An energy-balanced task scheduling heuristic for heterogeneous wireless sensor networks

In this paper, we propose a static scheduling algorithm forassigning tasks with precedence constraints onto a cluster of heterogeneoussensor nodes connected by a single-hop wireless network so as tomaximize the lifetime of the sensor network. The processing element oneach sensor node is equipped with dynamic voltage scaling capability. Inour algorithm, we assign the tasks to the sensor nodes so as to minimizethe energy consumption of the tasks on each sensor node while keepingthe energy consumption as balanced as possible. We also propose an algorithmto generate a second schedule that can improve the lifetime ofthe network further when it is used together with the original schedule.We observe up to 311% lifetime improvement in our simulations whenour algorithms are compared to the baseline case where dynamic voltagescaling is not used.

[1]  Qi Yang,et al.  Energy-aware partitioning for multiprocessor real-time systems , 2003, Proceedings International Parallel and Distributed Processing Symposium.

[2]  Viktor K. Prasanna,et al.  Power-aware resource allocation for independent tasks in heterogeneous real-time systems , 2002, Ninth International Conference on Parallel and Distributed Systems, 2002. Proceedings..

[3]  Wayne H. Wolf,et al.  TGFF: task graphs for free , 1998, Proceedings of the Sixth International Workshop on Hardware/Software Codesign. (CODES/CASHE'98).

[4]  Gürhan Küçük,et al.  Reducing reorder buffer complexity through selective operand caching , 2003, ISLPED '03.

[5]  Rami G. Melhem,et al.  Energy aware scheduling for distributed real-time systems , 2003, Proceedings International Parallel and Distributed Processing Symposium.

[6]  Niraj K. Jha,et al.  Power-conscious joint scheduling of periodic task graphs and aperiodic tasks in distributed real-time embedded systems , 2000, IEEE/ACM International Conference on Computer Aided Design. ICCAD - 2000. IEEE/ACM Digest of Technical Papers (Cat. No.00CH37140).

[7]  Mani B. Srivastava,et al.  Modulation scaling for Energy Aware Communication Systems , 2001, ISLPED '01.

[8]  Hakan Aydin,et al.  Energy-aware task allocation for rate monotonic scheduling , 2005, 11th IEEE Real Time and Embedded Technology and Applications Symposium.

[9]  Rami G. Melhem,et al.  Scheduling with Dynamic Voltage/Speed Adjustment Using Slack Reclamation in Multiprocessor Real-Time Systems , 2003, IEEE Trans. Parallel Distributed Syst..

[10]  Bashir M. Al-Hashimi,et al.  Considering power variations of DVS processing elements for energy minimisation in distributed systems , 2001, International Symposium on System Synthesis (IEEE Cat. No.01EX526).

[11]  Rami G. Melhem,et al.  Power aware scheduling for AND/OR graphs in multiprocessor real-time systems , 2002, Proceedings International Conference on Parallel Processing.

[12]  Petru Eles,et al.  Energy-efficient mapping and scheduling for DVS enabled distributed embedded systems , 2002, Proceedings 2002 Design, Automation and Test in Europe Conference and Exhibition.

[13]  Pai H. Chou,et al.  Fast and efficient voltage scheduling by evolutionary slack distribution , 2004 .

[14]  Sanjeev Baskiyar,et al.  Low Power Scheduling of DAGs to Minimize Finish Times , 2006, HiPC.

[15]  Viktor K. Prasanna,et al.  Energy-Balanced Task Allocation for Collaborative Processing in Wireless Sensor Networks , 2005, Mob. Networks Appl..

[16]  Jian-Jun Han,et al.  Dynamic power-aware scheduling algorithms for real-time task sets with fault-tolerance in parallel and distributed computing environment , 2005, 19th IEEE International Parallel and Distributed Processing Symposium.

[17]  Krzysztof Kuchcinski,et al.  LEneS: task scheduling for low-energy systems using variable supply voltage processors , 2001, ASP-DAC '01.

[18]  Yves Robert,et al.  High Performance Computing - HiPC 2006, 13th International Conference, Bangalore, India, December 18-21, 2006, Proceedings , 2006, HiPC.