DICSA: Distributed and concurrent link scheduling algorithm for data gathering in wireless sensor networks

Although link scheduling has been used to improve the performance of data gathering applications, unfortunately, existing link scheduling algorithms are either centralized or they rely on specific assumptions that are not realistic in wireless sensor networks. In this paper, we propose a distributed and concurrent link scheduling algorithm, called DICSA, that requires no specific assumption regarding the underlying network. The operation of DICSA is managed through two algorithms: (i) Primary State Machine (PSM): Enables each node to perform its own slot reservation; (ii) Secondary State Machine (SSM): Enables each node to concurrently participate in the slot reservation of its neighbors. Through these algorithms and a set of forbidden slots managed by them, DICSA provides concurrent and collision-free slot reservation. Our results show that the execution duration and energy consumption of DICSA are at least 50% and 40% less than that of DRAND, respectively. In terms of slot assignment efficiency, while our results show higher spatial reuse over DRAND, the maximum slot number assigned by DICSA is at least 60% lower than VDEC. In data-gathering applications, our results confirm the higher performance of DICSA in terms of throughput, delivery ratio and packet delay. We show that the network throughput achievable by DICSA is more than 50%, 70%, 90% and 170% higher than that of DRAND, SEEDEX, NCR and FPS, respectively.

[1]  Koen Langendoen,et al.  Experimental Evaluation of Simulation Abstractions for Wireless Sensor Network MAC Protocols , 2009, 2009 IEEE 14th International Workshop on Computer Aided Modeling and Design of Communication Links and Networks.

[2]  Kamin Whitehouse,et al.  CAMA: Efficient Modeling of the Capture Effect for Low-Power Wireless Networks , 2014 .

[3]  Shaojie Tang,et al.  A Delay-Efficient Algorithm for Data Aggregation in Multihop Wireless Sensor Networks , 2011, IEEE Transactions on Parallel and Distributed Systems.

[4]  Aravind Srinivasan,et al.  Approximation Algorithms for Computing Capacity of Wireless Networks with SINR Constraints , 2008, IEEE INFOCOM 2008 - The 27th Conference on Computer Communications.

[5]  M. Barba,et al.  Spinal Fusion in the Next Generation: Gene and Cell Therapy Approaches , 2014, TheScientificWorldJournal.

[6]  Bhaskar Krishnamachari,et al.  Minimum latency joint scheduling and routing in wireless sensor networks , 2007, Ad Hoc Networks.

[7]  S. Ramanathan,et al.  A unified framework and algorithm for channel assignment in wireless networks , 1999, Wirel. Networks.

[8]  Yingshu Li,et al.  An Energy-Efficient Distributed Algorithm for Minimum-Latency Aggregation Scheduling in Wireless Sensor Networks , 2010, 2010 IEEE 30th International Conference on Distributed Computing Systems.

[9]  Injong Rhee,et al.  DRAND: Distributed Randomized TDMA Scheduling for Wireless Ad Hoc Networks , 2009, IEEE Trans. Mob. Comput..

[10]  Ju Wang,et al.  Scheduling for information gathering on sensor network , 2009, Wirel. Networks.

[11]  Tzung-Shi Chen,et al.  Minimal Time and Conflict-Free Schedule for Convergecast in Wireless Sensor Networks , 2008, 2008 IEEE International Conference on Communications.

[12]  Mahmut C. Selekoglu,et al.  How to be Energy Efficient , 2008 .

[13]  Jimmi Grönkvist Assignment methods for spatial reuse TDMA , 2000, MobiHoc.

[14]  Catherine Rosenberg,et al.  What is the right model for wireless channel interference? , 2006, IEEE Transactions on Wireless Communications.

[15]  Katia Obraczka,et al.  Energy-efficient, application-aware medium access for sensor networks , 2005, IEEE International Conference on Mobile Adhoc and Sensor Systems Conference, 2005..

[16]  Ramesh Govindan,et al.  Monitoring civil structures with a wireless sensor network , 2006, IEEE Internet Computing.

[17]  Bhaskar Krishnamachari,et al.  Fast Data Collection in Tree-Based Wireless Sensor Networks , 2012, IEEE Transactions on Mobile Computing.

[18]  Ioanis Nikolaidis,et al.  An exploration of aggregation convergecast scheduling , 2013, Ad Hoc Networks.

[19]  Chenxi Zhu,et al.  A Five-Phase Reservation Protocol (FPRP) for Mobile Ad Hoc Networks , 2001, Wirel. Networks.

[20]  John Anderson,et al.  An analysis of a large scale habitat monitoring application , 2004, SenSys '04.

[21]  Ying Zhang,et al.  Distributed time-optimal scheduling for convergecast in wireless sensor networks , 2008, Comput. Networks.

[22]  Bhaskar Krishnamachari,et al.  Scheduling Algorithms for Tree-Based Data Collection in Wireless Sensor Networks , 2011, Theoretical Aspects of Distributed Computing in Sensor Networks.

[23]  Hwee Pink Tan,et al.  Modeling low-power wireless communications , 2015, J. Netw. Comput. Appl..

[24]  Marco Zuniga,et al.  An analysis of unreliability and asymmetry in low-power wireless links , 2007, TOSN.

