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Optimizing microservices with hyperparameter optimization 17

Optimizing microservices with hyperparameter optimization

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17th IEEE international conference on Mobility, Sensing and networking (MSN)

作者： Hai Dinh-Tuan Katsarou, Katerina Herbke, Patrick Tech Univ Berlin Serv Ctr Networking Berlin Germany

ISBN: (纸本)9781665406680

In the last few years, the cloudification of applications requires new concepts and techniques to fully reap the benefits of the new computing paradigm. Among them, the microservices architectural style, which is inspired by service-oriented architectures, has gained attention from both industry and academia. However, decomposing a monolith into multiple microservices also creates several challenges across the application's lifecycle. In this work, we focus on the operation aspect of microservices, and present our novel proposal to enable self-optimizing microservices systems based on grid search and random search techniques. the initial results show our approach is able to optimize the latency performance of microservices to up to 10.56%.

关键词： microservices optimization hyperparameter optimization grid search random search

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Information Retrieval from Facebook for Social Network Analysis

Information Retrieval from Facebook for Social Network Analy...

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international conference on Semantic computing

作者： Fabio Persia Daniela D’Auria DISIM University of L’Aquila L’Aquila Italy Faculty of Computer Science Free University of Bozen-Bolzano Bozen-Bolzano Italy

Complex Event Processing (CEP) is becoming increasingly important for effectively modeling and early identification of potentially dangerous events in many application domains, such as video surveillance, business process management, and social network analysis. Consequently, there is a growing need to automatically extract information from social networks that could be useful for further and deeper analysis. As a result, in this paper we describe an application that can automatically detect users’ interactions with Facebook, which has been used by many social network analysis applications and can serve as a guideline for researchers in this field.

关键词： Analytical models Social networking (online) Semantics Blogs Video surveillance Business process management Data mining

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Delay-Sensitive Slicing Resources Scheduling Based on Multi-MEC Collaboration in IoV 17th

Delay-Sensitive Slicing Resources Scheduling Based on Multi-...

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17th EAI international conference on collaborative computing: networking, applications, and worksharing, CollaborateCom 2021

作者： Liang, Yan Chen, Xin Ma, Shengcheng Jiao, Libo School of Computer Science Beijing Information Science and Technology University Beijing100101 China School of Computer Science and Engineering Beihang University Beijing100191 China

ISBN: (纸本)9783030926373

the emerging Vehicle to Infrastructure (V2I) technology supports the service of task offloading under the Internet of vehicle (IoV), which improves the computational efficiency of the task. Facing tasks with different demands, network slicing technology builds a variety of logic private networks on a unified infrastructure, divides and allocates resources according to different user needs, which improves the vehicle transmission efficiency. Nevertheless, the diversity of demand resources and the randomness of tasks make the network scenario of IoV more complex. It is still a challenge to consider how to combine the network slicing technology to reduce the cost of offloading the computing task. In this paper, we study the scenario of autonomous vehicle offloading the computing task to Roadside Units (RSUs), and consider the multi-Mobile Edge computing (multi-MEC) collaborative computing task to ensure that the task can be completed within tolerable delay. We consider the computing power and resource occupancy rate of MEC servers to ensure the user experience, and formulate a resource pricing scheme. then, we propose a Performance-Price Ratio Task Scheduling (PPRTS) algorithm, which aims to complete the computing task within the maximum tolerable delay and reduce the cost of user. Simulation results show that the algorithm can effectively reduce the cost of the user. © 2021, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： Mobile edge computing

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Federated Learning Meets Edge computing: A Hierarchical Aggregation Mechanism for Mobile Devices 17th

Federated Learning Meets Edge Computing: A Hierarchical Aggr...

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17th international conference on Wireless Algorithms, Systems, and applications (WASA)

作者： Chen, Jiewei Li, Wenjing Yang, Guoming Qiu, Xuesong Guo, Shaoyong Beijing Univ Post & Telecommun State Key Lab Networking & Switching Technol Beijing Peoples R China State Grid Informat & Commun Ind Co Ltd Beijing Peoples R China

ISBN: (纸本)9783031192104;9783031192111

Federated learning (FL) has been proposed and applied in edge computing scenarios. However, the complex edge environment of wireless networks, such as limited device computing resources and unstable signals, leads to increase communication overhead and reduced performance for federated learning. therefore, we propose a hierarchical aggregation mechanism to improve federated learning performance in a resource-constrained wireless edge environment. We propose three feature models to quantify the FL performance and design a fuzzy IC-means clustering mechanism. We construct an optimization problem for the process of hierarchical aggregation. And a cluster-based hierarchical federated learning algorithm (CluHFed) is designed, which consists of fuzzy clustering, asynchronous aggregation, and topology reconstruction. At last, we make an experiment with Pytorch. the results show that the proposed algorithm improves the accuracy by 2.6%-35.8% and reduces the latency of FL networks by 5.9% compared with other popular federated learning algorithms.

