Content centric routing in IoT networks and its integration in RPL

Display Omitted Internet of Things (IoT) networks can be used for many applications across different industry domains including infrastructure monitoring, civil service, security and surveillance applications etc. However, gathering large amounts of data from such networks including images and videos often cause traffic congestion in the central network area. In order to solve this problem, we proposed the content centric routing (CCR) technology, where routing paths are determined by content. By routing the correlated data to intermediate relay nodes for processing, a higher data aggregation ratio can be obtained, hence effectively reducing the traffic in the network. As a result, significant latency reduction can be achieved. Moreover, redundant data transmissions can also be eliminated after data aggregation which reduces the energy consumption spent predominantly on wireless communication thereby conserving limited battery. CCR was further integrated with the IETF RPL protocol and implemented in Contiki OS using the TelosB platform. Finally, both simulation and implementation results prove the superior performance of CCR in terms of low network latency, high energy efficiency, and high reliability.

[1]  Mayank Dave,et al.  A Review on Content Centric Networking and Caching Strategies , 2015, 2015 Fifth International Conference on Communication Systems and Network Technologies.

[2]  Bin Zhang,et al.  In-network data aggregation route strategy based on energy balance in WSNs , 2013, 2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt).

[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]  Rahim Tafazolli,et al.  An Energy-Efficient Clustering Solution for Wireless Sensor Networks , 2011, IEEE Transactions on Wireless Communications.

[5]  Suman Nath,et al.  Energy efficient sensor data logging with amnesic flash storage , 2009, 2009 International Conference on Information Processing in Sensor Networks.

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

[7]  Wei Hong,et al.  Proceedings of the 5th Symposium on Operating Systems Design and Implementation Tag: a Tiny Aggregation Service for Ad-hoc Sensor Networks , 2022 .

[8]  Azzedine Boukerche,et al.  DRINA: A Lightweight and Reliable Routing Approach for In-Network Aggregation in Wireless Sensor Networks , 2013, IEEE Transactions on Computers.

[9]  Mahesh Sooriyabandara,et al.  Content centric and Load-balancing Aware Dynamic data Aggregation in Multihop wireless networks , 2012, 2012 IEEE 8th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob).

[10]  Mohamed A. Sharaf,et al.  Balancing energy efficiency and quality of aggregate data in sensor networks , 2004, The VLDB Journal.

[11]  Yi Pan,et al.  Constructing Load-Balanced Data Aggregation Trees in Probabilistic Wireless Sensor Networks , 2014, IEEE Transactions on Parallel and Distributed Systems.

[12]  Adam Dunkels,et al.  A database in every sensor , 2011, SenSys.

[13]  Katia Obraczka,et al.  The impact of timing in data aggregation for sensor networks , 2004, 2004 IEEE International Conference on Communications (IEEE Cat. No.04CH37577).

[14]  Pascal Thubert,et al.  Objective Function Zero for the Routing Protocol for Low-Power and Lossy Networks (RPL) , 2012, RFC.

[15]  Yi Pan,et al.  Continuous data aggregation and capacity in probabilistic wireless sensor networks , 2013, J. Parallel Distributed Comput..

[16]  Adam Dunkels,et al.  Contiki - a lightweight and flexible operating system for tiny networked sensors , 2004, 29th Annual IEEE International Conference on Local Computer Networks.

[17]  Samuel Madden,et al.  TAG: a Tiny Aggregation Tree for ad-hoc sensor networks , 2002, OSDI 2002.

[18]  Nikos Fotiou,et al.  A Survey of Information-Centric Networking Research , 2014, IEEE Communications Surveys & Tutorials.

[19]  Mahesh Sooriyabandara,et al.  Link quality aware and content centric data aggregation in lossy wireless networks , 2014, 2014 IEEE Wireless Communications and Networking Conference (WCNC).

[20]  Biswanath Mukherjee,et al.  Wireless sensor network survey , 2008, Comput. Networks.

[21]  John B. Shoven,et al.  I , Edinburgh Medical and Surgical Journal.

[22]  Mark S. Ackerman,et al.  Surviving the Information Explosion: How People Find Their Electronic Information , 2003 .

[23]  Kiyohito Yoshihara,et al.  DAG based in-network aggregation for sensor network monitoring , 2006, International Symposium on Applications and the Internet (SAINT'06).

[24]  Olivier Festor,et al.  Named data aggregation in wireless sensor networks , 2014, 2014 IEEE Network Operations and Management Symposium (NOMS).

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

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

[27]  Patrick Crowley,et al.  Named data networking , 2014, CCRV.

[28]  Jeffrey H. Reed,et al.  Wireless distributed computing: a survey of research challenges , 2012, IEEE Communications Magazine.

[29]  Pramod K. Varshney,et al.  Data-aggregation techniques in sensor networks: a survey , 2006, IEEE Communications Surveys & Tutorials.

[30]  TanHüseyin Özgür,et al.  Power efficient data gathering and aggregation in wireless sensor networks , 2003 .

[31]  Hwa-Chun Lin,et al.  Constructing Maximum-Lifetime Data Gathering Trees in Sensor Networks with Data Aggregation , 2010, 2010 IEEE International Conference on Communications.

[32]  Jie Wu,et al.  EECS: an energy efficient clustering scheme in wireless sensor networks , 2005, PCCC 2005. 24th IEEE International Performance, Computing, and Communications Conference, 2005..

[33]  Ness B. Shroff,et al.  Constructing Maximum-Lifetime Data-Gathering Forests in Sensor Networks , 2010, IEEE/ACM Transactions on Networking.

[34]  Robert Tappan Morris,et al.  a high-throughput path metric for multi-hop wireless routing , 2003, MobiCom '03.