Energy-Efficient Task Mapping for Data-Driven Sensor Network Macroprogramming

Data-driven macroprogramming of wireless sensor networks (WSNs) provides an easy to use high-level task graph representation to the application developer. However, determining an energy-efficient initial placement of these tasks onto the nodes of the target network poses a set of interesting problems. We present a framework to model this task-mapping problem arising in WSN macroprogramming. Our model can capture task placement constraints, and supports easy specification of energy-based optimization goals. Using our framework, we provide mathematical formulations for the task-mapping problem for two different metrics -- energy balance and total energy spent. Due to the complex nature of the problems, these formulations are not linear. We provide linearization heuristics for the same, resulting in mixed-integer programming (MIP) formulations. We also provide efficient heuristics for the above. Our experiments show that the our heuristics give the same results as the MIP for real-world s...

• Type: Conference
• Year: 2008
• Where: DCOSS
• Authors: Animesh Pathak, Viktor K. Prasanna
• Keywords: DCOSS 2008, Distributed And Parallel Computing, Energy-efficient Initial Placement, Sensor Network, Task-mapping Problem