关键词： Edge computing Federated learning Clustering Topology reconstruction Heterogeneity

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Recommendation Model Based on Social Homogeneity Factor and Social Influence Factor 17th

Recommendation Model Based on Social Homogeneity Factor and ...

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17th EAI international conference on collaborative computing: networking, applications, and worksharing, CollaborateCom 2021

作者： Ying, Weizhi Yu, Qing Wang, Zuohua Tianjin Key Laboratory of Intelligence Computing and Network Security Tianjin University of Technology Tianjin300384 China China Everbright Bank CO. LTD. Beijing100035 China

ISBN: (纸本)9783030926342

In recent years, more and more recommendation algorithms incorporate social information. However, most social recommendation algorithms often only consider the social homogeneity factor between users and do not consider the social influence factor. To make the recommendation model more in line with the real-life situation, this paper proposes a novel graph attention network to model the homogeneity effect and the influence effect in the user domain. Besides, we also extended this idea to the item domain, using information from similar items to alleviate the problem of data sparsity. Also, considering that there will be interactions between the user domain and the item domain, which together affect the user’s preference for the item, we use a contextual multi-armed bandit to weigh the interaction between the two domains. We have conducted extensive comparative experiments and ablation experiments on two real public datasets. the experimental results show that the performance of our proposed model in the rating prediction task is better than other social recommendation model. © 2021, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： Recommender systems

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Loopster++: Termination Analysis for Multi-path Linear Loop 17th

Loopster++: Termination Analysis for Multi-path Linear Loop

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17th EAI international conference on collaborative computing: networking, applications, and worksharing, CollaborateCom 2021

作者： Jin, Hui Ge, Weimin Zhang, Yao Li, Xiaohong Deng, Zhidong College of Intelligence and Computing Tianjin University Tianjin China State Grid Customer Service Center Tianjin China

ISBN: (纸本)9783030926342

Loop structure is widely adopted in many applications, e.g. collaborative applications, social network applications, and edge computing. And the termination of the loop is of great significance to the correctness of the program. Most of the previous relative studies focused on determining the termination of a loop program by synthesizing the ranking functions, but not every ranking function can be synthesized. Although a class of linear loop program termination has been proven to be decidable, it is always difficult to analyze the termination of a multi-path linear loop. Xie et al. [20] presented Loopster to quickly check the termination of the multi-path loop program by analyzing the termination of each path and the dependency between paths. But it relies on the monotonicity of variables which is very complicated to check when the variables increase. To this end, we extend Loopster, named Loopster++, to analyze the termination of multi-path linear loops. In Loopster++, 1) we convert the iterable path into a single path linear loop to analyze its termination. 2) We also propose a novel method to analyze the dependency between linear loop paths. 3) For the cycle constituted by alternate execution between paths, we classify all cycles and give the termination method of the corresponding category cycle. We finally evaluate Loopster++ by analyzing the termination of the benchmarks from the competition on software verification and compare it with the state-of-the-art tools. the empirical results demonstrate the superiority of Loopster++ by achieving high accuracy of 83% in the shortest time. © 2021, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： Information retrieval

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Watching the Watchers: Resource-Efficient Mobile Video Decoding through Context-Aware Resolution Adaptation 20

Watching the Watchers: Resource-Efficient Mobile Video Decod...

引用

17th EAI international conference on Mobile and Ubiquitous Systems - computing, networking and Services (MobiQuitous)

作者： Machidon, Octavian Fajfar, Tine Pejovic, Veljko Univ Ljubljana Ljubljana Slovenia

ISBN: (纸本)9781450388405

Mobile computing evolution is critically threatened by the limitations of the battery technology, which does not keep pace with the increase in energy requirements of mobile applications. A novel approach for reducing the energy appetite of mobile apps comes from the approximate computing field, which proposes techniques that in a controlled manner sacrifice computation accuracy for higher energy savings. Building on this philosophy we propose a context-aware mobile video quality adaptation that reduces the energy needed for video playback, while ensuring that a user's quality expectations with respect to the mobile video are met. We confirm that the decoding resolution can play a significant role in reducing the overall power consumption of a mobile device and conduct a user study with 22 participants to investigate how the context in which a video is played modulates a user's quality expectations. We discover that a user's physical activity and the spatial/temporal properties of the video interact and jointly influence the minimal acceptable playback resolution, paving the way for context-adaptable approximate mobile computing.

