Wireless sensor networking (WSN) is a continuously evolving technology for various applications, such as environment monitoring, patient monitoring, and many industrial applications. Wireless sensors can potentially be deployed in a large geographical area via multihop Scheduling Multi-Channel and Multi-Timeslot in Time Constrained Wireless Sensor Networks via Simulated Annealing and Particle Swarm Optimization communications. Unlike delay-tolerant applications, patient monitoring, disaster warning, intruder detection, and many industrial applications require timely responses. However, it is challenging to provide timely and reliable communication in WSNs, mainly due to the fact that conventional WSNs operate on a single channel. Sensor nodes must Scheduling Multi-Channel and Multi-Timeslot in Time Constrained Wireless Sensor Networks via Simulated Annealing and Particle Swarm Optimization compete with other nodes to access a single channel medium of limited bandwidth. If a transceiver operates on multiple channels, multiple simultaneous transmissions and receptions are feasible on wireless media without interfering with each other, and the bandwidth limitation can be relieved. Therefore, using multiple channels and time slots facilitates timely communication. In IEEE Std 802.15.4 for WSNs, a superframe structure consists of a contention access period (CAP) and a guaranteed time slot (GTS). Our proposal utilizes this superframe structure, but each time slot is extended to accommodate multiple channels as in IEEE Std 802.15.4e to guarantee end-to-end delay. The channels and time slots available to a node vary because each Scheduling Multi-Channel and Multi-Timeslot in Time Constrained Wireless Sensor Networks via Simulated Annealing and Particle Swarm Optimization node’s selection of channels and time slots imposes a set of constraints on the channels and time slots available to its neighbors. Our proposal affords each node the freedom to choose the optimal time slot and channel in establishing communication links to its neighbors, resulting in high throughput and low delay. Scheduling Multi-Channel and Multi-Timeslot in Time Constrained Wireless Sensor Networks via Simulated Annealing and Particle Swarm Optimization Scheduling is a critical process for virtually all resource-allocation problems, especially to meet quality of service (QoS) requirements. Scheduling channels and time slots for all nodes constituting an end-to-end (e2e) path to meet certain delay bounds is challenging because each node has a different remaining path length to the destination and encounters dissimilar channel environments. Assuming the channels and time slots are integer-numbered from 1 to some arbitrary number, a simple approach would be to schedule them in a sequenced and Scheduling Multi-Channel and Multi-Timeslot in Time Constrained Wireless Sensor Networks via Simulated Annealing and Particle Swarm Optimization staggered fashion from the ource to the destination; that is, each node chooses the smallest number out of the available time slots and channels, and this channel-time slot combination becomes unavailable to its children, parent, and their neighbors.