Journal Home > Volume 27 , Issue 2
Tsinghua Science and Technology 2022, 27(2): 257-269 https://doi.org/10.26599/TST.2021.9010011
Open Access | Issue | Published: 29 September 2021

Implementation of Abstract MAC Layer Under Jamming

Show Author's Information Yifei Zou,  Minghui Xu,  Dongxiao Yu( ),  Liandong Chen,  Shaoyong Guo,  Xiaoshuang Xing
School of Computer Science and Technology, Shandong University, Qingdao 266237, China
Information and Telecommunication Branch, State Grid Hebei Electric Power Company Ltd., Shijiazhuang 050022, China
State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China
School of Computer Science and Engineering, Changshu Institute of Technology, Changshu 215500, China
Keywords:
distributed algorithm, abstract MAC layer, Rayleigh-fading model, jamming networks
Cite this article:
Zou Y, Xu M, Yu D, et al. Implementation of Abstract MAC Layer Under Jamming. Tsinghua Science and Technology, 2022, 27(2): 257-269. https://doi.org/10.26599/TST.2021.9010011
Download citation
EndNote(RIS)
BibTeX

649

Views

53

Downloads

Citations

2

Crossref

1

WoS

2

Scopus

0

CSCD

Abstract Full text About this article

In the past decades, with the widespread implementation of wireless networks, such as the Internet of Things, an enormous demand for designing relative algorithms for various realistic scenarios has arisen. However, with the widening of scales and deepening of network layers, it has become increasingly challenging to design such algorithms when the issues of message dissemination at high levels and the contention management at the physical layer are considered. Accordingly, the abstract medium access control (absMAC) layer, which was proposed in 2009, is designed to solve this problem. Specifically, the absMAC layer consists of two basic operations for network agents: the acknowledgement operation to broadcast messages to all neighbors and the progress operation to receive messages from neighbors. The absMAC layer divides the wireless algorithm design into two independent and manageable components, i.e., to implement the absMAC layer over a physical network and to solve higher-level problems based on the acknowledgement and progress operations provided by the absMAC layer, which makes the algorithm design easier and simpler. In this study, we consider the implementation of the absMAC layer under jamming. An efficient algorithm is proposed to implement the absMAC layer, attached with rigorous theoretical analyses and extensive simulation results. Based on the implemented absMAC layer, many high-level algorithms in non-jamming cases can be executed in a jamming network.


menu
Abstract
Full text
Outline
About this article

Implementation of Abstract MAC Layer Under Jamming

Show Author's information Yifei Zou, Minghui Xu, Dongxiao Yu( ), Liandong Chen, Shaoyong Guo, Xiaoshuang Xing
School of Computer Science and Technology, Shandong University, Qingdao 266237, China
Information and Telecommunication Branch, State Grid Hebei Electric Power Company Ltd., Shijiazhuang 050022, China
State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China
School of Computer Science and Engineering, Changshu Institute of Technology, Changshu 215500, China

Abstract

In the past decades, with the widespread implementation of wireless networks, such as the Internet of Things, an enormous demand for designing relative algorithms for various realistic scenarios has arisen. However, with the widening of scales and deepening of network layers, it has become increasingly challenging to design such algorithms when the issues of message dissemination at high levels and the contention management at the physical layer are considered. Accordingly, the abstract medium access control (absMAC) layer, which was proposed in 2009, is designed to solve this problem. Specifically, the absMAC layer consists of two basic operations for network agents: the acknowledgement operation to broadcast messages to all neighbors and the progress operation to receive messages from neighbors. The absMAC layer divides the wireless algorithm design into two independent and manageable components, i.e., to implement the absMAC layer over a physical network and to solve higher-level problems based on the acknowledgement and progress operations provided by the absMAC layer, which makes the algorithm design easier and simpler. In this study, we consider the implementation of the absMAC layer under jamming. An efficient algorithm is proposed to implement the absMAC layer, attached with rigorous theoretical analyses and extensive simulation results. Based on the implemented absMAC layer, many high-level algorithms in non-jamming cases can be executed in a jamming network.

