Energy-Optimal Data Aggregation and Dissemination for the Internet of Things

Established approaches to data aggregation in wireless sensor networks (WSNs) do not cover the variety of new use cases developing with the advent of the Internet of Things (IoT). In particular, the current push toward fog computing, in which control, computation, and storage are moved to nodes close to the network edge, induces a need to collect data at multiple sinks, rather than the single sink typically considered in WSN aggregation algorithms. Moreover, for machine-to-machine communication scenarios, actuators subscribing to sensor measurements may also be present, in which case data should be not only aggregated and processed in-network but also disseminated to actuator nodes. In this paper, we present mixed-integer programming formulations and algorithms for the problem of energy-optimal routing and multiple-sink aggregation, as well as joint aggregation and dissemination, of sensor measurement data in IoT edge networks. We consider optimization of the network for both minimal total energy usage, and min-max per-node energy usage. We also provide a formulation and algorithm for throughput-optimal scheduling of transmissions under the physical interference model in the pure aggregation case. We have conducted a numerical study to compare the energy required for the two use cases, as well as the time to solve them, in generated network scenarios with varying topologies and between 10 and 40 nodes. Although aggregation only accounts for less than 15% of total energy usage in all cases tested, it provides substantial energy savings. Our results show more than 13 times greater energy usage for 40-node networks using direct, shortest-path flows from sensors to actuators, compared with our aggregation and dissemination solutions.

[1]  Deborah Estrin,et al.  Impact of network density on data aggregation in wireless sensor networks , 2002, Proceedings 22nd International Conference on Distributed Computing Systems.

[2]  Wendi Heinzelman,et al.  Proceedings of the 33rd Hawaii International Conference on System Sciences- 2000 Energy-Efficient Communication Protocol for Wireless Microsensor Networks , 2022 .

[3]  Ossama Younis,et al.  HEED: a hybrid, energy-efficient, distributed clustering approach for ad hoc sensor networks , 2004, IEEE Transactions on Mobile Computing.

[4]  Deborah Estrin,et al.  The impact of data aggregation in wireless sensor networks , 2002, Proceedings 22nd International Conference on Distributed Computing Systems Workshops.

[5]  Di Yuan,et al.  Optimizing link rate assignment and transmission scheduling in WMN through compatible set generation , 2016, Telecommun. Syst..

[6]  Yuguang Fang,et al.  Energy-efficient reporting mechanisms for multi-type real-time monitoring in Machine-to-Machine communications networks , 2012, 2012 Proceedings IEEE INFOCOM.

[7]  Konstantinos Kalpakis,et al.  MAXIMUM LIFETIME DATA GATHERING AND AGGREGATION IN WIRELESS SENSOR NETWORKS , 2002 .

[8]  Hyung Seok Kim,et al.  Minimum-energy asynchronous dissemination to mobile sinks in wireless sensor networks , 2003, SenSys '03.

[9]  Deborah Estrin,et al.  Modelling Data-Centric Routing in Wireless Sensor Networks , 2002 .

[10]  Antonio Capone,et al.  Routing, scheduling and channel assignment in Wireless Mesh Networks: Optimization models and algorithms , 2010, Ad Hoc Networks.

[11]  Catherine Rosenberg,et al.  Design guidelines for wireless sensor networks: communication, clustering and aggregation , 2004, Ad Hoc Networks.

[12]  Yingshu Li,et al.  Minimum-latency aggregation scheduling in wireless sensor network , 2016, J. Comb. Optim..

[13]  Dirk Timmermann,et al.  Low energy adaptive clustering hierarchy with deterministic cluster-head selection , 2002, 4th International Workshop on Mobile and Wireless Communications Network.

[14]  Chih-Min Chao,et al.  Design of Structure-Free and Energy-Balanced Data Aggregation in Wireless Sensor Networks , 2009, 2009 11th IEEE International Conference on High Performance Computing and Communications.

[15]  Prasun Sinha,et al.  Structure-Free Data Aggregation in Sensor Networks , 2007, IEEE Transactions on Mobile Computing.

[16]  Melody Moh,et al.  On data aggregation quality and energy efficiency of wireless sensor network protocols - extended summary , 2004, First International Conference on Broadband Networks.

