Li Wang et al.· IEEE Transactions on Mobile...· 0 citations
Today’s networks include decentralized intelligence, scattered over multiple computing facilities, for the execution of computation-intensive tasks that are necessary for both network management and service provision to end users. This raises a number of questions regarding task allocation, in terms of both the task pl...
V. Mancuso, P. Castagno, Leonardo Badia et al.· IEEE Transactions on Mobile...· 1 citation
Mobile edge computing effectively reduces delay and improves the system efficiency by offloading computing tasks. However, the standard communication channel, Orthogonal Frequency Division Multiple Access (OFDMA), is difficult to support large-scale connections in dense networks. Meanwhile, existing task offloading met...
Yang Xia, Min-Cong Chen, Qiang He et al.· IEEE Transactions on Mobile...· 0 citations
The rapid expansion of computation-intensive applications renders current mobile edge computing (MEC) frameworks inadequate for delivering high-quality computing services in environments with sparse network infrastructure. Air-based stations, represented by low-altitude unmanned aerial vehicles (UAVs) and high-altitude...
Meng Li, Hao-Yu Wan, Su-Yu Lv et al.· IEEE Transactions on Mobile...· 1 citation
Facing the rapid development of both user equipment (UE) and mobile applications, mobile edge computing (MEC) emerged as a new paradigm to furnish UE with satisfactory computational capability and task latency. Studies on MEC have put a great deal of focus on computation offloading, mainly involving multi-step task off...
Zhe-Yuan Hu, Jian-Wei Niu, Tao Ren et al.· IEEE Transactions on Mobile...· 0 citations
The rapid proliferation of Internet of Things (IoT) and the diversity of services demand for a more efficient and intelligent resource allocation framework to enhance network performance. To this end, we construct a novel satellite-terrestrial integrated network (STIN) integrating multi-access edge computing (MEC) and...
Fang-Fang Yin, Qi-Hong Liu, Mu-Lei Wu et al.· IEEE Transactions on Mobile...· 0 citations
Owing to increased power density with each newer technology node, transistors suffer from increased Self-Heating (SH) at room temperature, which is a daunting challenge for circuits and processors’ reliability. Given the increasing interest in leveraging cryogenic temperatures to enhance the performance and energy effi...
S. S. Parihar, F. Klemme, Anirban Kar et al.· IEEE transactions on compute...· 1 citation
In large areas, mobile edge computing (MEC) systems enabled by drones, also known as unmanned aerial vehicles (UAVs), can provide flexible edge computing services and facilitate low-altitude inspection. Such systems are primarily limited by the computing resources and energy of the drone, as well as their reliance on c...
W. Qi, Wei-Feng Zhong, Jia-Wen Kang et al.· IEEE Transactions on Mobile...· 1 citation
Host Sowbhagya Suresh shares some of the latest news and cutting-edge research from across Microsoft—from understanding the challenges facing coding agents to uncovering how people use AI at work and improving extended-range weather forecasting. The post Microsoft Research Focus – Edition #97 appeared first on Microsoft Research.
MIT News · Artificial Intelligence· news.mit.eduOct 28, 2026
Professor Paris Smaragdis develops computers with superhuman hearing for applications like speech recognition, music understanding, and environmental monitoring.
For decades, a fundamental question about the difficulty of computing in high-dimensional spaces has resisted proof. New research resolves this question, removing a major theoretical obstacle to understanding the efficiency of randomized algorithms used across science and computing. The Kannan–Lovász–Simonovits (KLS) conjecture was proposed in 1995. It asks whether, for a broad class of high-dimensional […] The post Solving a 31-year-old grand challenge in mathematics – the KLS conjecture appear…
MIT News · Artificial Intelligence· news.mit.eduOct 15, 2026
A new computational approach reveals how cells communicate to assemble into tissues. This could accelerate stem cell engineering, improve disease models, and inform therapies.
Microsoft Research Blog· microsoft.comOct 15, 2026
Zero-knowledge proofs can verify computing results without rerunning workloads or exposing sensitive data. Magnetar helps bring them into the mainstream with support for standard programming languages, major speed gains, and quantum-resistant security. The post Proof-based general-purpose computing with Magnetar appeared first on Microsoft Research.
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