Keywords: distributed algorithm, abstract MAC layer, Rayleigh-fading model, jamming networks

References(48)

[1]
Y. Zou, D. Yu, L. Wu, J. Yu, Y. Wu, Q. Hua, and F. C. M. Lau, Fast distributed backbone construction despite strong adversarial jamming, presented at the IEEE INFOCOM 2019 - IEEE Conf. on Computer Communications, Paris, France, 2019.
DOI
[2]
D. Yu, Y. Zou, J. Yu, Y. Zhang, F. Li, X. Cheng, F. Dressler, and F. C. M. Lau, Implementing abstract MAC layer in dynamic networks, IEEE Transactions on Mobile Computing, vol. 20, no. 5, pp. 1832-1845, 2020.
DOI Google Scholar
[3]
F. Kuhn, N. Lynch, and C. Newport, The abstract MAC layer, Distributed Computing, vol. 24, nos. 3 & 4, pp. 187-206, 2011.
DOI Google Scholar
[4]
C. Newport, Consensus with an abstract MAC layer, in Proc. of the 2014 ACM symposium on Principles of distributed computing, Paris, France, 2014, pp. 66-75.
DOI
[5]
M. Ghaffari, E. Kantor, N. Lynch, and C. Newport, Multimessage broadcast with abstract mac layers and unreliable links, in Proc. of the 2014 ACM symposium on Principles of distributed computing, New York, NY, USA, 2014, pp. 56-65.
DOI
[6]
M. M. Halldórsson, S. Holzer, and N. Lynch, A local broadcast layer for the SINR network model, in Proc. of the 2015 ACM Symposium on Principles of Distributed Computing, Donostia-San Sebastián, Spain, 2015, pp. 129-138.
DOI
[7]
M. Khabbazian, D. R. Kowalski, F. Kuhn, and N. Lynch, Decomposing broadcast algorithms using abstract MAC layers, in Proc. of the 6th International Workshop on Foundations of Mobile Computing, Cambridge, MA, USA, pp. 13-22.
[8]
D. Yu, Y. Zou, M. Xu, Y. Xu, Y. Zhang, B. Gong, and X. Xing, Competitive age of information in dynamic IoT networks, IEEE Internet of Things Journal, p.1, 2020.
DOI Google Scholar
[9]
D. Yu, Y. Zou, Y. Zhang, F. Li, J. Yu, Y. Wu, X. Cheng, and F. C. M. Lau, Distributed dominating set and connected dominating set construction in the dynamic SINR model, presented at the 2019 IEEE International Parallel and Distributed Processing Symposium, Rio de Janeiro, Brazil, 2019.
DOI
[10]
J. Li, M. Siddula, X. Cheng, W. Cheng, Z. Tian, and Y. Li, Approximate data aggregation in sensor equipped IoT networks, Tsinghua Science and Technology, vol. 25, no. 1, pp. 44-55, 2020.
DOI Google Scholar
[11]
Z. Cai, Q. Chen, L. Cheng, and H. Gao, Latency-and-Coverage aware data aggregation scheduling for multihop battery-free wireless networks, IEEE Transactions on Mobile Computing, .
DOI Google Scholar
[12]
Q. Chen, Z. Cai, L. Cheng, and H. Gao, Structure-free general data aggregation scheduling for multihop battery-free wireless networks, IEEE Transactions on Mobile Computing, .
DOI Google Scholar
[13]
Z. Cai and T. Shi, Distributed query processing in the edge assisted IoT data monitoring system, IEEE Internet of Things Journal, vol. 8, no. 16, pp. 12679-12693, 2020.
DOI Google Scholar
[14]
Z. He, Z. Cai, S. Cheng, and X. Wang, Approximate aggregation for tracking quantiles and range countings in wireless sensor networks, Theoretical Compute Science, vol. 607, no. 3, pp. 381-390, 2015.
DOI Google Scholar
[15]
C. Wang, C. Wang, Z. Wang, X. Ye, and P. S. Yu, Edge2vec: Edge-based social network embedding, ACM Transactions on Knowledge Discovery from Data, vol. 14, no. 4, pp. 1-24, 2020.
DOI Google Scholar
[16]
C. Wang, C. Wang, Z. Wang, X. Ye, J. X. Yu, and B. Wang, DeepDirect: Learning directions of social ties with edge-based network embedding, IEEE Transactions on Knowledge and Data Engineering, vol. 31, no. 12, pp. 2277-2291, 2019.
DOI Google Scholar
[17]
J. Yang, C. Ma, J. Man, H. Xu, G. Zheng, and H. Song, Cache-enabled in cooperative cognitive radio networks for transmission performance, Tsinghua Science and Technology, vol. 25, no. 1, pp. 1-11, 2020.
