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Energy-Optimal Mobile Cloud Computing under Stochastic Wireless Channel

Weiwen Zhang, Yonggang Wen, Kyle Guan, Dan Kilper, Haiyun Luo, Dapeng Oliver Wu
2013 IEEE Transactions on Wireless Communications  
One can, in the former case sequentially reconfigure the CPU frequency; or in the latter case dynamically vary the data transmission rate to the cloud, in response to the stochastic channel condition.  ...  We formulate both scheduling problems as constrained optimization problems, and obtain closed-form solutions for optimal scheduling policies.  ...  In Section IV and V, we solve the optimization problems for the optimal CPU clock-frequency scheduling in the mobile execution and the optimal transmission data-rate scheduling in the cloud execution,  ... 
doi:10.1109/twc.2013.072513.121842 fatcat:6jyqpkmd6fgwfbklwj7hnop7c4

Synthesis of Robust Control Systems under Resource Constraints [chapter]

Luigi Palopoli, Claudio Pinello, Alberto Sangiovanni Vincentelli, Laurent Elghaoui, Antonio Bicchi
2002 Lecture Notes in Computer Science  
Assuming a time-triggered model of computation for control processes and a real-time preemptive scheduling policy, the problem of optimizing robustness of the controlled systems is formulated.  ...  Specifically, we address the problem of controlling a set of independent systems by using a shared single CPU processor board.  ...  The underlying architecture is assumed to be based on a single CPU board shared among concurrent processes via a preemptive scheduling scheme.  ... 
doi:10.1007/3-540-45873-5_27 fatcat:ncs2s6gx4fdwlpsmpk6akb64re

Hardware Acceleration of Sparse and Irregular Tensor Computations of ML Models: A Survey and Insights [article]

Shail Dave, Riyadh Baghdadi, Tony Nowatzki, Sasikanth Avancha, Aviral Shrivastava, Baoxin Li
2021 arXiv   pre-print
and execution costs; analyzes achievable accelerations for recent DNNs; highlights further opportunities in terms of hardware/software/model co-design optimizations (inter/intra-module).  ...  The takeaways from this paper include: understanding the key challenges in accelerating sparse, irregular-shaped, and quantized tensors; understanding enhancements in accelerator systems for supporting  ...  (a) Flexible dot product engine in SIGMA accelerator [105] features a data distribution NoC with configurable switches interconnected via Benes topology.  ... 
arXiv:2007.00864v2 fatcat:k4o2xboh4vbudadfiriiwjp7uu

Biobjective VoIP Service Management in Cloud Infrastructure

Jorge M. Cortés-Mendoza, Andrei Tchernykh, Fermin A. Armenta-Cano, Pascal Bouvry, Alexander Yu. Drozdov, Loic Didelot
2016 Scientific Programming  
In this paper, we formulate the problem of scheduling of VoIP services in distributed cloud environments and propose a new model for biobjective optimization.  ...  Voice over Internet Protocol (VoIP) allows communication of voice and/or data over the internet in less expensive and reliable manner than traditional ISDN systems.  ...  Distributed cloud-based VoIP architecture assumes that voice nodes are distributed geographically; hence, they are grouped in different locations (data centers).  ... 
doi:10.1155/2016/5706790 fatcat:bkwp2te2nreq3ctqlkfrms7nme

Edge Intelligence: The Confluence of Edge Computing and Artificial Intelligence [article]

Shuiguang Deng, Hailiang Zhao, Weijia Fang, Jianwei Yin, Schahram Dustdar, Albert Y. Zomaya
2020 arXiv   pre-print
Billions of data bytes, generated at the network edge, put massive demands on data processing and structural optimization.  ...  Along with the rapid developments in communication technologies and the surge in the use of mobile devices, a brand-new computation paradigm, Edge Computing, is surging in popularity.  ...  In this paper, we define an edge site as a micro data center with applications deployed, attached to a Small-cell Base Station (SBS).  ... 
arXiv:1909.00560v2 fatcat:jmg3fyagazdzfbn7duiqihagea