关键词： mobile computing approximate computing video decoding context inference spatial information temporal information

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SOAR: Minimizing Network Utilization with Bounded In-network computing 21

SOAR: Minimizing Network Utilization with Bounded In-network...

引用

17th ACM international conference on Emerging networking EXperiments and Technologies (ACM CoNEXT)

作者： Segal, Raz Avin, Chen Scalosub, Gabriel Ben Gurion Univ Negev Sch Elect & Comp Engn Negev Israel

ISBN: (纸本)9781450390989

In-network computing via smart networking devices is a recent trend for modern datacenter networks. State-of-the-art switches with near line rate computing and aggregation capabilities are developed to enable, e.g., acceleration and better utilization for modern applications like big data analytics, and large scale distributed and federated machine learning. We formulate and study the problem of activating a limited number of in-network computing devices within a network, aiming at reducing the overall network utilization for a given workload. Such limitations on the number of in-network computing elements per workload arise, e.g., in incremental upgrades of network infrastructure, and are also due to requiring specialized middleboxes, or FPGAs, that should support heterogeneous workloads, and multiple tenants. We present an optimal and efficient algorithm for placing such devices in tree networks with arbitrary link rates, and further evaluate our proposed solution in various scenarios and for various tasks. Our results show that having merely a small fraction of network devices support in-network aggregation can lead to a significant reduction in network utilization. Furthermore, we show that various intuitive strategies for performing such placements exhibit significantly inferior performance compared to our solution, for varying workloads, tasks, and link rates.

关键词： Data Analytics

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D2D-Based Multi-relay-Assisted Computation Offloading in Edge computing Network 17th

D2D-Based Multi-relay-Assisted Computation Offloading in Ed...

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17th EAI international conference on collaborative computing: networking, applications, and worksharing, CollaborateCom 2021

作者： Zhao, Xuan Zhang, Song Liu, Bowen Jiang, Xutong Dou, Wanchun State Key Laboratory for Novel Software Technology Nanjing University Nanjing210023 China

ISBN: (纸本)9783030926373

With the rapid development of edge computing, a large number of compute-intensive tasks are offloaded to the edge server, and computation offloading strategy has become a hot research topic. Because the deployment of edge servers is still in its infancy, there would be some service blind area. through D2D technology, mobile devices in the blind area can obtain edge services with the help of relays. However, the existing methods usually select single relay to transmit tasks, and seldom consider the sensitivity of processing delay for compute-intensive tasks. When the available bandwidth of single relay is not enough to complete the data transmission in a limited time, it will produce a large delay, which seriously affects the quality of user experience. In view of this challenge, a D2D-based multi-relay-assisted computation offloading method is proposed. Technically, multiple mobile devices in the available area of edge service are used as the relays. Based on D2D technology, mobile devices in the blind area use the relays to transmit the computing task to the edge server to improve the application computing efficiency. A large number of experiments with real-world datasets have proved the feasibility and effectiveness of our method. © 2021, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： computation offloading

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Computation Offloading for Multi-user Sequential Tasks in Heterogeneous Mobile Edge computing 17th

Computation Offloading for Multi-user Sequential Tasks in He...

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17th EAI international conference on collaborative computing: networking, applications, and worksharing, CollaborateCom 2021

作者： Xu, Huanhuan Zhou, Jingya Gu, Fei School of Computer Science and Technology Soochow University Suzhou215006 China State Key Laboratory of Mathematical Engineering and Advanced Computing Wuxi214125 China

ISBN: (纸本)9783030926342

Currently, many computation offloading studies in Mobile Edge computing (MEC) mainly focus on the multi-user and multi-task offloading, where the tasks are independent and inseparable. However, nowadays many mobile applications, such as Augmented Reality (AR) glasses, face recognition, etc., can be classified into sequential tasks. Dependencies among tasks and resource competition among multiple users in the heterogeneous edge environment make the offloading problem very challenging. In this paper, we propose a new multi-user sequential task (MUST) framework to address the above challenge. Specifically, we present a comprehensive analysis of the time cost of the task offloading process in the MUST framework and define the multi-user sequential task offloading problem. Moreover, we prove the problem is NP-hard and propose a reMUST algorithm based on regular expression to obtain the approximate optimal solution. Numerous experiments have shown that the proposed method is superior to existing alternatives in terms of cost and system scalability. © 2021, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： computation offloading

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