[17]  Di Yuan,et al.  On end-to-end delay minimization in wireless networks under the physical interference model , 2015, 2015 IEEE Conference on Computer Communications (INFOCOM).

[18]  Krishna M. Sivalingam,et al.  Data Gathering Algorithms in Sensor Networks Using Energy Metrics , 2002, IEEE Trans. Parallel Distributed Syst..

[19]  Anantha P. Chandrakasan,et al.  An application-specific protocol architecture for wireless microsensor networks , 2002, IEEE Trans. Wirel. Commun..

[20]  Di Yuan,et al.  On max-min fair flow optimization in wireless mesh networks , 2014, Ad Hoc Networks.

[21]  Rudra Dutta,et al.  A Survey of Network Design Problems and Joint Design Approaches in Wireless Mesh Networks , 2011, IEEE Communications Surveys & Tutorials.

[22]  Raja Lavanya,et al.  Fog Computing and Its Role in the Internet of Things , 2019, Advances in Computer and Electrical Engineering.

[23]  Ibrahim Korpeoglu,et al.  Power efficient data gathering and aggregation in wireless sensor networks , 2003, SGMD.

[24]  Di Yuan,et al.  Resource optimization of spatial TDMA in ad hoc radio networks: a column generation approach , 2003, IEEE INFOCOM 2003. Twenty-second Annual Joint Conference of the IEEE Computer and Communications Societies (IEEE Cat. No.03CH37428).

[25]  Ivan Stojmenovic,et al.  Machine-to-Machine Communications With In-Network Data Aggregation, Processing, and Actuation for Large-Scale Cyber-Physical Systems , 2014, IEEE Internet of Things Journal.

[26]  D. K. Lobiyal,et al.  Performance evaluation of data aggregation for cluster-based wireless sensor network , 2013, Human-centric Computing and Information Sciences.

[27]  Shaojie Tang,et al.  Wireless link scheduling under physical interference model , 2011, 2011 Proceedings IEEE INFOCOM.

[28]  Kwang-Cheng Chen,et al.  In-Network Computations of Machine-to-Machine Communications for Wireless Robotics , 2013, Wirel. Pers. Commun..

[29]  A.E. Kamal,et al.  Data aggregation in wireless sensor networks - exact and approximate algorithms , 2004, 2004 Workshop on High Performance Switching and Routing, 2004. HPSR..

[30]  Qun Li,et al.  A Survey of Fog Computing: Concepts, Applications and Issues , 2015, Mobidata@MobiHoc.

[31]  Miodrag Potkonjak,et al.  Gateway placement for latency and energy efficient data aggregation [wireless sensor networks] , 2004, 29th Annual IEEE International Conference on Local Computer Networks.

[32]  Michal Pioro,et al.  Packet routing and frame length optimization in wireless mesh networks with multicast communications , 2016, 2016 17th International Telecommunications Network Strategy and Planning Symposium (Networks).

[33]  Johannes Gehrke,et al.  Query Processing in Sensor Networks , 2003, CIDR.

[34]  Jiannong Cao,et al.  Construction of Optimal Data Aggregation Trees for Wireless Sensor Networks , 2006, Proceedings of 15th International Conference on Computer Communications and Networks.

[35]  Deborah Estrin,et al.  Directed diffusion for wireless sensor networking , 2003, TNET.

[36]  Chuan Wu,et al.  Latency-minimizing data aggregation in wireless sensor networks under physical interference model , 2014, Ad Hoc Networks.

[37]  Xiao Lu,et al.  Machine-to-machine communications for home energy management system in smart grid , 2011, IEEE Communications Magazine.

[38]  Jörg Widmer,et al.  In-network aggregation techniques for wireless sensor networks: a survey , 2007, IEEE Wireless Communications.

[39]  Hasan Çam,et al.  Energy-efficient secure pattern based data aggregation for wireless sensor networks , 2006, Comput. Commun..

[40]  Biplab Sikdar,et al.  Optimal Cluster Head Selection in the LEACH Architecture , 2007, 2007 IEEE International Performance, Computing, and Communications Conference.

[41]  Michal Pioro.  Network optimization techniques , 2011 .

[42]  Yong Yao,et al.  The cougar approach to in-network query processing in sensor networks , 2002, SGMD.