DOI Google Scholar
[18]
Z. Cai and Z. He, Trading private range counting over big IoT data, presented at the 2019 IEEE 39th International Conference on Distributed Computing Systems, Dallas, TX, USA, 2019.
DOI
[19]
D. Yu, L. Zhang, Q. Luo, X. Cheng, J. Yu, and Z. Cai, Fast skyline community search in multi-valued networks, Big Data Mining and Analytics, vol. 3, no. 3, pp. 171-180, 2020.
DOI Google Scholar
[20]
M. Shi, Y. Tang, X. Zhang, Y. Zhang, and J. Xu, Modeling and simulation of packet delivery rate in LTEV network based on Markov chain, Tsinghua Science and Technology, vol. 25, no. 3, pp. 357-367, 2020.
DOI Google Scholar
[21]
J. Li, Y. Zhang, M. Shi, Q. Liu, and Y. Chen, Collision avoidance strategy supported by LTE-V-based vehicle automation and communication systems for car following, Tsinghua Science and Technology, vol. 25, no. 1, pp. 127-139, 2020.
DOI Google Scholar
[22]
J. Li, A. M. V. V. Sai, X. Cheng, W. Cheng, Z. Tian, and Y. Li, Sampling-based approximate skyline query in sensor equipped IoT networks, Tsinghua Science and Technology, vol. 26, no. 2, pp. 219-229, 2021.
DOI Google Scholar
[23]
Z. Hu, D. Li, and D. Guo, Balance resource allocation for spark jobs based on prediction of the optimal resource, Tsinghua Science and Technology, vol. 25, no. 4, pp. 487-497, 2020.
DOI Google Scholar
[24]
X. Fan, M. Dai, C. Liu, F. Wu, X. Yan, Y. Feng, Y. Feng, and B. Su, Effect of image noise on the classification of skin lesions using deep convolutional neural networks, Tsinghua Science and Technology, vol. 25, no. 3, pp. 425-434, 2020.
DOI Google Scholar
[25]
Q. Hou, M. Han, and Z. Cai, Survey on data analysis in social media: A practical application aspect, Big Data Mining and Analytics, vol. 3, no. 4, pp. 259-279, 2020.
DOI Google Scholar
[26]
E. Bayraktaroglu, C. King, X. Liu, G. Noubir, R. Rajaraman, and B. Thapa, Performance of IEEE 802.11 under jamming, Mobile Networks and Applications, vol. 18, no. 5, pp. 678-696, 2013.
DOI Google Scholar
[27]
A. Richa, C. Scheideler, S. Schmid, and J. Zhang, Competitive and fair medium access despite reactive jamming, presented at the 2011 31st International Conference on Distributed Computing Systems, Minneapolis, MN, USA, 2011.
DOI
[28]
A. Richa, C. Scheideler, S. Schmid, and J. Zhang, Selfstabilizing leader election for single-hop wireless networks despite jamming, in Proc. of the Twelfth ACM International Symposium on Mobile Ad Hoc Networking and Computing, Paris, France, 2011, pp. 1-10.
DOI
[29]
A. Richa, C. Scheideler, S. Schmid, and J. Zhang, Competitive throughput in multi-hop wireless networks despite adaptive jamming, Distributed Computing, vol. 26, no. 3, pp. 159-171, 2013.
DOI Google Scholar
[30]
G. Alnifie and R. Simon, A multi-channel defense against jamming attacks in wireless sensor networks, in Proc. of the 3rd ACM workshop on QoS and security for wireless and mobile networks, Chania Crete Island, Greece, 2007, pp. 95-104.
DOI
[31]
J. Chiang and Y. C. Hu, Cross-layer jamming detection and mitigation in wireless broadcast networks, IEEE/ACM Transactions on Networking, vol. 19, no. 1, pp. 286-298, 2011.
DOI Google Scholar
[32]
X. Liu, G. Noubir, R. Sundaram, and S. Tan, Spread: Foiling smart jammers using multi-layer agility, presented at the IEEE INFOCOM 2007 - 26th IEEE International Conference on Computer Communications, Anchorage, AK, USA, 2007.
DOI
[33]
V. Navda, A. Bohra, S. Ganguly, and D. Rubenstein, Using channel hopping to increase 802.11 resilience to jamming attacks, presented at the IEEE INFOCOM 2007 - 26th IEEE International Conference on Computer Communications, Anchorage, AK, USA, 2007.
DOI
[34]
