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The Internet of Things (IoT) has important applications in our daily livesincluding health and fitness tracking, environmental monitoring andtransportation. However, sensor nodes in IoT suffer from the limited lifetimeof batteries resulting from their finite energy availability. A promisingsolution is to harvest energy from environmental sources, such as solar,kinetic, thermal and radio frequency, for perpetual and continuous operation ofIoT sensor nodes. In addition to energy generation, recently energy harvestershave been used for context detection, eliminating the need for additionalactivity sensors (e.g. accelerometers), saving space, cost, and energyconsumption. Using energy harvesters for simultaneous sensing and energyharvesting enables energy positive sensing -- an important and emerging classof sensors, which harvest higher energy than required for signal acquisitionand the additional energy can be used to power other components of the system.Although simultaneous sensing and energy harvesting is an important stepforward towards autonomous self-powered sensor nodes, the energy andinformation availability can be still intermittent, unpredictable andtemporally misaligned with various computational tasks on the sensor node. Thispaper provides a comprehensive survey on task scheduling algorithms for theemerging class of energy harvesting-based sensors (i.e., energy positivesensors) to achieve the sustainable operation of IoT. We discuss inherentdifferences between conventional sensing and energy positive sensing andprovide an extensive critical analysis for devising new task schedulingalgorithms incorporating this new class of sensors. Finally, we outline futureresearch directions towards the implementation of autonomous and self-poweredIoT.

Task Scheduling for Simultaneous IoT Sensing and Energy Harvesting: A Survey and Critical Analysis