Abstract. In wireless sensor networks, the actual transmission of collected data is often the most energy-consuming operation. Frequently, it is worthwhile to spend energy aggregating the raw sensor data on the node to reduce the transmission effort. For many cases, lossless data compression can be employed as a general data aggregation method, as incompressible data (noise) generally does not carry any information worth transmitting. Nevertheless, the energy spent for data compression must be traded-off against the energy saved for transmitting the compressed data. In this work, sensor data of two real-life applications is compressed using a hardware-accelerator of the heterogeneous HaLOEWEn sensor node. The benefits of providing the node with a reconfigurable compute unit is demonstrated by comparing its energy consumption with that of of a purely software-based implementation.
Abstract. With increasing complexity of sensor network applications, the trade-off between node-local processing and transmission of data to a central node for handling becomes more significant. For distributed structural health monitoring applications (SHM), we consider different realization choices of the underlying wireless sensor network and implement a key part of the application (a high-order filter) on the novel HaLoMote architecture, a reconfigurable wireless sensor node (rWSN) with FPGAbased processing capability. We compare different tool flows supporting development of algorithms above the RTL regarding to achievable area and energy efficiency and outline the advantage of rWSN over traditional MCU-and DSP-based sensor systems in this scenario.
Abstract-Congestion-induced packet loss leads to throughput degradation in wireless sensor networks and often requires energetically expensive retransmissions. Though collisions can be avoided (CSMA/CA), the required carrier-sensing also increases the sensor node energy consumption. In this paper, an energyefficient routing protocol for a distributed monitoring application is proposed. Although the development of the new protocol was motivated by a specific use-case, it is applicable to all statictopology wireless sensor networks where multiple sensor nodes need to simultaneously distribute information to all other nodes in the network. First, we model the globally known network topology as two directed graphs representing reachability and interference. Based on this model, we define an integer linear program to find a collision-free communication schedule with the minimum number of transmissions and receptions required for distributing the data (multi-commodity information flooding). As these ILPs are hard to solve for larger networks, we also propose a heuristic for scheduling. Compared to other advanced flooding protocols, the proposed schedule can reduce wireless activity by up to 90 %, with the heuristic solver achieving a solution quality just 4 % worse than the optimal ILP solution.
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