Error resilient data transport in sensor network applications: A generic perspective

Abstract

SUMMARYThe error recovery problem in wireless sensor networks is studied from a generic resource-constrained energy-optimization perspective. To characterize the features of error recovery schemes that suit the majority of applications, an energy model is developed and inferences are drawn based on a suitable performance metric. For applications that require error control coding, an efficient scheme is proposed based on an interesting observation related to shortened Reed-Solomon (RS) codes for packet reliability. It is shown that multiple instances ( ) of RS codes defined on a smaller alphabet combined with interleaving results in smaller resource usage, while the performance exceeds the benefits of a shortened RS code defined over a larger alphabet. In particular, the proposed scheme can have an error correction capability of up to times larger than that of the conventional RS scheme without changing the rate of the code with much lower power, timing and memory requirements. Implementation results show that such a scheme is 43% more power efficient compared with the RS scheme with the same code rate. Besides, such an approach results in 46% faster computations and 53% reduction in memory requirements.

Area efficient evaluation based coding of shortened Reed-Solomon codes for memory constrained applications

“…For WSN applications [2], where the packet length, memory and hardware resources are limited, a shortened RS code is generally used [3]. The choice of using an error correcting code depends on these parameters as well as the channel characteristics and the implementation constraints(particularly power consumption and energy) in hardware and software.…”

Design space exploration for sparse matrix‐matrix multiplication on FPGAs

“…As an application accelerator, computational speed has traditionally been the most important metric in determining the merit of such components . However, as the overall system power consumption has become an increasingly important limiting factor in high‐performance computers, it is essential to also examine the power and energy implications of utilizing reconfigurable accelerators.…”