Combining K-Means and K-Harmonic with Fish School Search Algorithm for data clustering task on graphics processing units

Adriane B.S. Serapião, Guilherme S. Corrêa, Felipe B. Gonçalves, Veronica O. Carvalho
2016 Applied Soft Computing  
Data clustering is related to the split of a set of objects into smaller groups with common features.  ...  In this work, a Swarm Clustering Algorithm (SCA) is proposed based on the standard K-Means and on K-Harmonic Means (KHM) clustering algorithms, which are used as fitness functions for a SI algorithm: Fish  ...  Acknowledgments The authors would like to thank Fundaç ão de Amparo à Pesquisa  ... 
doi:10.1016/j.asoc.2015.12.032 fatcat:u3ens6ktqjdjhjdoijjexzajv4

Distributed Machine Learning for Wireless Communication Networks: Techniques, Architectures, and Applications [article]

S. Hu, X. Chen, W. Ni, E. Hossain, X. Wang
2020 arXiv   pre-print
This is due to improved capabilities of terminal devices, explosively growing data volume, congestion in the radio interfaces, and increasing concern of data privacy.  ...  There is a clear gap in the existing literature in that the DML techniques are yet to be systematically reviewed for their applicability to wireless systems.  ...  Given the finite bandwidth and memory, and potential compromise of privacy, it is generally impossible to deliver all data in a distributed edge environment.  ... 
arXiv:2012.01489v1 fatcat:pdauhq4xbbepvf26clhpqnc2ci

GLISSE: A GPU-optimized planetary system integrator with application to orbital stability calculations [article]

Kevin Zhang, Brett J. Gladman
2020 arXiv   pre-print
The GLISSE (Gpu Long-term Integrator for Solar System Evolution) code implements several optimizations to achieve a roughly factor of 100 speed increase over running the same code on a CPU.  ...  We present a GPU-accelerated numerical integrator specifically optimized for stability calculations of small bodies in planetary systems.  ...  As can be seen in Figure 2 , execution time is quantized.  ... 
arXiv:2011.03484v1 fatcat:zvxbcnjrarfitf6fshe4yetomq

A Comprehensive Survey on Aerial Mobile Edge Computing: Challenges, State-of-the-Art, and Future Directions [article]

Zhengyu Song, Xintong Qin, Yuanyuan Hao, Tianwei Hou, Jun Wang, Xin Sun
2022 arXiv   pre-print
allocation, UAV deployment, task scheduling and load balancing, interplay between aerial MEC and other technologies, as well as the machine-learning (ML)-driven optimization.  ...  Then, we provide a comprehensive review of the recent research advances, which is categorized by different domains, including the joint optimization of UAV trajectory, computation offloading and resource  ...  : In [87] , as the ground channels from IoT nodes to the data center is in severe fading, the UAV serves as a relay to froward the information from IoT nodes to the data center controlled by the fog computing  ... 
arXiv:2208.13965v1 fatcat:rglkodmjsve2fbncmmyatqos6y

Error Tolerant Multimedia Stream Processing: There's Plenty of Room at the Top (of the System Stack)

Yiannis Andreopoulos
2013 IEEE transactions on multimedia  
There is a growing realization that the expected fault rates and energy dissipation stemming from increases in CMOS integration will lead to the abandonment of traditional system reliability in favor of  ...  In this paper we review recent advances in this field from an MSP and a system (layer-by-layer) perspective, and attempt to foresee some of the components of future cross-layer error-tolerant system design  ...  Through the use of linear programming for the optimal scheduling of multiple multimedia processing and decoding tasks under delay deadlines, a bound has been derived recently on the optimal scheduling  ... 
doi:10.1109/tmm.2012.2232649 fatcat:x6p5wvaxyvgopc435hqyoprhri

Reinforcement Learning-Empowered Mobile Edge Computing for 6G Edge Intelligence [article]

