Power-Performance Tradeoffs for Mobile Devices in Next Generation WiFi Networks

The much higher data rates offered by the new generation of WiFi radios, supported by the 802.11n and 802.11ac standards, come at the cost of increased power consumption. This concern is particularly heightened for smartphones, where radio interfaces can account for up to 50% of the total power budget under typical use. Consequently, existing smartphones do not implement all the features offered by the standards, trading performance for savings in power consumption. This tradeoff can in turn significantly impact the performance and power consumption of other devices in a heterogeneous WLAN. At the same time, the increasing demand for computational features such as multimedia in mobile devices has led to the use of complex computational hardware for graphics and memory with increased contribution to the overall energy consumption. This calls for a holistic approach to power analysis that considers both the communication and the computational paradigms of these devices.

In the first part of this NSF-funded project, we are developing a set of measurement-based models describing the power-performance tradeoffs of WiFi in mobile devices and the impact of different features of the next generation WiFi standards on these tradeoffs. We further seek to develop realistic power models that consider diverse components of the system and their interactions, beyond just the CPU, as well as models for power-performance tradeoffs at the system level. Power analysis of the computational elements and peripherals will be performed, with considerations to varying factors that affect the power consumption, such as the applications, environment, and usage profile, through modeling and measurements. The results will be combined with the WiFi models towards a holistic power profile.

The second part of this project focuses on the design and implementation of novel power saving, rate adaptation, and network management protocols for a variety of wireless devices (smartphones, tablets, laptops, APs). The protocols will be designed based on the models developed in the first part of the project with the following two design goals: (i) to maximize power savings for power-constrained devices without compromising their performance, (ii) to allow co-existence of heterogeneous devices in WLANs with maximum performance and power savings for all types of devices.




Past Students

  • Shixiong Jiang (PhD)
  • Ramanujan K. Sheshadri (PhD)
  • Li Sun (PhD)
  • Pengzhan Yan (PhD)
  • Swati Sridhar Nair (MS)
  • Andrew Wilkinson (MS)
  • Chimaobi Ezele (UG)
  • Alexander Hargrave (UG)
  • Redwan Khan (UG)
  • Sean Mackay (UG)
  • Kevin Rathburn (UG)


  • Energy-efficient and reliable in-memory classifier for machine-learning applications.
    James Clay, Naveena Elango, Sheena Priya, Shixiong Jiang, and Ramalingam Sridhar.
    In IET Computers & Digital Techniques (CDT), Vol. 16(6), pp 443-452, October 2019.

  • A First Look at 802.11ad Performance on a Smartphone.
    Shivang Aggarwal, Arvind Thirumurugan, and Dimitrios Koutsonikolas.
    In Proceedings of the 3rd ACM Workshop on Millimeter-Wave Networks and Sensing Systems (mmNets 2019), Los Cabos, Mexico, Oct 25, 2019.

  • Poster: Can Mobile Hardware Keep Up with Today's Gigabit Wireless Technologies?.
    Shivang Aggarwal, Swetank Kumar Saha, Pranab Dash, Jiayi Meng, Arvind Thirumurugan, Dimitrios Koutsonikolas, and Y. Charlie Hu.
    In the 25th ACM Annual International Conference on Mobile Computing and Networking (MobiCom 2019), Los Cabos, Mexico, Oct 21-25, 2019.

  • An Energy Efficient In-Memory Computing Machine-Learning Classifier Scheme.
    Shixiong Jiang, Sheena Priya, Naveena Elango, James Clay and Ramalingam Sridhar.
    In Proceedings of the 32nd International Conference VLSI Design (VLSID 2019), New Delhi, India, January 2019.

  • Modeling Context-Adaptive Energy-Aware Security in Mobile Devices.
    Swapnoneel Roy, Sriram Sankaran, Preeti Singh and Ramalingam Sridhar.
    In Proceedings of the 43rd Conference on Local Computer Networks Workshops (LCN Workshops) (LCN 2018), Chicago, IL, October 1-4, 2018.

  • A Power Analysis of Cryptocurrency Mining: A Mobile Device Perspective.
    James Clay, Alexander Hargrave, Ramalingam Sridhar.
    In Proceedings of the 16th Annual Conference on Privacy, Security and Trust (PST 2018), Belfast, Northern Ireland, United Kingdom, August 28-30, 2018.

  • Power Analysis of Quaternion Neural Networks.
    James Clay, Sheena Priya, Naveena Elango, Ranjan Lokappa and Ramalingam Sridhar.
    Poster, In Proceedings of the ICCAD 2017 workshop on Hardware and Algorithms for Learning On-a-chip (HALO 2017), Irvine, CA, November 2017.

