research-article

Hotspot Detection in a Service-Oriented Architecture

Authors:

Pranay Anchuri,

Roshan Sumbaly,

Sam ShahAuthors Info & Claims

CIKM '14: Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management

Pages 1749 - 1758

https://doi.org/10.1145/2661829.2661991

Published: 03 November 2014 Publication History

Abstract

Large-scale websites are predominantly built as a service-oriented architecture. Here, services are specialized for a certain task, run on multiple machines, and communicate with each other to serve a user's request. Reducing latency and improving the cost to serve is quite important, but optimizing this service call graph is particularly challenging due to the volume of data and the graph's non-uniform and dynamic nature.

In this paper, we present a framework to detect hotspots in a service-oriented architecture. The framework is general, in that it can handle arbitrary objective functions. We show that finding the optimal set of hotspots for a metric, such as latency, is NP-complete and propose a greedy algorithm by relaxing some constraints. We use a pattern mining algorithm to rank hotspots based on the impact and consistency. Experiments on real world service call graphs from LinkedIn, the largest online professional social network, show that our algorithm consistently outperforms baseline methods.

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https://dl.acm.org/doi/10.1109/TITS.2021.3086827
Xiao XLi YXia YMa YJiang CZhong X(2021)Location-Aware Edge Service Migration for Mobile User Reallocation in Crowded ScenesCollaborative Computing: Networking, Applications and Worksharing10.1007/978-3-030-67537-0_27(441-457)Online publication date: 22-Jan-2021
https://doi.org/10.1007/978-3-030-67537-0_27
Palma FMoha NGuéhéneuc Y(2019)UniDoSA: The Unified Specification and Detection of Service AntipatternsIEEE Transactions on Software Engineering10.1109/TSE.2018.281918045:10(1024-1053)Online publication date: 1-Oct-2019
https://dl.acm.org/doi/10.1109/TSE.2018.2819180
Show More Cited By

Index Terms

Hotspot Detection in a Service-Oriented Architecture
1. Computing methodologies
  1. Machine learning
  2. Modeling and simulation
    1. Model development and analysis
      1. Modeling methodologies
2. Software and its engineering
  1. Software creation and management
    1. Software verification and validation
      1. Process validation

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Published In

cover image ACM Conferences

CIKM '14: Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management

November 2014

2152 pages

ISBN:9781450325981

DOI:10.1145/2661829

General Chairs:
Jianzhong Li
Harbin Inst. of Technology
,
X. Sean Wang
Fudan University
,
Program Chairs:
Minos Garofalakis
Technical University of Crete, Greece
,
Ian Soboroff
National Institute of Standards, USA
,
Torsten Suel
New York University, USA
,
Min Wang
Google Research, USA

Copyright © 2014 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 03 November 2014

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November 3 - 7, 2014

Shanghai, China

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Overall Acceptance Rate 1,466 of 6,316 submissions, 23%

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Cited By

Xiao XMa YXia YZhou MLuo XWang XFu XWei WJiang N(2022)Novel Workload-Aware Approach to Mobile User Reallocation in Crowded Mobile Edge Computing EnvironmentIEEE Transactions on Intelligent Transportation Systems10.1109/TITS.2021.308682723:7(8846-8856)Online publication date: 1-Jul-2022
https://dl.acm.org/doi/10.1109/TITS.2021.3086827
Xiao XLi YXia YMa YJiang CZhong X(2021)Location-Aware Edge Service Migration for Mobile User Reallocation in Crowded ScenesCollaborative Computing: Networking, Applications and Worksharing10.1007/978-3-030-67537-0_27(441-457)Online publication date: 22-Jan-2021
https://doi.org/10.1007/978-3-030-67537-0_27
Palma FMoha NGuéhéneuc Y(2019)UniDoSA: The Unified Specification and Detection of Service AntipatternsIEEE Transactions on Software Engineering10.1109/TSE.2018.281918045:10(1024-1053)Online publication date: 1-Oct-2019
https://dl.acm.org/doi/10.1109/TSE.2018.2819180
Buchgeher GKlammer CHeider WSchuetz MHuber H(2016)Improving Testing in an Enterprise SOA with an Architecture-Based Approach2016 13th Working IEEE/IFIP Conference on Software Architecture (WICSA)10.1109/WICSA.2016.24(231-240)Online publication date: Apr-2016
https://doi.org/10.1109/WICSA.2016.24

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