[25]  Behnam Dezfouli,et al.  Integration and Analysis of Neighbor Discovery and Link Quality Estimation in Wireless Sensor Networks , 2014, TheScientificWorldJournal.

[26]  J. J. Garcia-Luna-Aceves,et al.  Channel access scheduling in Ad Hoc networks with unidirectional links , 2001, DIALM '01.

[27]  Dariusz R. Kowalski,et al.  Fast Distributed Algorithm for Convergecast in Ad Hoc Geometric Radio Networks , 2005, Second Annual Conference on Wireless On-demand Network Systems and Services.

[28]  Ying Zhang,et al.  Distributed Minimal Time Convergecast Scheduling for Small or Sparse Data Sources , 2007, 28th IEEE International Real-Time Systems Symposium (RTSS 2007).

[29]  Kamalrulnizam Abu Bakar,et al.  LINKORD: link ordering-based data gathering protocol for wireless sensor networks , 2014, Computing.

[31]  Milind Dawande,et al.  Link scheduling in sensor networks: distributed edge coloring revisited , 2005, Proceedings IEEE 24th Annual Joint Conference of the IEEE Computer and Communications Societies..

[32]  Philip Levis,et al.  CTP , 2013, ACM Trans. Sens. Networks.

[33]  B. Hohlt,et al.  Flexible power scheduling for sensor networks , 2004, Third International Symposium on Information Processing in Sensor Networks, 2004. IPSN 2004.

[34]  Milind Dawande,et al.  Link scheduling in wireless sensor networks: Distributed edge-coloring revisited , 2008, J. Parallel Distributed Comput..

[35]  David E. Culler,et al.  TinyOS: An Operating System for Sensor Networks , 2005, Ambient Intelligence.

[36]  Eric A. Brewer,et al.  Network Power Scheduling for TinyOS Applications , 2006, DCOSS.

[37]  R. Rozovsky,et al.  SEEDEX: a MAC protocol for ad hoc networks , 2001, MobiHoc '01.

[38]  Pravin Varaiya,et al.  TDMA scheduling algorithms for wireless sensor networks , 2010, Wirel. Networks.

[39]  Myounggyu Won,et al.  CAMA: Efficient Modeling of the Capture Effect for Low-Power Wireless Networks , 2014, TOSN.

[40]  Kamalrulnizam Abu Bakar,et al.  Network Initialization in Low-Power Wireless Networks: A Comprehensive Study , 2014, Comput. J..

[41]  Kyungran Kang,et al.  A scalable joint routing and scheduling scheme for large-scale wireless sensor networks , 2013, Ad Hoc Networks.

[42]  Renjie Huang,et al.  TreeMAC: Localized TDMA MAC protocol for real-time high-data-rate sensor networks , 2009, Pervasive Mob. Comput..

[43]  Mei Zhou,et al.  Using MODIS land surface temperature to evaluate forest fire risk of northeast China , 2004, IEEE Geosci. Remote. Sens. Lett..

[44]  Xiaoqiao Meng,et al.  Real-time forest fire detection with wireless sensor networks , 2005, Proceedings. 2005 International Conference on Wireless Communications, Networking and Mobile Computing, 2005..

[45]  Cormac J. Sreenan,et al.  /spl mu/-MAC: an energy-efficient medium access control for wireless sensor networks , 2005, Proceeedings of the Second European Workshop on Wireless Sensor Networks, 2005..

[46]  Yu-Chee Tseng,et al.  Quick convergecast in ZigBee beacon-enabled tree-based wireless sensor networks , 2008, Comput. Commun..

[47]  Tzung-Shi Chen,et al.  Adjustable convergecast tree protocol for wireless sensor networks , 2010, Comput. Commun..

[48]  Katia Obraczka,et al.  Energy-efficient collision-free medium access control for wireless sensor networks , 2003, SenSys '03.

[49]  Shukor Abd Razak,et al.  A Medium Access Control Protocol with Adaptive Parent Selection Mechanism for Large-Scale Sensor Networks , 2011, 2011 IEEE Workshops of International Conference on Advanced Information Networking and Applications.

[50]  Hwee Pink Tan,et al.  Improving broadcast reliability for neighbor discovery, link estimation and collection tree construction in wireless sensor networks , 2014, Comput. Networks.

[51]  Bhaskar Krishnamachari,et al.  Enhancing the Data Collection Rate of Tree-Based Aggregation in Wireless Sensor Networks , 2008, 2008 5th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks.

[52]  F. Jiang,et al.  Exploiting the capture effect for collision detection and recovery , 2005, The Second IEEE Workshop on Embedded Networked Sensors, 2005. EmNetS-II..

[53]  J. J. Garcia-Luna-Aceves,et al.  A new approach to channel access scheduling for Ad Hoc networks , 2001, MobiCom '01.

[54]  Lei Tang,et al.  PW-MAC: An energy-efficient predictive-wakeup MAC protocol for wireless sensor networks , 2011, 2011 Proceedings IEEE INFOCOM.

[55]  Francesca Cuomo,et al.  Funneling-MAC: a localized, sink-oriented MAC for boosting fidelity in sensor networks , 2006, SenSys '06.