MQTT is a widely utilized protocol in the IoT domain, specifically designed to minimize energy consumption in battery-powered, energy-intensive IoT devices. With the proliferation of smart home devices, there is a notable increase in co-located IoT devices capable of publishing to the same topic, as well as an increase in subscribers accessing diverse data from these devices. However, the architecture of current MQTT brokers do not effectively optimize task scheduling among multiple potential publishers. Our observations suggest that although aggregating sensing tasks on the same IoT device does not significantly impact the total sensing energy consumption, it substantially reduces communication energy costs by minimizing the long-tail energy expenses associated with wireless communications. In this paper, we introduce MQTT-EES (MQTT Energy Efficient Scheduling), which further optimizes the energy efficiency of MQTT by allocating sensing tasks on IoT devices with the goals of 1) minimizing long-tail communication energy consumption; and 2) prolonging the overall lifespan of the IoT system. We formulate the energy consumption challenge as an NP-hard problem and propose a greedy algorithm to tackle it. Our simulations show that MQTT-EES reduces average energy consumption by up to 12% and extends the overall lifespan of the system 2.78 times compared to standard MQTT implementations.