CmpctArch: A Generic Low Power Architecture for Compact Data Structures in Energy Harvesting Devices [2022]

Small sub-mW sensor devices that rely on energy harvesting often have limited computation capability to locally process, query, and update data. Such energy harvesting devices (EHDs) need to operate under a strict power constraint and are also extremely cost-sensitive. Based on current costs and estimated near-term trends, we observe that the price of the nonvolatile memory component dominates (in ~20 USD devices). Hence, there is a pressing need to reduce the overall memory footprint in a data-intensive setting. This paper is the first to propose a generic hardware archi- tecture, CmpctArch, for implementing compact data structures (CDSs) on such devices. They reduce the memory footprint by up to 3.5X without significantly increasing the overall energy consumption or time taken (max. additional energy 1.04X and time 1.18X). The hardware implementations are 160-1200X more energy-efficient and 280-620X faster than the corresponding software implementations of CDSs. Our generic template can be used to instantiate a wide variety of data structures commonly used in EHD applications.

A Survey on Checkpointing Techniques in Intermittent Systems [2021]

Checkpointing plays a key role in energy harvesting systems. We are performing a detailed study of the various checkpointing approaches proposed by researchers. Along with a theoretical study, we are also comparing these approaches experimentally. There are some interesting questions/details about our studay that we present in a FAQ document, which is available here.

EHDSktch: A Generic Low Power Architecture for Sketching in Energy Harvesting Devices [2020]

Energy harvesting devices (EHDs) are becoming extremely preva- lent in remote and hazardous environments. They sense the ambient parameters and compute some statistics on them, which are then sent to a remote server. Due to the resource-constrained nature of EHDs, it is challenging to perform exact computations on streaming data; however, if we are willing to tolerate a slight amount of inaccu- racy, we can leverage the power of sketching algorithms to provide quick answers with significantly lower energy consumption. In this paper, we propose a novel hardware architecture called EHDSktch - a set of IP blocks that can be used to implement most of the popular sketching algorithms. We demonstrate an energy savings of 4-10X and a speedup of more than 10X over state-of- the-art software implementations. Leveraging the temporal locality further provides us a performance gain of 3-20% in energy and time and reduces the on-chip memory requirement by at least 50-75%.

FlexiCheck: An Adaptive Checkpointing Architecture for Energy Harvesting Devices [2019]

With the advent of 5G and M2M architectures, energy harvesting devices are expected to become far more prevalent. Such devices harvest energy from ambient sources such as solar energy or vibration energy (from machines) and use it for sensing the environmental parameters and further processing them. Given that the rate of energy consumption is more than the rate of energy production, it is necessary to frequently halt the processor and accumulate energy from the environment. During this period it is mandatory to take a checkpoint to avoid the loss of data. State of the art algorithms use software based methods that extensively rely on compiler analyses. In this work, we provide the first formal model for such systems, and show that we can arrive at an optimal checkpointing schedule using a quadratically constrained linear program (QCLP) solver. Using this as a baseline, we show that existing algorithms for checkpointing significantly underperform. Furthermore, we prove and demonstrate that when we have a relatively constant energy source, a greedy algorithm provides an optimal solution.