M. K. Simon, J. K. Omura, R. A. Schultz, and B.K. Levin, Spread Spectrum Communications Handbook. New York, NY, USA: McGraw-Hill Companies, Inc., 1994.
[35]
A. D. Wood, J. A. Stankovic, and G. Zhou, DEEJAM: Defeating energyefficient jamming in IEEE 802.15.4-based wireless networks, presented at the 2007 4th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks, San Diego, CA, USA, 2007.
DOI
[36]
W. Xu, T. Wood, and Y. Zhang, Channel surfing and spatial retreats: Defenses against wireless denial of service, in Proc. of the 3rd ACM workshop on Wireless security, Philadelphia, PA, USA, 2004, pp. 80-89.
DOI
[37]
B. Awerbuch, A. Richa, and C. Scheideler, A jamming-resistant mac protocol for single-hop wireless networks, in Proc. of the twenty-seventh ACM symposium on Principles of distributed computing, Toronto, Canada, 2008, pp. 45-54.
DOI
[38]
A. Richa, C. Scheideler, S. Schmid, and J. Zhang, A jamming-resistant mac protocol for multi-hop wireless networks, in Proc. of the 24th International Conference on Distributed Computing, Cambridge, MA, USA, 2010, pp. 179-193.
DOI
[39]
A. Ogierman, A. W. Richa, C. Scheideler, S. Schmid, and J. Zhang. Competitive MAC under adversarial SINR, presented at the IEEE INFOCOM 2014 - IEEE Conference on Computer Communications, Toronto, Canada, 2014.
DOI
[40]
A. Ogierman, A. W. Richa, C. Scheideler, S. Schmid, and J. Zhang, Sade: Competitive MAC under adversarial SINR, Distributed Computing, vol. 31, no. 3, pp. 241-254, 2018.
DOI Google Scholar
[41]
F. Kuhn, N. Lynch, and C. Newport, The abstract MAC layer, Distributed Computing, vol. 24, nos. 3&4, pp. 187-206, 2011.
DOI Google Scholar
[42]
S. Daum, S. Gilbert, F. Kuhn, and C. Newport, Broadcast in the Ad Hoc SINR model, in Proc. of the 27th International Symposium on Distributed Computing, Jerusalem, Israel, 2013, pp. 358-372.
DOI
[43]
M. Khabbazian, F. Kuhn, D. R. Kowalski, and N. Lynch, Decomposing broadcast algorithms using abstract MAC layers, Ad Hoc Networks, vol. 12, pp. 219-242, 2014.
DOI Google Scholar
[44]
M. Khabbazian, F. Kuhn, N. Lynch, M. Médard, and A. ParandehGheibi, MAC design for analog network coding, in Proc. of the 7th ACM ACM SIGACT/SIGMOBILE International Workshop on Foundations of Mobile Computing, San Jose, CA, USA, 2011, pp. 42-51.
DOI
[45]
D. Yu, Y. Zhang, Y. Huang, H. Jin, J. Yu, and Q. S. Hua, Exact implementation of abstract MAC layer via carrier sensing, presented at the IEEE INFOCOM 2018 - IEEE Conference on Computer Communications, Honolulu, HI, USA, 2018.
DOI
[46]
Y. Zou, M. Xu, H. Sheng, X. Xing, Y. Xu, and Y. Zhang, Crowd density computation and diffusi on via Internet of Things, IEEE Internet of Things Journal, vol. 7, no. 9, pp. 8111-8121, 2020.
DOI Google Scholar
[47]
D. Yu, Y. Zou, J. Yu, X. Cheng, Q. S. Hua, H. Jin, and F. C. M. Lau, Stable local broadcast in multihop wireless networks under SINR, IEEE/ACM Transactions on Networking, vol. 26, no. 3, pp. 1278-1291, 2018.
DOI Google Scholar
[48]
D. Yu, L. Ning, Y. Zou, J. Yu, X. Cheng, and F. C. M. Lau, Distributed spanner construction with physical interference: Constant stretch and linear sparseness, IEEE/ACM Transactions on Networking, vol. 25, no. 4, pp. 2138-2151, 2017.
DOI Google Scholar
Publication history
Copyright
Acknowledgements
Rights and permissions

Publication history

Received: 12 January 2021
Revised: 06 February 2021
Accepted: 22 February 2021
Published: 29 September 2021
Issue date: April 2022

Copyright

© The author(s) 2022

Acknowledgements

This work was partially supported by the National Key R&D Program of China (No. 2019YFB2102600) and the National Natural Science Foundation of China (NSFC) (No. 61971269).

Rights and permissions

The articles published in this open access journal are distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/).

Return