  • Multipath TCP in Smartphones: Impact on Performance, Energy, and CPU Utilization.
    Swetank Kumar Saha, Abhishek Kannan, Geunhyung Lee, Nishant Ravichandran, Parag Kamalakar Medhe, Naved Merchant, and Dimitrios Koutsonikolas.
    In Proceedings of the 15th ACM International Symposium on Mobility Management and Wireless Access (MobiWac 2017), Miami Beach, MI, USA, November 21-25, 2017.

  • A Detailed Look into Power Consumption of Commodity 60 GHz Devices.
    Swetank Kumar Saha, Tariq Siddiqui, Dimitrios Koutsonikolas, Adrian Loch, Joerg Widmer, Ramalingam Sridhar.
    In Proceedings of the 18th IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM 2017), Macau, China, June 12-15, 2017.

  • A Comparative Power-Performance Analysis of Microarchitecture Effects on Heterogeneous CPU-GPU.
    V. Saravanan and R. Sridhar.
    Poster, In Supercomputing 16 - The International Conference for High Performance Computing, Networking, Storage and Analysis (SC 2016), Salt Lake City, USA, November 13-18, 2016.

  • A Fully Parallel Content Addressable Memory Design Using Multi-Bank Structure.
    Shixiong Jiang, Vijayalakshmi Saravanan, Pengzhan Yan and Ramalingam Sridhar.
    In Proceedings of the 29th IEEE System on Chip Conference (SOCC 2016), Seattle, WA, September 6-9, 2016.

  • Revisiting 802.11 Power Consumption Modeling in Smartphones.
    Swetank Kumar Saha, Pratham Malik, Selvaganesh Dharmeswaran, and Dimitrios Koutsonikolas.
    In Proceedings of the 17th IEEE International International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM 2016), Coimbra, Portugal, June 21-24, 2016. (acceptance rate for full papers 24%)

  • Experimental Evaluation of WiFi Active Power/Energy Consumption Models for Smartphones.
    Li Sun, Haotian Deng, Ramanujan K. Sheshadri, Wei Zheng, and Dimitrios Koutsonikolas.
    In IEEE Transactions on Mobile Computing (TMC), Vol. 16(1), pp 115-129, January 2017.
    Paper datasets available on WiNS Lab Download Center.

  • A High Speed and Low Power Content-addressable Memory (CAM) Using Pipelined Scheme.
    Shixiong Jiang, Pengzhan Yan and Ramalingam Sridhar.
    In Proceedings of the 28th IEEE System on Chip Conference (SOCC 2015), Beijing, China, September 8-11, 2015.

  • Characterizing Mobile User Habits: The Case for Energy Budgeting.
    Ramanujan K. Sheshadri, Ioannis Pefkianakis, Henrik Lundgren, Dimitrios Koutsonikolas, Anna-Kaisa Pietilainen, Augustin Soule, and Jaideep Chandrashekar.
    In Proceedings of the 18th IEEE Global Internet Symposium (GI 2015), Hong Kong, April 27, 2015. (acceptance rate 32%)

  • Power-Throughput Tradeoffs of 802.11n/ac in Smartphones.
    Swetank Kumar Saha, Pratik Deshpande, Pranav P Inamdar, Ramanujan K. Sheshadri, and Dimitrios Koutsonikolas.
    In Proceedings of the IEEE Conference on Computer Communications (INFOCOM 2015), Hong Kong, April 26 - May 1, 2015. (acceptance rate 19%)

  • Bringing Mobility-Awareness to WLANs using PHY layer information.
    Li Sun, Souvik Sen, and Dimitrios Koutsonikolas.
    In Proceedings of the 10th International Conference on emerging Networking EXperiments and Technologies (CoNEXT 2014), Sydney, Australia, December 2-5, 2014. (acceptance rate 20%)

  • Modeling WiFi Active Power/Energy Consumption in Smartphones.
    Li Sun, Ramanujan K. Sheshadri, Wei Zheng, and Dimitrios Koutsonikolas.
    In Proceedings of the 34th IEEE International Conference on Distributed Computing Systems (ICDCS 2014), Madrid, Spain, 30 June - 3 July, 2014. (acceptance rate 13.2%)

  • A First Look at 802.11n Power Consumption in Smartphones.
    Ninad Wart, Ramanujan K. Sheshadri, Wei Zheng, and Dimitrios Koutsonikolas.
    In Proceedings of the ACM International Workshop on Practical Issues and Applications in Next Generation Wireless Networks (PINGEN 2012), Istanbul, Turkey, August 26, 2012.


802.11n/ac datasets (throughput, power, energy) from our ICDCS 2014 paper are available. Please email us with a brief description on how you are planning to use them.


This project is sponsored by the National Science Foundation under Grant CNS-1422304.