Peng Wei, Kun Guo, Ye Li, Jue Wang, Wei Feng, Shi Jin, Ning Ge, Ying-Chang Liang
2022 arXiv   pre-print
This paper provides a comprehensive research review on RL-enabled MEC and offers insight for development in this area.  ...  Mobile edge computing (MEC) is considered a novel paradigm for computation-intensive and delay-sensitive tasks in fifth generation (5G) networks and beyond.  ...  In a distributed caching system using neighboring mobile devices and MEC servers, a blockchain-based caching and delivery market mechanism is proposed.  ... 
arXiv:2201.11410v4 fatcat:24igkq4kbrb2pjzwf3mf3n7qtq

Online Offloading Scheduling for NOMA-Aided MEC Under Partial Device Knowledge

Meihui Hua, Hui Tian, Xinchen Lyu, Wanli Ni, Gaofeng Nie
2021 IEEE Internet of Things Journal  
Second, we propose to transform the non-convex per-slot subproblem of optimizing NOMA power allocation equivalently to a convex form by introducing a set of auxiliary variables, whereby the time-complexity  ...  Since the optimization variables are temporary coupled, we first apply Lyapunov technique to decouple the long-term stochastic optimization into a series of per-slot deterministic subproblems, which does  ...  The real-time scheduling mechanism provides an upper bound for the performance of our proposed algorithm. 2) T-intervals Schedule: The offloading strategies are conducted at each time slot according to  ... 
doi:10.1109/jiot.2021.3091849 fatcat:zuywrabkfbeubgy6lc5i4e3wru

The Four-C Framework for High Capacity Ultra-Low Latency in 5G Networks: A Review

Kelechi, Alsharif, Ramly, Abdullah, Nordin
2019 Energies  
Network latency will be a critical performance metric for the Fifth Generation (5G) networks expected to be fully rolled out in 2020 through the IMT-2020 project.  ...  The multi-user multiple-input multiple-output (MU-MIMO) technology is a key enabler for the 5G massive connectivity criterion, especially from the massive densification perspective.  ...  In [136] , a practical packet dropping along with finite power mechanism is proposed to enable the quality of service (QoS).  ... 
doi:10.3390/en12183449 fatcat:ukf7k5etubf2tjo7lk3oij5wsm

Edge Intelligence: Paving the Last Mile of Artificial Intelligence With Edge Computing

Zhi Zhou, Xu Chen, En Li, Liekang Zeng, Ke Luo, Junshan Zhang
2019 Proceedings of the IEEE  
| With the breakthroughs in deep learning, the recent years have witnessed a booming of artificial intelligence (AI) applications and services, spanning from personal assistant to recommendation systems  ...  However, research on EI is still in its infancy stage, and a dedicated venue for exchanging the recent advances of EI is highly desired by both the computer system and AI communities.  ...  Specifically, gradient quantization performs lossy compression of the gradient vectors by quantizing each of their elements to a finite-bit low precision value.  ... 
doi:10.1109/jproc.2019.2918951 fatcat:d53vxmklgfazbmzjhsq3tuoama

PTask

Christopher J. Rossbach, Jon Currey, Mark Silberstein, Baishakhi Ray, Emmett Witchel
2011 Proceedings of the Twenty-Third ACM Symposium on Operating Systems Principles - SOSP '11  
Because a PTask graph consists of OS-managed objects, the kernel has sufficient visibility and control to provide system-wide guarantees like fairness and performance isolation, and can streamline data  ...  where there were previously none, and can enable significant performance improvements, for example gaining a 5× improvement in maximum throughput for the gestural interface.  ...  This research is supported by NSF Career award CNS-0644205, NSF award CNS-1017785, and a 2010 NVIDIA research grant. We thank our shepherd, Steve Hand for his valuable and detailed feedback.  ... 
doi:10.1145/2043556.2043579 dblp:conf/sosp/RossbachCSRW11 fatcat:5cgrgj5h5ff6xapt6h7bebqikq
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